Extreme pH Profiles

workflowr

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Last updated: 2022-05-05

Checks: 7 0

Knit directory: bgc_argo_r_argodata/

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---

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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/extreme_pH.Rmd) and HTML (docs/extreme_pH.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
Rmd	bb146f4	pasqualina-vonlanthendinenna	2022-05-05	updated map colors and plotting
html	4cf88e4	pasqualina-vonlanthendinenna	2022-05-05	Build site.
Rmd	3bde57b	pasqualina-vonlanthendinenna	2022-05-05	added argo profile locations
html	f46b9da	pasqualina-vonlanthendinenna	2022-05-05	Build site.
Rmd	ebcc576	pasqualina-vonlanthendinenna	2022-05-05	added argo profile locations
html	708f923	pasqualina-vonlanthendinenna	2022-05-04	Build site.
Rmd	d569024	pasqualina-vonlanthendinenna	2022-05-04	added number of profiles to plot
html	b923426	pasqualina-vonlanthendinenna	2022-05-03	Build site.
Rmd	ab0c45f	pasqualina-vonlanthendinenna	2022-05-03	corrected pH profile depth axis
html	4e3571d	pasqualina-vonlanthendinenna	2022-05-03	Build site.
Rmd	a0139c2	pasqualina-vonlanthendinenna	2022-05-03	updated figure aspect for pH profiles
html	a107add	pasqualina-vonlanthendinenna	2022-05-03	Build site.
Rmd	6c57ac4	pasqualina-vonlanthendinenna	2022-05-03	added pH anomaly profiles
html	6a6e874	pasqualina-vonlanthendinenna	2022-04-29	Build site.
html	2d44f8a	pasqualina-vonlanthendinenna	2022-04-29	Build site.
Rmd	8b582f0	pasqualina-vonlanthendinenna	2022-04-29	added broullon climatology page, argo locations
html	e61c08e	pasqualina-vonlanthendinenna	2022-04-27	Build site.
Rmd	9664e0e	pasqualina-vonlanthendinenna	2022-04-27	added temp data page, changed double extremes
html	10036ed	pasqualina-vonlanthendinenna	2022-04-26	Build site.
html	c03dd24	pasqualina-vonlanthendinenna	2022-04-20	Build site.
html	8805f99	pasqualina-vonlanthendinenna	2022-04-11	Build site.
Rmd	d21c526	pasqualina-vonlanthendinenna	2022-04-11	cleaned up code
Rmd	f3ca885	pasqualina-vonlanthendinenna	2022-04-07	added OceanSODA-Argo SST comparison
html	9875dd0	pasqualina-vonlanthendinenna	2022-04-05	Build site.
Rmd	72a65a7	pasqualina-vonlanthendinenna	2022-04-05	added new biomes to extreme pH
html	eb8e3be	pasqualina-vonlanthendinenna	2022-03-31	Build site.
Rmd	c4d4031	pasqualina-vonlanthendinenna	2022-03-31	extended OceanSODA to 1995 for extreme detection
html	a2271df	pasqualina-vonlanthendinenna	2022-03-30	Build site.
Rmd	25d5eed	pasqualina-vonlanthendinenna	2022-03-30	updated figure aspects
html	968ad85	pasqualina-vonlanthendinenna	2022-03-29	Build site.
Rmd	5432acf	pasqualina-vonlanthendinenna	2022-03-29	added january pH climatology
html	dfd75e9	pasqualina-vonlanthendinenna	2022-03-29	Build site.
Rmd	b9a42f9	pasqualina-vonlanthendinenna	2022-03-29	added january plots and changed pH anomaly detection to mean
html	6dd0945	pasqualina-vonlanthendinenna	2022-03-25	Build site.
Rmd	5b93849	pasqualina-vonlanthendinenna	2022-03-25	added climatology pages
html	e12a216	pasqualina-vonlanthendinenna	2022-03-15	Build site.
Rmd	e4d1d1e	pasqualina-vonlanthendinenna	2022-03-15	updated to new only flag A data
html	c8451b9	pasqualina-vonlanthendinenna	2022-03-14	Build site.
html	1ffe07f	pasqualina-vonlanthendinenna	2022-03-11	Build site.
Rmd	f0fde29	pasqualina-vonlanthendinenna	2022-03-11	changed anomaly detection to 1x1 grid with old data
html	520dafe	pasqualina-vonlanthendinenna	2022-03-08	Build site.
Rmd	b1bb0ec	pasqualina-vonlanthendinenna	2022-03-08	subsetted profiles with flag A only for extremes
html	7540ae4	pasqualina-vonlanthendinenna	2022-03-08	Build site.
Rmd	18dff1b	pasqualina-vonlanthendinenna	2022-03-08	subsetted profiles with flag A only for extremes
html	33238fe	pasqualina-vonlanthendinenna	2022-03-02	Build site.
Rmd	17af9b5	pasqualina-vonlanthendinenna	2022-03-02	added January 2018 profile
html	97a098b	pasqualina-vonlanthendinenna	2022-03-02	Build site.
Rmd	5a073cb	pasqualina-vonlanthendinenna	2022-03-02	removed facet wrap
html	9d97f25	pasqualina-vonlanthendinenna	2022-03-02	Build site.
Rmd	9ccabc6	pasqualina-vonlanthendinenna	2022-03-02	removed facet wrap
html	e4188d2	pasqualina-vonlanthendinenna	2022-03-01	Build site.
Rmd	6ca535c	pasqualina-vonlanthendinenna	2022-03-01	updated profiles
html	da665ab	pasqualina-vonlanthendinenna	2022-03-01	Build site.
Rmd	57ada58	pasqualina-vonlanthendinenna	2022-03-01	updated figure aspects
html	5ef4df2	pasqualina-vonlanthendinenna	2022-03-01	Build site.
Rmd	8ef1277	pasqualina-vonlanthendinenna	2022-03-01	plotted Atlantic mean seasonal profiles
html	8ef1277	pasqualina-vonlanthendinenna	2022-03-01	plotted Atlantic mean seasonal profiles
Rmd	73463cc	pasqualina-vonlanthendinenna	2022-03-01	changed line thickness for H and L raw profiles
html	c4362e5	pasqualina-vonlanthendinenna	2022-02-28	Build site.
Rmd	5b0901d	pasqualina-vonlanthendinenna	2022-02-28	corrected dates and titles
html	ab29b31	pasqualina-vonlanthendinenna	2022-02-28	Build site.
Rmd	6e27fb1	pasqualina-vonlanthendinenna	2022-02-28	update with eval = false for single profile line thickness
html	d299359	pasqualina-vonlanthendinenna	2022-02-28	Build site.
Rmd	aad1df4	pasqualina-vonlanthendinenna	2022-02-28	plotted specific profiles
html	21582c5	pasqualina-vonlanthendinenna	2022-02-25	Build site.
Rmd	fe0b970	pasqualina-vonlanthendinenna	2022-02-25	plotted line profiles and changed HNL colors
html	fd521d1	pasqualina-vonlanthendinenna	2022-02-25	Build site.
Rmd	64c2c71	pasqualina-vonlanthendinenna	2022-02-25	plotted line profiles and changed HNL colors
html	daa0a8f	pasqualina-vonlanthendinenna	2022-02-24	Build site.
Rmd	4557a6e	pasqualina-vonlanthendinenna	2022-02-24	added st dev for pH profiles
html	08c8d4b	pasqualina-vonlanthendinenna	2022-02-23	Build site.
Rmd	7517b78	pasqualina-vonlanthendinenna	2022-02-23	updated regression and merging for extreme_pH
html	71ced5f	pasqualina-vonlanthendinenna	2022-02-23	Build site.
Rmd	48803ef	pasqualina-vonlanthendinenna	2022-02-23	updated regression and merging for extreme_pH
html	905d82f	pasqualina-vonlanthendinenna	2022-02-15	Build site.
html	54ea512	pasqualina-vonlanthendinenna	2022-02-10	Build site.
html	f2fa56a	pasqualina-vonlanthendinenna	2022-02-10	Build site.
Rmd	eda8ca8	pasqualina-vonlanthendinenna	2022-02-10	code review
html	25c9e6b	pasqualina-vonlanthendinenna	2022-02-03	Build site.
Rmd	ecf2f74	pasqualina-vonlanthendinenna	2022-02-03	corrected surface mean pH
html	2d1bdae	pasqualina-vonlanthendinenna	2022-02-03	Build site.
Rmd	dcc269c	pasqualina-vonlanthendinenna	2022-02-03	changed figure aspect
html	71958c4	pasqualina-vonlanthendinenna	2022-02-03	Build site.
Rmd	3f38f15	pasqualina-vonlanthendinenna	2022-02-03	corrected mean argo surface pH
html	d7debab	pasqualina-vonlanthendinenna	2022-02-02	Build site.
Rmd	a73c7cf	pasqualina-vonlanthendinenna	2022-02-02	changed to log scale and mean surface argo ph
html	d14b7f1	pasqualina-vonlanthendinenna	2022-02-02	Build site.
Rmd	bb15149	pasqualina-vonlanthendinenna	2022-02-02	changed map figure aspect
html	31e4d42	pasqualina-vonlanthendinenna	2022-02-02	Build site.
Rmd	09ab7e9	pasqualina-vonlanthendinenna	2022-02-02	changed map figure aspect
html	7376be6	pasqualina-vonlanthendinenna	2022-02-02	Build site.
Rmd	ce1bbab	pasqualina-vonlanthendinenna	2022-02-02	updated bar charts and argo vs oceansoda ph
html	de183c6	pasqualina-vonlanthendinenna	2022-02-01	Build site.
Rmd	db007b5	pasqualina-vonlanthendinenna	2022-02-01	updated figure aspect
html	44a2ec3	pasqualina-vonlanthendinenna	2022-02-01	Build site.
Rmd	f62e851	pasqualina-vonlanthendinenna	2022-02-01	added flat maps, bar charts and OceanSODA vs argo pH
html	44fcfb6	pasqualina-vonlanthendinenna	2022-02-01	Build site.
Rmd	b45a03e	pasqualina-vonlanthendinenna	2022-02-01	added sigma maps and log transform depth
html	28c8d17	jens-daniel-mueller	2022-01-29	Build site.
Rmd	c0c12d0	jens-daniel-mueller	2022-01-28	code cleaning: basinmask and regression
html	cfd734c	jens-daniel-mueller	2022-01-28	Build site.
Rmd	5024768	jens-daniel-mueller	2022-01-28	code review: basinmask and regression
html	5635ef2	pasqualina-vonlanthendinenna	2022-01-27	Build site.
Rmd	23dc282	pasqualina-vonlanthendinenna	2022-01-27	failed attempt at updating basinmask and regression
html	c44ff0f	pasqualina-vonlanthendinenna	2022-01-25	Build site.
Rmd	3851824	pasqualina-vonlanthendinenna	2022-01-25	added basin-mean profiles
html	962cdb9	pasqualina-vonlanthendinenna	2022-01-25	Build site.
Rmd	825a50a	pasqualina-vonlanthendinenna	2022-01-25	added seasonal and biome profiles
html	3ae43e4	pasqualina-vonlanthendinenna	2022-01-24	Build site.
Rmd	3f8e824	pasqualina-vonlanthendinenna	2022-01-24	updated 24/01
html	6b22341	pasqualina-vonlanthendinenna	2022-01-21	Build site.
Rmd	e72d7ca	pasqualina-vonlanthendinenna	2022-01-21	updated linear regression to monthly
html	587755e	pasqualina-vonlanthendinenna	2022-01-21	Build site.
Rmd	7a9209b	pasqualina-vonlanthendinenna	2022-01-21	updated threshold calculation 2
html	c96ad5e	pasqualina-vonlanthendinenna	2022-01-21	Build site.
Rmd	58b3b3b	pasqualina-vonlanthendinenna	2022-01-21	updated threshold calculation
html	ed3fef2	jens-daniel-mueller	2022-01-07	Build site.
Rmd	3d2f8fc	jens-daniel-mueller	2022-01-07	code review
html	486c9c8	jens-daniel-mueller	2022-01-07	Build site.
Rmd	e9ad067	jens-daniel-mueller	2022-01-07	code review
html	343689f	pasqualina-vonlanthendinenna	2022-01-06	Build site.
Rmd	f53cc2d	pasqualina-vonlanthendinenna	2022-01-06	updated profile page
html	b8a6482	pasqualina-vonlanthendinenna	2022-01-03	Build site.
Rmd	054f8a6	pasqualina-vonlanthendinenna	2022-01-03	added Argo profiles

---

Task

Compare depth profiles of normal pH and of extreme pH, as identified in the surface OceanSODA pH data product

theme_set(theme_bw())
HNL_colors <- c("H" = "#b2182b",
                "N" = "#636363",
                "L" = "#2166ac")

HNL_colors_map <- c('H' = 'red3',
                    'N' = 'gray90',
                    'L' = 'blue3')

Load data

path_argo <- '/nfs/kryo/work/updata/bgc_argo_r_argodata'
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")
path_emlr_utilities <- "/nfs/kryo/work/jenmueller/emlr_cant/utilities/files/"

# RECCAP2-ocean region mask

# region_masks_all_2x2 <- read_rds(file = paste0(path_argo_preprocessed,
#                                               "/region_masks_all_2x2.rds"))
# 
# region_masks_all_2x2 <- region_masks_all_2x2 %>%
#   rename(biome = value) %>% 
#   mutate(coast = as.character(coast))

# load in new Mayot biomes 

nm_biomes <- read_rds(file = paste0(path_argo_preprocessed, "/nm_biomes.rds"))

# WOA 18 basin mask

basinmask <-
  read_csv(
    paste(path_emlr_utilities,
          "basin_mask_WOA18.csv",
          sep = ""),
    col_types = cols("MLR_basins" = col_character())
  )

basinmask <- basinmask %>%
  filter(MLR_basins == unique(basinmask$MLR_basins)[1]) %>% 
  select(-c(MLR_basins, basin))

# OceanSODA
OceanSODA <- read_rds(file = paste0(path_argo_preprocessed, "/OceanSODA.rds"))

OceanSODA <- OceanSODA %>%
  mutate(year = year(date),
         month = month(date))

# argo pH data (flag A only)
full_argo <- read_rds(file = paste0(path_argo_preprocessed, "/bgc_merge_flag_A.rds")) %>%
  select(-c(temp_adjusted:temp_adjusted_error,
            profile_temp_qc))


# change the date format for compatibility with OceanSODA pH data
full_argo <- full_argo %>%
  mutate(year = year(date),
         month = month(date)) %>%
  mutate(date = ymd(format(date, "%Y-%m-15")))

map <-
  read_rds(paste(path_emlr_utilities,
                 "map_landmask_WOA18.rds",
                 sep = ""))

Regions

Biome grid reduction

map +
  geom_tile(data = nm_biomes, 
            aes(x = lon, 
                y = lat, 
                fill = biome_name))+
  lims(y = c(-85, -30))+
  scale_fill_brewer(palette = 'Dark2')+
  labs(title = 'Mayot biomes pre-grid reduction')

Past versions of biomes_flat_map_pre_grid_reduction-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
d14b7f1	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

nm_biomes_2x2 <- nm_biomes %>% 
  mutate(lon = cut(lon, seq(20, 380, 2), seq(21, 379, 2)),
         lon = as.numeric(as.character(lon)),
         lat = cut(lat, seq(-90, 90, 2), seq(-89, 89, 2)),
         lat = as.numeric(as.character(lat)))

nm_biomes_2x2 <- nm_biomes_2x2 %>%
   count(lon, lat, biome_name) %>%
   group_by(lon, lat) %>%
   slice_max(n, with_ties = FALSE) %>%
   ungroup()
 
rm(nm_biomes)

map+
  geom_tile(data = nm_biomes_2x2,
            aes(x = lon,
                y = lat,
                fill = biome_name))+
  lims(y = c(-85, -30))+
  scale_fill_brewer(palette = 'Dark2')+
  labs(title = 'Mayot biomes post-grid reduction')

Past versions of biomes_flat_map_post_grid_reduction-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
d14b7f1	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

Basin grid reduction

basinmask <- basinmask %>%
  filter(lat < -30)

map +
  geom_tile(data = basinmask, 
            aes(x = lon, 
                y = lat, 
                fill = basin_AIP))+
  lims(y = c(-85, -30))+
  scale_fill_brewer(palette = 'Dark2')

Past versions of basin_flat_map_pre_grid_reduction-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
d14b7f1	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

basinmask_2x2 <- basinmask %>%
  mutate(
    lat = cut(lat, seq(-90, 90, 2), seq(-89, 89, 2)),
    lat = as.numeric(as.character(lat)),
    lon = cut(lon, seq(20, 380, 2), seq(21, 379, 2)),
    lon = as.numeric(as.character(lon))
   ) # regrid into 2x2º grid
# 
# # assign basins from each pixel to to each 2 Lon x Lat pixel, based on the majority of basins in each 2x2 grid  
# 
basinmask_2x2 <- basinmask_2x2 %>%
  count(lon, lat, basin_AIP) %>%
  group_by(lon, lat) %>%
  slice_max(n, with_ties = FALSE) %>%
  ungroup() %>%
  select(-n)
# 
rm(basinmask)

map+
  geom_tile(data = basinmask_2x2 %>% filter(lat < -30),
            aes(x = lon,
                y = lat,
                fill = basin_AIP))+
  lims(y = c(-85, -30))+
  scale_fill_brewer(palette = 'Dark2')

Past versions of basin_flat_map_post_grid_reduction-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
d14b7f1	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

OceanSODA

Monthly clim surface pH

OceanSODA <- OceanSODA %>% 
  group_by(lon, lat, month) %>% 
  mutate(clim_ph = mean(ph_total, na.rm = TRUE),
         clim_diff = ph_total - clim_ph,
         .after = ph_total) %>% 
  ungroup()

Grid reduction

# Note: While reducing lon x lat grid,
# we keep the original number of observations

OceanSODA_2x2 <- OceanSODA %>%
  mutate(
    lat_raw = lat,
    lon_raw = lon,
    lat = cut(lat, seq(-90, 90, 2), seq(-89, 89, 2)),
    lat = as.numeric(as.character(lat)),
    lon = cut(lon, seq(20, 380, 2), seq(21, 379, 2)),
    lon = as.numeric(as.character(lon))) # regrid into 2x2º grid

rm(OceanSODA)

Apply region masks

# keep only Southern Ocean data
OceanSODA_2x2_SO <- inner_join(OceanSODA_2x2, nm_biomes_2x2)

# add in basin separations
OceanSODA_2x2_SO <- inner_join(OceanSODA_2x2_SO, basinmask_2x2)
# expected number of rows from -30 to -70º latitude, 360º longitude, for 12 months, 8 years:
# 40 lat x 360 lon x 12 months x 8 years = 1 382 400 rows 
# actual number of rows: 919 768

OceanSODA_2x2_SO <- OceanSODA_2x2_SO %>% 
  filter(!is.na(ph_total))

Maps

# map of climatological OceanSODA pH 
OceanSODA_2x2_SO %>% 
  group_split(month) %>% 
  #head(1) %>% 
  map(
    ~map+
      geom_tile(data = .x,
                aes(x = lon_raw,
                    y = lat_raw,
                    fill = clim_ph))+
      scale_fill_viridis_c()+
      lims(y = c(-80, -30))+
      labs(title = paste('climatological OceanSODA pH (1995-2020) month:', unique(.x$month)))
  )

[[1]]

Past versions of map_OceanSODA_pH_clim-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[2]]

Past versions of map_OceanSODA_pH_clim-2.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[3]]

Past versions of map_OceanSODA_pH_clim-3.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[4]]

Past versions of map_OceanSODA_pH_clim-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[5]]

Past versions of map_OceanSODA_pH_clim-5.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[6]]

Past versions of map_OceanSODA_pH_clim-6.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[7]]

Past versions of map_OceanSODA_pH_clim-7.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[8]]

Past versions of map_OceanSODA_pH_clim-8.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[9]]

Past versions of map_OceanSODA_pH_clim-9.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[10]]

Past versions of map_OceanSODA_pH_clim-10.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[11]]

Past versions of map_OceanSODA_pH_clim-11.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[12]]

Past versions of map_OceanSODA_pH_clim-12.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

# map of monthly anomaly relative to climatology

OceanSODA_2x2_SO %>% 
  filter(year >= 2013) %>% 
  group_split(month) %>% 
  #head(1) %>% 
  map(
    ~map+
      geom_tile(data = .x,
                aes(x = lon_raw,
                    y = lat_raw,
                    fill = clim_diff))+
      scale_fill_divergent(mid = 'grey80')+
      lims(y = c(-80, -30))+
      facet_wrap(~year, ncol = 2)+
      labs(title = paste('in-situ OceanSODA pH - clim OceanSODA pH, month:', unique(.x$month)))+
      theme(legend.position = 'right')
  )

[[1]]

Past versions of map_of_OceanSODA_pH_anomalies-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[2]]

Past versions of map_of_OceanSODA_pH_anomalies-2.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[3]]

Past versions of map_of_OceanSODA_pH_anomalies-3.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[4]]

Past versions of map_of_OceanSODA_pH_anomalies-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[5]]

Past versions of map_of_OceanSODA_pH_anomalies-5.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[6]]

Past versions of map_of_OceanSODA_pH_anomalies-6.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[7]]

Past versions of map_of_OceanSODA_pH_anomalies-7.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[8]]

Past versions of map_of_OceanSODA_pH_anomalies-8.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[9]]

Past versions of map_of_OceanSODA_pH_anomalies-9.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[10]]

Past versions of map_of_OceanSODA_pH_anomalies-10.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[11]]

Past versions of map_of_OceanSODA_pH_anomalies-11.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[12]]

Past versions of map_of_OceanSODA_pH_anomalies-12.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

OceanSODA pH anomalies

Grid level

Climatological thresholds

Fit lm models

# fit a linear regression of OceanSODA pH against time (temporal trend)
# in each lat/lon/month grid

OceanSODA_regression <- OceanSODA_2x2_SO %>% 
  # filter(basin_AIP == "Indian",
  #        biome_name == "SPSS",
  #        lon < 40) %>%
  nest(data = -c(lon, lat, month)) %>%
  mutate(fit = map(.x = data,
                   .f = ~ lm(clim_diff ~ year, data = .x)),
         tidied = map(.x = fit, .f = tidy),
         glanced = map(.x = fit, .f = glance),
         augmented = map(.x = fit, .f = augment))


OceanSODA_regression_tidied <- OceanSODA_regression %>%
  select(-c(data, fit, augmented, glanced)) %>%
  unnest(tidied)

OceanSODA_regression_tidied <- OceanSODA_regression_tidied %>% 
  select(lat:estimate) %>% 
  pivot_wider(names_from = term,
              values_from = estimate) %>% 
  rename(intercept = `(Intercept)`,
         slope = year)

OceanSODA_regression_data <- OceanSODA_regression %>% 
  select(-c(fit, tidied, glanced, augmented)) %>% 
  unnest(data)

OceanSODA_regression_augmented <- OceanSODA_regression %>%
  select(-c(fit, tidied, glanced, data)) %>%
  unnest(augmented) %>% 
  select(lat:year, .resid)

OceanSODA_regression_augmented <- bind_cols(
  OceanSODA_regression_augmented,
  OceanSODA_regression_data %>% select(
    date, basin_AIP, biome_name,  
    clim_ph, ph_total,
    lon_raw, lat_raw))

OceanSODA_regression_glanced <- OceanSODA_regression %>%
  select(-c(data, fit, tidied, augmented)) %>%
  unnest(glanced)

Fit mean

# identify the mean value
# in each lat/lon/month grid

OceanSODA_regression_tidied <- OceanSODA_2x2_SO %>% 
  # filter(basin_AIP == "Indian",
  #        biome_name == "SPSS",
  #        lon < 40) %>%
  group_by(lon, lat, month) %>%
  summarise(slope = 0,
            intercept = mean(clim_diff, na.rm = TRUE)) %>% 
  ungroup()

OceanSODA_regression_glanced <- OceanSODA_2x2_SO %>% 
  # filter(basin_AIP == "Indian",
  #        biome_name == "SPSS",
  #        lon < 40) %>%
  group_by(lon, lat, month) %>%
  summarise(sigma = sd(clim_diff, na.rm = TRUE)) %>% 
  ungroup()

OceanSODA_regression_augmented <- OceanSODA_2x2_SO %>% 
  # filter(basin_AIP == "Indian",
  #        biome_name == "SPSS",
  #        lon < 40) %>%
  mutate(.resid = clim_diff)

Slope maps

map+
  geom_tile(data = OceanSODA_regression_tidied,
            aes(x = lon,
                y = lat, 
                fill = slope))+
  scale_fill_scico(palette = 'vik', midpoint = 0)+
  lims(y = c(-85, -30))+
  facet_wrap(~month, ncol = 2)

Past versions of map_regression_slopes_flat-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
31e4d42	pasqualina-vonlanthendinenna	2022-02-02
de183c6	pasqualina-vonlanthendinenna	2022-02-01
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

Sigma maps

map+
  geom_tile(data = OceanSODA_regression_glanced,
            aes(x = lon,
                y = lat, 
                fill = sigma))+
  scale_fill_viridis_c()+
  lims(y = c(-85, -30))+
  facet_wrap(~month, ncol = 2)+
  labs(fill = '1 residual \nst. dev.')

Past versions of flat_map_sigma-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
31e4d42	pasqualina-vonlanthendinenna	2022-02-02
de183c6	pasqualina-vonlanthendinenna	2022-02-01
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

Anomaly identification

Calculate OceanSODA pH anomalies: L for abnormally low, H for abnormally high, N for normal pH

# when the in-situ OceanSODA pH is lower than the 5th percentile (predicted - 2*residual.st.dev), assign 'L' for low extreme
# when the in-situ OceanSODA pH exceeds the 95th percentile (predicted + 2*residual.st.dev), assign 'H' for high extreme
# when the in-situ OceanSODA pH is within 95% of the range, then assign 'N' for normal pH

# combine observations and regression statistics

OceanSODA_2x2_SO_extreme_grid <-
  full_join(
    OceanSODA_regression_augmented,
    OceanSODA_regression_glanced %>%
      select(lat:month, sigma)
  )

# identify observations in anomaly classes

OceanSODA_2x2_SO_extreme_grid <- OceanSODA_2x2_SO_extreme_grid %>%
  mutate(
    ph_extreme = case_when(
      .resid < -sigma*2 ~ 'L',
      .resid > sigma*2 ~ 'H',
      TRUE ~ 'N'
    )
  ) 

OceanSODA_2x2_SO_extreme_grid <- OceanSODA_2x2_SO_extreme_grid %>%
  mutate(ph_extreme = fct_relevel(ph_extreme, "H", "N", "L"))


# combine with regression coefficients

OceanSODA_2x2_SO_extreme_grid <-
  full_join(OceanSODA_2x2_SO_extreme_grid,
            OceanSODA_regression_tidied)

Write anomalies to file

OceanSODA_2x2_SO_extreme_grid %>% 
  write_rds(file = paste0(path = path_argo_preprocessed, "/OceanSODA_pH_anomaly_field.rds"))

OceanSODA_2x2_SO_extreme_grid %>%
  group_split(lon, lat, month) %>%
  head(8) %>%
  map(~ ggplot(data = .x) +
        geom_point(aes(x = year,
                       y = clim_diff,
                       col = ph_extreme)) +
        geom_abline(data = .x, aes(slope = slope,
                    intercept = intercept)) +
        geom_abline(data = .x, aes(slope = slope,
                    intercept = intercept + 2*sigma),
                    linetype = 2) +
        geom_abline(data = .x, aes(slope = slope,
                    intercept = intercept - 2*sigma),
                    linetype = 2) +
        labs(title = paste(fititle = paste(
          "lon:", unique(.x$lon),
          "| lat:", unique(.x$lat),
          "| month:", unique(.x$month)
          ))) +
        scale_color_manual(values = HNL_colors))

[[1]]

Past versions of anomaly_test_plot_grid-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

[[2]]

Past versions of anomaly_test_plot_grid-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

[[3]]

Past versions of anomaly_test_plot_grid-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

[[4]]

Past versions of anomaly_test_plot_grid-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

[[5]]

Past versions of anomaly_test_plot_grid-5.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

[[6]]

Past versions of anomaly_test_plot_grid-6.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

[[7]]

Past versions of anomaly_test_plot_grid-7.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21

[[8]]

Past versions of anomaly_test_plot_grid-8.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21

Anomaly maps

#use the original lat/lon grid to plot the extreme on a 1x1
#(anomalies detected with 1995-2020 data but mapped only from 2013 to 2020)

OceanSODA_2x2_SO_extreme_grid %>%
  filter(year >= 2013) %>% 
  group_split(month) %>%
  #head(1) %>%
  map(
    ~map +
      geom_tile(data = .x,
                aes(x = lon_raw,
                    y = lat_raw,
                    fill = ph_extreme))+
      scale_fill_manual(values = HNL_colors_map)+
      facet_wrap(~year, ncol = 2)+
      lims(y = c(-85, -30))+
      labs(title = paste('month:', unique(.x$month)),
           fill = 'pH')
  )

[[1]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
da665ab	pasqualina-vonlanthendinenna	2022-03-01

[[2]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-2.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
da665ab	pasqualina-vonlanthendinenna	2022-03-01

[[3]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-3.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
da665ab	pasqualina-vonlanthendinenna	2022-03-01

[[4]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
e4188d2	pasqualina-vonlanthendinenna	2022-03-01

[[5]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-5.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
e4188d2	pasqualina-vonlanthendinenna	2022-03-01

[[6]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-6.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
e4188d2	pasqualina-vonlanthendinenna	2022-03-01

[[7]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-7.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
e4188d2	pasqualina-vonlanthendinenna	2022-03-01

[[8]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-8.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
e4188d2	pasqualina-vonlanthendinenna	2022-03-01

[[9]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-9.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[10]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-10.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[11]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-11.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[12]]

Past versions of flat_map_OceanSODA_ph_extremes_1x1_plot-12.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

# map the anomalies on the original 1x1 grid 

Anomaly time series

# calculate a regional mean pH for each biome, basin, and ph extreme (H/L/N) and plot a timeseries 

OceanSODA_2x2_SO_extreme_grid %>% 
  group_by(year, biome_name, basin_AIP, ph_extreme) %>% 
  summarise(ph_regional = mean(ph_total, na.rm = TRUE)) %>% 
  ungroup() %>% 
  ggplot(aes(x = year, y = ph_regional, col = ph_extreme))+
  geom_point(size = 0.3)+
  geom_line()+
  scale_color_manual(values = HNL_colors) +
  facet_grid(basin_AIP~biome_name)+
  theme(legend.position = 'bottom')

Past versions of extreme_pH_timeseries_grid-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
587755e	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

Anomaly histogram

OceanSODA_2x2_SO_extreme_grid %>%
  ggplot(aes(ph_total, col = ph_extreme)) +
  geom_density() +
  scale_color_manual(values = HNL_colors) +
  facet_grid(basin_AIP ~ biome_name) +
  coord_cartesian(xlim = c(8, 8.2)) +
  labs(x = 'value',
       y = 'density',
       col = 'pH anomaly') +
  theme(legend.position = 'bottom')

Past versions of extreme_pH_histogram_grid-1.png

Version	Author	Date
8805f99	pasqualina-vonlanthendinenna	2022-04-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29
cfd734c	jens-daniel-mueller	2022-01-28
962cdb9	pasqualina-vonlanthendinenna	2022-01-25
6b22341	pasqualina-vonlanthendinenna	2022-01-21
587755e	pasqualina-vonlanthendinenna	2022-01-21
c96ad5e	pasqualina-vonlanthendinenna	2022-01-21
486c9c8	jens-daniel-mueller	2022-01-07

Argo

Grid reduction

# Note: While reducing lon x lat grid,
# we keep the original number of observations

full_argo_2x2 <- full_argo %>%
  mutate(
    lat_raw = lat,
    lon_raw = lon,
    lat = cut(lat, seq(-90, 90, 2), seq(-89, 89, 2)),
    lat = as.numeric(as.character(lat)),
    lon = cut(lon, seq(20, 380, 2), seq(21, 379, 2)),
    lon = as.numeric(as.character(lon)))  # re-grid to 2x2

Apply region masks

# keep only Southern Ocean argo data
full_argo_2x2_SO <- inner_join(full_argo_2x2, nm_biomes_2x2)

# add in basin separations
full_argo_2x2_SO <- inner_join(full_argo_2x2_SO, basinmask_2x2)

Join OceanSODA

# rename OceanSODA columns
OceanSODA_2x2_SO_extreme_grid <- OceanSODA_2x2_SO_extreme_grid %>%
  select(-c(lon, lat)) %>%
  rename(OceanSODA_ph = ph_total,
         lon = lon_raw,
         lat = lat_raw) %>% 
  filter(year >= 2013)

# combine the argo profile data to the surface extreme data
profile_extreme <- inner_join(
  full_argo %>% 
    select(year, month, date, lon, lat, depth,
           ph_in_situ_total_adjusted,
           platform_number,
           cycle_number),
  OceanSODA_2x2_SO_extreme_grid %>% 
    select(year, month, date, lon, lat,
           OceanSODA_ph, ph_extreme,
           clim_ph, clim_diff,
           biome_name, basin_AIP))
  
profile_extreme <- profile_extreme %>% 
  unite('platform_cycle', platform_number:cycle_number, sep = '_', remove = FALSE)

Location of Argo profiles

OceanSODA_2x2_SO_extreme_grid %>% 
  group_split(month) %>%
  head(1) %>%
  map(
    ~map +
      geom_tile(data = .x,
                aes(x = lon,
                    y = lat,
                    fill = ph_extreme),
                alpha = 0.5)+
      geom_tile(data = profile_extreme %>% 
                   filter(depth < 10),
                 aes(x = lon, 
                     y = lat,
                     fill = 'black',
                     height = 1,
                     width = 1),
                 alpha = 0.3)+
      scale_fill_manual(values = HNL_colors_map)+
      facet_wrap(~year, ncol = 1)+
      lims(y = c(-85, -30))+
      labs(title = paste('month:', unique(.x$month)),
           fill = 'pH')
  )

[[1]]

Past versions of map_location_argo_profiles-1.png

Version	Author	Date
4cf88e4	pasqualina-vonlanthendinenna	2022-05-05
f46b9da	pasqualina-vonlanthendinenna	2022-05-05
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

Plot profiles

Argo profiles plotted according to the surface OceanSODA pH

L profiles correspond to a surface acidification event (low pH), as recorded in OceanSODA

H profiles correspond to an event of high surface pH, as recorded in OceanSODA

N profiles correspond to normal surface OceanSODA pH

Raw

profile_extreme %>%
  group_split(biome_name, basin_AIP, year) %>% 
  head(6) %>% 
  map(
    ~ ggplot(
      data = .x,
      aes(
        x = ph_in_situ_total_adjusted,
        y = depth,
        group = platform_cycle,
        col = ph_extreme
      )
    ) +
      geom_path(data = .x %>% filter(ph_extreme == 'N'),
                aes(x = ph_in_situ_total_adjusted,
                    y = depth,
                    group = platform_cycle,
                    col = ph_extreme),
                size = 0.3) +
      geom_path(data = .x %>% filter(ph_extreme == 'H' | ph_extreme == 'L'),
                aes(x = ph_in_situ_total_adjusted,
                    y = depth,
                    group = platform_cycle,
                    col = ph_extreme),
                size = 0.5)+
      scale_y_reverse() +
      scale_color_manual(values = HNL_colors) +
      facet_wrap(~ month, ncol = 6) +
      labs(
        x = 'Argo pH (total scale)',
        y = 'depth (m)',
        title = paste(
          unique(.x$basin_AIP),
          "|",
          unique(.x$year),
          "| biome:",
          unique(.x$biome_name)
        ),
        col = 'OceanSODA pH \nanomaly'
      )
  )

[[1]]

Past versions of profiles_raw-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
8ef1277	pasqualina-vonlanthendinenna	2022-03-01
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29

[[2]]

Past versions of profiles_raw-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
8ef1277	pasqualina-vonlanthendinenna	2022-03-01
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29

[[3]]

Past versions of profiles_raw-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
8ef1277	pasqualina-vonlanthendinenna	2022-03-01
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29

[[4]]

Past versions of profiles_raw-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
8ef1277	pasqualina-vonlanthendinenna	2022-03-01
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29

[[5]]

Past versions of profiles_raw-5.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
8ef1277	pasqualina-vonlanthendinenna	2022-03-01
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29

[[6]]

Past versions of profiles_raw-6.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
8ef1277	pasqualina-vonlanthendinenna	2022-03-01
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
28c8d17	jens-daniel-mueller	2022-01-29

Atl, STSS biome, Aug 2017

# plot profiles for the Atlantic basin, biome 1, month 08, 2017 

OceanSODA_SO_extreme_grid_2017 <-  
  OceanSODA_2x2_SO_extreme_grid %>% 
  filter(date == '2017-08-15')

map+
  geom_tile(data = OceanSODA_SO_extreme_grid_2017,
            aes(x = lon,
                y = lat,
                fill = ph_extreme))+
  scale_fill_manual(values = HNL_colors_map)+
  lims(y = c(-85, -30))+
  labs(title = 'August 2017',
       fill = 'OceanSODA pH \nextreme')

profile_extreme_Atl_2017 <- profile_extreme %>% 
  filter(date == '2017-08-15',
         basin_AIP == 'Atlantic',
         biome_name == 'STSS')

profile_extreme_Atl_2017 %>% 
  ggplot(aes(y = depth, 
             x = ph_in_situ_total_adjusted,
             group = platform_cycle,
             col = ph_extreme))+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'N'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth, 
                group = platform_cycle,
                col = ph_extreme),
            size = 0.3)+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'H'| ph_extreme == 'L'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle,
                col = ph_extreme),
            size = 0.5)+
  scale_y_reverse()+
  scale_color_manual(values = HNL_colors)+
  labs(title = 'Atlantic basin, STSS biome, August 2017',
       col = 'OceanSODA\npH anomaly',
       x = 'Argo pH')

rm(OceanSODA_SO_extreme_grid_2017, profile_extreme_Atl_2017)

Atl, STSS biome, Dec 2017

# Plot profiles for the Pacific basin, biome 3, months 12, 2017

OceanSODA_SO_extreme_grid_2017 <-   
  OceanSODA_2x2_SO_extreme_grid %>% 
  filter(date == '2017-12-15')

map+
  geom_tile(data = OceanSODA_SO_extreme_grid_2017,
            aes(x = lon,
                y = lat,
                fill = ph_extreme))+
  scale_fill_manual(values = HNL_colors_map)+
  lims(y = c(-85, -30))+
  labs(title = 'December 2017',
       fill = 'OceanSODA pH \nextreme')

profile_extreme_Atl_2017 <- profile_extreme %>% 
  filter(date == '2017-12-15',
         basin_AIP == 'Atlantic',
         biome_name == 'STSS')

profile_extreme_Atl_2017 %>% 
  ggplot(aes(y = depth, 
             x = ph_in_situ_total_adjusted,
             group = platform_cycle,
             col = ph_extreme))+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'N'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle,
                col = ph_extreme),
            size = 0.3)+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'H' | ph_extreme == 'L'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle,
                col = ph_extreme),
            size = 0.5)+
  scale_y_reverse()+
  scale_color_manual(values = HNL_colors)+
  labs(title = 'Atlantic basin, STSS biome, December 2017',
       col = 'OceanSODA\npH anomaly',
       x = 'Argo pH')

rm(OceanSODA_SO_extreme_grid_2017, profile_extreme_Atl_2017)

Atl, STSS biome, Jan 2018

OceanSODA_SO_extreme_grid_2018 <-   
  OceanSODA_2x2_SO_extreme_grid %>% 
  filter(date == '2018-01-15')

map+
  geom_tile(data = OceanSODA_SO_extreme_grid_2018,
            aes(x = lon,
                y = lat,
                fill = ph_extreme))+
  scale_fill_manual(values = HNL_colors_map)+
  lims(y = c(-85, -30))+
  labs(title = 'January 2018',
       fill = 'OceanSODA pH \nextreme')

profile_extreme_Atl_2018 <- profile_extreme %>% 
  filter(date == '2018-01-15',
         basin_AIP == 'Atlantic',
         biome_name == 'STSS')

profile_extreme_Atl_2018 %>% 
  ggplot(aes(y = depth, 
             x = ph_in_situ_total_adjusted,
             group = platform_cycle,
             col = ph_extreme))+
  geom_path(data = profile_extreme_Atl_2018 %>% filter(ph_extreme == 'N'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle,
                col = ph_extreme),
            size = 0.3)+
  geom_path(data = profile_extreme_Atl_2018 %>% filter(ph_extreme == 'H' | ph_extreme == 'L'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle,
                col = ph_extreme),
            size = 0.5)+
  scale_y_reverse()+
  scale_color_manual(values = HNL_colors)+
  labs(title = 'Atlantic basin, STSS biome, January 2018',
       col = 'OceanSODA\npH anomaly',
       x = 'Argo pH')

rm(OceanSODA_SO_extreme_grid_2018, profile_extreme_Atl_2018)

Averaged profiles

# calculate mean profiles in each basin and biome, for each month between 2014 and 2021 
# cut depth levels at 10, 20, .... etc m
# add seasons 
# Dec, Jan, Feb <- summer 
# Mar, Apr, May <- autumn 
# Jun, Jul, Aug <- winter 
# Sep, Oct, Nov <- spring 

profile_extreme <- profile_extreme %>%
  mutate(
    depth = Hmisc::cut2(
      depth,
      cuts = c(10, 20, 30, 50, 70, 100, 300, 500, 800, 1000, 1500, 2000, 2500),
      m = 5,
      levels.mean = TRUE
    ),
    depth = as.numeric(as.character(depth))
  ) %>%
  mutate(
    season = case_when(
      between(month, 3, 5) ~ 'autumn',
      between(month, 6, 8) ~ 'winter',
      between(month, 9, 11) ~ 'spring',
      month == 12 | 1 | 2 ~ 'summer'
    ),
    .after = date
  ) 

Overall mean

profile_extreme_mean <- profile_extreme %>%
  group_by(ph_extreme, depth) %>%
  summarise(ph_mean = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
            ph_std = sd(ph_in_situ_total_adjusted, na.rm = TRUE)) %>%
  ungroup()

profile_extreme_mean %>%
  arrange(depth) %>%
  ggplot(aes(
    x = ph_mean,
    y = depth,
    group = ph_extreme,
    col = ph_extreme
  )) +
  geom_ribbon(aes(xmin = ph_mean - ph_std,
                  xmax = ph_mean + ph_std,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_path() +
  scale_color_manual(values = HNL_colors) +
  scale_fill_manual(values = HNL_colors)+
  labs(title = "Overall mean",
       col = 'OceanSODA\npH anomaly \n(mean ± st dev)',
       fill = 'OceanSODA\npH anomaly \n(mean ± st dev)',
       y = 'depth (m)',
       x = 'Argo mean pH') +
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))

Past versions of mean_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
daa0a8f	pasqualina-vonlanthendinenna	2022-02-24
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01
44fcfb6	pasqualina-vonlanthendinenna	2022-02-01
28c8d17	jens-daniel-mueller	2022-01-29

rm(profile_extreme_mean)

Number of profiles

profile_count_mean <- profile_extreme %>% 
  distinct(ph_extreme, platform_number, cycle_number) %>% 
  count(ph_extreme)

profile_count_mean %>% 
  ggplot(aes(x = ph_extreme, y = n, fill = ph_extreme))+
  geom_col(width = 0.5)+
  scale_y_continuous(trans = 'log10')+
  labs(y = 'log(number of profiles)',
       title = 'Number of profiles')

Past versions of mean_profile_count-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

# rm(profile_count_mean)

Surface Argo pH vs surface OceanSODA pH (20 m)

# calculate surface-mean argo pH, for each profile 
surface_ph_mean <- profile_extreme %>% 
  filter(depth <= 20) %>% 
  group_by(ph_extreme, platform_number, cycle_number) %>% 
  summarise(argo_surf_ph = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
            OceanSODA_surf_ph = mean(OceanSODA_ph, na.rm = TRUE))


surface_ph_mean %>% 
  group_by(ph_extreme) %>% 
  group_split(ph_extreme) %>% 
  map(
  ~ggplot(data = .x, aes(x = OceanSODA_surf_ph, 
             y = argo_surf_ph))+
  geom_bin2d(data = .x, aes(x = OceanSODA_surf_ph, 
                 y = argo_surf_ph)) +
  scale_fill_viridis_c()+
  geom_abline(slope = 1, intercept = 0)+
  coord_fixed(ratio = 1, 
              xlim = c(7.9, 8.21),
              ylim = c(7.9, 8.21))+
  # facet_grid(basin_AIP ~ biome) +
    labs(title = paste('pH extreme:', unique(.x$ph_extreme)),
         x = 'OceanSODA pH',
         y = 'Argo pH')
  )

[[1]]

Past versions of argo_vs_OceanSODA_ph_mean-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[2]]

Past versions of argo_vs_OceanSODA_ph_mean-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[3]]

Past versions of argo_vs_OceanSODA_ph_mean-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

rm(surface_ph_mean)

January Overall Mean Profiles

profile_extreme_mean_jan <- profile_extreme %>%
  filter(month == 1) %>% 
  group_by(ph_extreme, depth) %>%
  summarise(ph_mean = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
            ph_std = sd(ph_in_situ_total_adjusted, na.rm = TRUE)) %>%
  ungroup()

profile_extreme_mean_jan %>%
  arrange(depth) %>%
  ggplot(aes(
    x = ph_mean,
    y = depth,
    group = ph_extreme,
    col = ph_extreme
  )) +
  geom_ribbon(aes(xmin = ph_mean - ph_std,
                  xmax = ph_mean + ph_std,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_path() +
  scale_color_manual(values = HNL_colors) +
  scale_fill_manual(values = HNL_colors)+
  labs(title = "Overall mean January profiles",
       col = 'OceanSODA\npH anomaly \n(mean ± st dev)',
       fill = 'OceanSODA\npH anomaly \n(mean ± st dev)',
       y = 'depth (m)',
       x = 'Argo mean pH') +
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))

Past versions of overall_mean_january_ph_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

rm(profile_extreme_mean_jan)

Season x Mayot biome

profile_extreme_biome <- profile_extreme %>% 
  group_by(season, biome_name, ph_extreme, depth) %>% 
  summarise(ph_biome = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
            ph_biome_std = sd(ph_in_situ_total_adjusted, na.rm = TRUE)) %>% 
  ungroup()
  

profile_extreme_biome %>%
  ggplot(aes(
    x = ph_biome,
    y = depth,
    group = ph_extreme,
    col = ph_extreme
  )) +
  geom_ribbon(aes(xmin = ph_biome - ph_biome_std,
                  xmax = ph_biome + ph_biome_std,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA, 
              alpha = 0.2)+
  geom_path() +
  scale_color_manual(values = HNL_colors) +
  scale_fill_manual(values = HNL_colors)+
  labs(col = 'OceanSODA\npH anomaly \n(mean ± st dev)',
       fill = 'OceanSODA\npH anomaly \n(mean ± st dev)',
       y = 'depth (m)',
       x = 'Biome mean Argo pH',
       title = 'Biome-mean Argo profiles') +
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500))) +
  facet_grid(season ~ biome_name)

Past versions of mean_profiles_season_biome-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
daa0a8f	pasqualina-vonlanthendinenna	2022-02-24
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01
44fcfb6	pasqualina-vonlanthendinenna	2022-02-01
28c8d17	jens-daniel-mueller	2022-01-29

rm(profile_extreme_biome)

Number of profiles season x biome

profile_count_biome <- profile_extreme %>% 
  distinct(season, biome_name, ph_extreme, platform_number, cycle_number) %>% 
  group_by(season, biome_name, ph_extreme) %>% 
  count(ph_extreme)

profile_count_biome %>% 
  ggplot(aes(x = ph_extreme, y = n, fill = ph_extreme))+
  geom_col(width = 0.5)+
  facet_grid(season ~ biome_name)+
  scale_y_continuous(trans = 'log10')+
  labs(y = 'log(number of profiles)',
       title = 'Number of profiles season x biome')

Past versions of count_profiles_season_biome-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

# rm(profile_count_biome)

Surface Argo vs surface OceanSODA pH (20 m) season x biome

surface_ph_biome <- profile_extreme %>% 
  filter(depth <= 20) %>% 
  group_by(season, biome_name, ph_extreme, platform_number, cycle_number) %>% 
  summarise(argo_surf_ph = mean(ph_in_situ_total_adjusted, na.rm=TRUE),
            OceanSODA_surf_ph = mean(OceanSODA_ph, na.rm = TRUE))

surface_ph_biome %>% 
  group_by(ph_extreme) %>% 
  group_split(ph_extreme) %>% 
  map(
  ~ggplot(data = .x, aes(x = OceanSODA_surf_ph, 
             y = argo_surf_ph))+
  geom_bin2d(data = .x, aes(x = OceanSODA_surf_ph, 
                 y = argo_surf_ph)) +
  scale_fill_viridis_c()+
  geom_abline(slope = 1, intercept = 0)+
  coord_fixed(ratio = 1, 
              xlim = c(7.94, 8.21),
              ylim = c(7.94, 8.21))+
  facet_grid(season~biome_name) +
    labs(title = paste( 'pH extreme:', unique(.x$ph_extreme)),
         x = 'OceanSODA pH',
         y = 'Argo pH')
  )

[[1]]

Past versions of argo_vs_OceanSODA_biome-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[2]]

Past versions of argo_vs_OceanSODA_biome-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[3]]

Past versions of argo_vs_OceanSODA_biome-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

rm(surface_ph_biome)

Season x basin

profile_extreme_basin <- profile_extreme %>% 
  group_by(season, basin_AIP, ph_extreme, depth) %>% 
  summarise(ph_basin = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
            ph_basin_std = sd(ph_in_situ_total_adjusted, na.rm = TRUE)) %>% 
  ungroup()

profile_extreme_basin %>% 
  ggplot(aes(x = ph_basin, 
             y = depth, 
             group = ph_extreme, 
             col = ph_extreme))+
  geom_ribbon(aes(xmax = ph_basin + ph_basin_std,
                  xmin = ph_basin - ph_basin_std,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.3)+
  geom_path()+
  scale_color_manual(values = HNL_colors)+
  scale_fill_manual(values = HNL_colors)+
  labs(col = 'OceanSODA\npH anomaly\n(mean ± st dev)',
       fill = 'OceanSODA\npH anomaly\n(mean ± st dev)',
       y = 'depth (m)',
       x = 'Basin mean Argo pH',
       title = 'Basin-mean Argo profiles')+
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500))) +
  facet_grid(season~basin_AIP)

Past versions of mean_basin_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
daa0a8f	pasqualina-vonlanthendinenna	2022-02-24
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01
44fcfb6	pasqualina-vonlanthendinenna	2022-02-01
28c8d17	jens-daniel-mueller	2022-01-29
cfd734c	jens-daniel-mueller	2022-01-28
c44ff0f	pasqualina-vonlanthendinenna	2022-01-25

rm(profile_extreme_basin)

Number of profiles season x basin

profile_count_basin <- profile_extreme %>% 
  distinct(season, basin_AIP, ph_extreme, platform_number, cycle_number) %>% 
  group_by(season, basin_AIP, ph_extreme) %>% 
  count(ph_extreme)

profile_count_basin %>% 
  ggplot(aes(x = ph_extreme, y = n, fill = ph_extreme))+
  geom_col(width = 0.5)+
  facet_grid(season~basin_AIP)+
  scale_y_continuous(trans = 'log10')+
  labs(y = 'log(number of profiles)',
       title = 'Number of profiles season x basin')

Past versions of count_basin_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

# rm(profile_count_basin)

Surface Argo vs surface OceanSODA pH (20 m) season x basin

# calculate surface-mean argo pH to compare against OceanSODA surface pH (one value)
surface_ph_basin <- profile_extreme %>% 
  filter(depth <= 20) %>% 
  group_by(season, basin_AIP, ph_extreme, platform_number, cycle_number) %>% 
  summarise(surf_argo_ph = mean(ph_in_situ_total_adjusted, na.rm=TRUE),
            surf_OceanSODA_ph = mean(OceanSODA_ph, na.rm = TRUE)) 

surface_ph_basin %>% 
  group_by(ph_extreme) %>% 
  group_split(ph_extreme) %>% 
  map(
  ~ggplot(data = .x, aes(x = surf_OceanSODA_ph, 
             y = surf_argo_ph))+
  geom_bin2d(data = .x, aes(x = surf_OceanSODA_ph, 
                 y = surf_argo_ph)) +
  scale_fill_viridis_c()+
  geom_abline(slope = 1, intercept = 0)+
  coord_fixed(ratio = 1, 
              xlim = c(7.94, 8.21),
              ylim = c(7.94, 8.21))+
  facet_grid(season~basin_AIP) +
    labs(title = paste('pH extreme:', unique(.x$ph_extreme)),
         x = 'OceanSODA pH',
         y = 'Argo pH')
  )

[[1]]

Past versions of argo_vs_OceanSODA_pH_basin-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
2d1bdae	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[2]]

Past versions of argo_vs_OceanSODA_pH_basin-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
2d1bdae	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[3]]

Past versions of argo_vs_OceanSODA_pH_basin-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
2d1bdae	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

rm(surface_ph_basin)

Biome-basin January mean

profile_extreme_biome_basin_jan <- profile_extreme %>%
  filter(month == 1) %>% 
  group_by(biome_name, basin_AIP, ph_extreme, depth) %>%
  summarise(ph_mean = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
            ph_std = sd(ph_in_situ_total_adjusted, na.rm = TRUE)) %>%
  ungroup()

profile_extreme_biome_basin_jan %>%
  arrange(depth) %>%
  ggplot(aes(x = ph_mean,
             y = depth)) +
  geom_ribbon(aes(xmin = ph_mean - ph_std,
                  xmax = ph_mean + ph_std,
                  fill = ph_extreme), 
              alpha = 0.2)+
  geom_path(aes(x = ph_mean,
                col = ph_extreme))+
  facet_grid(basin_AIP~biome_name)+
  scale_color_manual(values = HNL_colors) +
  scale_fill_manual(values = HNL_colors)+
  labs(title = "Basin-biome-mean January profiles",
       col = 'OceanSODA\nph anomaly \n(mean ± st dev)',
       fill = 'OceanSODA\nph anomaly \n(mean ± st dev)',
       y = 'sqrt(depth)',
       x = 'mean Argo pH)') +
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))

Past versions of january_biome_basin_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
a2271df	pasqualina-vonlanthendinenna	2022-03-30

rm(profile_extreme_biome_basin_jan)

Season x biome x basin

profile_extreme_season <- profile_extreme %>%
  group_by(season, biome_name, basin_AIP, ph_extreme, depth) %>%
  summarise(ph_mean = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
            ph_std = sd(ph_in_situ_total_adjusted, na.rm = TRUE)) %>%
  ungroup()

profile_extreme_season %>%
  arrange(depth) %>%
  group_split(season) %>%
  # head(1) %>%
  map(
    ~ ggplot(
      data = .x,
      aes(
        x = ph_mean,
        y = depth,
        group = ph_extreme,
        col = ph_extreme
      )
    ) +
      geom_ribbon(aes(xmax = ph_mean + ph_std,
                      xmin = ph_mean - ph_std,
                      group = ph_extreme,
                      fill = ph_extreme),
                  col = NA,
                  alpha = 0.2)+
      geom_path() +
      scale_color_manual(values = HNL_colors) +
      scale_fill_manual(values = HNL_colors)+
      labs(title = paste("season:", unique(.x$season)),
           col = 'OceanSODA\npH anomaly\n(mean ± st dev)',
           fill = 'OceanSODA\npH anomaly\n(mean ± st dev)',
           y = 'sqrt(depth)',
           x = 'Argo pH') +
      scale_y_continuous(
        trans = trans_reverser("sqrt"),
        breaks = c(10, 100, 250, 500, seq(1000, 5000, 500))
      ) +
      facet_grid(basin_AIP ~ biome_name)
  )

[[1]]

Past versions of mean_profiles_season_biome_basin-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
daa0a8f	pasqualina-vonlanthendinenna	2022-02-24
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01
44fcfb6	pasqualina-vonlanthendinenna	2022-02-01
28c8d17	jens-daniel-mueller	2022-01-29

[[2]]

Past versions of mean_profiles_season_biome_basin-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
daa0a8f	pasqualina-vonlanthendinenna	2022-02-24
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01
44fcfb6	pasqualina-vonlanthendinenna	2022-02-01
28c8d17	jens-daniel-mueller	2022-01-29

[[3]]

Past versions of mean_profiles_season_biome_basin-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
daa0a8f	pasqualina-vonlanthendinenna	2022-02-24
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01
44fcfb6	pasqualina-vonlanthendinenna	2022-02-01
28c8d17	jens-daniel-mueller	2022-01-29

[[4]]

Past versions of mean_profiles_season_biome_basin-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
daa0a8f	pasqualina-vonlanthendinenna	2022-02-24
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01
44fcfb6	pasqualina-vonlanthendinenna	2022-02-01
28c8d17	jens-daniel-mueller	2022-01-29

Number of profiles per season x biome x basin x pH extreme

profile_count_season <- profile_extreme %>% 
  distinct(season, biome_name, basin_AIP,
           ph_extreme, platform_number, cycle_number) %>% 
  group_by(season, biome_name, basin_AIP, ph_extreme) %>% 
  count(ph_extreme)


profile_count_season %>% 
  group_by(season) %>% 
  group_split(season) %>% 
  map(
    ~ggplot()+
      geom_col(data =.x, 
               aes(x = ph_extreme,
                   y = n,
                   fill = ph_extreme),
               width = 0.5)+
      facet_grid(basin_AIP ~ biome_name)+
      scale_y_continuous(trans = 'log10')+
      labs(y = 'log(number of profiles)',
           title = paste('season:', unique(.x$season)))
  )

[[1]]

Past versions of count_number_season_biome_basin_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
2d1bdae	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

[[2]]

Past versions of count_number_season_biome_basin_profiles-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
2d1bdae	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

[[3]]

Past versions of count_number_season_biome_basin_profiles-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
2d1bdae	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

[[4]]

Past versions of count_number_season_biome_basin_profiles-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
2d1bdae	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

# rm(profile_count_season)

Surface OceanSODA pH vs surface Argo pH (20 m)

# calculate surface-mean argo pH, for each season x biome x basin x ph extreme 
surface_ph_season <- profile_extreme %>% 
  filter(depth <= 20) %>% 
  group_by(season, 
           basin_AIP, 
           biome_name, 
           ph_extreme, 
           platform_number, 
           cycle_number) %>% 
  summarise(surf_argo_ph = mean(ph_in_situ_total_adjusted, na.rm=TRUE),
            surf_OceanSODA_ph = mean(OceanSODA_ph, na.rm = TRUE)) 

surface_ph_season %>% 
  group_by(season, ph_extreme) %>% 
  group_split(season, ph_extreme) %>% 
  map(
  ~ggplot(data = .x, aes(x = surf_OceanSODA_ph, 
             y = surf_argo_ph))+
  geom_bin2d(data = .x, aes(x = surf_OceanSODA_ph, 
                 y = surf_argo_ph)) +
  scale_fill_viridis_c()+
  geom_abline(slope = 1, intercept = 0)+
  coord_fixed(ratio = 1, 
              xlim = c(7.94, 8.21),
              ylim = c(7.94, 8.21))+
  facet_grid(basin_AIP ~ biome_name) +
    labs(title = paste('season:', unique(.x$season), 
                        '| pH extreme:', unique(.x$ph_extreme)),
         x = 'OceanSODA pH',
         y = 'Argo pH')
  )

[[1]]

Past versions of surface_OceanSODA_vs_argo_ph-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
de183c6	pasqualina-vonlanthendinenna	2022-02-01
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

[[2]]

Past versions of surface_OceanSODA_vs_argo_ph-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
de183c6	pasqualina-vonlanthendinenna	2022-02-01
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

[[3]]

Past versions of surface_OceanSODA_vs_argo_ph-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
de183c6	pasqualina-vonlanthendinenna	2022-02-01
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

[[4]]

Past versions of surface_OceanSODA_vs_argo_ph-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02
de183c6	pasqualina-vonlanthendinenna	2022-02-01
44a2ec3	pasqualina-vonlanthendinenna	2022-02-01

[[5]]

Past versions of surface_OceanSODA_vs_argo_ph-5.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[6]]

Past versions of surface_OceanSODA_vs_argo_ph-6.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[7]]

Past versions of surface_OceanSODA_vs_argo_ph-7.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[8]]

Past versions of surface_OceanSODA_vs_argo_ph-8.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[9]]

Past versions of surface_OceanSODA_vs_argo_ph-9.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[10]]

Past versions of surface_OceanSODA_vs_argo_ph-10.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[11]]

Past versions of surface_OceanSODA_vs_argo_ph-11.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

[[12]]

Past versions of surface_OceanSODA_vs_argo_ph-12.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
fd521d1	pasqualina-vonlanthendinenna	2022-02-25
71ced5f	pasqualina-vonlanthendinenna	2022-02-23
25c9e6b	pasqualina-vonlanthendinenna	2022-02-03
71958c4	pasqualina-vonlanthendinenna	2022-02-03
d7debab	pasqualina-vonlanthendinenna	2022-02-02
7376be6	pasqualina-vonlanthendinenna	2022-02-02

rm(surface_ph_season)

Atl, SPSS biome, winter

profile_extreme_season %>%
  filter(basin_AIP == 'Atlantic',
         season == 'winter',
         biome_name == 'SPSS') %>% 
  arrange(depth) %>%
  ggplot(aes(x = ph_mean,
             y = depth,
             group = ph_extreme,
             col = ph_extreme)) +
  geom_ribbon(aes(xmax = ph_mean + ph_std,
                  xmin = ph_mean - ph_std,
                  group = ph_extreme,
                  fill = ph_extreme),
                col = NA,
                alpha = 0.2)+
  geom_path() +
  scale_color_manual(values = HNL_colors) +
  scale_fill_manual(values = HNL_colors)+
  labs(title = 'Atlantic basin, SPSS biome, winter',
       col = 'OceanSODA\npH anomaly\n(mean ± st dev)',
       fill = 'OceanSODA\npH anomaly\n(mean ± st dev)',
       y = 'sqrt(depth)',
       x = 'Argo pH') +
  scale_y_continuous(
        trans = trans_reverser("sqrt"),
        breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))

Past versions of season_biome_1_Atlantic_profile_winter-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
a2271df	pasqualina-vonlanthendinenna	2022-03-30
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
e4188d2	pasqualina-vonlanthendinenna	2022-03-01

Atl, STSS biome, summer

profile_extreme_season %>%
  filter(basin_AIP == 'Atlantic',
         season == 'summer',
         biome_name == 'STSS') %>% 
  arrange(depth) %>%
  ggplot(aes(x = ph_mean,
             y = depth,
             group = ph_extreme,
             col = ph_extreme)) +
  geom_ribbon(aes(xmax = ph_mean + ph_std,
                  xmin = ph_mean - ph_std,
                  group = ph_extreme,
                  fill = ph_extreme),
                col = NA,
                alpha = 0.2)+
  geom_path() +
  scale_color_manual(values = HNL_colors) +
  scale_fill_manual(values = HNL_colors)+
  labs(title = 'Atlantic basin, STSS biome, summer',
       col = 'OceanSODA\npH anomaly\n(mean ± st dev)',
       fill = 'OceanSODA\npH anomaly\n(mean ± st dev)',
       y = 'sqrt(depth)',
       x = 'Argo pH') +
  scale_y_continuous(
        trans = trans_reverser("sqrt"),
        breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))

Past versions of Atlantic_biome_1_profile_season_summer-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
a2271df	pasqualina-vonlanthendinenna	2022-03-30
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
e12a216	pasqualina-vonlanthendinenna	2022-03-15
1ffe07f	pasqualina-vonlanthendinenna	2022-03-11
7540ae4	pasqualina-vonlanthendinenna	2022-03-08
e4188d2	pasqualina-vonlanthendinenna	2022-03-01

Remove climatology

Plot the Argo H/N/L profiles as anomalies relative to the UCSD Argo pH climatology

# # keep only january profiles 
profile_extreme_jan <- profile_extreme %>%
  filter(month == 1)

profile_extreme_jan_binned <- profile_extreme_jan %>%
  group_by(lon, lat, year, month, platform_cycle,
           biome_name, basin_AIP, ph_extreme,
           depth) %>%
  summarize(ph_adjusted_binned = mean(ph_in_situ_total_adjusted, na.rm = TRUE)) %>%
  ungroup()

Argo UCSD pH climatology

ucsd_clim_argo_ph_jan <- read_rds(file = paste0(path_argo_preprocessed, "/ucsd_ph_clim_jan.rds"))

# compatibility with profile_temp_extreme_jan
ucsd_clim_argo_ph_jan_SO <- ucsd_clim_argo_ph_jan %>% 
  filter(lat < -30) %>% 
  mutate(depth_ucsd = depth)

# grid average climatological temp into the argo depth bins 
ucsd_clim_argo_ph_jan_SO <- ucsd_clim_argo_ph_jan_SO %>%
  mutate(
    depth = cut(
      depth_ucsd,
      breaks = c(0, 10, 20, 30, 50, 70, 100, 300, 500, 800, 1000, 1500, 2000),
      include.lowest = TRUE,
      labels = as.factor(unique(profile_extreme_jan$depth))
    ),
    depth = as.numeric(as.character(depth))
  )


# calculate mean climatological pH per depth bin
ucsd_clim_argo_ph_jan_SO_binned <- ucsd_clim_argo_ph_jan_SO %>% 
  group_by(lon, lat, depth, month) %>% 
  summarise(clim_ph_jan_binned = mean(clim_pH_jan, na.rm = TRUE)) %>%
  ungroup()


# join climatology and ARGO profiles

remove_clim_jan <- inner_join(profile_extreme_jan_binned, 
                              ucsd_clim_argo_ph_jan_SO_binned %>% 
                                mutate(lat = lat + 0.5))

Profiles - Jan

Points are the January climatological pH, lines are the depth-binned Argo profiles colored by H/N/L classification

Absolute

remove_clim_jan %>%
  group_split(biome_name, basin_AIP, year) %>%
  head(6) %>%
  map(
    ~ ggplot() +
      geom_path(
        data = .x %>%
          filter(ph_extreme == 'N'),
        aes(
          x = ph_adjusted_binned,
          y = depth,
          group = platform_cycle,
          col = ph_extreme
        ),
        size = 0.3
      ) +
      geom_path(
        data = .x %>%
          filter(ph_extreme == 'H' | ph_extreme == 'L'),
        aes(
          x = ph_adjusted_binned,
          y = depth,
          group = platform_cycle,
          col = ph_extreme
        ),
        size = 0.5
      ) +
      geom_point(
        data = .x,
        aes(x = clim_ph_jan_binned,
            y = depth,
            col = ph_extreme),
        size = 0.5
      ) +
      scale_y_reverse() +
      scale_color_manual(values = HNL_colors) +
      labs(
        x = 'Argo pH',
        y = 'depth (m)',
        title = paste(
          "Biome:",
          unique(.x$biome_name),
          "| basin:",
          unique(.x$basin_AIP),
          " | Jan",
          unique(.x$year)
        ),
        col = 'OceanSODA pH \nanomaly'
      )
  )

[[1]]

Past versions of plot_raw_ph_profiles_with_clim-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
968ad85	pasqualina-vonlanthendinenna	2022-03-29

[[2]]

Past versions of plot_raw_ph_profiles_with_clim-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[3]]

Past versions of plot_raw_ph_profiles_with_clim-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[4]]

Past versions of plot_raw_ph_profiles_with_clim-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[5]]

Past versions of plot_raw_ph_profiles_with_clim-5.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[6]]

Past versions of plot_raw_ph_profiles_with_clim-6.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

# calculate the difference between the binned climatological argo and in-situ argo for each depth level and grid cell 

remove_clim_jan <- remove_clim_jan %>% 
  mutate(argo_ph_anomaly = ph_adjusted_binned - clim_ph_jan_binned)

Anomaly

remove_clim_jan %>% 
  group_split(year) %>% 
  #head(1) %>% 
  map(
    ~ggplot()+
      geom_path(data = .x %>% filter(ph_extreme == 'N'),
                aes(x = argo_ph_anomaly,
                    y = depth,
                    group = platform_cycle,
                    col = ph_extreme),
                size = 0.2)+
      geom_path(data = .x %>% filter(ph_extreme == 'H'| ph_extreme == 'L'),
                 aes(x = argo_ph_anomaly,
                     y = depth,
                     group = platform_cycle,
                     col = ph_extreme),
                 size = 0.3)+
      geom_vline(xintercept = 0)+
      scale_y_continuous(trans = trans_reverser("sqrt"),
                         breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
      scale_color_manual(values = HNL_colors)+
      scale_fill_manual(values = HNL_colors)+
      facet_grid(basin_AIP~biome_name)+
      labs(title = paste('January', unique(.x$year)))
  )

[[1]]

Past versions of plot_january_anomaly_ph_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
a2271df	pasqualina-vonlanthendinenna	2022-03-30
968ad85	pasqualina-vonlanthendinenna	2022-03-29

[[2]]

Past versions of plot_january_anomaly_ph_profiles-2.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[3]]

Past versions of plot_january_anomaly_ph_profiles-3.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[4]]

Past versions of plot_january_anomaly_ph_profiles-4.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[5]]

Past versions of plot_january_anomaly_ph_profiles-5.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

[[6]]

Past versions of plot_january_anomaly_ph_profiles-6.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

Overall mean anomaly

remove_clim_jan_overall_mean <- remove_clim_jan %>% 
  group_by(ph_extreme, depth) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm = TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_jan_overall_mean %>% 
  ggplot()+
  geom_path(aes(x = ph_anomaly_mean,
                y = depth,
                group = ph_extreme,
                col = ph_extreme))+
  geom_ribbon(aes(xmax = ph_anomaly_mean + ph_anomaly_sd,
                  xmin = ph_anomaly_mean - ph_anomaly_sd,
                  y = depth,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_vline(xintercept = 0)+
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
  scale_color_manual(values = HNL_colors)+
  scale_fill_manual(values = HNL_colors)+
  labs(title = 'January Overall Mean Anomaly Profiles')

Past versions of plot_overall_mean_clim_removed_profiles_ph-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
a2271df	pasqualina-vonlanthendinenna	2022-03-30
968ad85	pasqualina-vonlanthendinenna	2022-03-29

rm(remove_clim_jan_overall_mean)

Biome-mean anomaly

# using the Mayot biomes 

remove_clim_jan_biome_mean <- remove_clim_jan %>% 
  group_by(ph_extreme, depth, biome_name) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm = TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_jan_biome_mean %>% 
  ggplot(aes(x = ph_anomaly_mean,
                y = depth,
                group = ph_extreme,
                col = ph_extreme))+
  geom_path()+
  geom_ribbon(aes(xmax = ph_anomaly_mean + ph_anomaly_sd,
                  xmin = ph_anomaly_mean - ph_anomaly_sd,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_vline(xintercept = 0)+
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
  scale_fill_manual(values = HNL_colors)+
  scale_color_manual(values = HNL_colors)+
  labs(title = 'January Biome-mean anomaly profiles')+
  facet_wrap(~biome_name)

Past versions of plot_biome_mean_clim_removed_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
a2271df	pasqualina-vonlanthendinenna	2022-03-30
968ad85	pasqualina-vonlanthendinenna	2022-03-29

rm(remove_clim_jan_biome_mean)

Basin-mean anomaly

remove_clim_jan_basin_mean <- remove_clim_jan %>% 
  group_by(basin_AIP, ph_extreme, depth) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm = TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_jan_basin_mean %>% 
  ggplot(aes(x = ph_anomaly_mean,
             y = depth, 
             group = ph_extreme,
             col = ph_extreme))+
  geom_path()+
  geom_ribbon(aes(xmax = ph_anomaly_mean + ph_anomaly_sd,
                  xmin = ph_anomaly_mean - ph_anomaly_sd,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_vline(xintercept = 0)+
  facet_wrap(~basin_AIP)+
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
  scale_color_manual(values = HNL_colors)+
  scale_fill_manual(values = HNL_colors)+
  labs(title = 'January Basin-mean anomaly profiles')

Past versions of plot_basin_mean_anomaly_profiles-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
a2271df	pasqualina-vonlanthendinenna	2022-03-30
968ad85	pasqualina-vonlanthendinenna	2022-03-29

rm(remove_clim_jan_basin_mean)

Basin-biome-mean anomaly

remove_clim_jan_basin_biome_mean <- remove_clim_jan %>% 
  group_by(basin_AIP, biome_name, ph_extreme, depth) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm = TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_jan_basin_biome_mean %>% 
  ggplot(aes(x = ph_anomaly_mean,
             y = depth, 
             group = ph_extreme,
             col = ph_extreme))+
  geom_path()+
  geom_ribbon(aes(xmax = ph_anomaly_mean + ph_anomaly_sd,
                  xmin = ph_anomaly_mean - ph_anomaly_sd,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_vline(xintercept = 0)+
  facet_grid(basin_AIP~biome_name)+
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
  scale_color_manual(values = HNL_colors)+
  scale_fill_manual(values = HNL_colors)+
  labs(title = 'January Basin-biome-mean anomaly profiles')

Past versions of plot_basin_biome_mean_anomaly_profiles_ph-1.png

Version	Author	Date
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
a2271df	pasqualina-vonlanthendinenna	2022-03-30
968ad85	pasqualina-vonlanthendinenna	2022-03-29

rm(remove_clim_jan_basin_biome_mean)

Broullón TA-DIC pH climatology

profile_extreme_binned <- profile_extreme %>%
  group_by(lon, lat, year, month, platform_cycle,
           biome_name, basin_AIP, ph_extreme,
           depth, season) %>%
  summarise(ph_adjusted_binned = mean(ph_in_situ_total_adjusted, na.rm = TRUE)) %>%
  ungroup()

broullon_clim <- read_rds(file = paste0(path_argo_preprocessed, 
                                        '/broullon_TA_DIC_clim_SO_pH.rds'))

# compatibility with profile_extreme
broullon_clim <- broullon_clim %>% 
  mutate(depth_broullon = depth)

# grid average climatological temp into the argo depth bins 
broullon_clim <- broullon_clim %>%
  mutate(
    depth = cut(
      depth_broullon,
      breaks = c(0, 10, 20, 30, 50, 70, 100, 300, 500, 800, 1000, 1500, 2000),
      include.lowest = TRUE,
      labels = as.factor(unique(profile_extreme$depth))
    ),
    depth = as.numeric(as.character(depth))
  )


# calculate mean climatological pH per depth bin
broullon_clim_binned <- broullon_clim %>% 
  group_by(lon, lat, depth, month, basin_AIP, biome_name) %>% 
  summarise(clim_ph_binned = mean(pH, na.rm = TRUE)) %>%
  ungroup()


# join climatology and ARGO profiles

remove_clim <- inner_join(profile_extreme_binned, 
                              broullon_clim_binned)

Profiles - Absolute

remove_clim %>%
  group_split(biome_name, basin_AIP, year) %>%
  head(6) %>%
  map(
    ~ ggplot() +
      geom_path(
        data = .x %>%
          filter(ph_extreme == 'N'),
        aes(
          x = ph_adjusted_binned,
          y = depth,
          group = platform_cycle,
          col = ph_extreme
        ),
        size = 0.3
      ) +
      geom_path(
        data = .x %>%
          filter(ph_extreme == 'H' | ph_extreme == 'L'),
        aes(
          x = ph_adjusted_binned,
          y = depth,
          group = platform_cycle,
          col = ph_extreme
        ),
        size = 0.5
      ) +
      geom_point(
        data = .x,
        aes(x = clim_ph_binned,
            y = depth,
            col = ph_extreme),
        size = 0.5
      ) +
      scale_y_reverse() +
      scale_color_manual(values = HNL_colors) +
      labs(
        x = 'Argo pH',
        y = 'depth (m)',
        title = paste(
          "Biome:",
          unique(.x$biome_name),
          "| basin:",
          unique(.x$basin_AIP),
          " | ",
          unique(.x$year)
        ),
        col = 'OceanSODA pH \nanomaly'
      )
  )

[[1]]

Past versions of plot_raw_profiles_with_broullon_clim-1.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[2]]

Past versions of plot_raw_profiles_with_broullon_clim-2.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[3]]

Past versions of plot_raw_profiles_with_broullon_clim-3.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[4]]

Past versions of plot_raw_profiles_with_broullon_clim-4.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[5]]

Past versions of plot_raw_profiles_with_broullon_clim-5.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[6]]

Past versions of plot_raw_profiles_with_broullon_clim-6.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

Profiles - Anomaly

remove_clim <- remove_clim %>% 
  mutate(argo_ph_anomaly = ph_adjusted_binned - clim_ph_binned)

remove_clim %>% 
  group_split(month) %>% 
  #head(1) %>% 
  map(
    ~ggplot()+
      geom_path(data = .x %>% filter(ph_extreme == 'N'),
                aes(x = argo_ph_anomaly,
                    y = depth,
                    group = platform_cycle,
                    col = ph_extreme),
                size = 0.2)+
      geom_path(data = .x %>% filter(ph_extreme == 'H'| ph_extreme == 'L'),
                 aes(x = argo_ph_anomaly,
                     y = depth,
                     group = platform_cycle,
                     col = ph_extreme),
                 size = 0.3)+
      geom_vline(xintercept = 0)+
      scale_y_continuous(trans = trans_reverser("sqrt"),
                         breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
      scale_color_manual(values = HNL_colors)+
      scale_fill_manual(values = HNL_colors)+
      facet_grid(basin_AIP~biome_name)+
      labs(title = paste('month:', unique(.x$month)))
  )

[[1]]

Past versions of plot_anomaly_profiles_broullon_clim-1.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[2]]

Past versions of plot_anomaly_profiles_broullon_clim-2.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[3]]

Past versions of plot_anomaly_profiles_broullon_clim-3.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[4]]

Past versions of plot_anomaly_profiles_broullon_clim-4.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[5]]

Past versions of plot_anomaly_profiles_broullon_clim-5.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[6]]

Past versions of plot_anomaly_profiles_broullon_clim-6.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[7]]

Past versions of plot_anomaly_profiles_broullon_clim-7.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[8]]

Past versions of plot_anomaly_profiles_broullon_clim-8.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[9]]

Past versions of plot_anomaly_profiles_broullon_clim-9.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[10]]

Past versions of plot_anomaly_profiles_broullon_clim-10.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[11]]

Past versions of plot_anomaly_profiles_broullon_clim-11.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[12]]

Past versions of plot_anomaly_profiles_broullon_clim-12.png

Version	Author	Date
a107add	pasqualina-vonlanthendinenna	2022-05-03

Overall mean anomaly profiles

remove_clim_overall_mean <- remove_clim %>% 
  group_by(ph_extreme, depth) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm = TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_overall_mean %>% 
  ggplot()+
  geom_path(aes(x = ph_anomaly_mean,
                y = depth,
                group = ph_extreme,
                col = ph_extreme))+
  geom_ribbon(aes(xmax = ph_anomaly_mean + ph_anomaly_sd,
                  xmin = ph_anomaly_mean - ph_anomaly_sd,
                  y = depth,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_vline(xintercept = 0)+
  scale_y_continuous(trans = trans_reverser("sqrt"),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
  scale_color_manual(values = HNL_colors)+
  scale_fill_manual(values = HNL_colors)+
  geom_text_repel(data = profile_count_mean,
                  aes(x = -0.075,
                      y = 1500,
                      label = paste0(n),
                      col = ph_extreme),
                  size = 7,
                  segment.color = 'transparent')+
  labs(title = 'Overall Mean Anomaly Profiles')

Past versions of overall_mean_anomaly_profiles_broullon-1.png

Version	Author	Date
708f923	pasqualina-vonlanthendinenna	2022-05-04
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
a107add	pasqualina-vonlanthendinenna	2022-05-03

rm(remove_clim_overall_mean, profile_count_mean)

Biome-mean anomaly profiles

remove_clim_biome <- remove_clim %>% 
  group_by(depth, ph_extreme, biome_name, season) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm = TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_biome %>% 
  ggplot()+
  geom_path(aes(x = ph_anomaly_mean,
                y = depth,
                group = ph_extreme,
                col = ph_extreme))+
  geom_ribbon(aes(xmax = ph_anomaly_mean + ph_anomaly_sd,
                  xmin = ph_anomaly_mean - ph_anomaly_sd,
                  y = depth, 
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  geom_vline(xintercept = 0)+
  scale_y_continuous(trans = trans_reverser('sqrt'),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
  facet_grid(season~biome_name)+
  scale_color_manual(values = HNL_colors)+
  scale_fill_manual(values = HNL_colors)+
  geom_text_repel(data = profile_count_biome,
                  aes(x = -0.085,
                      y = 1500,
                      label = paste0(n),
                      col = ph_extreme),
                  size = 4,
                  segment.color = 'transparent')+
  labs(title = 'Biome-mean anomaly profiles')

Past versions of biome_mean_broullon_anomaly-1.png

Version	Author	Date
708f923	pasqualina-vonlanthendinenna	2022-05-04
b923426	pasqualina-vonlanthendinenna	2022-05-03
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
a107add	pasqualina-vonlanthendinenna	2022-05-03

rm(remove_clim_biome, profile_count_biome)

Basin-mean anomaly profiles

remove_clim_basin <-  remove_clim %>% 
  group_by(depth, ph_extreme, basin_AIP, season) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm = TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_basin %>% 
  ggplot()+
  geom_path(aes(x = ph_anomaly_mean,
                y = depth,
                group = ph_extreme,
                col = ph_extreme))+
  geom_ribbon(aes(xmax = ph_anomaly_mean + ph_anomaly_sd,
                  xmin = ph_anomaly_mean - ph_anomaly_sd,
                  y = depth,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
  scale_y_continuous(trans = trans_reverser('sqrt'),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
  geom_vline(xintercept = 0)+
  facet_grid(season~basin_AIP)+
  scale_color_manual(values = HNL_colors)+
  scale_fill_manual(values = HNL_colors)+
  geom_text_repel(data = profile_count_basin,
                  aes(x = -0.1,
                      y = 1500,
                      label = paste0(n),
                      col = ph_extreme),
                  size = 4,
                  segment.color = 'transparent')+
  labs(title = 'Basin-mean anomaly profiles')

Past versions of basin_mean_anomaly_profiles_broullon-1.png

Version	Author	Date
708f923	pasqualina-vonlanthendinenna	2022-05-04
b923426	pasqualina-vonlanthendinenna	2022-05-03
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
a107add	pasqualina-vonlanthendinenna	2022-05-03

rm(remove_clim_basin, profile_count_basin)

Basin-biome-mean anomaly profiles

remove_clim_basin_biome <- remove_clim %>% 
  group_by(depth, ph_extreme, season, basin_AIP, biome_name) %>% 
  summarise(ph_anomaly_mean = mean(argo_ph_anomaly, na.rm=TRUE),
            ph_anomaly_sd = sd(argo_ph_anomaly, na.rm = TRUE))

remove_clim_basin_biome %>% 
  group_by(season) %>% 
  group_split(season) %>% 
  map(
    ~ggplot()+
      geom_path(data = .x,
            aes(x = ph_anomaly_mean,
                y = depth,
                group = ph_extreme,
                col = ph_extreme))+
      geom_ribbon(data = .x,
              aes(xmax = ph_anomaly_mean+ph_anomaly_sd,
                  xmin = ph_anomaly_mean-ph_anomaly_sd,
                  y = depth,
                  group = ph_extreme,
                  fill = ph_extreme),
              col = NA,
              alpha = 0.2)+
      geom_vline(xintercept = 0)+
      scale_y_continuous(trans = trans_reverser('sqrt'),
                     breaks = c(10, 100, 250, 500, seq(1000, 5000, 500)))+
      facet_grid(biome_name~basin_AIP)+
      scale_color_manual(values = HNL_colors)+
      scale_fill_manual(values = HNL_colors)+
      labs(title = paste0('basin-biome-mean profiles ', unique(.x$season)))
  )

[[1]]

Past versions of basin_biome_mean_broullon-1.png

Version	Author	Date
b923426	pasqualina-vonlanthendinenna	2022-05-03
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[2]]

Past versions of basin_biome_mean_broullon-2.png

Version	Author	Date
b923426	pasqualina-vonlanthendinenna	2022-05-03
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[3]]

Past versions of basin_biome_mean_broullon-3.png

Version	Author	Date
b923426	pasqualina-vonlanthendinenna	2022-05-03
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[4]]

Past versions of basin_biome_mean_broullon-4.png

Version	Author	Date
b923426	pasqualina-vonlanthendinenna	2022-05-03
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
a107add	pasqualina-vonlanthendinenna	2022-05-03

rm(remove_clim_basin_biome)

Session information

sessionInfo()

R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.3

Matrix products: default
BLAS:   /usr/local/R-4.1.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.1.2/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] ggrepel_0.9.1     ggforce_0.3.3     metR_0.11.0       scico_1.3.0      
 [5] ggOceanMaps_1.2.6 ggspatial_1.1.5   broom_0.7.11      lubridate_1.8.0  
 [9] forcats_0.5.1     stringr_1.4.0     dplyr_1.0.7       purrr_0.3.4      
[13] readr_2.1.1       tidyr_1.1.4       tibble_3.1.6      ggplot2_3.3.5    
[17] tidyverse_1.3.1   workflowr_1.7.0  

loaded via a namespace (and not attached):
  [1] colorspace_2.0-2    ellipsis_0.3.2      class_7.3-20       
  [4] rgdal_1.5-28        rprojroot_2.0.2     htmlTable_2.4.0    
  [7] base64enc_0.1-3     fs_1.5.2            rstudioapi_0.13    
 [10] proxy_0.4-26        farver_2.1.0        bit64_4.0.5        
 [13] fansi_1.0.2         xml2_1.3.3          codetools_0.2-18   
 [16] splines_4.1.2       knitr_1.37          polyclip_1.10-0    
 [19] Formula_1.2-4       jsonlite_1.7.3      cluster_2.1.2      
 [22] dbplyr_2.1.1        png_0.1-7           rgeos_0.5-9        
 [25] compiler_4.1.2      httr_1.4.2          backports_1.4.1    
 [28] assertthat_0.2.1    Matrix_1.4-0        fastmap_1.1.0      
 [31] cli_3.1.1           later_1.3.0         tweenr_1.0.2       
 [34] htmltools_0.5.2     tools_4.1.2         gtable_0.3.0       
 [37] glue_1.6.0          Rcpp_1.0.8          cellranger_1.1.0   
 [40] jquerylib_0.1.4     raster_3.5-11       vctrs_0.3.8        
 [43] xfun_0.29           ps_1.6.0            rvest_1.0.2        
 [46] lifecycle_1.0.1     terra_1.5-12        getPass_0.2-2      
 [49] MASS_7.3-55         scales_1.1.1        vroom_1.5.7        
 [52] hms_1.1.1           promises_1.2.0.1    parallel_4.1.2     
 [55] RColorBrewer_1.1-2  yaml_2.2.1          gridExtra_2.3      
 [58] sass_0.4.0          rpart_4.1-15        latticeExtra_0.6-29
 [61] stringi_1.7.6       highr_0.9           e1071_1.7-9        
 [64] checkmate_2.0.0     rlang_1.0.2         pkgconfig_2.0.3    
 [67] evaluate_0.14       lattice_0.20-45     sf_1.0-5           
 [70] htmlwidgets_1.5.4   labeling_0.4.2      bit_4.0.4          
 [73] processx_3.5.2      tidyselect_1.1.1    magrittr_2.0.1     
 [76] R6_2.5.1            generics_0.1.1      Hmisc_4.6-0        
 [79] DBI_1.1.2           foreign_0.8-82      pillar_1.6.4       
 [82] haven_2.4.3         whisker_0.4         withr_2.4.3        
 [85] units_0.7-2         nnet_7.3-17         survival_3.2-13    
 [88] sp_1.4-6            modelr_0.1.8        crayon_1.4.2       
 [91] KernSmooth_2.23-20  utf8_1.2.2          tzdb_0.2.0         
 [94] rmarkdown_2.11      jpeg_0.1-9          grid_4.1.2         
 [97] readxl_1.3.1        data.table_1.14.2   callr_3.7.0        
[100] git2r_0.29.0        reprex_2.0.1        digest_0.6.29      
[103] classInt_0.4-3      httpuv_1.6.5        munsell_0.5.0      
[106] viridisLite_0.4.0   bslib_0.3.1