Last updated: 2024-06-11

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Knit directory: heatwave_co2_flux_2023/analysis/

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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")

Read data

path_pCO2_products <-
  "/nfs/kryo/work/datasets/gridded/ocean/2d/observation/pco2/"

path_OceanSODA <-
  "/nfs/kryo/work/gregorl/projects/OceanSODA-ETHZ/releases/v2023-full_carbonate_system/OceanSODA_ETHZ_HRLR-v2023.01-co2fluxvars-netCDF/"
library(ncdf4)
nc <-
  nc_open(paste0(
    path_pCO2_products,
    "VLIZ-SOM_FFN/VLIZ-SOM_FFN_predict.nc"
  ))

print(nc)
print("VLIZ-SOM_FFN/VLIZ-SOM_FFN_vBAMS2024.nc")
[1] "VLIZ-SOM_FFN/VLIZ-SOM_FFN_vBAMS2024.nc"
pco2_product <-
  read_ncdf(
    paste0(
      path_pCO2_products,
      "VLIZ-SOM_FFN/VLIZ-SOM_FFN_predict.nc"
    ),
    var = c("dco2", "atm_co2", "sol", "kw", "spco2_smoothed", "fgco2_smoothed"),
    ignore_bounds = TRUE,
    make_units = FALSE
  )

pco2_product_input <-
  read_ncdf(
    paste0(
      path_pCO2_products,
      "VLIZ-SOM_FFN/VLIZ-SOM_FFN_inputs.nc"
    ),
    var = c("sst", "sss", "chl", "wind"),
    ignore_bounds = TRUE,
    make_units = FALSE
  )

pco2_product <- c(pco2_product, pco2_product_input)
rm(pco2_product_input)
  
pco2_product <- pco2_product %>%
  as_tibble()

pco2_product <-
  pco2_product %>%
  rename(spco2 = spco2_smoothed,
         fgco2 = fgco2_smoothed,
         salinity = sss,
         temperature = sst)

pco2_product <-
  pco2_product %>%
  mutate(across(-c(lon, lat, time), ~ replace(., . >= 1e+19, NA)))

pco2_product <-
  pco2_product %>%
  mutate(area = earth_surf(lat, lon),
         year = year(time),
         month = month(time))

pco2_product <-
  pco2_product %>% 
  mutate(lon = if_else(lon < 20, lon + 360, lon),
         wind = sqrt(wind))

pco2_product <-
  pco2_product %>%
  mutate(
    sfco2 = p2fCO2(T = temperature,
                   pCO2 = spco2),
    atm_fco2 = p2fCO2(T = temperature,
                      pCO2 = atm_co2),
    dfco2 = sfco2 - atm_fco2
  )

pco2_product <-
  pco2_product %>% 
  mutate(kw_sol = kw * sol)

# pco2_product %>% 
#   ggplot(aes(dco2-(spco2-atm_co2))) +
#   geom_histogram()
# 
# pco2_product %>% 
#   ggplot(aes(dfco2-(sfco2-atm_fco2))) +
#   geom_histogram()

pco2_product <-
  pco2_product %>%
  select(-c(dco2, atm_co2, spco2))
pCO2_product_preprocessing <-
  knitr::knit_expand(
    file = here::here("analysis/child/pCO2_product_preprocessing.Rmd"),
    product_name = "SOM_FFN"
  )

Preprocessing

# model <- TRUE
model <- str_detect('SOM_FFN', "FESOM-REcoM|ETHZ_CESM")

Load masks

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

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

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"))

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

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 == "sdissic") {
    i_legend_title <- "sDIC<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 == "stalk") {
    i_legend_title <- "sTA<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 == "so") {
    i_legend_title <- "salinity"
  }
  
  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")$i_legend_title,
    "sdissic" = labels_breaks("sdissic")$i_legend_title,
    "cstar" = labels_breaks("cstar")$i_legend_title,
    "talk" = labels_breaks("talk")$i_legend_title,
    "stalk" = labels_breaks("stalk")$i_legend_title,
    "spco2" = labels_breaks("spco2")$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,
    "so" = labels_breaks("so")$i_legend_title,
    "chl" = labels_breaks("chl")$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
  )

Analysis settings

name_quadratic_fit <- c("atm_co2", "atm_fco2", "spco2", "sfco2")

start_year <- 1990

name_divergent <- c("dco2", "dfco2", "fgco2", "fgco2_hov", "fgco2_int")

Data preprocessing

pco2_product <-
  pco2_product %>%
  filter(year >= start_year)
pco2_product_interior <-
  pco2_product_interior %>%
  filter(time >= ymd(paste0(start_year, "-01-01")))
biome_mask <- biome_mask %>% 
  mutate(area = earth_surf(lat, lon))

pco2_product <-
  full_join(pco2_product,
            biome_mask)

# set all values outside biome mask to NA

pco2_product <-
  pco2_product %>%
  mutate(across(-c(lat, lon, time, area, year, month, biome), 
                ~ if_else(is.na(biome), NA, .)))

Compuations

# apply coarse grid

pco2_product_coarse <-
  pco2_product %>%
  mutate(lon_grid = lon,
         lat_grid = lat)

# pco2_product_coarse <-
#   m_grid_horizontal_coarse(pco2_product)

# pco2_product_coarse <-
#   pco2_product_coarse %>%
#   select(-c(lon, lat, time, biome)) %>%
#   group_by(year, month, lon_grid, lat_grid) %>%
#   summarise(across(-area,
#                    ~ weighted.mean(., area))) %>%
#   ungroup() %>%
#   rename(lon = lon_grid, lat = lat_grid)

pco2_product_coarse <-
  pco2_product_coarse %>%
  select(-c(lon, lat, time, biome)) %>%
  fgroup_by(year, month, lon_grid, lat_grid) %>%
  fmean(w = area,
        keep.w = FALSE,
        na.rm = FALSE) %>%
  rename(lon = lon_grid, lat = lat_grid)

pco2_product_coarse <-
  pco2_product_coarse %>%
  pivot_longer(-c(year, month, lon, lat)) %>% 
  drop_na() %>%
  pivot_wider()

gc()
            used (Mb) gc trigger    (Mb)   max used    (Mb)
Ncells   3014204  161    5636098   301.1    5636098   301.1
Vcells 677374823 5168 3191650029 24350.4 3962783839 30233.7
# compute annual means

pco2_product_coarse_annual <-
  pco2_product_coarse %>%
  select(-month) %>% 
  fgroup_by(year, lon, lat) %>%
  fmean(na.rm = FALSE)

pco2_product_coarse_annual <-
  pco2_product_coarse_annual %>% 
  pivot_longer(-c(year, lon, lat))

## compute monthly means

pco2_product_coarse_monthly <-
  pco2_product_coarse %>%
  fgroup_by(year, month, lon, lat) %>%
  fmean()

pco2_product_coarse_monthly <-
  pco2_product_coarse_monthly %>% 
  pivot_longer(-c(year, month, lon, lat))

gc()
             used    (Mb) gc trigger    (Mb)   max used    (Mb)
Ncells    3014391   161.0    5636098   301.1    5636098   301.1
Vcells 1597586371 12188.7 3191650029 24350.4 3962783839 30233.7
pco2_product_monthly_global <-
  pco2_product %>%
  filter(!is.na(fgco2)) %>%
  mutate(fgco2_int = fgco2) %>%
  mutate(biome = case_when(str_detect(biome, "SO-") ~ "Southern Ocean",
                           TRUE ~ "other")) %>%
  filter(biome == "other") %>%
  select(-c(lon, lat, year, month, biome)) %>%
  group_by(time) %>%
  summarise(across(-c(fgco2_int, area),
                   ~ weighted.mean(., area, na.rm = TRUE)),
            across(fgco2_int,
                   ~ sum(. * area, na.rm = TRUE) * 12.01 * 1e-15)) %>%
  ungroup()

pco2_product_monthly_biome <-
  pco2_product %>%
  filter(!is.na(fgco2)) %>% 
  mutate(fgco2_int = fgco2) %>% 
  select(-c(lon, lat, year, month)) %>% 
  group_by(time, biome) %>%
  summarise(across(-c(fgco2_int, area),
                   ~ weighted.mean(., area, na.rm = TRUE)),
            across(fgco2_int,
                   ~ sum(. * area, na.rm = TRUE) * 12.01 * 1e-15)) %>%
  ungroup()


pco2_product_monthly_biome_super <-
  pco2_product %>%
  filter(!is.na(fgco2)) %>% 
  mutate(fgco2_int = fgco2) %>% 
  mutate(
    biome = case_when(
      str_detect(biome, "NA-") ~ "North Atlantic",
      str_detect(biome, "NP-") ~ "North Pacific",
      str_detect(biome, "SO-") ~ "Southern Ocean",
      TRUE ~ "other"
    )
  ) %>%
  filter(biome != "other") %>%
  select(-c(lon, lat, year, month)) %>%
  group_by(time, biome) %>%
  summarise(across(-c(fgco2_int, area),
                   ~ weighted.mean(., area, na.rm = TRUE)),
            across(fgco2_int,
                   ~ sum(. * area, na.rm = TRUE) * 12.01 * 1e-15)) %>%
  ungroup()

pco2_product_monthly <-
  bind_rows(pco2_product_monthly_global %>%
              mutate(biome = "Global"),
            pco2_product_monthly_biome,
            pco2_product_monthly_biome_super)

rm(
  pco2_product_monthly_global,
  pco2_product_monthly_biome,
  pco2_product_monthly_biome_super
)


pco2_product_monthly <-
  pco2_product_monthly %>% 
  filter(!is.na(biome))

pco2_product_monthly <-
  pco2_product_monthly %>%
  mutate(year = year(time),
         month = month(time),
         .after = time)

pco2_product_monthly <-
  pco2_product_monthly %>%
  pivot_longer(-c(time, year, month, biome))
pco2_product_interior <- 
  left_join(
    biome_mask,
    pco2_product_interior
  )

pco2_product_profiles <- pco2_product_interior %>%
  fselect(-c(lat, lon)) %>%
  fgroup_by(biome, depth, time) %>% {
    add_vars(fgroup_vars(., "unique"),
             fmean(.,
                   w = area,
                   keep.w = FALSE,
                   keep.group_vars = FALSE))
  }

pco2_product_profiles <-
  pco2_product_profiles %>%
  mutate(
    year = year(time),
    month = month(time)
  )

gc()
pco2_product_interior <- 
  left_join(
    region_mask,
    pco2_product_interior %>% select(-c(biome, area))
  )

pco2_product_zonal_mean <- pco2_product_interior %>%
  fselect(-c(lon)) %>%
  fgroup_by(region, depth, lat, time) %>% {
    add_vars(fgroup_vars(., "unique"),
             fmean(.,
                   keep.group_vars = FALSE))
  }

pco2_product_zonal_mean <-
  pco2_product_zonal_mean %>%
  mutate(
    year = year(time),
    month = month(time)
  )

gc()

# pco2_product_zonal_mean %>% 
#   filter(region == "atlantic",
#          year == 2023,
#          month == 1) %>% 
#   ggplot(aes(lat, depth, z = no3)) +
#   geom_contour_filled() +
#   scale_y_reverse() +
#   scale_fill_viridis_d()

rm(pco2_product_interior)
gc()

Absolute values

Hovmoeller plots

The following Hovmoeller plots show the value of each variable as provided through the pCO2 product. Hovmoeller plots are first presented as annual means, and than as monthly means.

Annual means

pco2_product_hovmoeller_monthly_annual <-
  pco2_product %>%
  mutate(fgco2_int = fgco2) %>% 
  select(-c(lon, time, month, biome)) %>%
  group_by(year, lat) %>%
  summarise(across(-c(fgco2_int, area),
                   ~ weighted.mean(., area, na.rm = TRUE)),
            across(fgco2_int,
                   ~ sum(. * area, na.rm = TRUE) * 12.01 * 1e-15)) %>%
  ungroup() %>%
  rename(fgco2_hov = fgco2_int) %>% 
  filter(fgco2_hov != 0)

pco2_product_hovmoeller_monthly_annual <-
  pco2_product_hovmoeller_monthly_annual %>%
  pivot_longer(-c(year, lat)) %>% 
  drop_na()

pco2_product_hovmoeller_monthly_annual %>%
  filter(!(name %in% name_divergent)) %>% 
  group_split(name) %>%
  # tail(5) %>%
  map(
    ~ ggplot(data = .x,
             aes(year, lat, fill = value)) +
      geom_raster() +
      scale_fill_viridis_c(name = labels_breaks(.x %>% distinct(name))) +
      theme(legend.title = element_markdown()) +
      coord_cartesian(expand = 0) +
      labs(title = "Annual means",
           y = "Latitude") +
      theme(axis.title.x = element_blank())
  )
[[1]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[2]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[3]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[4]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[5]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[6]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
b0129aa jens-daniel-mueller 2024-04-23
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[7]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3946ecd jens-daniel-mueller 2024-03-27
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[8]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[9]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
b0129aa jens-daniel-mueller 2024-04-23
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 
pco2_product_hovmoeller_monthly_annual %>%
  filter(name %in% name_divergent) %>% 
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(year, lat, fill = value)) +
      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$value, .01), quantile(.x$value, .99)),
        oob = squish
      ) +
      theme(legend.title = element_markdown()) +
      coord_cartesian(expand = 0) +
      labs(title = "Annual means",
           y = "Latitude") +
      theme(axis.title.x = element_blank())
  )
[[1]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
b0129aa jens-daniel-mueller 2024-04-23
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[2]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
51df30d jens-daniel-mueller 2024-05-15
909f6c8 jens-daniel-mueller 2024-05-14
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[3]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
51df30d jens-daniel-mueller 2024-05-15

Monthly means

pco2_product_hovmoeller_monthly <-
  pco2_product %>%
  mutate(fgco2_int = fgco2) %>% 
  select(-c(lon, time, biome)) %>%
  group_by(year, month, lat) %>%
  summarise(across(-c(fgco2_int, area),
                   ~ weighted.mean(., area, na.rm = TRUE)),
            across(fgco2_int,
                   ~ sum(. * area, na.rm = TRUE) * 12.01 * 1e-15)) %>%
  ungroup() %>%
  rename(fgco2_hov = fgco2_int) %>% 
  filter(fgco2_hov != 0)


pco2_product_hovmoeller_monthly <-
  pco2_product_hovmoeller_monthly %>%
  pivot_longer(-c(year, month, lat)) %>% 
  drop_na()

pco2_product_hovmoeller_monthly <-
  pco2_product_hovmoeller_monthly %>% 
  mutate(decimal = year + (month-1) / 12)

pco2_product_hovmoeller_monthly %>%
  filter(!(name %in% name_divergent)) %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(decimal, lat, fill = value)) +
      geom_raster() +
      scale_fill_viridis_c(name = labels_breaks(.x %>% distinct(name))) +
      theme(legend.title = element_markdown()) +
      labs(title = "Monthly means",
           y = "Latitude") +
      coord_cartesian(expand = 0) +
      theme(axis.title.x = element_blank())
  )
[[1]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[2]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[3]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[4]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[5]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[6]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
b0129aa jens-daniel-mueller 2024-04-23
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27
934da22 jens-daniel-mueller 2024-03-22
ae4041c jens-daniel-mueller 2024-03-22
b41fa51 jens-daniel-mueller 2024-03-19 

[[7]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3946ecd jens-daniel-mueller 2024-03-27
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[8]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[9]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
3b5d16b jens-daniel-mueller 2024-05-13
b0129aa jens-daniel-mueller 2024-04-23
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 
pco2_product_hovmoeller_monthly %>%
  filter(name %in% name_divergent) %>%
  group_split(name) %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(decimal, lat, fill = value)) +
      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$value, .01), quantile(.x$value, .99)),
        oob = squish
      )+
      theme(legend.title = element_markdown()) +
      labs(title = "Monthly means",
           y = "Latitude") +
      coord_cartesian(expand = 0) +
      theme(axis.title.x = element_blank())
  )
[[1]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
909f6c8 jens-daniel-mueller 2024-05-14
009791f jens-daniel-mueller 2024-05-14
b0129aa jens-daniel-mueller 2024-04-23
dfcf790 jens-daniel-mueller 2024-04-11
d5075c5 jens-daniel-mueller 2024-04-11
3a9a60f jens-daniel-mueller 2024-03-29
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[2]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
51df30d jens-daniel-mueller 2024-05-15
909f6c8 jens-daniel-mueller 2024-05-14
6343e59 jens-daniel-mueller 2024-03-27
1546f6d jens-daniel-mueller 2024-03-27 

[[3]]

Version Author Date
a3743ec jens-daniel-mueller 2024-05-25
51df30d jens-daniel-mueller 2024-05-15 
pCO2productanalysis_2023 <-
  knitr::knit_expand(
    file = here::here("analysis/child/pCO2_product_analysis.Rmd"),
    product_name = "SOM_FFN",
    year_anom = 2023
  )

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] scales_1.2.1        cmocean_0.3-1       ggtext_0.1.2       
 [4] broom_1.0.5         khroma_1.9.0        ggnewscale_0.4.8   
 [7] seacarb_3.3.1       SolveSAPHE_2.1.0    oce_1.7-10         
[10] gsw_1.1-1           lubridate_1.9.0     timechange_0.1.1   
[13] stars_0.6-0         abind_1.4-5         terra_1.7-65       
[16] sf_1.0-9            rnaturalearth_0.1.0 geomtextpath_0.1.1 
[19] colorspace_2.0-3    marelac_2.1.10      shape_1.4.6        
[22] ggforce_0.4.1       metR_0.13.0         scico_1.3.1        
[25] patchwork_1.1.2     collapse_1.8.9      forcats_0.5.2      
[28] stringr_1.5.0       dplyr_1.1.3         purrr_1.0.2        
[31] readr_2.1.3         tidyr_1.3.0         tibble_3.2.1       
[34] ggplot2_3.4.4       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] xml2_1.3.3              codetools_0.2-18        cachem_1.0.6           
[16] knitr_1.41              polyclip_1.10-4         jsonlite_1.8.3         
[19] dbplyr_2.2.1            compiler_4.2.2          httr_1.4.4             
[22] backports_1.4.1         assertthat_0.2.1        fastmap_1.1.0          
[25] gargle_1.2.1            cli_3.6.1               later_1.3.0            
[28] tweenr_2.0.2            htmltools_0.5.3         tools_4.2.2            
[31] rnaturalearthdata_0.1.0 gtable_0.3.1            glue_1.6.2             
[34] Rcpp_1.0.11             RNetCDF_2.6-1           cellranger_1.1.0       
[37] jquerylib_0.1.4         vctrs_0.6.4             lwgeom_0.2-10          
[40] xfun_0.35               ps_1.7.2                rvest_1.0.3            
[43] ncmeta_0.3.5            lifecycle_1.0.3         googlesheets4_1.0.1    
[46] getPass_0.2-2           MASS_7.3-58.1           vroom_1.6.0            
[49] hms_1.1.2               promises_1.2.0.1        parallel_4.2.2         
[52] yaml_2.3.6              memoise_2.0.1           sass_0.4.4             
[55] stringi_1.7.8           highr_0.9               e1071_1.7-12           
[58] checkmate_2.1.0         commonmark_1.8.1        rlang_1.1.1            
[61] pkgconfig_2.0.3         systemfonts_1.0.4       evaluate_0.18          
[64] lattice_0.20-45         labeling_0.4.2          bit_4.0.5              
[67] processx_3.8.0          tidyselect_1.2.0        here_1.0.1             
[70] magrittr_2.0.3          R6_2.5.1                generics_0.1.3         
[73] DBI_1.1.3               pillar_1.9.0            haven_2.5.1            
[76] whisker_0.4             withr_2.5.0             units_0.8-0            
[79] sp_1.5-1                modelr_0.1.10           crayon_1.5.2           
[82] KernSmooth_2.23-20      utf8_1.2.2              tzdb_0.3.0             
[85] rmarkdown_2.18          grid_4.2.2              readxl_1.4.1           
[88] data.table_1.14.6       callr_3.7.3             git2r_0.30.1           
[91] reprex_2.0.2            digest_0.6.30           classInt_0.4-8         
[94] httpuv_1.6.6            textshaping_0.3.6       munsell_0.5.0          
[97] viridisLite_0.4.1       bslib_0.4.1