Extreme pH Profiles

workflowr

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Last updated: 2024-04-12

Checks: 7 0

Knit directory: bgc_argo_r_argodata/analysis/

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---

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    Modified:   analysis/MHWs_categorisation.Rmd
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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
html	c076fba	mlarriere	2024-04-12	Build site.
html	91f08a6	mlarriere	2024-04-07	Build site.
html	db21f55	mlarriere	2024-04-06	Build site.
html	c851476	mlarriere	2024-04-01	Build site.
Rmd	3ee6c97	mlarriere	2024-04-01	extreme_pH building test
html	f9de50e	ds2n19	2024-01-01	Build site.
html	07d4eb8	ds2n19	2023-12-20	Build site.
html	fa6cf38	ds2n19	2023-12-14	Build site.
Rmd	64fd104	ds2n19	2023-12-14	revised coverage analysis and SO focused cluster analysis.
html	f110b74	ds2n19	2023-12-13	Build site.
Rmd	fa9795c	ds2n19	2023-12-12	dependencies listed are start of markdown files.
Rmd	a434982	ds2n19	2023-12-11	test run of coverage maps
html	e60ebd2	ds2n19	2023-12-07	Build site.
html	23a24d1	ds2n19	2023-12-05	Revised extreme identification. Adjusted profiles for cluster analysis based on max anomaly.
Rmd	3cb4b17	ds2n19	2023-12-04	Cluster under surface extreme.
Rmd	fa1083d	ds2n19	2023-12-01	Additional analysis to cluster process.
html	cec2a2a	ds2n19	2023-11-24	Build site.
Rmd	3dc557d	ds2n19	2023-11-24	Switched to new profile details.
Rmd	59f5cc4	ds2n19	2023-11-23	Moved spatiotemporal analysis to use aligned profiles.
html	ff31fef	ds2n19	2023-11-20	Build site.
Rmd	44ce113	ds2n19	2023-11-20	Switched to new profile details.
html	80c16c2	ds2n19	2023-11-15	Build site.
html	56c8f49	ds2n19	2023-10-20	Build site.
html	1cd9ec1	ds2n19	2023-10-19	Build site.
Rmd	6dfb0be	ds2n19	2023-10-19	moved from month by month regression to annual with monthly
html	879821d	ds2n19	2023-10-18	Build site.
Rmd	dba28d5	ds2n19	2023-10-18	Clean up BGC load and re-run coverage and extreme packages.
html	93b4545	ds2n19	2023-10-18	Build site.
html	2efb8f2	ds2n19	2023-10-17	Build site.
Rmd	a8f4bb0	ds2n19	2023-10-17	standard range v climatology, season order resolved and count labels to
html	a97d9c1	ds2n19	2023-10-17	Build site.
Rmd	4293339	ds2n19	2023-10-17	standard range v climatology, season order resolved and count labels to
html	4b55c43	ds2n19	2023-10-12	Build site.
html	1ae81b3	ds2n19	2023-10-11	reworked core load process to work initially by year and then finally create consolidated all years files.
html	44f5720	ds2n19	2023-10-09	manual commit
Rmd	ce19a66	ds2n19	2023-10-04	Revised version of OceanSODA product -v2023
html	7b3d8c5	pasqualina-vonlanthendinenna	2022-08-29	Build site.
html	bdd516d	pasqualina-vonlanthendinenna	2022-05-23	Build site.
Rmd	b41e65f	pasqualina-vonlanthendinenna	2022-05-23	recreate data in bgc_argo_preprocessed_data
html	ae0f995	jens-daniel-mueller	2022-05-12	Build site.
Rmd	018f4b4	jens-daniel-mueller	2022-05-12	scaled DIC to 2019 (rather than 2015)
html	71e58d6	jens-daniel-mueller	2022-05-12	Build site.
Rmd	1bdcd6e	jens-daniel-mueller	2022-05-12	revised color scale for argo location map
html	4173c20	jens-daniel-mueller	2022-05-12	Build site.
Rmd	78acca9	jens-daniel-mueller	2022-05-12	run with DIC clim scaled to 2016
html	dfe89d7	jens-daniel-mueller	2022-05-12	Build site.
html	710edd4	jens-daniel-mueller	2022-05-11	Build site.
Rmd	2f20a76	jens-daniel-mueller	2022-05-11	rebuild all after subsetting AB profiles and code cleaning
html	b917bd0	jens-daniel-mueller	2022-05-11	Build site.
Rmd	86144c6	jens-daniel-mueller	2022-05-11	rerun with flag A and B subset
html	ca30beb	pasqualina-vonlanthendinenna	2022-05-05	Build site.
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. BGC pH profiles have already been validate for coverage and aligned to climatology depths.

Dependencies

OceanSODA.rds - bgc preprocessed folder, created by OceanSODA_argo_pH.

pH_bgc_va.rds - bgc preprocessed folder, created by ph_align_climatology.

pH_anomaly_va.rds - bgc preprocessed folder, created by ph_align_climatology.

Outputs

OceanSODA_pH_anomaly_field_01.rds (or _02.rds)

OceanSODA_global_pH_anomaly_field_01.rds (or _02.rds)

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

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

# opt_min_profile_range
# profiles with profile_range >= opt_min_profile_range will be selected 1 = profiles of at least 614m, 2 = profiles of at least 1225m, 3 = profiles of at least 1600m
opt_min_profile_range = 3

# opt_extreme_determination
# 1 - based on the trend of de-seasonal data - we believe this results in more summer extremes where variation tend to be greater.
# 2 - based on the trend of de-seasonal data by month. grouping is by lat, lon and month.
opt_extreme_determination <- 2

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/"

path_argo <- '/nfs/kryo/work/datasets/ungridded/3d/ocean/floats/bgc_argo'
# /nfs/kryo/work/datasets/ungridded/3d/ocean/floats/bgc_argo/preprocessed_bgc_data
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")

# 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))

# load validated and vertically aligned pH profiles, 
full_argo <-
  read_rds(file = paste0(path_argo_preprocessed, "/pH_bgc_va.rds")) %>%
  filter(profile_range >= opt_min_profile_range) %>%
  mutate(date = ymd(format(date, "%Y-%m-15")))

# map data
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
c076fba	mlarriere	2024-04-12
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

# Commented
# 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()

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

# Commented
#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')

Basin grid reduction

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

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

Past versions of basin_flat_map_pre_grid_reduction-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
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

# Commented
# 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))
#    )
# 
# # 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)

# Added
basinmask <- basinmask %>%
  count(lon, lat, basin_AIP) %>%
  group_by(lon, lat) %>%
  slice_max(n, with_ties = FALSE) %>%
  ungroup() %>%
  select(-n)

# commented
#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')

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

OceanSODA <- OceanSODA %>%
  mutate(
    lat_raw = lat,
    lon_raw = lon)

# 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))

## keep only Southern Ocean data
# OceanSODA_SO <- inner_join(OceanSODA, nm_biomes %>% 
#                                       select(-n)) 

# add in basin separations
OceanSODA <- inner_join(OceanSODA, basinmask)

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

Maps

OceanSODA %>% 
  filter(year == 2020) %>% 
  ggplot(aes(lon_raw, lat_raw, fill = clim_ph)) +
  geom_tile() +
  scale_fill_viridis_c() +
  facet_wrap(~ month, ncol = 2) +
  coord_quickmap(expand = 0)

Past versions of map_OceanSODA_ph_clim_diff-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11

# map of climatological OceanSODA pH 
OceanSODA %>% 
  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()+
      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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[5]]

Past versions of map_OceanSODA_pH_clim-5.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[8]]

Past versions of map_OceanSODA_pH_clim-8.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[9]]

Past versions of map_OceanSODA_pH_clim-9.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[10]]

Past versions of map_OceanSODA_pH_clim-10.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[11]]

Past versions of map_OceanSODA_pH_clim-11.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[12]]

Past versions of map_OceanSODA_pH_clim-12.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

# map of monthly anomaly relative to climatology

OceanSODA %>%
  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') +
      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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[5]]

Past versions of map_of_OceanSODA_pH_anomalies-5.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[8]]

Past versions of map_of_OceanSODA_pH_anomalies-8.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[9]]

Past versions of map_of_OceanSODA_pH_anomalies-9.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[10]]

Past versions of map_of_OceanSODA_pH_anomalies-10.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[11]]

Past versions of map_of_OceanSODA_pH_anomalies-11.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

[[12]]

Past versions of map_of_OceanSODA_pH_anomalies-12.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
710edd4	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05

OceanSODA pH anomalies

Grid level

Climatological thresholds

Fit lm models

OceanSODA <- OceanSODA %>%
  mutate(decimal_year = decimal_date(date), .after = year)

# fit a linear regression of OceanSODA pH against time (temporal trend)
# in each lat/lon/month grid
# in each lat/lon/month grid, month is used depending on opt_extreme_determination
if (opt_extreme_determination == 1){
  OceanSODA_regression <- OceanSODA %>%
    nest(data = -c(lon, lat)) %>%
    mutate(
      fit = map(
        .x = data,
        .f = ~ lm(clim_diff ~ decimal_year, data = .x)
      ),
      tidied = map(.x = fit, .f = tidy),
      glanced = map(.x = fit, .f = glance),
      augmented = map(.x = fit, .f = augment)
    )
} else if (opt_extreme_determination == 2){
  OceanSODA_regression <- OceanSODA %>%
    nest(data = -c(lon, lat, month)) %>%
    mutate(
      fit = map(
        .x = data,
        .f = ~ lm(clim_diff ~ decimal_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 = decimal_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:decimal_year, .resid)

OceanSODA_regression_augmented <- bind_cols(
  OceanSODA_regression_augmented,
  OceanSODA_regression_data %>% select(
    date, basin_AIP,   
    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_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_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_SO %>% 
#   # filter(basin_AIP == "Indian",
#   #        biome_name == "SPSS",
#   #        lon < 40) %>%
#   mutate(.resid = clim_diff)

Slope maps

if (opt_extreme_determination == 1){
  map +
    geom_tile(data = OceanSODA_regression_tidied,
              aes(x = lon,
                  y = lat,
                  fill = slope)) +
    scale_fill_scico(palette = 'vik', midpoint = 0)
} else if (opt_extreme_determination == 2){
  map +
    geom_tile(data = OceanSODA_regression_tidied,
              aes(x = lon,
                  y = lat,
                  fill = slope)) +
    scale_fill_scico(palette = 'vik', midpoint = 0) +
    facet_wrap( ~ month, ncol = 2)
}

Past versions of map_regression_slopes_flat-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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

if (opt_extreme_determination == 1){
  map +
    geom_tile(data = OceanSODA_regression_glanced,
              aes(x = lon,
                  y = lat,
                  fill = sigma)) +
    scale_fill_viridis_c() +
    labs(fill = '1 residual \nst. dev.')
} else if (opt_extreme_determination == 2){
  map +
    geom_tile(data = OceanSODA_regression_glanced,
              aes(x = lon,
                  y = lat,
                  fill = sigma)) +
    scale_fill_viridis_c() +
    labs(fill = '1 residual \nst. dev.') +
    facet_wrap(~month, ncol = 2)
}

Past versions of flat_map_sigma-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f110b74	ds2n19	2023-12-13
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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

if (opt_extreme_determination == 1){
  OceanSODA_extreme_grid <-
    full_join(
      OceanSODA_regression_augmented,
      OceanSODA_regression_glanced %>%
        select(lat:lon, sigma)
    )
} else if (opt_extreme_determination == 2){
  OceanSODA_extreme_grid <-
    full_join(
      OceanSODA_regression_augmented,
      OceanSODA_regression_glanced %>%
        select(lat:month, sigma)
    )
}

# identify observations in anomaly classes

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

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


# combine with regression coefficients

OceanSODA_extreme_grid <-
  full_join(OceanSODA_extreme_grid,
            OceanSODA_regression_tidied)

OceanSODA_extreme_grid <- OceanSODA_extreme_grid %>%
  mutate(year = year(date),
         month = month(date),
         .after = decimal_year)

Write anomalies to file

# Restrict to SO by inner join to nm_biomes
OceanSODA_SO_extreme_grid <- inner_join(OceanSODA_extreme_grid, nm_biomes %>% 
                                        select(-n)) 



# if (opt_extreme_determination == 1){
#   OceanSODA_SO_extreme_grid %>%
#     write_rds(file = paste0(path = path_argo_preprocessed, "/OceanSODA_pH_anomaly_field_01.rds"))
#   OceanSODA_extreme_grid %>%
#     write_rds(file = paste0(path = path_argo_preprocessed, "/OceanSODA_global_pH_anomaly_field_01.rds"))
# } else if (opt_extreme_determination == 2){
#   OceanSODA_SO_extreme_grid %>%
#     write_rds(file = paste0(path = path_argo_preprocessed, "/OceanSODA_pH_anomaly_field_02.rds"))
#   OceanSODA_extreme_grid %>%
#     write_rds(file = paste0(path = path_argo_preprocessed, "/OceanSODA_global_pH_anomaly_field_02.rds"))
# }

if (opt_extreme_determination == 1){
  OceanSODA_SO_extreme_grid %>%
    group_split(lon, lat) %>%
    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))
        )) +
        scale_color_manual(values = HNL_colors)
    )
} else if (opt_extreme_determination == 2){
  OceanSODA_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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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_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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
4173c20	jens-daniel-mueller	2022-05-12
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31

Anomaly time series

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

OceanSODA_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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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_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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
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

full_argo <- full_argo %>%
  mutate(
    lat_raw = lat,
    lon_raw = lon)

Apply region masks

# keep only Southern Ocean argo data
full_argo_SO <- inner_join(full_argo, nm_biomes)

# add in basin separations
full_argo_SO <- inner_join(full_argo_SO, basinmask)

Join OceanSODA

# rename OceanSODA columns
OceanSODA_SO_extreme_grid <- OceanSODA_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(
      file_id, 
      year, 
      month, 
      date, 
      lon, 
      lat, 
      depth, 
      pH
      ),
  OceanSODA_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_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
      ) +
      scale_fill_manual(values = HNL_colors_map) +
      new_scale_fill() +
      geom_tile(
        data = profile_extreme %>%
          distinct(lon, lat, file_id, year, month),
        aes(
          x = lon,
          y = lat,
          fill = 'argo\nprofiles',
          height = 1,
          width = 1
        ),
        alpha = 0.5
      ) +
      scale_fill_manual(values = "springgreen4",
                        name = "") +
      facet_wrap( ~ year, ncol = 1) +
      lims(y = c(-85, -30)) +
      labs(title = paste('month:', unique(.x$month)))
  )

[[1]]

Past versions of map_location_argo_profiles-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
ca30beb	pasqualina-vonlanthendinenna	2022-05-05
4cf88e4	pasqualina-vonlanthendinenna	2022-05-05
f46b9da	pasqualina-vonlanthendinenna	2022-05-05
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[2]]

Past versions of map_location_argo_profiles-2.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[3]]

Past versions of map_location_argo_profiles-3.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[4]]

Past versions of map_location_argo_profiles-4.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[5]]

Past versions of map_location_argo_profiles-5.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[6]]

Past versions of map_location_argo_profiles-6.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[7]]

Past versions of map_location_argo_profiles-7.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[8]]

Past versions of map_location_argo_profiles-8.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[9]]

Past versions of map_location_argo_profiles-9.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[10]]

Past versions of map_location_argo_profiles-10.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[11]]

Past versions of map_location_argo_profiles-11.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
4e3571d	pasqualina-vonlanthendinenna	2022-05-03
2d44f8a	pasqualina-vonlanthendinenna	2022-04-29

[[12]]

Past versions of map_location_argo_profiles-12.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
71e58d6	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
710edd4	jens-daniel-mueller	2022-05-11
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,
        y = depth,
        group = file_id,
        col = ph_extreme
      )
    ) +
      geom_path(data = .x %>% filter(ph_extreme == 'N'),
                aes(x = pH,
                    y = depth,
                    group = file_id,
                    col = ph_extreme),
                size = 0.3) +
      geom_path(data = .x %>% filter(ph_extreme == 'H' | ph_extreme == 'L'),
                aes(x = pH,
                    y = depth,
                    group = file_id,
                    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
c076fba	mlarriere	2024-04-12
ff31fef	ds2n19	2023-11-20
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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_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,
             group = file_id,
             col = ph_extreme))+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'N'),
            aes(x = pH,
                y = depth, 
                group = file_id,
                col = ph_extreme),
            size = 0.3)+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'H'| ph_extreme == 'L'),
            aes(x = pH,
                y = depth,
                group = file_id,
                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_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,
             group = file_id,
             col = ph_extreme))+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'N'),
            aes(x = pH,
                y = depth,
                group = file_id,
                col = ph_extreme),
            size = 0.3)+
  geom_path(data = profile_extreme_Atl_2017 %>% filter(ph_extreme == 'H' | ph_extreme == 'L'),
            aes(x = pH,
                y = depth,
                group = file_id,
                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_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,
             group = file_id,
             col = ph_extreme))+
  geom_path(data = profile_extreme_Atl_2018 %>% filter(ph_extreme == 'N'),
            aes(x = pH,
                y = depth,
                group = file_id,
                col = ph_extreme),
            size = 0.3)+
  geom_path(data = profile_extreme_Atl_2018 %>% filter(ph_extreme == 'H' | ph_extreme == 'L'),
            aes(x = pH,
                y = depth,
                group = file_id,
                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(
    season = case_when(
      between(month, 3, 5) ~ 'autumn',
      between(month, 6, 8) ~ 'winter',
      between(month, 9, 11) ~ 'spring',
      month == 12 | 1 | 2 ~ 'summer'
    ),
    season_order = case_when(
      between(month, 3, 5) ~ 2,
      between(month, 6, 8) ~ 3,
      between(month, 9, 11) ~ 4,
      month == 12 | 1 | 2 ~ 1
    ),
    .after = date
  ) 

Overall mean

profile_extreme_mean <- profile_extreme %>%
  group_by(ph_extreme, depth) %>%
  summarise(ph_mean = mean(pH, na.rm = TRUE),
            ph_std = sd(pH, 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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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, file_id) %>% 
  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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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, file_id) %>% 
  summarise(argo_surf_ph = mean(pH, na.rm = TRUE),
            OceanSODA_surf_ph = mean(OceanSODA_ph, na.rm = TRUE)) %>%
  ungroup()



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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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, na.rm = TRUE),
            ph_std = sd(pH, 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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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_order, season, biome_name, ph_extreme, depth) %>% 
  summarise(ph_biome = mean(pH, na.rm = TRUE),
            ph_biome_std = sd(pH, na.rm = TRUE)) %>% 
  ungroup()

facet_label <- as_labeller(c("1"="summer", 
                             "2"="autumn", 
                             "3"="winter", 
                             "4"="spring", 
                             "ICE" = "ICE", 
                             "SPSS" = "SPSS",
                             "STSS" = "STSS",
                             "Atlantic" = "Atlantic",
                             "Indian" = "Indian",
                             "Pacific" = "Pacific"
                             ))

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_order ~ biome_name, labeller = facet_label)

Past versions of mean_profiles_season_biome-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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_order, season, biome_name, ph_extreme, file_id) %>% 
  group_by(season_order, 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_order ~ biome_name, labeller = facet_label)+
  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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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_order, season, biome_name, ph_extreme, file_id) %>% 
  summarise(argo_surf_ph = mean(pH, 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_order~biome_name, labeller = facet_label) +
    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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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_order, season, basin_AIP, ph_extreme, depth) %>% 
  summarise(ph_basin = mean(pH, na.rm = TRUE),
            ph_basin_std = sd(pH, 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_order~basin_AIP, labeller = facet_label)

Past versions of mean_basin_profiles-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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_order, season, basin_AIP, ph_extreme, file_id) %>% 
  group_by(season_order, 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_order~basin_AIP, labeller = facet_label)+
  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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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_order, season, basin_AIP, ph_extreme, file_id) %>% 
  summarise(surf_argo_ph = mean(pH, 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_order~basin_AIP, labeller = facet_label) +
    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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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, na.rm = TRUE),
            ph_std = sd(pH, 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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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_order, season, biome_name, basin_AIP, ph_extreme, depth) %>%
  summarise(ph_mean = mean(pH, na.rm = TRUE),
            ph_std = sd(pH, na.rm = TRUE)) %>%
  ungroup()

profile_extreme_season %>%
  arrange(depth) %>%
  group_split(season_order) %>%
  # 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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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_order, season, biome_name, basin_AIP,
           ph_extreme, file_id) %>% 
  group_by(season_order, season, biome_name, basin_AIP, ph_extreme) %>% 
  count(ph_extreme)


profile_count_season %>% 
  group_by(season_order) %>% 
  group_split(season_order) %>% 
  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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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_order,
           season, 
           basin_AIP, 
           biome_name, 
           ph_extreme, 
           file_id) %>% 
  summarise(surf_argo_ph = mean(pH, na.rm=TRUE),
            surf_OceanSODA_ph = mean(OceanSODA_ph, na.rm = TRUE)) 

surface_ph_season %>% 
  group_by(season_order, ph_extreme) %>% 
  group_split(season_order, 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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
9875dd0	pasqualina-vonlanthendinenna	2022-04-05
eb8e3be	pasqualina-vonlanthendinenna	2022-03-31
968ad85	pasqualina-vonlanthendinenna	2022-03-29
dfd75e9	pasqualina-vonlanthendinenna	2022-03-29
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
b917bd0	jens-daniel-mueller	2022-05-11
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

Anomaly profiles

Read anomalies

# profile_extreme_binned <- profile_extreme %>%
#   group_by(lon, lat, year, month, file_id,
#            biome_name, basin_AIP, ph_extreme,
#            depth, season, season_order) %>%
#   summarise(ph_adjusted_binned = mean(pH, 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))[1:12]
#     ),
#     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)


remove_clim <-
  read_rds(file = paste0(path_argo_preprocessed, "/pH_anomaly_va.rds")) %>%
  filter(profile_range >= opt_min_profile_range) %>%
  mutate(date = ymd(format(date, "%Y-%m-15")))

remove_clim <- inner_join(
  remove_clim %>%
    select(
      file_id, 
      year, 
      month, 
      date, 
      lon, 
      lat, 
      depth, 
      pH,
      clim_pH,
      anomaly_pH
      ),
  OceanSODA_SO_extreme_grid %>%
    select(
      year,
      month,
      date,
      lon,
      lat,
      OceanSODA_ph,
      ph_extreme,
      biome_name,
      basin_AIP
    )
)

remove_clim <- remove_clim %>%
  mutate(
    season = case_when(
      between(month, 3, 5) ~ 'autumn',
      between(month, 6, 8) ~ 'winter',
      between(month, 9, 11) ~ 'spring',
      month == 12 | 1 | 2 ~ 'summer'
    ),
    season_order = case_when(
      between(month, 3, 5) ~ 2,
      between(month, 6, 8) ~ 3,
      between(month, 9, 11) ~ 4,
      month == 12 | 1 | 2 ~ 1
    ),
    .after = date
  ) 

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,
          y = depth,
          group = file_id,
          col = ph_extreme
        ),
        size = 0.3
      ) +
      geom_path(
        data = .x %>%
          filter(ph_extreme == 'H' | ph_extreme == 'L'),
        aes(
          x = pH,
          y = depth,
          group = file_id,
          col = ph_extreme
        ),
        size = 0.5
      ) +
      geom_point(
        data = .x,
        aes(x = clim_pH,
            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
c076fba	mlarriere	2024-04-12
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[2]]

Past versions of plot_raw_profiles_with_broullon_clim-2.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[3]]

Past versions of plot_raw_profiles_with_broullon_clim-3.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[4]]

Past versions of plot_raw_profiles_with_broullon_clim-4.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[5]]

Past versions of plot_raw_profiles_with_broullon_clim-5.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[6]]

Past versions of plot_raw_profiles_with_broullon_clim-6.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

Profiles - Anomaly

remove_clim %>% 
  group_split(month) %>% 
  #head(1) %>% 
  map(
    ~ggplot()+
      geom_path(data = .x %>% filter(ph_extreme == 'N'),
                aes(x = anomaly_pH,
                    y = depth,
                    group = file_id,
                    col = ph_extreme),
                size = 0.2)+
      geom_path(data = .x %>% filter(ph_extreme == 'H'| ph_extreme == 'L'),
                 aes(x = anomaly_pH,
                     y = depth,
                     group = file_id,
                     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
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[2]]

Past versions of plot_anomaly_profiles_broullon_clim-2.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[3]]

Past versions of plot_anomaly_profiles_broullon_clim-3.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[4]]

Past versions of plot_anomaly_profiles_broullon_clim-4.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[5]]

Past versions of plot_anomaly_profiles_broullon_clim-5.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[6]]

Past versions of plot_anomaly_profiles_broullon_clim-6.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[7]]

Past versions of plot_anomaly_profiles_broullon_clim-7.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[8]]

Past versions of plot_anomaly_profiles_broullon_clim-8.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[9]]

Past versions of plot_anomaly_profiles_broullon_clim-9.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[10]]

Past versions of plot_anomaly_profiles_broullon_clim-10.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
91f08a6	mlarriere	2024-04-07
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[11]]

Past versions of plot_anomaly_profiles_broullon_clim-11.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
a107add	pasqualina-vonlanthendinenna	2022-05-03

[[12]]

Past versions of plot_anomaly_profiles_broullon_clim-12.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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(anomaly_pH, na.rm = TRUE),
            ph_anomaly_sd = sd(anomaly_pH, na.rm = TRUE)) %>%
  ungroup()

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')+
  geom_text(data = profile_count_mean[2,],
          aes(x = -0.07,
              y = 1200,
              label = paste0(n),
              col = ph_extreme),
          size = 6)+
  geom_text(data = profile_count_mean[1,],
          aes(x = -0.07,
              y = 1400,
              label = paste0(n),
              col = ph_extreme),
          size = 6)+
  geom_text(data = profile_count_mean[3,],
          aes(x = -0.07,
              y = 1600,
              label = paste0(n),
              col = ph_extreme),
          size = 6)+
  coord_cartesian(xlim = c(-0.08, 0.08))+
  scale_x_continuous(breaks = c(-0.08, -0.04, 0, 0.04, 0.08))+
  labs(title = 'Overall Mean Anomaly Profiles')

Past versions of overall_mean_anomaly_profiles_broullon-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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_order, season) %>% 
  summarise(ph_anomaly_mean = mean(anomaly_pH, na.rm = TRUE),
            ph_anomaly_sd = sd(anomaly_pH, 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_order~biome_name, labeller = facet_label)+
  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')+
  geom_text(data = profile_count_biome %>% filter (ph_extreme == 'N'),
          aes(x = -0.07,
              y = 800,
              label = paste0(n),
              col = ph_extreme),
          size = 4)+
  geom_text(data = profile_count_biome %>% filter (ph_extreme == 'H'),
          aes(x = -0.07,
              y = 1200,
              label = paste0(n),
              col = ph_extreme),
          size = 4)+
  geom_text(data = profile_count_biome %>% filter (ph_extreme == 'L'),
          aes(x = -0.07,
              y = 1600,
              label = paste0(n),
              col = ph_extreme),
          size = 4)+
  coord_cartesian(xlim = c(-0.08, 0.08))+
  scale_x_continuous(breaks = c(-0.08, -0.04, 0, 0.04, 0.08))+
  labs(title = 'Biome-mean anomaly profiles')

Past versions of biome_mean_broullon_anomaly-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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_order, season) %>% 
  summarise(ph_anomaly_mean = mean(anomaly_pH, na.rm = TRUE),
            ph_anomaly_sd = sd(anomaly_pH, 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_order~basin_AIP, labeller = facet_label)+
  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')+
  geom_text(data = profile_count_basin %>% filter (ph_extreme == 'N'),
          aes(x = -0.07,
              y = 800,
              label = paste0(n),
              col = ph_extreme),
          size = 4)+
  geom_text(data = profile_count_basin %>% filter (ph_extreme == 'H'),
          aes(x = -0.07,
              y = 1200,
              label = paste0(n),
              col = ph_extreme),
          size = 4)+
  geom_text(data = profile_count_basin %>% filter (ph_extreme == 'L'),
          aes(x = -0.07,
              y = 1600,
              label = paste0(n),
              col = ph_extreme),
          size = 4)+
  coord_cartesian(xlim = c(-0.08, 0.08))+
  scale_x_continuous(breaks = c(-0.08, -0.04, 0, 0.04, 0.08))+
  labs(title = 'Basin-mean anomaly profiles')

Past versions of basin_mean_anomaly_profiles_broullon-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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_order, season, basin_AIP, biome_name) %>% 
  summarise(ph_anomaly_mean = mean(anomaly_pH, na.rm=TRUE),
            ph_anomaly_sd = sd(anomaly_pH, na.rm = TRUE))

remove_clim_basin_biome %>% 
  group_by(season_order) %>% 
  group_split(season_order) %>% 
  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(basin_AIP~biome_name)+
      scale_color_manual(values = HNL_colors)+
      scale_fill_manual(values = HNL_colors)+
      geom_text(data = profile_count_season %>% filter (ph_extreme == 'N' & season == unique(.x$season)),
              aes(x = -0.07,
                  y = 800,
                  label = paste0(n),
                  col = ph_extreme),
              size = 4)+
      geom_text(data = profile_count_season %>% filter (ph_extreme == 'H' & season == unique(.x$season)),
              aes(x = -0.07,
                  y = 1200,
                  label = paste0(n),
                  col = ph_extreme),
              size = 4)+
      geom_text(data = profile_count_season %>% filter (ph_extreme == 'L' & season == unique(.x$season)),
              aes(x = -0.07,
                  y = 1600,
                  label = paste0(n),
                  col = ph_extreme),
              size = 4)+
      coord_cartesian(xlim = c(-0.08, 0.08))+
      scale_x_continuous(breaks = c(-0.08, -0.04, 0, 0.04, 0.08))+
      labs(title = paste0('basin-biome-mean profiles ', unique(.x$season)))
  )

[[1]]

Past versions of basin_biome_mean_broullon-1.png

Version	Author	Date
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
2efb8f2	ds2n19	2023-10-17
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
2efb8f2	ds2n19	2023-10-17
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
2efb8f2	ds2n19	2023-10-17
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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
c076fba	mlarriere	2024-04-12
f9de50e	ds2n19	2024-01-01
23a24d1	ds2n19	2023-12-05
cec2a2a	ds2n19	2023-11-24
ff31fef	ds2n19	2023-11-20
80c16c2	ds2n19	2023-11-15
1cd9ec1	ds2n19	2023-10-19
879821d	ds2n19	2023-10-18
2efb8f2	ds2n19	2023-10-17
a97d9c1	ds2n19	2023-10-17
1ae81b3	ds2n19	2023-10-11
44f5720	ds2n19	2023-10-09
ae0f995	jens-daniel-mueller	2022-05-12
4173c20	jens-daniel-mueller	2022-05-12
b917bd0	jens-daniel-mueller	2022-05-11
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 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.5

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

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

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

other attached packages:
 [1] ggnewscale_0.4.8  ggrepel_0.9.2     ggforce_0.4.1     metR_0.13.0      
 [5] scico_1.3.1       ggOceanMaps_1.3.4 ggspatial_1.1.7   broom_1.0.5      
 [9] lubridate_1.9.0   timechange_0.1.1  forcats_0.5.2     stringr_1.5.0    
[13] dplyr_1.1.3       purrr_1.0.2       readr_2.1.3       tidyr_1.3.0      
[17] tibble_3.2.1      ggplot2_3.4.4     tidyverse_1.3.2  

loaded via a namespace (and not attached):
 [1] fs_1.5.2            sf_1.0-9            bit64_4.0.5        
 [4] RColorBrewer_1.1-3  httr_1.4.4          rprojroot_2.0.3    
 [7] tools_4.2.2         backports_1.4.1     bslib_0.4.1        
[10] utf8_1.2.2          R6_2.5.1            KernSmooth_2.23-20 
[13] rgeos_0.5-9         DBI_1.2.2           colorspace_2.0-3   
[16] raster_3.6-11       withr_2.5.0         sp_1.5-1           
[19] tidyselect_1.2.0    bit_4.0.5           compiler_4.2.2     
[22] git2r_0.30.1        cli_3.6.1           rvest_1.0.3        
[25] xml2_1.3.3          labeling_0.4.2      sass_0.4.4         
[28] checkmate_2.1.0     scales_1.2.1        classInt_0.4-8     
[31] proxy_0.4-27        digest_0.6.30       rmarkdown_2.18     
[34] pkgconfig_2.0.3     htmltools_0.5.8.1   highr_0.9          
[37] dbplyr_2.2.1        fastmap_1.1.0       rlang_1.1.1        
[40] readxl_1.4.1        rstudioapi_0.15.0   farver_2.1.1       
[43] jquerylib_0.1.4     generics_0.1.3      jsonlite_1.8.3     
[46] vroom_1.6.0         googlesheets4_1.0.1 magrittr_2.0.3     
[49] Rcpp_1.0.10         munsell_0.5.0       fansi_1.0.3        
[52] lifecycle_1.0.3     terra_1.7-65        stringi_1.7.8      
[55] whisker_0.4         yaml_2.3.6          MASS_7.3-58.1      
[58] grid_4.2.2          parallel_4.2.2      promises_1.2.0.1   
[61] crayon_1.5.2        lattice_0.20-45     haven_2.5.1        
[64] hms_1.1.2           knitr_1.41          pillar_1.9.0       
[67] codetools_0.2-18    reprex_2.0.2        glue_1.6.2         
[70] evaluate_0.18       data.table_1.14.6   modelr_0.1.10      
[73] tweenr_2.0.2        vctrs_0.6.4         tzdb_0.3.0         
[76] httpuv_1.6.6        cellranger_1.1.0    polyclip_1.10-4    
[79] gtable_0.3.1        assertthat_0.2.1    cachem_1.0.6       
[82] xfun_0.35           e1071_1.7-12        later_1.3.0        
[85] viridisLite_0.4.1   class_7.3-20        googledrive_2.0.0  
[88] gargle_1.2.1        memoise_2.0.1       workflowr_1.7.0    
[91] units_0.8-0         ellipsis_0.3.2