pCO2 product synopsis 2023

workflowr

• Summary
• Checks
• Past versions

Last updated: 2024-05-28

Checks: 7 0

Knit directory: heatwave_co2_flux_2023/analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

---

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20240307)

The command set.seed(20240307) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: b99b329

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version b99b329. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:

Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/

Unstaged changes:
    Modified:   analysis/child/pCO2_product_synopsis.Rmd
    Modified:   code/Workflowr_project_managment.R

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/pco2_product_synopsis_2023.Rmd) and HTML (docs/pco2_product_synopsis_2023.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
html	b99b329	jens-daniel-mueller	2024-05-28	Build site.
html	b754e95	jens-daniel-mueller	2024-05-28	Build site.
html	fbba0a0	jens-daniel-mueller	2024-05-28	Build site.
html	d533f68	jens-daniel-mueller	2024-05-28	Build site.
html	555c1c8	jens-daniel-mueller	2024-05-27	Build site.
html	7b6f27c	jens-daniel-mueller	2024-05-27	Build site.
html	4be90dd	jens-daniel-mueller	2024-05-27	Build site.
html	e1e0ccb	jens-daniel-mueller	2024-05-27	Build site.
html	7013182	jens-daniel-mueller	2024-05-27	Build site.
html	97eff6a	jens-daniel-mueller	2024-05-25	Build site.
html	fe97ed3	jens-daniel-mueller	2024-05-25	Build site.
html	ac8cc7e	jens-daniel-mueller	2024-05-24	Build site.
html	12f6571	jens-daniel-mueller	2024-05-22	Build site.
html	7868a54	jens-daniel-mueller	2024-05-22	Build site.
html	571e2f8	jens-daniel-mueller	2024-05-22	Build site.
html	563345f	jens-daniel-mueller	2024-05-21	Build site.
html	29e0ec4	jens-daniel-mueller	2024-05-21	Build site.
html	7c08e1c	jens-daniel-mueller	2024-05-21	Build site.
html	1eefab2	jens-daniel-mueller	2024-05-21	Build site.
html	5af03d1	jens-daniel-mueller	2024-05-17	Build site.
html	a29d870	jens-daniel-mueller	2024-05-16	Build site.
html	dbc1fc6	jens-daniel-mueller	2024-05-16	Build site.
html	aea0b99	jens-daniel-mueller	2024-05-16	Build site.
html	3310cf6	jens-daniel-mueller	2024-05-16	Build site.
html	fcd728c	jens-daniel-mueller	2024-05-16	Build site.
html	960912c	jens-daniel-mueller	2024-05-16	Build site.
html	b7d0689	jens-daniel-mueller	2024-05-15	Build site.
html	00ad9d5	jens-daniel-mueller	2024-05-15	Build site.
html	47f8868	jens-daniel-mueller	2024-05-15	Build site.
html	589243f	jens-daniel-mueller	2024-05-15	Build site.
html	1e4c153	jens-daniel-mueller	2024-05-14	Build site.
html	009791f	jens-daniel-mueller	2024-05-14	Build site.
html	8c96de4	jens-daniel-mueller	2024-05-08	Build site.
html	3fea035	jens-daniel-mueller	2024-05-08	Build site.
html	4b81eaf	jens-daniel-mueller	2024-05-07	Build site.
html	60abdac	jens-daniel-mueller	2024-04-23	Build site.
html	e44a62b	jens-daniel-mueller	2024-04-23	Build site.
html	7f9c687	jens-daniel-mueller	2024-04-23	Build site.
html	1ff6eb0	jens-daniel-mueller	2024-04-22	Build site.
html	9ecd92e	jens-daniel-mueller	2024-04-22	Build site.
html	231f7cd	jens-daniel-mueller	2024-04-17	Build site.
html	f6e9707	jens-daniel-mueller	2024-04-17	Build site.
html	ce4e2a6	jens-daniel-mueller	2024-04-17	Build site.
html	a5911f0	jens-daniel-mueller	2024-04-17	Build site.
html	6709afa	jens-daniel-mueller	2024-04-12	Build site.
html	58e3680	jens-daniel-mueller	2024-04-11	Build site.
html	238d229	jens-daniel-mueller	2024-04-11	Build site.
html	dfcf790	jens-daniel-mueller	2024-04-11	Build site.
html	139bc97	jens-daniel-mueller	2024-04-11	manual deletion of files
html	2c6f421	jens-daniel-mueller	2024-04-11	Build site.
html	37ccea4	jens-daniel-mueller	2024-04-08	Build site.
html	19f40c9	jens-daniel-mueller	2024-04-05	Build site.
Rmd	2336de2	jens-daniel-mueller	2024-04-05	ensemble mean estimates added
html	2793f67	jens-daniel-mueller	2024-04-05	Build site.
html	69dc18c	jens-daniel-mueller	2024-04-04	Build site.
html	c9d994c	jens-daniel-mueller	2024-04-04	Build site.
html	40cb158	jens-daniel-mueller	2024-04-03	Build site.
html	7bb6113	jens-daniel-mueller	2024-04-03	Build site.
Rmd	7be0147	jens-daniel-mueller	2024-04-03	trend maps included
html	27b48a1	jens-daniel-mueller	2024-04-03	Build site.
html	a83c8fc	jens-daniel-mueller	2024-04-03	Build site.
Rmd	53c89bd	jens-daniel-mueller	2024-04-03	rebuild entire website incl 2022 anomalies

---

center <- -160
boundary <- center + 180
target_crs <- paste0("+proj=robin +over +lon_0=", center)
# target_crs <- paste0("+proj=eqearth +over +lon_0=", center)
# target_crs <- paste0("+proj=eqearth +lon_0=", center)
# target_crs <- paste0("+proj=igh_o +lon_0=", center)

worldmap <- ne_countries(scale = 'small',
                         type = 'map_units',
                         returnclass = 'sf')

worldmap <- worldmap %>% st_break_antimeridian(lon_0 = center)
worldmap_trans <- st_transform(worldmap, crs = target_crs)

# ggplot() +
#   geom_sf(data = worldmap_trans)

coastline <- ne_coastline(scale = 'small', returnclass = "sf")
coastline <- st_break_antimeridian(coastline, lon_0 = 200)
coastline_trans <- st_transform(coastline, crs = target_crs)

# ggplot() +
#   geom_sf(data = worldmap_trans, fill = "grey", col="grey") +
#   geom_sf(data = coastline_trans)


bbox <- st_bbox(c(xmin = -180, xmax = 180, ymax = 65, ymin = -78), crs = st_crs(4326))
bbox <- st_as_sfc(bbox)
bbox_trans <- st_break_antimeridian(bbox, lon_0 = center)

bbox_graticules <- st_graticule(
  x = bbox_trans,
  crs = st_crs(bbox_trans),
  datum = st_crs(bbox_trans),
  lon = c(20, 20.001),
  lat = c(-78,65),
  ndiscr = 1e3,
  margin = 0.001
)

bbox_graticules_trans <- st_transform(bbox_graticules, crs = target_crs)
rm(worldmap, coastline, bbox, bbox_trans)

# ggplot() +
#   geom_sf(data = worldmap_trans, fill = "grey", col="grey") +
#   geom_sf(data = coastline_trans) +
#   geom_sf(data = bbox_graticules_trans)

lat_lim <- ext(bbox_graticules_trans)[c(3,4)]*1.002
lon_lim <- ext(bbox_graticules_trans)[c(1,2)]*1.005

# ggplot() +
#   geom_sf(data = worldmap_trans, fill = "grey90", col = "grey90") +
#   geom_sf(data = coastline_trans) +
#   geom_sf(data = bbox_graticules_trans, linewidth = 1) +
#   coord_sf(crs = target_crs,
#            ylim = lat_lim,
#            xlim = lon_lim,
#            expand = FALSE) +
#   theme(
#     panel.border = element_blank(),
#     axis.text = element_blank(),
#     axis.ticks = element_blank()
#   )

latitude_graticules <- st_graticule(
  x = bbox_graticules,
  crs = st_crs(bbox_graticules),
  datum = st_crs(bbox_graticules),
  lon = c(20, 20.001),
  lat = c(-60,-30,0,30,60),
  ndiscr = 1e3,
  margin = 0.001
)

latitude_graticules_trans <- st_transform(latitude_graticules, crs = target_crs)

latitude_labels <- data.frame(lat_label = c("60°N","30°N","Eq.","30°S","60°S"),
                 lat = c(60,30,0,-30,-60)-4, lon = c(35)-c(0,2,4,2,0))

latitude_labels <- st_as_sf(x = latitude_labels,
               coords = c("lon", "lat"),
               crs = "+proj=longlat")

latitude_labels_trans <- st_transform(latitude_labels, crs = target_crs)

# ggplot() +
#   geom_sf(data = worldmap_trans, fill = "grey", col = "grey") +
#   geom_sf(data = coastline_trans) +
#   geom_sf(data = bbox_graticules_trans) +
#   geom_sf(data = latitude_graticules_trans,
#           col = "grey60",
#           linewidth = 0.2) +
#   geom_sf_text(data = latitude_labels_trans,
#                aes(label = lat_label),
#                size = 3,
#                col = "grey60")

pCO2_product_synopsis <-
  knitr::knit_expand(
    file = here::here("analysis/child/pCO2_product_synopsis.Rmd"),
    year_anom = 2023
  )

Read data

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_anomaly_map_annual.csv"),
                    full.names = TRUE)

pco2_product_coarse_annual_regression <-
  read_csv(files,
           id = "product")

pco2_product_coarse_annual_regression <-
  pco2_product_coarse_annual_regression %>% 
  mutate(product = str_extract(product, "OceanSODA|SOM_FFN|CMEMS|NRT_fco2residual|ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_anomaly_map_monthly.csv"),
                    full.names = TRUE)

pco2_product_coarse_monthly_regression <-
  read_csv(files,
           id = "product")

pco2_product_coarse_monthly_regression <-
  pco2_product_coarse_monthly_regression %>% 
  mutate(product = str_extract(product, "OceanSODA|SOM_FFN|CMEMS|NRT_fco2residual|ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_anomaly_hovmoeller_monthly.csv"),
                    full.names = TRUE)

pco2_product_hovmoeller_monthly_regression <-
  read_csv(files,
           id = "product")

pco2_product_hovmoeller_monthly_regression <-
  pco2_product_hovmoeller_monthly_regression %>% 
  mutate(product = str_extract(product, "OceanSODA|SOM_FFN|CMEMS|NRT_fco2residual|ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_biome_annual_regression.csv"),
                    full.names = TRUE)

pco2_product_annual_regression <-
  read_csv(files,
           id = "product")

pco2_product_annual_regression <-
  pco2_product_annual_regression %>% 
  mutate(product = str_extract(product, "OceanSODA|SOM_FFN|CMEMS|NRT_fco2residual|ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_biome_annual_detrended.csv"),
                    full.names = TRUE)

pco2_product_annual_detrended <-
  read_csv(files,
           id = "product")

pco2_product_annual_detrended <-
  pco2_product_annual_detrended %>% 
  mutate(product = str_extract(product, "OceanSODA|SOM_FFN|CMEMS|NRT_fco2residual|ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_biome_monthly_regression.csv"),
                    full.names = TRUE)

pco2_product_monthly_regression <-
  read_csv(files,
           id = "product")

pco2_product_monthly_regression <-
  pco2_product_monthly_regression %>% 
  mutate(product = str_extract(product, "OceanSODA|SOM_FFN|CMEMS|NRT_fco2residual|ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_biome_monthly_detrended.csv"),
                    full.names = TRUE)

pco2_product_monthly_detrended <-
  read_csv(files,
           id = "product")

pco2_product_monthly_detrended <-
  pco2_product_monthly_detrended %>% 
  mutate(product = str_extract(product, "OceanSODA|SOM_FFN|CMEMS|NRT_fco2residual|ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_profiles_monthly.csv"),
                    full.names = TRUE)

pco2_product_profiles_monthly <-
  read_csv(files,
           id = "product")

pco2_product_profiles_monthly <-
  pco2_product_profiles_monthly %>% 
  mutate(product = str_extract(product, "ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_profiles_annual.csv"),
                    full.names = TRUE)

pco2_product_profiles_annual <-
  read_csv(files,
           id = "product")

pco2_product_profiles_annual <-
  pco2_product_profiles_annual %>% 
  mutate(product = str_extract(product, "ETHZ_CESM|FESOM-REcoM"))

files <- list.files(here::here("data/"),
                    pattern = paste0(2023,"_zonal_mean_sections_annual.csv"),
                    full.names = TRUE)

pco2_product_zonal_mean_sections_annual <-
  read_csv(files,
           id = "product")

pco2_product_zonal_mean_sections_annual <-
  pco2_product_zonal_mean_sections_annual %>% 
  mutate(product = str_extract(product, "ETHZ_CESM|FESOM-REcoM"))

map <-
  read_rds(here::here("data/map.rds"))

key_biomes <-
  read_rds(here::here("data/key_biomes.rds"))


super_biomes <-
  read_rds(here::here("data/super_biomes.rds"))

biome_mask <-
  read_rds(here::here("data/biome_mask.rds"))

biome_mask <-
  bind_rows(
    biome_mask,
    biome_mask %>% mutate(biome = "Global")
  )

name_core <- c("fgco2", "fgco2_int", "fgco2_hov",
               "sfco2", "atm_fco2", "dfco2",
               "kw_sol", "temperature",
               "dissic", "talk", "cstar", 
               "no3", "o2",
               "mld", "thetao",
               "intpp", "chl")


all_product_list <- c("OceanSODA",
                      "SOM_FFN",
                      "NRT_fco2residual",
                      "CMEMS",
                      "ETHZ_CESM",
                      "FESOM-REcoM")

gobm_product_list <- c("ETHZ_CESM",
                       "FESOM-REcoM")


pco2_product_list <- c("OceanSODA",
                      "SOM_FFN",
                      "NRT_fco2residual",
                      "CMEMS"
                      )

color_products <- c(
  "OceanSODA" = "#672933",
  "SOM_FFN" = "#d1495b",
  "NRT_fco2residual" = "#edae49",
  "CMEMS" = "#AD8E55",
  "ETHZ_CESM" = "#66a182",
  "FESOM-REcoM" = "#00798c"
)

warm_color <- "#B84A60FF"
cold_color <- "#16877CFF"

# pco2_product_annual_regression %>%
#   distinct(product,name) %>%
#   print(n=50)

pco2_product_coarse_annual_regression <-
  pco2_product_coarse_annual_regression %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

pco2_product_coarse_monthly_regression <-
  pco2_product_coarse_monthly_regression %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

pco2_product_hovmoeller_monthly_regression <-
  pco2_product_hovmoeller_monthly_regression %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))


pco2_product_annual_detrended <- pco2_product_annual_detrended %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

pco2_product_annual_regression <- pco2_product_annual_regression %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))


pco2_product_monthly_detrended <- pco2_product_monthly_detrended %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

pco2_product_monthly_regression <-
  pco2_product_monthly_regression %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

pco2_product_profiles_monthly <-
  pco2_product_profiles_monthly %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

pco2_product_profiles_annual <-
  pco2_product_profiles_annual %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

pco2_product_zonal_mean_sections_annual <-
  pco2_product_zonal_mean_sections_annual %>%
  mutate(
    name = factor(name, levels = name_core),
    product = factor(product, levels = all_product_list)
  ) %>%
  filter(!is.na(name))

Define labels and breaks

labels_breaks <- function(i_name) {
  
  if (i_name == "dco2") {
    i_legend_title <- "ΔpCO<sub>2</sub><br>(µatm)"
  }
  
  if (i_name == "dfco2") {
    i_legend_title <- "ΔfCO<sub>2</sub><br>(µatm)"
  }
  
  if (i_name == "atm_co2") {
    i_legend_title <- "pCO<sub>2,atm</sub><br>(µatm)"
  }
  
  if (i_name == "atm_fco2") {
    i_legend_title <- "fCO<sub>2,atm</sub><br>(µatm)"
  }
  
  if (i_name == "sol") {
    i_legend_title <- "K<sub>0</sub><br>(mol m<sup>-3</sup> µatm<sup>-1</sup>)"
  }
  
  if (i_name == "kw") {
    i_legend_title <- "k<sub>w</sub><br>(m yr<sup>-1</sup>)"
  }
  
  if (i_name == "kw_sol") {
    i_legend_title <- "k<sub>w</sub> K<sub>0</sub><br>(mol yr<sup>-1</sup> m<sup>-2</sup> µatm<sup>-1</sup>)"
  }
  
  if (i_name == "spco2") {
    i_legend_title <- "pCO<sub>2,ocean</sub><br>(µatm)"
  }
  
  if (i_name == "sfco2") {
    i_legend_title <- "fCO<sub>2,ocean</sub><br>(µatm)"
  }
  
  if (i_name == "intpp") {
    i_legend_title <- "NPP<sub>int</sub><br>(mol s<sup>-1</sup> m<sup>-2</sup>)"
  }

  if (i_name == "no3") {
    i_legend_title <- "NO<sub>3</sub><br>(μmol kg<sup>-1</sup>)"
  }

  if (i_name == "o2") {
    i_legend_title <- "O<sub>2</sub><br>(μmol kg<sup>-1</sup>)"
  }

  if (i_name == "dissic") {
    i_legend_title <- "DIC<br>(μmol kg<sup>-1</sup>)"
  }

  if (i_name == "cstar") {
    i_legend_title <- "C*<br>(μmol kg<sup>-1</sup>)"
  }

  if (i_name == "talk") {
    i_legend_title <- "TA<br>(μmol kg<sup>-1</sup>)"
  }
  
  if (i_name == "sfco2_total") {
    i_legend_title <- "total"
  }
  
  if (i_name == "sfco2_therm") {
    i_legend_title <- "thermal"
  }
  
  if (i_name == "sfco2_nontherm") {
    i_legend_title <- "non-thermal"
  }
  
  if (i_name == "fgco2") {
    i_legend_title <- "FCO<sub>2</sub><br>(mol m<sup>-2</sup> yr<sup>-1</sup>)"
  }
  
  if (i_name == "fgco2_hov") {
    i_legend_title <- "FCO<sub>2</sub><br>(PgC deg<sup>-1</sup> yr<sup>-1</sup>)"
  }
  
  if (i_name == "fgco2_int") {
    i_legend_title <- "FCO<sub>2</sub><br>(PgC yr<sup>-1</sup>)"
  }
  
  if (i_name == "thetao") {
    i_legend_title <- "Temp.<br>(°C)"
  }
  
  if (i_name == "temperature") {
    i_legend_title <- "SST<br>(°C)"
  }
  
  if (i_name == "salinity") {
    i_legend_title <- "SSS"
  }
  
  if (i_name == "chl") {
    i_legend_title <- "lg(Chl-a)<br>(lg(mg m<sup>-3</sup>))"
  }
  
  if (i_name == "mld") {
    i_legend_title <- "MLD<br>(m)"
  }
  
  if (i_name == "press") {
    i_legend_title <- "pressure<sub>atm</sub><br>(Pa)"
  }
  
  if (i_name == "wind") {
    i_legend_title <- "Wind <br>(m sec<sup>-1</sup>)"
  }
  
  if (i_name == "SSH") {
    i_legend_title <- "SSH <br>(m)"
  }
  
  if (i_name == "fice") {
    i_legend_title <- "Sea ice <br>(%)"
  }
  
    
  if (i_name == "resid_fgco2") {
    i_legend_title <-
      "Observed"
  }
    
  if (i_name == "resid_fgco2_dfco2") {
    i_legend_title <-
      "ΔfCO<sub>2</sub>"
  }
    
  if (i_name == "resid_fgco2_kw_sol") {
    i_legend_title <-
      "k<sub>w</sub> K<sub>0</sub>"
  }
    
  if (i_name == "resid_fgco2_dfco2_kw_sol") {
    i_legend_title <-
      "k<sub>w</sub> K<sub>0</sub> X ΔfCO<sub>2</sub>"
  }
    
  if (i_name == "resid_fgco2_sum") {
    i_legend_title <-
      "∑"
  }
    
  if (i_name == "resid_fgco2_offset") {
    i_legend_title <-
      "Obs. - ∑"
  }
  
  all_labels_breaks <- lst(i_legend_title)
  
  return(all_labels_breaks)
  
}

x_axis_labels <-
  c(
    "dco2" = labels_breaks("dco2")$i_legend_title,
    "dfco2" = labels_breaks("dfco2")$i_legend_title,
    "atm_co2" = labels_breaks("atm_co2")$i_legend_title,
    "atm_fco2" = labels_breaks("atm_fco2")$i_legend_title,
    "sol" = labels_breaks("sol")$i_legend_title,
    "kw" = labels_breaks("kw")$i_legend_title,
    "kw_sol" = labels_breaks("kw_sol")$i_legend_title,
    "intpp" = labels_breaks("intpp")$i_legend_title,
    "no3" = labels_breaks("no3")$i_legend_title,
    "o2" = labels_breaks("o2")$i_legend_title,
    "dissic" = labels_breaks("dissic")$i_legend_title,
    "cstar" = labels_breaks("cstar")$i_legend_title,
    "talk" = labels_breaks("talk")$i_legend_title,
    "spco2" = labels_breaks("spco2")$i_legend_title,
    "sfco2" = labels_breaks("sfco2")$i_legend_title,
    "sfco2_total" = labels_breaks("sfco2_total")$i_legend_title,
    "sfco2_therm" = labels_breaks("sfco2_therm")$i_legend_title,
    "sfco2_nontherm" = labels_breaks("sfco2_nontherm")$i_legend_title,
    "fgco2" = labels_breaks("fgco2")$i_legend_title,
    "fgco2_hov" = labels_breaks("fgco2_hov")$i_legend_title,
    "fgco2_int" = labels_breaks("fgco2_int")$i_legend_title,
    "thetao" = labels_breaks("thetao")$i_legend_title,
    "temperature" = labels_breaks("temperature")$i_legend_title,
    "salinity" = labels_breaks("salinity")$i_legend_title,
    "chl" = labels_breaks("chl")$i_legend_title,
    "mld" = labels_breaks("mld")$i_legend_title,
    "press" = labels_breaks("press")$i_legend_title,
    "wind" = labels_breaks("wind")$i_legend_title,
    "SSH" = labels_breaks("SSH")$i_legend_title,
    "fice" = labels_breaks("fice")$i_legend_title,
    "resid_fgco2" = labels_breaks("resid_fgco2")$i_legend_title,
    "resid_fgco2_dfco2" = labels_breaks("resid_fgco2_dfco2")$i_legend_title,
    "resid_fgco2_kw_sol" = labels_breaks("resid_fgco2_kw_sol")$i_legend_title,
    "resid_fgco2_dfco2_kw_sol" = labels_breaks("resid_fgco2_dfco2_kw_sol")$i_legend_title,
    "resid_fgco2_sum" = labels_breaks("resid_fgco2_sum")$i_legend_title,
    "resid_fgco2_offset" = labels_breaks("resid_fgco2_offset")$i_legend_title
  )

Functions

Seasonality plots

p_season <- function(df, 
                     dim_row = "name", 
                     dim_col = "product", 
                     title = NULL, 
                     var = "resid",
                     scales = "free_y") {
  
  p <- ggplot(data = df,
         aes(month, !!ensym(var)))
  
  if(var == "resid"){
      p <- p +
        geom_hline(yintercept = 0, linewidth =0.5)
    
  }
  
  p <- p +
      geom_path(data = . %>% filter(year != 2023),
                aes(group = as.factor(year),
                    col = as.factor(paste(min(year), max(year), sep = "-"))),
                alpha = 0.5) +
      geom_path(data = . %>% 
                  filter(year != 2023) %>% 
                  group_by_at(vars(month, dim_col, dim_row)) %>% 
                  summarise(!!ensym(var) := mean(!!ensym(var))),
                aes(col = "Climatological\nmean"),
                linewidth = 1) +
    scale_color_manual(values = c("grey", "black"),
                       guide = guide_legend(order = 2,
                                            reverse = TRUE)) +
    new_scale_color()+
    geom_path(data = . %>% filter(year == 2023),
                aes(col = as.factor(year)),
                linewidth = 1) +
      scale_color_manual(
        values = warm_color,
        guide = guide_legend(order = 1)
      ) +
      scale_x_continuous(breaks = seq(1, 12, 3), expand = c(0, 0)) +
      labs(title = title,
           x = "Month")
  
  
  if (!(is.null(dim_col))) {
    p <- p +
      facet_grid(
        as.formula(paste(dim_row, "~", dim_col)),
        scales = scales,
        labeller = labeller(name = x_axis_labels),
        switch = "y"
      )
    
    
  } else {
    p <- p +
      facet_grid(
        as.formula(paste(dim_row, "~ .")),
        scales = "free_y",
        labeller = labeller(name = x_axis_labels),
        switch = "y"
      )
  }
  
  p <- p +
    theme(
      strip.text.y.left = element_markdown(),
      strip.placement = "outside",
      strip.background.y = element_blank(),
      axis.title.y = element_blank(),
      legend.title = element_blank()
    )
  
  p
  
}

fCO2 decomposition

fco2_decomposition <- function(df, ...) {
  
  group_by <- quos(...)
  # group_by <- quos(lon, lat, month)
  # group_by <- quos(biome, year, month)
  
  pco2_product_biome_monthly_fCO2_decomposition <-
    df %>%
    filter(name %in% c("temperature", "sfco2"))
  
  pco2_product_biome_monthly_fCO2_decomposition <-
    inner_join(
      pco2_product_biome_monthly_fCO2_decomposition %>%
        filter(name == "temperature") %>%
        select(-c(value, fit)) %>%
        pivot_wider(values_from = resid),
      pco2_product_biome_monthly_fCO2_decomposition %>%
        filter(name == "sfco2") %>%
        select(-c(value, resid)) %>%
        pivot_wider(values_from = fit)
    )
  
  pco2_product_biome_monthly_fCO2_decomposition <-
    pco2_product_biome_monthly_fCO2_decomposition %>%
    mutate(sfco2_therm = (sfco2 * exp(0.0423 * temperature)) - sfco2)
  
  
  pco2_product_biome_monthly_fCO2_decomposition <-
    inner_join(
      pco2_product_biome_monthly_fCO2_decomposition,
      df %>%
        filter(name %in% c("sfco2")) %>%
        select(-c(value, fit, name)) %>%
        rename(sfco2_total = resid)
    )
  
  
  pco2_product_biome_monthly_fCO2_decomposition <-
    pco2_product_biome_monthly_fCO2_decomposition %>%
    mutate(sfco2_nontherm = sfco2_total - sfco2_therm)
  
  pco2_product_biome_monthly_fCO2_decomposition <-
    pco2_product_biome_monthly_fCO2_decomposition %>%
    select(-c(temperature, sfco2)) %>%
    pivot_longer(starts_with("sfco2"),
                 values_to = "resid")
  
}

Flux attribution

flux_attribution <- function(df, ...) {
  
  group_by <- quos(...)
  # group_by <- quos(lon, lat, month)
  
  pco2_product_flux_attribution <-
    df %>%
    filter(name %in% c("dfco2", "kw_sol", "fgco2"))
  
  
  pco2_product_flux_attribution <-
    inner_join(
      pco2_product_flux_attribution %>%
        select(-c(value, fit)) %>%
        pivot_wider(values_from = resid,
                    names_prefix = "resid_"),
      pco2_product_flux_attribution %>%
        select(-c(value, resid)) %>%
        filter(name != "fgco2") %>%
        pivot_wider(values_from = fit)
    )
  
    pco2_product_flux_attribution <-
    pco2_product_flux_attribution %>%
    mutate(
      resid_fgco2_dfco2 = resid_dfco2 * kw_sol,
      resid_fgco2_kw_sol = resid_kw_sol * dfco2,
      resid_fgco2_dfco2_kw_sol = resid_dfco2 * resid_kw_sol
      # resid_fgco2_sum = resid_fgco2_dfco2 + resid_fgco2_kw_sol + resid_fgco2_dfco2_kw_sol
    )
  
  # pco2_product_flux_attribution <-
  #   pco2_product_flux_attribution %>%
  #   mutate(resid_fgco2_offset = resid_fgco2 - resid_fgco2_sum)
  
  pco2_product_flux_attribution <-
    pco2_product_flux_attribution %>%
    select(product, !!!group_by, starts_with("resid_fgco2")) %>%
    pivot_longer(starts_with("resid_"),
                 values_to = "resid")
  
  
  pco2_product_flux_attribution <-
    pco2_product_flux_attribution %>%
    filter(str_detect(name, "dfco2|kw_sol")) %>% 
    mutate(name = factor(
      name,
      levels = c(
        "resid_fgco2",
        "resid_fgco2_dfco2",
        "resid_fgco2_kw_sol",
        "resid_fgco2_dfco2_kw_sol",
        "resid_fgco2_sum",
        "resid_fgco2_offset"
      )
    ))
  
}

Maps

The following maps show the anomalies of each variable in 2023 as provided through the pCO2 product. Anomalies are determined based on the predicted value of a linear regression model fit to the available data from 1990 to 2022.

Maps are first presented as annual means, and than as monthly means. Note that the 2023 predictions for the monthly maps are done individually for each month, such the mean seasonal anomaly from the annual mean is removed.

Note: The increase the computational speed, I regridded all maps to 5X5° grid.

Annual means

2023 anomaly

bivariate_map <- 
pco2_product_coarse_annual_regression %>%
  filter(year == 2023,
         name %in% c("fgco2", "temperature")) %>%
  select(product, name, lon, lat, resid) %>% 
  pivot_wider(names_from = name,
              values_from = resid) %>% 
  drop_na()

map +
  geom_tile(data = bivariate_map,
            aes(lon, lat, fill = temperature)) +
  scale_fill_gradientn(
    colours = cmocean("curl")(100),
    rescaler = ~ scales::rescale_mid(.x, mid = 0),
    name = labels_breaks("temperature"),
    oob = squish
  ) +
  facet_wrap( ~ product, ncol = 2) +
  theme(legend.title = element_markdown())

Past versions of bivariate_anomaly_year_annual_mean_maps-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
6709afa	jens-daniel-mueller	2024-04-12

map +
  geom_tile(data = bivariate_map,
            aes(lon, lat, fill = fgco2)) +
  scale_fill_gradientn(
    colours = cmocean("curl")(100),
    rescaler = ~ scales::rescale_mid(.x, mid = 0),
    name = labels_breaks("fgco2"),
    oob = squish
  ) +
  facet_wrap(~ product, ncol = 2) +
  theme(legend.title = element_markdown())

Past versions of bivariate_anomaly_year_annual_mean_maps-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
6709afa	jens-daniel-mueller	2024-04-12

dim_set <- 4

bivariate_map <-
  bi_class(
    bivariate_map,
    x = temperature,
    y = fgco2,
    dim = dim_set,
    style = "quantile"
  )

bi_breaks <-
  bi_class_breaks(
    bivariate_map,
    x = temperature,
    y = fgco2,
    dim = dim_set,
    style = "quantile",
    dig_lab = 1
  )

map +
  geom_tile(data = bivariate_map,
            aes(lon, lat, fill = bi_class)) +
  bi_scale_fill(pal = "DkViolet2", dim = dim_set) +
  theme(legend.position = "none") +
  facet_wrap(~ product, ncol = 2)

Past versions of bivariate_anomaly_year_annual_mean_maps-3.png

Version	Author	Date
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
6709afa	jens-daniel-mueller	2024-04-12

bi_legend(
  pal = "DkViolet2",
  xlab = labels_breaks("temperature")$i_legend_title,
  ylab = labels_breaks("fgco2")$i_legend_title,
  dim = dim_set,
  pad_width = 2,
  breaks = bi_breaks,
  arrows = FALSE
) +
  theme(
    axis.title.x = element_markdown(),
    axis.title.y = element_markdown(),
    axis.ticks = element_blank(),
    axis.text = element_text(size = 10)
  )

Past versions of bivariate_anomaly_year_annual_mean_maps-4.png

Version	Author	Date
fe97ed3	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
6709afa	jens-daniel-mueller	2024-04-12

# cowplot::plot_grid(
#   bi_map, bi_legend,
#   rel_heights = c(5, 3),
#   ncol = 1
# )

# library(cmocean)

pco2_product_coarse_annual_regression %>%
  filter(year == 2023) %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid)) +
      labs(title =  paste(2023, "anomaly")) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid, .01), quantile(.x$resid, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown()) +
      facet_wrap(~ product, ncol = 2)
  )

[[1]]

Past versions of anomaly_year_annual_mean_maps-1.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[2]]

Past versions of anomaly_year_annual_mean_maps-2.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[3]]

Past versions of anomaly_year_annual_mean_maps-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[4]]

Past versions of anomaly_year_annual_mean_maps-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[5]]

Past versions of anomaly_year_annual_mean_maps-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[6]]

Past versions of anomaly_year_annual_mean_maps-6.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[7]]

Past versions of anomaly_year_annual_mean_maps-7.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[8]]

Past versions of anomaly_year_annual_mean_maps-8.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[9]]

Past versions of anomaly_year_annual_mean_maps-9.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[10]]

Past versions of anomaly_year_annual_mean_maps-10.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[11]]

Past versions of anomaly_year_annual_mean_maps-11.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
6709afa	jens-daniel-mueller	2024-04-12
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[12]]

Past versions of anomaly_year_annual_mean_maps-12.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fbba0a0	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

# library(cmocean)

pco2_product_coarse_annual_regression %>%
  filter(year == 2023,
         product == "ETHZ_CESM") %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid)) +
      labs(title =  paste(2023, "CESM anomaly")) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid, .01), quantile(.x$resid, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown())
  )

[[1]]

[[2]]

[[3]]

[[4]]

[[5]]

[[6]]

[[7]]

[[8]]

[[9]]

[[10]]

[[11]]

[[12]]

pco2_product_coarse_annual_regression_ensemble <-
  pco2_product_coarse_annual_regression %>% 
  filter(year == 2023,
         product %in% pco2_product_list) %>%
  group_by(name, lon, lat) %>%
  summarize(
    resid_sd = sd(resid),
    resid_range = max(resid) - min(resid),
    resid_mean = mean(resid),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n == length(pco2_product_list)) %>% 
  select(-n)

pco2_product_coarse_annual_regression_ensemble %>%
  mutate(product = "Ensemble mean") %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid_mean)) +
      geom_point(data = .x %>% filter(abs(resid_mean) < resid_sd),
                aes(lon, lat, shape = "Ensemble mean\n< StDev"),
                col = "grey", size = 1) +
      labs(title =  paste(2023, "ensemble mean anomaly")) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      ) +
      scale_shape_manual(values = 20, name = "") +
      theme(legend.title = element_markdown())
  )

[[1]]

Past versions of anomaly_annual_mean_maps_ensemble_mean-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

[[2]]

Past versions of anomaly_annual_mean_maps_ensemble_mean-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

[[3]]

Past versions of anomaly_annual_mean_maps_ensemble_mean-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

[[4]]

Past versions of anomaly_annual_mean_maps_ensemble_mean-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

[[5]]

Past versions of anomaly_annual_mean_maps_ensemble_mean-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

[[6]]

Past versions of anomaly_annual_mean_maps_ensemble_mean-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

[[7]]

Past versions of anomaly_annual_mean_maps_ensemble_mean-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27

pco2_product_coarse_annual_regression_ensemble_gobm <-
  pco2_product_coarse_annual_regression %>% 
  filter(year == 2023,
         product %in% gobm_product_list) %>%
  group_by(name, lon, lat) %>%
  summarize(
    resid_sd = sd(resid),
    resid_range = max(resid) - min(resid),
    resid_mean = mean(resid),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n == length(gobm_product_list)) %>% 
  select(-n)

pco2_product_coarse_annual_regression_ensemble_gobm %>%
  mutate(product = "Ensemble mean") %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid_mean)) +
      geom_point(data = .x %>% filter(abs(resid_mean) < resid_sd),
                aes(lon, lat, shape = "Ensemble mean\n< StDev"),
                col = "grey", size = 1) +
      labs(title =  paste(2023, "GOBM ensemble mean anomaly")) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      ) +
      scale_shape_manual(values = 20, name = "") +
      theme(legend.title = element_markdown())
  )

[[1]]

[[2]]

[[3]]

[[4]]

[[5]]

[[6]]

[[7]]

[[8]]

[[9]]

[[10]]

[[11]]

[[12]]

pco2_product_coarse_annual_regression_ensemble <-
left_join(
    pco2_product_coarse_annual_regression_ensemble,
    pco2_product_coarse_annual_regression %>% 
      filter(year == 2023,
             product %in% pco2_product_list)
  ) %>%
  mutate(`Anomaly offset` = resid - resid_mean) %>% 
  select(name, lon, lat, product, `Anomaly offset`)

pco2_product_coarse_annual_regression_ensemble_baseline <-
  pco2_product_coarse_annual_regression %>% 
  filter(year == 2023,
         product %in% pco2_product_list) %>%
  group_by(name, lon, lat) %>%
  summarize(
    fit_mean = mean(fit),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n == length(pco2_product_list)) %>% 
  select(-n)

pco2_product_coarse_annual_regression_ensemble_baseline <-
left_join(
    pco2_product_coarse_annual_regression_ensemble_baseline,
    pco2_product_coarse_annual_regression %>% 
      filter(year == 2023,
             product %in% pco2_product_list)
  ) %>%
  mutate(`Baseline offset` = fit - fit_mean) %>% 
  select(name, lon, lat, product, `Baseline offset`)

full_join(
  pco2_product_coarse_annual_regression_ensemble,
  pco2_product_coarse_annual_regression_ensemble_baseline
) %>%
  pivot_longer(contains("offset"),
               names_to = "offset") %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = value)) +
      labs(title =  paste(2023, "offset from ensemble mean")) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$value, .01), quantile(.x$value, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown()) +
      facet_grid(product ~ offset)
  )

[[1]]

Past versions of anomaly_annual_mean_maps_ensemble_mean_offset-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16

[[2]]

Past versions of anomaly_annual_mean_maps_ensemble_mean_offset-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16

[[3]]

Past versions of anomaly_annual_mean_maps_ensemble_mean_offset-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16

[[4]]

Past versions of anomaly_annual_mean_maps_ensemble_mean_offset-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16

[[5]]

Past versions of anomaly_annual_mean_maps_ensemble_mean_offset-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16

[[6]]

Past versions of anomaly_annual_mean_maps_ensemble_mean_offset-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16

[[7]]

Past versions of anomaly_annual_mean_maps_ensemble_mean_offset-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27

Monthly means

2023 anomaly

pco2_product_coarse_monthly_regression %>%
  filter(name %in% name_core,
         year == 2023) %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid)) +
      labs(title = paste(2023, "anomaly")) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid, .01), quantile(.x$resid, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown()) +
      facet_grid(month ~ product) +
      theme(legend.position = "bottom")
  )

[[1]]

Past versions of anomaly_2023_monthly_mean_maps-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[2]]

Past versions of anomaly_2023_monthly_mean_maps-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[3]]

Past versions of anomaly_2023_monthly_mean_maps-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[4]]

Past versions of anomaly_2023_monthly_mean_maps-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[5]]

Past versions of anomaly_2023_monthly_mean_maps-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[6]]

Past versions of anomaly_2023_monthly_mean_maps-6.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[7]]

Past versions of anomaly_2023_monthly_mean_maps-7.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
231f7cd	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[8]]

Past versions of anomaly_2023_monthly_mean_maps-8.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[9]]

Past versions of anomaly_2023_monthly_mean_maps-9.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[10]]

Past versions of anomaly_2023_monthly_mean_maps-10.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[11]]

Past versions of anomaly_2023_monthly_mean_maps-11.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[12]]

Past versions of anomaly_2023_monthly_mean_maps-12.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

fCO2 decomposition

pco2_product_coarse_monthly_fCO2_decomposition <-
  fco2_decomposition(pco2_product_coarse_monthly_regression,
                     year, month, lon, lat)


pco2_product_coarse_monthly_fCO2_decomposition %>%
  filter(year == 2023) %>% 
  group_split(product) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid)) +
      labs(title = paste(2023, "thermal vs non-thermal fCO2 anomaly"),
           subtitle = .x$product) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks("sfco2"),
        limits = c(quantile(.x$resid, .01), quantile(.x$resid, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown(),
            legend.position = "bottom") +
      facet_grid(
        month ~ name,
        labeller = labeller(name = x_axis_labels)
      )
  )

[[1]]

Past versions of fCO2_decomposition_monthly_maps-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16

[[2]]

Past versions of fCO2_decomposition_monthly_maps-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16

[[3]]

Past versions of fCO2_decomposition_monthly_maps-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16

[[4]]

Past versions of fCO2_decomposition_monthly_maps-4.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16

[[5]]

Past versions of fCO2_decomposition_monthly_maps-5.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16

[[6]]

Past versions of fCO2_decomposition_monthly_maps-6.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16

pco2_product_coarse_monthly_fCO2_decomposition %>%
  filter(year == 2023,
         product %in% pco2_product_list) %>%
  group_by(name, lon, lat, month) %>%
  summarize(
    resid_sd = sd(resid),
    resid_mean = mean(resid),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n == length(pco2_product_list)) %>% 
  select(-n) %>% 
  mutate(product = "Ensemble mean") %>% 
  group_split(product) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid_mean)) +
      geom_point(
        data = .x %>% filter(abs(resid_mean) < resid_sd),
        aes(lon, lat, shape = "Ensemble mean\n< StDev"),
        col = "grey"
      ) +
      labs(title = paste(2023,"thermal vs non-thermal anomaly"),
           subtitle = .x$product) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks("sfco2"),,
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      ) +
      scale_shape_manual(values = 46, name = "") +
      theme(legend.title = element_markdown(),
            legend.position = "bottom") +
      facet_grid(
        month ~ name,
        labeller = labeller(name = x_axis_labels)
      )
  )

[[1]]

Past versions of fCO2_decomposition_monthly_maps-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
5af03d1	jens-daniel-mueller	2024-05-17

pco2_product_coarse_annual_fCO2_decomposition <-
  pco2_product_coarse_monthly_fCO2_decomposition %>% 
  group_by(product, year, lat, lon, name) %>% 
  summarise(resid = mean(resid, na.rm = TRUE)) %>% 
  ungroup()


map +
  geom_tile(data = pco2_product_coarse_annual_fCO2_decomposition %>% 
              filter(year == 2023),
            aes(lon, lat, fill = resid)) +
  scale_fill_gradientn(
    colours = cmocean("curl")(100),
    rescaler = ~ scales::rescale_mid(.x, mid = 0),
    name = labels_breaks("sfco2"),
    limits = c(quantile(pco2_product_coarse_annual_fCO2_decomposition$resid, .01), 
               quantile(pco2_product_coarse_annual_fCO2_decomposition$resid, .99)),
    oob = squish
  )+
  labs(title = paste(2023, "annual mean fCO2 anomaly decomposition")) +
  theme(legend.title = element_markdown(),
        legend.position = "bottom") +
  facet_grid(product ~ name,
             labeller = labeller(name = x_axis_labels)) +
  theme(strip.text.x.top = element_markdown())

Past versions of fCO2_decomposition_annual_maps-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16

pco2_product_coarse_annual_fCO2_decomposition %>%
  filter(product %in% pco2_product_list,
         year == 2023) %>%
  group_by(name, lon, lat) %>%
  summarize(
    resid_sd = sd(resid),
    resid_mean = mean(resid),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n == length(pco2_product_list)) %>% 
  select(-n) %>% 
  mutate(product = "Ensemble mean") %>% 
  group_split(product) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid_mean)) +
      geom_point(
        data = .x %>% filter(abs(resid_mean) < resid_sd),
        aes(lon, lat, shape = "Ensemble mean\n< StDev"),
        col = "grey",
        size = 1
      )+
      labs(title = paste(2023, "fCO2 anomaly decomposition"),
           subtitle = .x$product) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks("sfco2"),
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      ) +
      scale_shape_manual(values = 20, name = "")+
      theme(legend.title = element_markdown(),
            legend.position = "bottom") +
      facet_wrap(
         ~ name,
        labeller = labeller(name = x_axis_labels),
        ncol = 1
      ) +
      theme(strip.text.x.top = element_markdown())
  )

[[1]]

Past versions of fCO2_decomposition_annual_maps-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
1eefab2	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16

Flux attribution

pco2_product_coarse_monthly_flux_attribution <-
  flux_attribution(pco2_product_coarse_monthly_regression,
                   year, month, lon, lat)

pco2_product_coarse_monthly_flux_attribution %>%
  filter(year == 2023) %>% 
  drop_na() %>% 
  group_split(product) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid)) +
      labs(title = paste(2023, "monthly flux anomaly decomposition"),
           subtitle = .x$product) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks("fgco2"),
        limits = c(quantile(.x$resid, .01), quantile(.x$resid, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown(), 
            legend.position = "bottom") +
      facet_grid(
        month ~ name,
        labeller = labeller(name = x_axis_labels)
      ) +
      theme(
        strip.text.x.top = element_markdown()
      )
  )

[[1]]

Past versions of flux_attribution_seasonal_maps-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16

[[2]]

Past versions of flux_attribution_seasonal_maps-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16

[[3]]

Past versions of flux_attribution_seasonal_maps-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16

[[4]]

Past versions of flux_attribution_seasonal_maps-4.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16

[[5]]

Past versions of flux_attribution_seasonal_maps-5.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16

[[6]]

Past versions of flux_attribution_seasonal_maps-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16

pco2_product_coarse_monthly_flux_attribution %>%
  filter(year == 2023) %>% 
  drop_na() %>% 
  filter(product %in% pco2_product_list) %>%
  group_by(name, lon, lat, month) %>%
  summarize(
    resid_sd = sd(resid),
    resid_mean = mean(resid),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n == length(pco2_product_list)) %>% 
  select(-n) %>% 
  mutate(product = "Ensemble mean") %>% 
  drop_na() %>% 
  group_split(product) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid_mean)) +
      geom_point(data = .x %>% filter(abs(resid_mean) < resid_sd),
                 aes(lon, lat, shape = "Ensemble mean\n< StDev"))+
      labs(title = paste(2023, "flux anomaly decomposition"),
           subtitle = .x$product) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks("fgco2"),
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      )+
      scale_shape_manual(values = 46, name = "") +
      theme(legend.title = element_markdown(),
            legend.position = "bottom") +
      facet_grid(
        month ~ name,
        labeller = labeller(name = x_axis_labels)
      ) +
      theme(strip.text.x.top = element_markdown())
  )

[[1]]

Past versions of flux_attribution_seasonal_maps-7.png

Version	Author	Date
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16

pco2_product_coarse_annual_flux_attribution <-
  pco2_product_coarse_monthly_flux_attribution %>% 
  group_by(product, year, lat, lon, name) %>% 
  summarise(resid = mean(resid, na.rm = TRUE)) %>% 
  ungroup()

map +
  geom_tile(data = pco2_product_coarse_annual_flux_attribution %>% 
              filter(year == 2023),
            aes(lon, lat, fill = resid)) +
  scale_fill_gradientn(
    colours = cmocean("curl")(100),
    rescaler = ~ scales::rescale_mid(.x, mid = 0),
    name = labels_breaks("fgco2"),
    limits = c(quantile(pco2_product_coarse_annual_flux_attribution$resid, .01, na.rm = TRUE), 
               quantile(pco2_product_coarse_annual_flux_attribution$resid, .99, na.rm = TRUE)),
    oob = squish
  )+
  labs(title = paste(2023, "annual mean flux anomaly decomposition")) +
  theme(legend.title = element_markdown(),
        legend.position = "bottom") +
  facet_grid(product ~ name,
             labeller = labeller(name = x_axis_labels)) +
  theme(strip.text.x.top = element_markdown())

Past versions of flux_attribution_annual_maps-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

pco2_product_coarse_annual_flux_attribution %>%
  filter(year == 2023,
         product %in% pco2_product_list) %>%
  group_by(name, lon, lat) %>%
  summarize(
    resid_sd = sd(resid),
    resid_mean = mean(resid),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n == length(pco2_product_list)) %>% 
  select(-n) %>% 
  mutate(product = "Ensemble mean") %>% 
  drop_na() %>% 
  group_split(product) %>%
  # head(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(lon, lat, fill = resid_mean)) +
      geom_point(data = .x %>% filter(abs(resid_mean) < resid_sd),
                 aes(lon, lat, shape = "Ensemble mean\n< StDev"),
                col = "grey", size = 1)+
      labs(title = paste(2023, "flux anomaly decomposition"),
           subtitle = .x$product) +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks("fgco2"),
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      )+
      scale_shape_manual(values = 20, name = "") +
      theme(legend.title = element_markdown(),
            legend.position = "bottom") +
      facet_wrap(
         ~ name,
        labeller = labeller(name = x_axis_labels),
        ncol = 1
      ) +
      theme(strip.text.x.top = element_markdown())
  )

[[1]]

Past versions of flux_attribution_annual_maps-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
1eefab2	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16

Hovmoeller plots

The following Hovmoeller plots show the anomalies from the prediction of a linear/quadratic fit to the data from 1990 to 2022.

Hovmoeller plots are presented as monthly means. Note that the predictions for the monthly Hovmoeller plots are done individually for each month, such the mean seasonal anomaly from the annual mean is removed.

Monthly means

Anomalies

pco2_product_hovmoeller_monthly_regression %>%
  filter(name %in% name_core) %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(decimal, lat, fill = resid)) +
      geom_raster() +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid,.01),quantile(.x$resid,.99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown()) +
      coord_cartesian(expand = 0) +
      labs(title = "Monthly mean anomalies",
           y = "Latitude") +
      theme(axis.title.x = element_blank()) +
      facet_wrap(~ product, ncol = 1)
  )

[[1]]

Past versions of hovmoeller_monthly_anomalies-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[2]]

Past versions of hovmoeller_monthly_anomalies-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[3]]

Past versions of hovmoeller_monthly_anomalies-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[4]]

Past versions of hovmoeller_monthly_anomalies-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[5]]

Past versions of hovmoeller_monthly_anomalies-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[6]]

Past versions of hovmoeller_monthly_anomalies-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[7]]

Past versions of hovmoeller_monthly_anomalies-7.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
231f7cd	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[8]]

Past versions of hovmoeller_monthly_anomalies-8.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[9]]

Past versions of hovmoeller_monthly_anomalies-9.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[10]]

Past versions of hovmoeller_monthly_anomalies-10.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[11]]

Past versions of hovmoeller_monthly_anomalies-11.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[12]]

Past versions of hovmoeller_monthly_anomalies-12.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[13]]

Past versions of hovmoeller_monthly_anomalies-13.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

pco2_product_hovmoeller_monthly_regression_ensemble <-
  pco2_product_hovmoeller_monthly_regression %>% 
  group_by(name, decimal, lat) %>%
  summarize(
    resid_range = max(resid) - min(resid),
    resid_mean = mean(resid),
    n = n()
  ) %>%
  ungroup() %>%
  filter(n > 1)
  

pco2_product_hovmoeller_monthly_regression_ensemble %>%
  mutate(product = "Ensemble mean") %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(decimal, lat, fill = resid_mean)) +
      geom_raster() +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown()) +
      coord_cartesian(expand = 0) +
      labs(title = "Monthly mean anomalies",
           y = "Latitude") +
      theme(axis.title.x = element_blank()) +
      facet_wrap( ~ product, ncol = 1)
  )

[[1]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[2]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08

[[3]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08

[[4]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08

[[5]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08

[[6]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
7f9c687	jens-daniel-mueller	2024-04-23
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08

[[7]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-7.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
7f9c687	jens-daniel-mueller	2024-04-23
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17

[[8]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-8.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17

[[9]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-9.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
7f9c687	jens-daniel-mueller	2024-04-23
9ecd92e	jens-daniel-mueller	2024-04-22

[[10]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-10.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[11]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-11.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[12]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-12.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[13]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean-13.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27

left_join(
    pco2_product_hovmoeller_monthly_regression_ensemble,
    pco2_product_hovmoeller_monthly_regression
  ) %>%
  mutate(resid_offset = resid - resid_mean) %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(decimal, lat, fill = resid_offset)) +
      geom_raster() +
      scale_fill_gradientn(
        colours = cmocean("curl")(100),
        rescaler = ~ scales::rescale_mid(.x, mid = 0),
        name = labels_breaks(.x %>% distinct(name)),
        limits = c(quantile(.x$resid_mean, .01), quantile(.x$resid_mean, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown()) +
      coord_cartesian(expand = 0)+
      labs(title = "Monthly offset from ensemble mean anomalies",
           y = "Latitude") +
      theme(axis.title.x = element_blank()) +
      facet_wrap( ~ product, ncol = 1)
  )

[[1]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[2]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[3]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[4]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[5]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
a29d870	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[6]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[7]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-7.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
a29d870	jens-daniel-mueller	2024-05-16
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[8]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-8.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[9]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-9.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
960912c	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
7f9c687	jens-daniel-mueller	2024-04-23
9ecd92e	jens-daniel-mueller	2024-04-22
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[10]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-10.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[11]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-11.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
37ccea4	jens-daniel-mueller	2024-04-08
19f40c9	jens-daniel-mueller	2024-04-05

[[12]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-12.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[13]]

Past versions of hovmoeller_monthly_anomalies_ensemble_mean_offset-13.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27

Regional means and integrals

The following plots show biome-, super biome- or global- averaged/integrated values of each variable as provided through the pCO2 product, represented here as the anomalies from the prediction of a linear/quadratic fit to the data from 1990 to 2022.

Anomalies are presented relative to the predicted annual mean of each year, hence preserving the seasonality.

Annual anomalies

pco2_product_annual_regression %>%
  filter(name %in% c("fgco2", "temperature"),
         biome == "Global") %>%
  ggplot(aes(year, value, col = product)) +
  geom_smooth(data = . %>% filter(year != 2023),
              method = "lm",
              se = FALSE,
              fullrange = TRUE) +
  # geom_smooth(data = . %>% filter(year != 2023),
  #             method = "lm",
  #             se = FALSE) +
  geom_path(linewidth = 0.3) +
  geom_point(data = . %>% filter(year == 2023),
             shape = 21, fill = "transparent", size = 2, stroke = 1) +
  scale_color_manual(values = color_products) +
  facet_grid(name ~ .,
             scales = "free_y",
             labeller = labeller(name = x_axis_labels),
             switch = "y") +
  theme(
    legend.title = element_blank(),
    axis.title = element_blank(),
    strip.text.y.left = element_markdown(),
    strip.placement = "outside",
    strip.background.y = element_blank(),
    legend.position = "top"
  )

Past versions of absolute_integrals_trends-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
12f6571	jens-daniel-mueller	2024-05-22
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
1eefab2	jens-daniel-mueller	2024-05-21

pco2_product_annual_regression_ensemble <-
  pco2_product_annual_regression %>%
  filter(product %in% pco2_product_list) %>%
  group_by(year, name, biome) %>%
  summarise(resid_sd = sd(resid),
            resid = mean(resid),
            value = mean(value),
            fit = mean(fit)) %>%
  ungroup()

bind_rows(
  pco2_product_annual_regression_ensemble,
  pco2_product_annual_regression_ensemble %>%
    filter(year == max(year)) %>%
    mutate(year = year + 1) %>% 
    select(-c(resid, resid_sd))
) %>% 
  filter(name %in% c("fgco2", "temperature"),
         biome == "Global") %>%
  ggplot() +
  geom_path(
    data = pco2_product_monthly_regression %>%
      filter(product %in% pco2_product_list,
             name %in% c("fgco2", "temperature"),
             biome == "Global") %>% 
      group_by(year, month, name, biome) %>%
      summarise(value = mean(value)) %>%
      ungroup(),
    aes(year + month / 12, value),
    col = "grey90"
  )+
  geom_rect(
    data = . %>% filter(year != max(year)),
    aes(
      xmin = year,
      xmax = year + 1,
      ymin = fit,
      ymax = value,
      fill = as.factor(sign(-resid))
    ),
    alpha = 0.5
  ) +
  scale_color_manual(values = c("grey40", "grey10"),
                     name = "Annual mean values") +
  scale_fill_manual(
    values = c(warm_color, cold_color),
    labels = c("positive", "negative"),
    name = "Annual mean anomalies"
  ) +
  geom_step(aes(year, fit, col = "Baseline")) +
  geom_step(aes(year, value, col = "Observed"))+
  geom_errorbar(aes(
      x = year + 0.5,
      ymin = value - resid_sd,
      ymax = value + resid_sd
    ), width = 0.2, col = "grey10"
  ) +
  scale_x_continuous(limits = c(1989.5,2024.5), expand = c(0,0)) +
  facet_grid(
    name ~ .,
    scales = "free_y",
    labeller = labeller(name = x_axis_labels),
    switch = "y"
  ) +
  theme(
    axis.title = element_blank(),
    strip.text.y.left = element_markdown(),
    strip.placement = "outside",
    strip.background.y = element_blank(),
    legend.position = "top",
    legend.direction = "vertical"
  )

Past versions of absolute_integrals_trends-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
ac8cc7e	jens-daniel-mueller	2024-05-24

bind_rows(
  pco2_product_annual_regression,
  pco2_product_annual_regression %>%
    filter(year == max(year)) %>%
    mutate(year = year + 1) %>% 
    select(-c(resid))
) %>% 
  filter(name %in% c("fgco2", "temperature"),
         biome == "Global") %>%
  ggplot() +
  geom_path(
    data = pco2_product_monthly_regression %>%
      filter(name %in% c("fgco2", "temperature"),
             biome == "Global"),
    aes(year + month / 12, value),
    col = "grey90"
  )+
  geom_rect(
    data = . %>% filter(year != max(year)),
    aes(
      xmin = year,
      xmax = year + 1,
      ymin = fit,
      ymax = value,
      fill = as.factor(sign(-resid))
    ),
    alpha = 0.5
  ) +
  scale_color_manual(values = c("grey40", "grey10"),
                     name = "Annual mean values") +
  scale_fill_manual(
    values = c(warm_color, cold_color),
    labels = c("positive", "negative"),
    name = "Annual mean anomalies"
  ) +
  geom_step(aes(year, fit, col = "Baseline")) +
  geom_step(aes(year, value, col = "Observed")) +
  scale_x_continuous(limits = c(1989.5,2024.5), expand = c(0,0),
                     breaks = c(1990,2010)) +
  facet_grid(
    name ~ product,
    scales = "free_y",
    labeller = labeller(name = x_axis_labels),
    switch = "y"
  ) +
  theme(
    axis.title = element_blank(),
    strip.text.y.left = element_markdown(),
    strip.placement = "outside",
    strip.background.y = element_blank(),
    legend.position = "top",
    legend.direction = "vertical"
  )

Past versions of absolute_integrals_trends-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
ac8cc7e	jens-daniel-mueller	2024-05-24

bind_rows(
  pco2_product_monthly_regression,
  pco2_product_monthly_regression %>%
    filter(year == max(year),
           month == 12) %>%
    mutate(month = month + 1)
) %>%
  mutate(year = year + month/12) %>% 
  filter(name %in% c("fgco2", "temperature"),
         product == "OceanSODA",
         biome == "Global") %>%
  ggplot() +
  geom_rect(
    data = . %>% filter(year != max(year)),
    aes(
      xmin = year,
      xmax = year + 1/12,
      ymin = fit,
      ymax = value,
      fill = as.factor(sign(-resid))
    ),
    alpha = 0.5
  ) +
  scale_color_manual(values = c("grey10", "grey80"),
                     name = "Monthly mean values") +
  scale_fill_manual(
    values = c(warm_color, cold_color),
    labels = c("positive", "negative"),
    name = "Annual mean anomalies"
  ) +
  geom_step(aes(year, fit, col = "Baseline")) +
  # geom_step(aes(year, value, col = "Observed")) +
  facet_grid(
    name ~ .,
    scales = "free_y",
    labeller = labeller(name = x_axis_labels),
    switch = "y"
  ) +
  coord_cartesian(expand = 0) +
  theme(
    axis.title = element_blank(),
    strip.text.y.left = element_markdown(),
    strip.placement = "outside",
    strip.background.y = element_blank(),
    legend.position = "top",
    legend.direction = "vertical"
  )

Past versions of absolute_integrals_trends-4.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
ac8cc7e	jens-daniel-mueller	2024-05-24

pco2_product_annual_regression %>%
  filter(year == 2023,
         name %in% c("fgco2", "fgco2_int", "dfco2",
                     "kw_sol", "temperature",
                     "no3", "mld", "intpp", "chl")) %>%
  mutate(region = case_when(biome == "Global" ~ "Global",
                            biome %in% super_biomes ~ "Super biomes",
                            TRUE ~ "Biomes"),
         region = factor(region, levels = c("Global", "Super biomes", "Biomes"))) %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_col(aes(biome, value, fill = product),
                 position = "dodge2") +
      scale_fill_manual(values = color_products) +
      geom_col(aes(biome, fit, group = product, col = paste0(2023,"\nlinear\nprediction")),
               position = "dodge2",
               fill = "transparent") +
      labs(y = labels_breaks(unique(.x$name))$i_legend_title,
           title = "Absolute") +
      scale_color_grey() +
      facet_grid(.~region, scales = "free_x", space = "free_x") +
      theme(legend.title = element_blank(),
            axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
            axis.title.x = element_blank(),
            axis.title.y = element_markdown(),
            strip.background = element_blank(),
            legend.position = "top")
  )

[[1]]

Past versions of absolute_integrals-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[2]]

Past versions of absolute_integrals-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[3]]

Past versions of absolute_integrals-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[4]]

Past versions of absolute_integrals-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[5]]

Past versions of absolute_integrals-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[6]]

Past versions of absolute_integrals-6.png

Version	Author	Date
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[7]]

Past versions of absolute_integrals-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
231f7cd	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[8]]

Past versions of absolute_integrals-8.png

Version	Author	Date
7b6f27c	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[9]]

Past versions of absolute_integrals-9.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

full_join(
  pco2_product_annual_regression %>%
    filter(year != 2023,
           name %in% name_core) %>%
    group_by(product, name, biome) %>% 
    summarise(resid_sd = sd(resid)) %>% 
    ungroup(),
  pco2_product_annual_regression %>%
    filter(year == 2023,
           name %in% name_core)) %>%
  mutate(
    region = case_when(
      biome == "Global" ~ "Global",
      biome %in% super_biomes ~ "Super biomes",
      TRUE ~ "Biomes"
    ),
    region = factor(region, levels = c("Global", "Super biomes", "Biomes"))
  ) %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_col(aes(biome, value - fit, fill = product),
                 position = "dodge2") +
      scale_fill_manual(values = color_products) +
      geom_col(aes(biome, resid_sd * sign(value - fit), 
                   group = product, col = paste0("Anomaly SD\nexcl.",2023)),
               position = "dodge2",
               fill = "transparent") +
      labs(y = labels_breaks(unique(.x$name))$i_legend_title,
           title = "Anomalies") +
      scale_color_grey() +
      facet_grid(.~region, scales = "free_x", space = "free_x") +
      theme(legend.title = element_blank(),
            axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
            axis.title.x = element_blank(),
            axis.title.y = element_markdown(),
            strip.background = element_blank(),
            legend.position = "top")
  )

[[1]]

Past versions of absolute_anomaly_integrals-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[2]]

Past versions of absolute_anomaly_integrals-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[3]]

Past versions of absolute_anomaly_integrals-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[4]]

Past versions of absolute_anomaly_integrals-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[5]]

Past versions of absolute_anomaly_integrals-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[6]]

Past versions of absolute_anomaly_integrals-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
60abdac	jens-daniel-mueller	2024-04-23
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[7]]

Past versions of absolute_anomaly_integrals-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
231f7cd	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[8]]

Past versions of absolute_anomaly_integrals-8.png

Version	Author	Date
7b6f27c	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[9]]

Past versions of absolute_anomaly_integrals-9.png

Version	Author	Date
7b6f27c	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[10]]

Past versions of absolute_anomaly_integrals-10.png

Version	Author	Date
7b6f27c	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[11]]

Past versions of absolute_anomaly_integrals-11.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05

[[12]]

Past versions of absolute_anomaly_integrals-12.png

Version	Author	Date
7b6f27c	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[13]]

Past versions of absolute_anomaly_integrals-13.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

Global region definition

pco2_product_annual_regression_recompute <-
  full_join(
    pco2_product_annual_regression,
    biome_mask %>%
      mutate(area = earth_surf(lat, lon)) %>%
      group_by(biome) %>%
      summarise(area = sum(area)) %>%
      ungroup() %>%
      filter(biome != "Global")
  ) %>% 
  pivot_longer(value:resid,
               names_to = "estimate") %>% 
  pivot_wider()

pco2_product_annual_regression_recompute <-
bind_rows(
  # pco2_product_annual_regression %>%
  #   mutate(region = case_when(biome == "Global" ~ "Global (direct)")) %>%
  #   filter(!(is.na(region))) %>%
  #   pivot_longer(value:resid,
  #                names_to = "estimate") %>%
  #   pivot_wider(),
  pco2_product_annual_regression_recompute %>%
    filter(biome != "Global",
           !(biome %in% super_biomes)) %>%
    select(-biome) %>% 
    group_by(product, estimate, year) %>%
    summarise(across(-c(fgco2_int, area),
                     ~ weighted.mean(., area, na.rm = TRUE)),
              across(fgco2_int,
                     ~ sum(., na.rm = TRUE))) %>%
    ungroup() %>%
    mutate(region = "Global all"),
  pco2_product_annual_regression_recompute %>%
    filter(biome != "Global",
           !str_detect(biome, "SO"),
           !(biome %in% super_biomes)) %>%
    select(-biome) %>% 
    group_by(product, estimate, year) %>%
    summarise(across(-c(fgco2_int, area),
                     ~ weighted.mean(., area, na.rm = TRUE)),
              across(fgco2_int,
                     ~ sum(., na.rm = TRUE))) %>%
    ungroup() %>%
    mutate(region = "Global excl. SO"),
  pco2_product_annual_regression_recompute %>%
    filter(str_detect(biome, "NA-|SA-|AEQU")) %>%
    select(-biome) %>% 
    group_by(product, estimate, year) %>%
    summarise(across(-c(fgco2_int, area),
                     ~ weighted.mean(., area, na.rm = TRUE)),
              across(fgco2_int,
                     ~ sum(., na.rm = TRUE))) %>%
    ungroup() %>%
    mutate(region = "Global Atlantic"),
  pco2_product_annual_regression_recompute %>%
    filter(str_detect(biome, "NA")) %>%
    select(-biome) %>% 
    group_by(product, estimate, year) %>%
    summarise(across(-c(fgco2_int, area),
                     ~ weighted.mean(., area, na.rm = TRUE)),
              across(fgco2_int,
                     ~ sum(., na.rm = TRUE))) %>%
    ungroup() %>%
    mutate(region = "Global NA only")) %>% 
  mutate(region = fct_inorder(region)) %>% 
  pivot_longer(-c(product, year, region, estimate)) %>% 
  pivot_wider(names_from = estimate)

pco2_product_annual_regression_recompute %>% 
  filter(year == 2023,
         name %in% c("fgco2", "fgco2_int", "dfco2")) %>%    
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_hline(yintercept = 0) +
      geom_col(aes(region, value, fill = product),
                 position = "dodge2") +
      scale_fill_manual(values = color_products) +
      geom_col(aes(region, fit, group = product, col = paste0(2023,"\nlinear\nprediction")),
               position = "dodge2",
               fill = "transparent") +
      labs(y = labels_breaks(unique(.x$name))$i_legend_title,
           title = "Absolute") +
      scale_color_grey() +
      facet_grid(.~region, scales = "free_x", space = "free_x") +
      theme(legend.title = element_blank(),
            axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
            axis.title.x = element_blank(),
            axis.title.y = element_markdown(),
            strip.background = element_blank(),
            legend.position = "top")
  )

[[1]]

Past versions of absolute_integrals_global_definitions-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[2]]

Past versions of absolute_integrals_global_definitions-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[3]]

Past versions of absolute_integrals_global_definitions-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

full_join(pco2_product_annual_regression_recompute %>%
  group_by(product, name, region) %>%
  summarise(resid_sd = sd(resid, na.rm = TRUE)) %>%
  ungroup(),
pco2_product_annual_regression_recompute %>%  
  filter(year == 2023)) %>% 
  filter(name %in% c("fgco2",
                     "fgco2_int",
                     "dfco2",
                     "kw_sol",
                     "temperature",
                     "no3",
                     "mld",
                     "intpp",
                     "chl")) %>%    
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_col(aes(region, resid, fill = product),
               position = "dodge2") +
      scale_fill_manual(values = color_products) +
      geom_col(aes(region, resid_sd * sign(value - fit), 
                   group = product, col = paste0("Anomaly SD\nexcl.",2023)),
               position = "dodge2",
               fill = "transparent") +
      labs(y = labels_breaks(unique(.x$name))$i_legend_title,
           title = "Anomaly") +
      scale_color_grey() +
      facet_grid(. ~ region, scales = "free_x", space = "free_x") +
      theme(
        legend.title = element_blank(),
        axis.text.x = element_text(
          angle = 90,
          vjust = 0.5,
          hjust = 1
        ),
        axis.title.x = element_blank(),
        axis.title.y = element_markdown(),
        strip.background = element_blank(),
        legend.position = "top"
      )
  )

[[1]]

Past versions of absolute_integrals_global_definitions-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[2]]

Past versions of absolute_integrals_global_definitions-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[3]]

Past versions of absolute_integrals_global_definitions-6.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[4]]

Past versions of absolute_integrals_global_definitions-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[5]]

Past versions of absolute_integrals_global_definitions-8.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[6]]

Past versions of absolute_integrals_global_definitions-9.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[7]]

Past versions of absolute_integrals_global_definitions-10.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[8]]

Past versions of absolute_integrals_global_definitions-11.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[9]]

Past versions of absolute_integrals_global_definitions-12.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
4be90dd	jens-daniel-mueller	2024-05-27
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

Seasonal anomalies

Annual mean trends

pco2_product_annual_detrended %>%
  filter(biome %in% "Global",
         name %in% c("fgco2", "temperature"),
         product %in% pco2_product_list) %>%
  select(-c(time, product)) %>% 
  group_by(year, month, biome, name) %>% 
  summarise(across(where(is.numeric), mean)) %>% 
  ungroup() %>% 
  # mutate(product = "Ensemble mean") %>% 
  p_season(title = "Ensemble mean anomalies from predicted annual mean | Global",
           dim_col = NULL)

Past versions of anomalies_from_annual_mean_trends_overview_OceanSODA-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
555c1c8	jens-daniel-mueller	2024-05-27
1eefab2	jens-daniel-mueller	2024-05-21

pco2_product_annual_detrended %>% 
  filter(biome %in% "Global",
         name %in% c("fgco2", "temperature")) %>%
  p_season(title = "Anomalies from predicted annual mean | Global")

Past versions of anomalies_from_annual_mean_trends_overview_pCO2_products-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
1eefab2	jens-daniel-mueller	2024-05-21

pco2_product_annual_detrended %>% 
  filter(biome %in% "Global",
         name %in% name_core) %>%
  p_season(title = "Anomalies from predicted annual mean | Global")

Past versions of anomalies_from_annual_mean_trends_overview-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

pco2_product_annual_detrended %>%
  filter(biome %in% super_biomes,
         name %in% name_core) %>%
  group_split(biome) %>%
  # head(1) %>%
  map(~ p_season(
    df = .x,
    title = paste("Anomalies from predicted annual mean |", .x$biome)
  ))

[[1]]

Past versions of anomalies_from_annual_mean_trends_key_biomes_super-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[2]]

Past versions of anomalies_from_annual_mean_trends_key_biomes_super-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[3]]

Past versions of anomalies_from_annual_mean_trends_key_biomes_super-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

pco2_product_annual_detrended %>%
  filter(biome %in% key_biomes,
         name %in% name_core) %>%
  group_split(biome) %>%
  # head(1) %>%
  map(~ p_season(
    df = .x,
    title = paste("Anomalies from predicted annual mean |", .x$biome)
  ))

[[1]]

Past versions of anomalies_from_annual_mean_trends_key_biomes-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[2]]

Past versions of anomalies_from_annual_mean_trends_key_biomes-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
6709afa	jens-daniel-mueller	2024-04-12
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[3]]

Past versions of anomalies_from_annual_mean_trends_key_biomes-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
6709afa	jens-daniel-mueller	2024-04-12
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

[[4]]

Past versions of anomalies_from_annual_mean_trends_key_biomes-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14
6709afa	jens-daniel-mueller	2024-04-12
238d229	jens-daniel-mueller	2024-04-11
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
a83c8fc	jens-daniel-mueller	2024-04-03

Monthly mean trends

pco2_product_monthly_detrended %>% 
  filter(biome %in% "Global",
         name %in% name_core) %>%
  p_season(title = "Anomalies from predicted monthly mean | Global")

Past versions of anomalies_from_monthly_mean_trends_overview-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

pco2_product_monthly_detrended %>%
  filter(biome %in% super_biomes,
         name %in% name_core) %>%
  group_split(biome) %>%
  # head(1) %>%
  map(
    ~ p_season(df = .x,
               title = paste("Anomalies from predicted monthly mean |", .x$biome))
  )

[[1]]

Past versions of anomalies_from_monthly_mean_trends_key_biomes_super-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[2]]

Past versions of anomalies_from_monthly_mean_trends_key_biomes_super-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[3]]

Past versions of anomalies_from_monthly_mean_trends_key_biomes_super-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25

pco2_product_monthly_detrended %>%
  filter(biome %in% key_biomes,
         name %in% name_core) %>%
  group_split(biome) %>%
  # head(1) %>%
  map(~ p_season(
    df = .x,
    title = paste("Anomalies from predicted monthly mean |", .x$biome)
  ))

[[1]]

Past versions of anomalies_from_monthly_mean_trends_key_biomes-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[2]]

Past versions of anomalies_from_monthly_mean_trends_key_biomes-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[3]]

Past versions of anomalies_from_monthly_mean_trends_key_biomes-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[4]]

Past versions of anomalies_from_monthly_mean_trends_key_biomes-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
47f8868	jens-daniel-mueller	2024-05-15
589243f	jens-daniel-mueller	2024-05-15
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

Flux anomaly correlation

The following plots aim to unravel the correlation between biome-, super-biome- or globally- integrated monthly flux anomalies and the corresponding anomalies of the means/integrals of each other variable.

Anomalies are first presented are first presented in absolute units. Due to the different flux magnitudes, we need to plot the globally and biome-integrated fluxes separately. Secondly, we normalize the anomalies to the monthly spread (expressed as standard deviation) of the anomalies from 1990 to 2021.

Annual anomalies

Absolute

pco2_product_annual_regression %>%
  filter(biome %in% "Global",
         name %in% name_core) %>%
  select(-c(value, fit)) %>%
  pivot_wider(values_from = resid) %>%
  pivot_longer(-c(product, year, biome, fgco2_int))  %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(value, fgco2_int)) +
      geom_hline(yintercept = 0) +
      geom_point(
        data = . %>% filter(year != 2023),
        aes(fill = year),
        shape = 21
      ) +
      geom_smooth(
        data = . %>% filter(year != 2023),
        method = "lm",
        se = FALSE,
        fullrange = TRUE,
        aes(col = paste("Regression fit\nexcl.", 2023))
      ) +
      scale_color_grey() +
      scale_fill_grayC() +
      new_scale_fill() +
      geom_point(
        data = . %>% filter(between(year, 2023-1, 2023)),
        aes(fill = as.factor(year)),
        shape = 21,
        size = 2
      )  +
      scale_fill_manual(
        values = c("orange", "red"),
        guide = guide_legend(reverse = TRUE,
                             order = 1)
      ) +
      labs(y = labels_breaks("fgco2_int")$i_legend_title,
           x = labels_breaks(unique(.x$name))$i_legend_title) +
      facet_wrap(
        . ~ product,
        scales = "free_y",
        ncol = 2
      ) +
      theme(
        axis.title.x = element_markdown(),
        axis.title.y = element_markdown(),
        legend.title = element_blank()
      )
  )

[[1]]

Past versions of anomalies_correlation_absolute_annual_global-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[2]]

Past versions of anomalies_correlation_absolute_annual_global-2.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[3]]

Past versions of anomalies_correlation_absolute_annual_global-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[4]]

Past versions of anomalies_correlation_absolute_annual_global-4.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[5]]

Past versions of anomalies_correlation_absolute_annual_global-5.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[6]]

Past versions of anomalies_correlation_absolute_annual_global-6.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[7]]

Past versions of anomalies_correlation_absolute_annual_global-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[8]]

Past versions of anomalies_correlation_absolute_annual_global-8.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[9]]

Past versions of anomalies_correlation_absolute_annual_global-9.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[10]]

Past versions of anomalies_correlation_absolute_annual_global-10.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[11]]

Past versions of anomalies_correlation_absolute_annual_global-11.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[12]]

Past versions of anomalies_correlation_absolute_annual_global-12.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

pco2_product_annual_regression %>%
  filter(biome %in% super_biomes,
         name %in% name_core) %>%
  select(-c(value, fit)) %>%
  pivot_wider(values_from = resid) %>%
  pivot_longer(-c(product, year, biome, fgco2_int))  %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(value, fgco2_int)) +
      geom_hline(yintercept = 0) +
      geom_point(
        data = . %>% filter(year != 2023),
        aes(fill = year),
        shape = 21
      ) +
      geom_smooth(
        data = . %>% filter(year != 2023),
        method = "lm",
        se = FALSE,
        fullrange = TRUE,
        aes(col = paste("Regression fit\nexcl.", 2023))
      ) +
      scale_color_grey() +
      scale_fill_grayC() +
      new_scale_fill() +
      geom_point(
        data = . %>% filter(between(year, 2023-1, 2023)),
        aes(fill = as.factor(year)),
        shape = 21,
        size = 2
      )  +
      scale_fill_manual(
        values = c("orange", "red"),
        guide = guide_legend(reverse = TRUE,
                             order = 1)
      ) +
      labs(y = labels_breaks("fgco2_int")$i_legend_title,
           x = labels_breaks(unique(.x$name))$i_legend_title) +
      facet_grid(
        biome ~ product,
        scales = "free_y"
      ) +
      theme(
        axis.title.x = element_markdown(),
        axis.title.y = element_markdown(),
        legend.title = element_blank()
      )
  )

[[1]]

Past versions of anomalies_correlation_absolute_annual_biome_super-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[2]]

Past versions of anomalies_correlation_absolute_annual_biome_super-2.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[3]]

Past versions of anomalies_correlation_absolute_annual_biome_super-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[4]]

Past versions of anomalies_correlation_absolute_annual_biome_super-4.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[5]]

Past versions of anomalies_correlation_absolute_annual_biome_super-5.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[6]]

Past versions of anomalies_correlation_absolute_annual_biome_super-6.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[7]]

Past versions of anomalies_correlation_absolute_annual_biome_super-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[8]]

Past versions of anomalies_correlation_absolute_annual_biome_super-8.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[9]]

Past versions of anomalies_correlation_absolute_annual_biome_super-9.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[10]]

Past versions of anomalies_correlation_absolute_annual_biome_super-10.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[11]]

Past versions of anomalies_correlation_absolute_annual_biome_super-11.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[12]]

Past versions of anomalies_correlation_absolute_annual_biome_super-12.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

pco2_product_annual_regression %>%
  filter(biome %in% key_biomes,
         name %in% name_core) %>%
  select(-c(value, fit)) %>%
  pivot_wider(values_from = resid) %>%
  pivot_longer(-c(product, year, biome, fgco2_int))  %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(value, fgco2_int)) +
      geom_hline(yintercept = 0) +
      geom_point(
        data = . %>% filter(year != 2023),
        aes(fill = year),
        shape = 21
      ) +
      geom_smooth(
        data = . %>% filter(year != 2023),
        method = "lm",
        se = FALSE,
        fullrange = TRUE,
        aes(col = paste("Regression fit\nexcl.", 2023))
      ) +
      scale_color_grey() +
      scale_fill_grayC() +
      new_scale_fill() +
      geom_point(
        data = . %>% filter(between(year, 2023-1, 2023)),
        aes(fill = as.factor(year)),
        shape = 21,
        size = 2
      )  +
      scale_fill_manual(
        values = c("orange", "red"),
        guide = guide_legend(reverse = TRUE,
                             order = 1)
      ) +
      labs(y = labels_breaks("fgco2_int")$i_legend_title,
           x = labels_breaks(unique(.x$name))$i_legend_title) +
      facet_grid(
        biome ~ product,
        scales = "free_y"
      ) +
      theme(
        axis.title.x = element_markdown(),
        axis.title.y = element_markdown(),
        legend.title = element_blank()
      )
  )

[[1]]

Past versions of anomalies_correlation_absolute_annual_biome_key-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[2]]

Past versions of anomalies_correlation_absolute_annual_biome_key-2.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[3]]

Past versions of anomalies_correlation_absolute_annual_biome_key-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[4]]

Past versions of anomalies_correlation_absolute_annual_biome_key-4.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[5]]

Past versions of anomalies_correlation_absolute_annual_biome_key-5.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[6]]

Past versions of anomalies_correlation_absolute_annual_biome_key-6.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[7]]

Past versions of anomalies_correlation_absolute_annual_biome_key-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[8]]

Past versions of anomalies_correlation_absolute_annual_biome_key-8.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[9]]

Past versions of anomalies_correlation_absolute_annual_biome_key-9.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[10]]

Past versions of anomalies_correlation_absolute_annual_biome_key-10.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
dfcf790	jens-daniel-mueller	2024-04-11
d5075c5	jens-daniel-mueller	2024-04-11
19f40c9	jens-daniel-mueller	2024-04-05
a83c8fc	jens-daniel-mueller	2024-04-03

[[11]]

Past versions of anomalies_correlation_absolute_annual_biome_key-11.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[12]]

Past versions of anomalies_correlation_absolute_annual_biome_key-12.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

Monthly anomalies

Absolute

pco2_product_monthly_detrended %>%
  filter(biome == "Global") %>%
  select(-c(time, fit, value)) %>% 
  pivot_wider(values_from = resid) %>%
  pivot_longer(-c(product, year, month, biome, fgco2_int))  %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(value, fgco2_int)) +
      geom_hline(yintercept = 0) +
      geom_point(
        data = . %>% filter(year != 2023),
        aes(col = paste(min(year), max(year), sep = "-")),
        alpha = 0.2
      ) +
      geom_smooth(
        data = . %>% filter(year != 2023),
        aes(col = paste(min(year), max(year), sep = "-")),
        method = "lm",
        se = FALSE,
        fullrange = TRUE
      )  +
      scale_color_grey(name = "") +
      new_scale_color() +
      geom_path(data = . %>% filter(year == 2023),
      aes(col = as.factor(month), group = 1))  +
      geom_point(
        data = . %>% filter(year == 2023),
        aes(fill =  as.factor(month)),
        shape = 21,
        size = 3
      )  +
      scale_color_scico_d(
        palette = "buda",
        guide = guide_legend(reverse = TRUE,
                             order = 1),
        name = paste("Month\nof", 2023)
      ) +
      scale_fill_scico_d(
        palette = "buda",
        guide = guide_legend(reverse = TRUE,
                             order = 1),
        name = paste("Month\nof", 2023)
      ) +
      labs(
        y = labels_breaks("fgco2_int")$i_legend_title,
        x = labels_breaks(unique(.x$name))$i_legend_title
      ) +
      facet_grid(biome ~ product,
                 scales = "free_y") +
      theme(
        axis.title.x = element_markdown(),
        axis.title.y = element_markdown()
      )
  )

[[1]]

Past versions of anomalies_correlation_absolute_monthly_global-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12
58e3680	jens-daniel-mueller	2024-04-11

[[2]]

Past versions of anomalies_correlation_absolute_monthly_global-2.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[3]]

Past versions of anomalies_correlation_absolute_monthly_global-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[4]]

Past versions of anomalies_correlation_absolute_monthly_global-4.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[5]]

Past versions of anomalies_correlation_absolute_monthly_global-5.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[6]]

Past versions of anomalies_correlation_absolute_monthly_global-6.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[7]]

Past versions of anomalies_correlation_absolute_monthly_global-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[8]]

Past versions of anomalies_correlation_absolute_monthly_global-8.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[9]]

Past versions of anomalies_correlation_absolute_monthly_global-9.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[10]]

Past versions of anomalies_correlation_absolute_monthly_global-10.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[11]]

Past versions of anomalies_correlation_absolute_monthly_global-11.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[12]]

Past versions of anomalies_correlation_absolute_monthly_global-12.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

pco2_product_monthly_detrended %>%
  filter(biome %in% super_biomes) %>%
  select(-c(time, fit, value)) %>% 
  pivot_wider(values_from = resid) %>%
  pivot_longer(-c(product, year, month, biome, fgco2_int))  %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(value, fgco2_int)) +
      geom_hline(yintercept = 0) +
      geom_point(
        data = . %>% filter(year != 2023),
        aes(col = paste(min(year), max(year), sep = "-")),
        alpha = 0.2
      ) +
      geom_smooth(
        data = . %>% filter(year != 2023),
        aes(col = paste(min(year), max(year), sep = "-")),
        method = "lm",
        se = FALSE,
        fullrange = TRUE
      )  +
      scale_color_grey(name = "") +
      new_scale_color() +
      geom_path(data = . %>% filter(year == 2023),
      aes(col = as.factor(month), group = 1))  +
      geom_point(
        data = . %>% filter(year == 2023),
        aes(fill =  as.factor(month)),
        shape = 21,
        size = 3
      )  +
      scale_color_scico_d(
        palette = "buda",
        guide = guide_legend(reverse = TRUE,
                             order = 1),
        name = paste("Month\nof", 2023)
      ) +
      scale_fill_scico_d(
        palette = "buda",
        guide = guide_legend(reverse = TRUE,
                             order = 1),
        name = paste("Month\nof", 2023)
      ) +
      labs(
        y = labels_breaks("fgco2_int")$i_legend_title,
        x = labels_breaks(unique(.x$name))$i_legend_title
      ) +
      facet_grid(biome ~ product,
                 scales = "free_y") +
      theme(
        axis.title.x = element_markdown(),
        axis.title.y = element_markdown()
      )
  )

[[1]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[2]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-2.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[3]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[4]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-4.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[5]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-5.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[6]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-6.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[7]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[8]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-8.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[9]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-9.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[10]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-10.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[11]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-11.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[12]]

Past versions of anomalies_correlation_absolute_monthly_biomes_super-12.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

pco2_product_monthly_detrended %>%
  filter(biome %in% key_biomes) %>%
  select(-c(time, fit, value)) %>% 
  pivot_wider(values_from = resid) %>%
  pivot_longer(-c(product, year, month, biome, fgco2_int))  %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(value, fgco2_int)) +
      geom_hline(yintercept = 0) +
      geom_point(
        data = . %>% filter(year != 2023),
        aes(col = paste(min(year), max(year), sep = "-")),
        alpha = 0.2
      ) +
      geom_smooth(
        data = . %>% filter(year != 2023),
        aes(col = paste(min(year), max(year), sep = "-")),
        method = "lm",
        se = FALSE,
        fullrange = TRUE
      )  +
      scale_color_grey(name = "") +
      new_scale_color() +
      geom_path(data = . %>% filter(year == 2023),
      aes(col = as.factor(month), group = 1))  +
      geom_point(
        data = . %>% filter(year == 2023),
        aes(fill =  as.factor(month)),
        shape = 21,
        size = 3
      )  +
      scale_color_scico_d(
        palette = "buda",
        guide = guide_legend(reverse = TRUE,
                             order = 1),
        name = paste("Month\nof", 2023)
      ) +
      scale_fill_scico_d(
        palette = "buda",
        guide = guide_legend(reverse = TRUE,
                             order = 1),
        name = paste("Month\nof", 2023)
      ) +
      labs(
        y = labels_breaks("fgco2_int")$i_legend_title,
        x = labels_breaks(unique(.x$name))$i_legend_title
      ) +
      facet_grid(biome ~ product,
                 scales = "free_y") +
      theme(
        axis.title.x = element_markdown(),
        axis.title.y = element_markdown()
      )
  )

[[1]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[2]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-2.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[3]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[4]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-4.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[5]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-5.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[6]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-6.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[7]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-7.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[8]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-8.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
dbc1fc6	jens-daniel-mueller	2024-05-16
589243f	jens-daniel-mueller	2024-05-15
009791f	jens-daniel-mueller	2024-05-14
8c96de4	jens-daniel-mueller	2024-05-08
3fea035	jens-daniel-mueller	2024-05-08
4b81eaf	jens-daniel-mueller	2024-05-07
60abdac	jens-daniel-mueller	2024-04-23
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[9]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-9.png

Version	Author	Date
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25
e44a62b	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[10]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-10.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
e44a62b	jens-daniel-mueller	2024-04-23
7f9c687	jens-daniel-mueller	2024-04-23
1ff6eb0	jens-daniel-mueller	2024-04-22
9ecd92e	jens-daniel-mueller	2024-04-22
231f7cd	jens-daniel-mueller	2024-04-17
a5911f0	jens-daniel-mueller	2024-04-17
6709afa	jens-daniel-mueller	2024-04-12

[[11]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-11.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

[[12]]

Past versions of anomalies_correlation_absolute_monthly_biomes_key-12.png

Version	Author	Date
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27

fCO2 decomposition

# pco2_product_biome_monthly_fCO2_decomposition <-
#   fco2_decomposition(pco2_product_annual_detrended %>%
#                        select(-c(time)),
#                      biome, year, month)


pco2_product_biome_monthly_fCO2_decomposition <-
  full_join(pco2_product_coarse_monthly_fCO2_decomposition,
            biome_mask,
            relationship = "many-to-many") %>% 
  group_by(product, year, month, biome, name) %>% 
  summarise(resid = mean(resid, na.rm = TRUE)) %>% 
  ungroup() %>% 
  drop_na()


pco2_product_biome_annual_fCO2_decomposition <-
  pco2_product_biome_monthly_fCO2_decomposition %>%
  group_by(product, year, biome, name) %>%
  summarise(resid = mean(resid)) %>%
  ungroup()



pco2_product_biome_monthly_fCO2_decomposition %>%
  filter(biome %in% "Global") %>%
  group_split(biome) %>%
  # head(1) %>%
  map(
    ~ p_season(df = .x,
               title  = paste("Anomalies from predicted monthly mean |", .x$biome))
  )

[[1]]

Past versions of pCO2_decomposition-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

# pco2_product_biome_monthly_fCO2_decomposition %>%
#   filter(biome %in% super_biomes) %>%
#   group_split(biome) %>%
#   # head(1) %>%
#   map(
#     ~ p_season(df = .x,
#                title  = paste("Anomalies from predicted monthly mean |", .x$biome))
#   )

pco2_product_biome_monthly_fCO2_decomposition %>%
  filter(biome %in% key_biomes) %>%
  group_split(biome) %>%
  # head(1) %>%
  map(
    ~ p_season(df = .x,
               title  = paste("Anomalies from predicted monthly mean |", .x$biome))
  )

[[1]]

Past versions of pCO2_decomposition-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[2]]

Past versions of pCO2_decomposition-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[3]]

Past versions of pCO2_decomposition-4.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
1e4c153	jens-daniel-mueller	2024-05-14
009791f	jens-daniel-mueller	2024-05-14

[[4]]

Past versions of pCO2_decomposition-5.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
5af03d1	jens-daniel-mueller	2024-05-17
dbc1fc6	jens-daniel-mueller	2024-05-16
1e4c153	jens-daniel-mueller	2024-05-14

Flux attribution

Seasonal

pco2_product_biome_monthly_flux_attribution <-
  full_join(pco2_product_coarse_monthly_flux_attribution,
            biome_mask,
            relationship = "many-to-many") %>% 
  group_by(product, year, month, biome, name) %>% 
  summarise(resid = mean(resid, na.rm = TRUE)) %>% 
  ungroup() %>% 
  drop_na()

pco2_product_biome_monthly_flux_attribution_total <-
  full_join(pco2_product_coarse_monthly_regression %>% 
              filter(name == "fgco2") %>% 
              mutate(name = "resid_fgco2"),
            biome_mask,
            relationship = "many-to-many") %>% 
  group_by(product, year, month, biome, name) %>% 
  summarise(resid = mean(resid, na.rm = TRUE)) %>% 
  ungroup() %>% 
  drop_na()

pco2_product_biome_monthly_flux_attribution <-
  bind_rows(
    pco2_product_biome_monthly_flux_attribution,
    pco2_product_biome_monthly_flux_attribution_total
  )


pco2_product_biome_annual_flux_attribution <-
  pco2_product_biome_monthly_flux_attribution %>%
  group_by(product, year, biome, name) %>%
  summarise(resid = mean(resid)) %>%
  ungroup()


ggplot() +
  geom_hline(yintercept = 0) +
  geom_col(
    data = pco2_product_biome_annual_flux_attribution %>%
      filter(year == 2023,
             biome %in% c("Global", key_biomes),
             product %in% pco2_product_list) %>% 
      group_by(biome, name) %>% 
      summarise(resid = mean(resid)) %>% 
      ungroup(),
    aes("", resid),
    fill = "grey90", col = "grey20"
  ) +
  geom_point(
    data = pco2_product_biome_annual_flux_attribution %>%
      filter(year == 2023,
             biome %in% c("Global", key_biomes)),
    aes("", resid, fill = product),
    shape = 21
  ) +
  scale_fill_manual(values = color_products) +
  scale_y_continuous(breaks = seq(-10,10,0.1)) +
  labs(y = labels_breaks(unique("fgco2"))$i_legend_title) +
  facet_grid(biome ~ name,
             labeller = labeller(name = x_axis_labels),
             scales = "free_y",
             space = "free_y",
             switch = "x") +
  theme(
    legend.title = element_blank(),
    axis.text.x = element_blank(),
    axis.ticks.x = element_blank(),
    axis.title.x = element_blank(),
    axis.title.y = element_markdown(),
    strip.text.x.bottom = element_markdown(),
    strip.placement = "outside",
    strip.background.x = element_blank(),
    legend.position = "top"
  )

Past versions of flux_attribution-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
563345f	jens-daniel-mueller	2024-05-21
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15
00ad9d5	jens-daniel-mueller	2024-05-15
47f8868	jens-daniel-mueller	2024-05-15

ggplot() +
  geom_hline(yintercept = 0) +
  geom_col(
    data = pco2_product_biome_annual_flux_attribution %>%
      filter(year == 2023,
             biome %in% c("Global", key_biomes)),
    aes("", resid, fill = product),
    position = position_dodge(width = 1),
    alpha = 0.5, col = "grey30"
  ) +
  geom_point(
    data = pco2_product_biome_monthly_flux_attribution %>%
      filter(year == 2023,
             biome %in% c("Global", key_biomes)),
    aes("", resid, fill = product),
    position = position_dodge(width = 1),
    shape = 21, alpha = 0.5, col = "grey30"
  ) +
  scale_fill_manual(values = color_products) +
  # scale_color_manual(values = color_products) +
  scale_y_continuous(breaks = seq(-10,10,0.2)) +
  labs(y = labels_breaks(unique("fgco2"))$i_legend_title) +
  facet_grid(biome ~ name,
             labeller = labeller(name = x_axis_labels),
                          scales = "free_y",
             space = "free_y",
             switch = "x") +
  theme(
    legend.title = element_blank(),
    axis.text.x = element_blank(),
    axis.ticks.x = element_blank(),
    axis.title.x = element_blank(),
    axis.title.y = element_markdown(),
    strip.text.x.bottom = element_markdown(),
    strip.placement = "outside",
    strip.background.x = element_blank(),
    legend.position = "top"
  )

Past versions of flux_attribution-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
563345f	jens-daniel-mueller	2024-05-21
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15
00ad9d5	jens-daniel-mueller	2024-05-15
47f8868	jens-daniel-mueller	2024-05-15

pco2_product_biome_monthly_flux_attribution %>%
  filter(year == 2023,
         biome %in% c("Global", key_biomes)) %>%
  ggplot() +
  geom_hline(yintercept = 0) +
  geom_path(
    aes(month, resid, col = product)
  ) +
  geom_point(
    aes(month, resid, fill = product),
    shape = 21,
    alpha = 0.5,
    col = "grey30"
  ) +
  scale_fill_manual(values = color_products) +
  scale_color_manual(values = color_products) +
  scale_y_continuous(breaks = seq(-10,10,0.2)) +
  scale_x_continuous(position = "top", breaks = seq(1,12,3)) +
  labs(y = labels_breaks(unique("fgco2"))$i_legend_title) +
  facet_grid(biome ~ name,
             labeller = labeller(name = x_axis_labels),
             scales = "free_y",
             space = "free_y", 
             switch = "x") +
  theme(
    legend.title = element_blank(),
    axis.title.y = element_markdown(),
    strip.text.x.bottom = element_markdown(),
    strip.placement = "outside",
    strip.background.x = element_blank(),
    legend.position = "top"
  )

Past versions of flux_attribution-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
571e2f8	jens-daniel-mueller	2024-05-22
563345f	jens-daniel-mueller	2024-05-21
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
b7d0689	jens-daniel-mueller	2024-05-15
00ad9d5	jens-daniel-mueller	2024-05-15
47f8868	jens-daniel-mueller	2024-05-15

pco2_product_biome_monthly_flux_attribution %>%
  filter(biome %in% "Global") %>% 
  group_split(biome) %>%
  map(
    ~ p_season(
      df = .x,
      title  = paste("Anomalies from predicted monthly mean |", .x$biome)
    ) +
      facet_grid(
        name ~ product,
        labeller = labeller(name = x_axis_labels),
        switch = "y"
      ) +
      theme(
        strip.text.y.left = element_markdown(),
        strip.placement = "outside",
        strip.background.y = element_blank(),
        axis.title.y = element_blank(),
        legend.title = element_blank()
      )
  )

[[1]]

Past versions of flux_attribution_seasonal-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

pco2_product_biome_monthly_flux_attribution %>%
  filter(biome %in% super_biomes) %>% 
  group_split(biome) %>%
  # head(1) %>%
  map(
    ~ p_season(
      df = .x,
      title  = paste("Anomalies from predicted monthly mean |", .x$biome)
    ) +
      facet_grid(
        name ~ product,
        labeller = labeller(name = x_axis_labels),
        switch = "y"
      ) +
      theme(
        strip.text.y.left = element_markdown(),
        strip.placement = "outside",
        strip.background.y = element_blank(),
        axis.title.y = element_blank(),
        legend.title = element_blank()
      )
  )

list()

pco2_product_biome_monthly_flux_attribution %>%
  filter(biome %in% key_biomes) %>% 
  group_split(biome) %>%
  # head(1) %>%
  map(
    ~ p_season(
      df = .x,
      title  = paste("Anomalies from predicted monthly mean |", .x$biome)
    ) +
      facet_grid(
        name ~ product,
        labeller = labeller(name = x_axis_labels),
        switch = "y"
      ) +
      theme(
        strip.text.y.left = element_markdown(),
        strip.placement = "outside",
        strip.background.y = element_blank(),
        axis.title.y = element_blank(),
        legend.title = element_blank()
      )
  )

[[1]]

Past versions of flux_attribution_seasonal-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

[[2]]

Past versions of flux_attribution_seasonal-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

[[3]]

Past versions of flux_attribution_seasonal-4.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

[[4]]

Past versions of flux_attribution_seasonal-5.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

Annual

pco2_product_biome_annual_flux_attribution <-
full_join(
pco2_product_biome_annual_flux_attribution %>% 
  filter(year == 2023) %>% 
  select(-year),
pco2_product_biome_annual_flux_attribution %>% 
  filter(year != 2023) %>% 
  group_by(product, biome, name) %>% 
  summarise(resid_mean = mean(abs(resid))) %>% 
  ungroup())

pco2_product_biome_annual_flux_attribution %>%
  filter(biome %in% "Global") %>% 
  group_split(biome) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_col(aes("x", resid, fill = product),
               position = "dodge2") +
      scale_fill_manual(values = color_products) +
      geom_col(
        aes(
          "x",
          resid_mean * sign(resid),
          group = product,
          col = paste0("Mean\nexcl.",2023)
        ),
        position = "dodge2",
        fill = "transparent"
      ) +
      labs(y = labels_breaks(unique("fgco2"))$i_legend_title,
           title = .x$biome) +
      facet_grid(
        .~name,
        labeller = labeller(name = x_axis_labels),
        switch = "x"
      ) +
      scale_color_grey() +
      theme(
        legend.title = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        axis.title.x = element_blank(),
        axis.title.y = element_markdown(),
        strip.text.x.bottom = element_markdown(),
        strip.placement = "outside",
        strip.background.x = element_blank(),
        legend.position = "top"
      )
  )

[[1]]

Past versions of flux_attribution_annual-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

pco2_product_biome_annual_flux_attribution %>%
  filter(biome %in% key_biomes) %>% 
  group_split(biome) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_col(aes("x", resid, fill = product),
               position = "dodge2") +
      scale_fill_manual(values = color_products) +
      geom_col(
        aes(
          "x",
          resid_mean * sign(resid),
          group = product,
          col = paste0("Mean\nexcl.",2023)
        ),
        position = "dodge2",
        fill = "transparent"
      ) +
      labs(y = labels_breaks(unique("fgco2"))$i_legend_title,
           title = .x$biome) +
      facet_grid(
        .~name,
        labeller = labeller(name = x_axis_labels),
        switch = "x"
      ) +
      scale_color_grey() +
      theme(
        legend.title = element_blank(),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        axis.title.x = element_blank(),
        axis.title.y = element_markdown(),
        strip.text.x.bottom = element_markdown(),
        strip.placement = "outside",
        strip.background.x = element_blank(),
        legend.position = "top"
      )
  )

[[1]]

Past versions of flux_attribution_annual-2.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

[[2]]

Past versions of flux_attribution_annual-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

[[3]]

Past versions of flux_attribution_annual-4.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

[[4]]

Past versions of flux_attribution_annual-5.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
7b6f27c	jens-daniel-mueller	2024-05-27
29e0ec4	jens-daniel-mueller	2024-05-21
7c08e1c	jens-daniel-mueller	2024-05-21
dbc1fc6	jens-daniel-mueller	2024-05-16
aea0b99	jens-daniel-mueller	2024-05-16
3310cf6	jens-daniel-mueller	2024-05-16
b7d0689	jens-daniel-mueller	2024-05-15

Merged seasonality plots

key_biomes <- key_biomes[!str_detect(key_biomes, "NP")]


pco2_product_monthly_detrended %>% 
  filter(product == "OceanSODA",
         name %in% c("temperature", "fgco2"),
         biome %in% key_biomes) %>%
  p_season(dim_col = "biome",
           title = "Anomalies from predicted monthly mean")

Past versions of merged_seasonality_OceanSODA-1.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
7868a54	jens-daniel-mueller	2024-05-22

pco2_product_biome_monthly_flux_attribution %>%
  filter(
    product == "OceanSODA",
    name %in% c("resid_fgco2_dfco2", "resid_fgco2_kw_sol"),
    biome %in% key_biomes
  ) %>%
  p_season(dim_col = "biome",
           title = "Main drivers of flux anomaly",
           scales = "fixed")

Past versions of merged_seasonality_OceanSODA-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
7868a54	jens-daniel-mueller	2024-05-22

pco2_product_biome_monthly_fCO2_decomposition %>%
  filter(product == "OceanSODA",
         name %in% c("sfco2_nontherm", "sfco2_therm"),
         biome %in% key_biomes) %>%
  p_season(dim_col = "biome",
           title = "Decomposition of fCO2 anomaly",
           scales = "fixed")  

Past versions of merged_seasonality_OceanSODA-3.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
fe97ed3	jens-daniel-mueller	2024-05-25
7868a54	jens-daniel-mueller	2024-05-22

pco2_product_monthly_detrended %>%
  filter(product %in% pco2_product_list) %>%
  group_by(year, month, biome, name) %>%
  summarise(across(where(is.numeric), mean)) %>%
  ungroup() %>%
  filter(name %in% c("temperature", "fgco2"),
         biome %in% key_biomes) %>%
  p_season(dim_col = "biome",
           title = "Ensemble mean anomalies from predicted monthly mean")

Past versions of merged_seasonality_ensemble_mean-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28

pco2_product_biome_monthly_flux_attribution %>%
  filter(product %in% pco2_product_list) %>%
  group_by(year, month, biome, name) %>%
  summarise(across(where(is.numeric), mean)) %>%
  ungroup() %>%
  filter(name %in% c("resid_fgco2_dfco2", "resid_fgco2_kw_sol"),
         biome %in% key_biomes) %>%
  p_season(dim_col = "biome",
           title = "Ensemble mean drivers of flux anomaly",
           scales = "fixed")

Past versions of merged_seasonality_ensemble_mean-2.png

Version	Author	Date
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28

pco2_product_biome_monthly_fCO2_decomposition %>%
  filter(product %in% pco2_product_list) %>%
  group_by(year, month, biome, name) %>%
  summarise(across(where(is.numeric), mean)) %>%
  ungroup() %>%
  filter(name %in% c("sfco2_nontherm", "sfco2_therm"),
         biome %in% key_biomes) %>%
  p_season(dim_col = "biome",
           title = "Ensemble mean decomposition of fCO2 anomaly",
           scales = "fixed")  

Past versions of merged_seasonality_ensemble_mean-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
b754e95	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28

pco2_product_monthly_detrended %>% 
  filter(year == 2023,
         name %in% c("temperature", "fgco2"),
         biome %in% key_biomes) %>%
  ggplot(aes(month, resid)) +
  geom_hline(yintercept = 0, linewidth = 0.5) +
  geom_path(aes(col = product)) +
  scale_color_manual(values = color_products) +
  scale_x_continuous(breaks = seq(1, 12, 3), expand = c(0, 0)) +
  labs(x = "Month",
       title = "Anomalies from predicted monthly mean") +
  facet_grid(
    name ~ biome,
    scales = "free_y",
    labeller = labeller(name = x_axis_labels),
    switch = "y"
  ) +
  theme(
    strip.text.y.left = element_markdown(),
    strip.placement = "outside",
    strip.background.y = element_blank(),
    axis.title.y = element_blank(),
    legend.title = element_blank()
  )

Past versions of merged_seasonality_all_products-1.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
7868a54	jens-daniel-mueller	2024-05-22

pco2_product_biome_monthly_flux_attribution %>%
  filter(year == 2023,
         name %in% c("resid_fgco2_dfco2", "resid_fgco2_kw_sol"),
         biome %in% key_biomes) %>%
  ggplot(aes(month, resid)) +
  geom_hline(yintercept = 0, linewidth = 0.5) +
  geom_path(aes(col = product)) +
  scale_color_manual(values = color_products) +
  scale_x_continuous(breaks = seq(1, 12, 3), expand = c(0, 0)) +
  labs(x = "Month",
       title = "Main drivers of flux anomaly") +
  facet_grid(
    name ~ biome,
    scales = "fixed",
    labeller = labeller(name = x_axis_labels),
    switch = "y"
  ) +
  theme(
    strip.text.y.left = element_markdown(),
    strip.placement = "outside",
    strip.background.y = element_blank(),
    axis.title.y = element_blank(),
    legend.title = element_blank()
  )

Past versions of merged_seasonality_all_products-2.png

Version	Author	Date
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
7868a54	jens-daniel-mueller	2024-05-22

pco2_product_biome_monthly_fCO2_decomposition %>% 
  filter(year == 2023,
         name %in% c("sfco2_nontherm", "sfco2_therm"),
         biome %in% key_biomes) %>%
  ggplot(aes(month, resid)) +
  geom_hline(yintercept = 0, linewidth = 0.5) +
  geom_path(aes(col = product)) +
  scale_color_manual(values = color_products) +
  scale_x_continuous(breaks = seq(1, 12, 3), expand = c(0, 0)) +
  labs(x = "Month",
       title = "Decomposition of fCO2 anomaly") +
  facet_grid(
    name ~ biome,
    scales = "fixed",
    labeller = labeller(name = x_axis_labels),
    switch = "y"
  ) +
  theme(
    strip.text.y.left = element_markdown(),
    strip.placement = "outside",
    strip.background.y = element_blank(),
    axis.title.y = element_blank(),
    legend.title = element_blank()
  )

Past versions of merged_seasonality_all_products-3.png

Version	Author	Date
b99b329	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
fe97ed3	jens-daniel-mueller	2024-05-25
7868a54	jens-daniel-mueller	2024-05-22

Zonal mean sections

The following analysis is available for GOBMs only.

Annual means

2023 anomaly

pco2_product_zonal_mean_sections_annual %>%
  filter(year == 2023,
         region != "Southern") %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_contour_filled(aes(lat, depth, z = resid)) +
      scale_fill_gradientn(colours = cmocean(name = "curl")(100),
                           rescaler = ~ scales::rescale_mid(.x, mid = 0),
                           super = ScaleDiscretised,
                           name = labels_breaks(.x %>% distinct(name))$i_legend_title) +
      # scale_fill_distiller(type = "div",
      #                      palette = "RdBu",
      #                      rescaler = ~ scales::rescale_mid(.x, mid = 0),
      #                      super = ScaleDiscretised,
      #                      name = labels_breaks(.x %>% distinct(name))$i_legend_title) +
      scale_y_continuous(trans = trans_reverser("sqrt"),
                         breaks = c(50, 100, 200, 400)) +
      scale_x_continuous(breaks = seq(-100, 100, 20)) +
      coord_cartesian(expand = 0) +
      facet_grid(region ~ product) +
      labs(y = "Depth (m)", x = "Latitude (°N)") +
      guides(
        fill = guide_colorsteps(
          barheight = unit(0.3, "cm"),
          barwidth = unit(6, "cm"),
          ticks = TRUE,
          ticks.colour = "grey20",
          frame.colour = "grey20",
          label.position = "top",
          direction = "horizontal"
        )
      ) +
      theme(
        legend.position = "top",
        legend.title.align = 1,
        legend.box.spacing = unit(0.1, "cm"),
        legend.title = element_markdown(halign = 1,
                                        lineheight = 1.5)
      )
  )

[[1]]

Past versions of 2023_anomaly_zonal_mean_sections_annual-1.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25

[[2]]

Past versions of 2023_anomaly_zonal_mean_sections_annual-2.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25

[[3]]

Past versions of 2023_anomaly_zonal_mean_sections_annual-3.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

[[4]]

Past versions of 2023_anomaly_zonal_mean_sections_annual-4.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

[[5]]

Past versions of 2023_anomaly_zonal_mean_sections_annual-5.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

Biome profiles

The following analysis is available for GOBMs only.

Annual means

2023 anomaly

pco2_product_profiles_annual %>%
  filter(biome %in% key_biomes) %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_vline(xintercept = 0) +
      geom_path(aes(resid, depth, group = year), col = "grey30", alpha = 0.3) +
      geom_path(data = .x %>% filter(year == 2023),
                aes(resid, depth, col = as.factor(year)),
                linewidth = 1) +
      scale_color_brewer(palette = "Set1") +
      scale_y_continuous(trans = trans_reverser("sqrt"),
                         breaks = c(50,100,200,400)) +
      coord_cartesian(expand = 0) +
      facet_grid2(biome ~ product,
                  scales = "free_x", independent = "x") +
      labs(y = "Depth (m)",
           x = labels_breaks(.x %>% distinct(name))$i_legend_title) +
      theme(legend.title = element_blank(),
            axis.title.x = element_markdown())
  )

[[1]]

Past versions of 2023_anomaly_profiles_annual-1.png

Version	Author	Date
d533f68	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25

[[2]]

Past versions of 2023_anomaly_profiles_annual-2.png

Version	Author	Date
d533f68	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25

[[3]]

Past versions of 2023_anomaly_profiles_annual-3.png

Version	Author	Date
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

[[4]]

Past versions of 2023_anomaly_profiles_annual-4.png

Version	Author	Date
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

[[5]]

Past versions of 2023_anomaly_profiles_annual-5.png

Version	Author	Date
d533f68	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

Monthly means

2023 anomaly

pco2_product_profiles_monthly %>%
  filter(year == 2023,
         biome %in% key_biomes) %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x) +
      geom_vline(xintercept = 0) +
      geom_path(aes(resid, depth, col = as.factor(month)),
                linewidth = 1) +
      scale_color_viridis_d(option = "magma", end = .8) +
      scale_y_continuous(trans = trans_reverser("sqrt"),
                         breaks = c(50,100,200,400)) +
      coord_cartesian(expand = 0) +
      facet_grid2(biome ~ product,
                  scales = "free_x", independent = "x") +
      labs(y = "Depth (m)",
           x = labels_breaks(.x %>% distinct(name))$i_legend_title) +
      theme(legend.title = element_blank(),
            axis.title.x = element_markdown())
  )

[[1]]

Past versions of 2023_anomaly_profiles_monthly-1.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25

[[2]]

Past versions of 2023_anomaly_profiles_monthly-2.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
97eff6a	jens-daniel-mueller	2024-05-25

[[3]]

Past versions of 2023_anomaly_profiles_monthly-3.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

[[4]]

Past versions of 2023_anomaly_profiles_monthly-4.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

[[5]]

Past versions of 2023_anomaly_profiles_monthly-5.png

Version	Author	Date
fbba0a0	jens-daniel-mueller	2024-05-28
d533f68	jens-daniel-mueller	2024-05-28
e1e0ccb	jens-daniel-mueller	2024-05-27
7013182	jens-daniel-mueller	2024-05-27
97eff6a	jens-daniel-mueller	2024-05-25

pco2_product_profiles_monthly %>%
  filter(year == 2023,
         biome %in% key_biomes,
         product == "ETHZ_CESM",
         name != "cstar") %>% 
  ggplot() +
  geom_vline(xintercept = 0) +
  geom_path(aes(resid, depth, col = as.factor(month)),
            linewidth = 1) +
  scale_color_viridis_d(option = "magma", end = .8,
                        name = paste("Month of\n", 2023)) +
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(50, 100, 200, 400)) +
  coord_cartesian(expand = 0) +
  facet_grid2(
    biome ~ name,
    scales = "free_x",
    independent = "x",
    labeller = labeller(name = x_axis_labels),
    switch = "x"
  ) +
  theme(
    strip.text.x.bottom = element_markdown(),
    strip.placement = "outside",
    strip.background.x = element_blank(),
    axis.title.x = element_blank(),
    legend.title = element_blank()
  ) +
  labs(y = "Depth (m)")

Session information

sessionInfo()

R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.5

Matrix products: default
BLAS:   /usr/local/R-4.2.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.2.2/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] cmocean_0.3-1       ggh4x_0.2.3         scales_1.2.1       
 [4] biscale_1.0.0       ggtext_0.1.2        khroma_1.9.0       
 [7] ggnewscale_0.4.8    terra_1.7-65        sf_1.0-9           
[10] rnaturalearth_0.1.0 geomtextpath_0.1.1  colorspace_2.0-3   
[13] marelac_2.1.10      shape_1.4.6         ggforce_0.4.1      
[16] metR_0.13.0         scico_1.3.1         patchwork_1.1.2    
[19] collapse_1.8.9      forcats_0.5.2       stringr_1.5.0      
[22] dplyr_1.1.3         purrr_1.0.2         readr_2.1.3        
[25] tidyr_1.3.0         tibble_3.2.1        ggplot2_3.4.4      
[28] tidyverse_1.3.2     workflowr_1.7.0    

loaded via a namespace (and not attached):
  [1] googledrive_2.0.0       ellipsis_0.3.2          class_7.3-20           
  [4] rprojroot_2.0.3         markdown_1.4            fs_1.5.2               
  [7] gridtext_0.1.5          rstudioapi_0.15.0       proxy_0.4-27           
 [10] farver_2.1.1            bit64_4.0.5             fansi_1.0.3            
 [13] lubridate_1.9.0         xml2_1.3.3              splines_4.2.2          
 [16] codetools_0.2-18        cachem_1.0.6            knitr_1.41             
 [19] polyclip_1.10-4         jsonlite_1.8.3          gsw_1.1-1              
 [22] broom_1.0.5             dbplyr_2.2.1            compiler_4.2.2         
 [25] httr_1.4.4              backports_1.4.1         Matrix_1.5-3           
 [28] assertthat_0.2.1        fastmap_1.1.0           gargle_1.2.1           
 [31] cli_3.6.1               later_1.3.0             tweenr_2.0.2           
 [34] htmltools_0.5.3         tools_4.2.2             rnaturalearthdata_0.1.0
 [37] gtable_0.3.1            glue_1.6.2              Rcpp_1.0.11            
 [40] cellranger_1.1.0        jquerylib_0.1.4         vctrs_0.6.4            
 [43] nlme_3.1-160            xfun_0.35               ps_1.7.2               
 [46] rvest_1.0.3             timechange_0.1.1        lifecycle_1.0.3        
 [49] googlesheets4_1.0.1     oce_1.7-10              getPass_0.2-2          
 [52] MASS_7.3-58.1           vroom_1.6.0             hms_1.1.2              
 [55] promises_1.2.0.1        parallel_4.2.2          RColorBrewer_1.1-3     
 [58] yaml_2.3.6              memoise_2.0.1           sass_0.4.4             
 [61] stringi_1.7.8           highr_0.9               e1071_1.7-12           
 [64] checkmate_2.1.0         commonmark_1.8.1        rlang_1.1.1            
 [67] pkgconfig_2.0.3         systemfonts_1.0.4       evaluate_0.18          
 [70] lattice_0.20-45         SolveSAPHE_2.1.0        labeling_0.4.2         
 [73] bit_4.0.5               processx_3.8.0          tidyselect_1.2.0       
 [76] here_1.0.1              seacarb_3.3.1           magrittr_2.0.3         
 [79] R6_2.5.1                generics_0.1.3          DBI_1.1.3              
 [82] mgcv_1.8-41             pillar_1.9.0            haven_2.5.1            
 [85] whisker_0.4             withr_2.5.0             units_0.8-0            
 [88] sp_1.5-1                modelr_0.1.10           crayon_1.5.2           
 [91] KernSmooth_2.23-20      utf8_1.2.2              tzdb_0.3.0             
 [94] rmarkdown_2.18          isoband_0.2.6           grid_4.2.2             
 [97] readxl_1.4.1            data.table_1.14.6       callr_3.7.3            
[100] git2r_0.30.1            reprex_2.0.2            digest_0.6.30          
[103] classInt_0.4-8          httpuv_1.6.6            textshaping_0.3.6      
[106] munsell_0.5.0           viridisLite_0.4.1       bslib_0.4.1