OceanSODA-Argo pH
Pasqualina Vonlanthen & Jens Daniel Müller
22 December, 2021
Last updated: 2021-12-22
Checks: 7 0
Knit directory: bgc_argo_r_argodata/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 89c3e41 | pasqualina-vonlanthendinenna | 2021-12-22 | added basin separations to OceanSODA |
| html | 7f3cfe7 | pasqualina-vonlanthendinenna | 2021-12-17 | Build site. |
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| html | 123e5db | pasqualina-vonlanthendinenna | 2021-12-07 | Build site. |
| Rmd | f8abe59 | pasqualina-vonlanthendinenna | 2021-12-07 | suppressed output messages and updated plots |
| html | 9abcd5e | pasqualina-vonlanthendinenna | 2021-12-03 | Build site. |
| Rmd | 78ba6f5 | pasqualina-vonlanthendinenna | 2021-12-03 | made date axis better |
| html | c391b99 | pasqualina-vonlanthendinenna | 2021-12-03 | Build site. |
| Rmd | fa75050 | pasqualina-vonlanthendinenna | 2021-12-03 | added regions to offset plot |
| html | 38a5110 | pasqualina-vonlanthendinenna | 2021-12-03 | Build site. |
| Rmd | 0829a92 | pasqualina-vonlanthendinenna | 2021-12-03 | updated offsets and divergent color scales |
| html | 6a5024e | pasqualina-vonlanthendinenna | 2021-12-02 | Build site. |
| Rmd | 65e4748 | pasqualina-vonlanthendinenna | 2021-12-02 | updated offsets between Argo and OceanSODA |
| Rmd | 315bab7 | jens-daniel-mueller | 2021-11-30 | manual commit |
| html | 10ddefb | jens-daniel-mueller | 2021-11-30 | Build site. |
| Rmd | 8392c32 | jens-daniel-mueller | 2021-11-30 | code review |
| html | 3dc093a | pasqualina-vonlanthendinenna | 2021-11-30 | Build site. |
| Rmd | 4b89d69 | pasqualina-vonlanthendinenna | 2021-11-30 | added Argo plots to OceanSODA page |
| html | 930ea26 | pasqualina-vonlanthendinenna | 2021-11-26 | Build site. |
| html | e09c60b | pasqualina-vonlanthendinenna | 2021-11-26 | Build site. |
| html | 1305d6b | pasqualina-vonlanthendinenna | 2021-11-26 | Build site. |
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| html | 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 | Build site. |
| Rmd | 9b5df99 | pasqualina-vonlanthendinenna | 2021-11-26 | added oceanSODA page |
Task
Compare BGC-Argo pH data to pH from the OceanSODA surface data product
theme_set(theme_bw())Load data
Load in surface Argo pH and the OceanSODA pH, gridded to 1x1º
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/"# load in OceanSODA data and Argo pH
OceanSODA <- read_rds(file = paste0(path_argo_preprocessed, "/OceanSODA.rds"))
argo <- read_rds(file = paste0(path_argo_preprocessed, "/ph_surface_1x1.rds")) %>%
select(-c(platform_number:pi_name),
-c(direction:platform_type),
-c(firmware_version, wmo_inst_type, positioning_system, config_mission_number))
# for plotting later, load in region and coastline information
region_masks_all_seamask_2x2 <- read_rds(file = paste0(
path_argo_preprocessed, "/region_masks_all_seamask_2x2.rds"))
region_masks_all_2x2 <- read_rds(file = paste0(path_argo_preprocessed, "/region_masks_all_2x2.rds"))
region_masks_all_1x1 <- read_rds(file = paste0(path_argo_preprocessed, "/region_masks_all_1x1.rds"))# read in the map from updata
map <-
read_rds(paste(path_emlr_utilities,
"map_landmask_WOA18.rds",
sep = ""))Harmonise the two datasets
Calculate monthly average pH for Argo pH for each lon/lat grid, centered on the 15th of each month, to match the format of OceanSODA
argo_monthly <- argo %>%
mutate(date = format_ISO8601(date, precision = "ym")) %>%
group_by(year, month, date, lat, lon) %>%
summarise(
argo_ph_month = mean(ph_in_situ_total_adjusted, na.rm = TRUE),
# calculate monthly mean argo parameters
argo_temp_month = mean(temp_adjusted, na.rm = TRUE),
argo_psal_month = mean(psal_adjusted, na.rm = TRUE)
) %>%
ungroup() %>%
select(
date,
year,
month,
lon,
lat,
argo_temp_month,
argo_psal_month,
argo_ph_month
)Join the two datasets
OceanSODA <- OceanSODA %>%
mutate(date = format_ISO8601(date, precision = "ym")) # change date format in OceanSODA to match argo date (yyyy-mm)
argo_OceanSODA <- left_join(argo_monthly, OceanSODA) %>%
rename(OceanSODA_ph = ph_total,
OceanSODA_ph_error = ph_total_uncert) argo_OceanSODA %>%
write_rds(file = paste0(path_argo_preprocessed, "/argo_OceanSODA.rds"))Southern Ocean surface pH
The focus here is on Southern Ocean surface pH, south of 30ºS, as defined in the RECCAP biome regions
region_masks_all_1x1_SO <- region_masks_all_1x1 %>%
filter(region == 'southern',
value != 0)
# keep only Southern Ocean data
argo_OceanSODA_SO <-
inner_join(region_masks_all_1x1_SO, argo_OceanSODA)Monthly climatological OceanSODA pH
Map monthly mean pH from the OceanSODA data product
Climatological OceanSODA pH
# calculate average monthly pH between April 2014 and August 2021
argo_OceanSODA_SO_clim <- argo_OceanSODA_SO %>%
group_by(lon, lat, month) %>%
summarise(
clim_OceanSODA_ph = mean(OceanSODA_ph, na.rm = TRUE),
clim_argo_ph = mean(argo_ph_month, na.rm = TRUE),
offset_clim = clim_OceanSODA_ph - clim_argo_ph
) %>%
ungroup()
# regrid to a 2x2 grid for mapping
argo_OceanSODA_SO_clim_2x2 <- argo_OceanSODA_SO_clim %>%
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))
) %>%
group_by(lon, lat, month) %>%
summarise(
clim_OceanSODA_ph = mean(clim_OceanSODA_ph, na.rm = TRUE),
clim_argo_ph = mean(clim_argo_ph, na.rm = TRUE),
offset_clim = mean(offset_clim, na.rm = TRUE)
) %>%
ungroup()
map +
geom_tile(data = argo_OceanSODA_SO_clim_2x2,
aes(lon, lat, fill = clim_OceanSODA_ph)) +
lims(y = c(-85, -25)) +
scale_fill_viridis_c() +
labs(x = 'lon',
y = 'lat',
fill = 'pH',
title = 'Monthly climatological \nOceanSODA pH (Apr 2014 - Aug 2021)') +
theme(legend.position = 'right') +
facet_wrap(~month, ncol = 2)
# plot the climatological monthly OceanSODA pH on a polar projection
basemap(limits = -32, data = argo_OceanSODA_SO_clim_2x2) + # change to polar projection
geom_spatial_tile(data = argo_OceanSODA_SO_clim_2x2,
aes(x = lon,
y = lat,
fill = clim_OceanSODA_ph),
linejoin = 'mitre',
col = 'transparent',
detail = 60)+
scale_fill_viridis_c()+
theme(legend.position = 'right')+
labs(x = 'lon',
y = 'lat',
fill = 'pH',
title = 'monthly climatological \nOceanSODA pH (Apr 2014 - Aug 2021)')+
facet_wrap(~month, ncol = 2)
Climatological monthly Argo pH
Climatological Argo pH
map +
geom_tile(data = argo_OceanSODA_SO_clim_2x2,
aes(lon, lat, fill = clim_argo_ph)) +
lims(y = c(-85, -25)) +
scale_fill_viridis_c() +
labs(x = 'lon',
y = 'lat',
fill = 'pH',
title = 'Monthly climatological \nArgo pH (Apr 2014 - Aug 2021)') +
theme(legend.position = 'right') +
facet_wrap(~month, ncol = 2)
basemap(limits = -32, data = argo_OceanSODA_SO_clim_2x2) + # change to polar projection
geom_spatial_tile(data = argo_OceanSODA_SO_clim_2x2,
aes(x = lon,
y = lat,
fill = clim_argo_ph),
linejoin = 'mitre',
col = 'transparent',
detail = 60)+
scale_fill_viridis_c()+
theme(legend.position = 'right')+
labs(x = 'lon',
y = 'lat',
fill = 'pH',
title = 'monthly climatological \nArgo pH (Apr 2014 - Aug 2021)')+
facet_wrap(~month, ncol = 2)
Timeseries of monthly OceanSODA pH
Evolution of monthly surface pH, for the three Southern Ocean RECCAP regions
map +
geom_raster(data = region_masks_all_seamask_2x2 %>%
filter(seamask == 0),
aes(x = lon, y = lat)) +
geom_raster(data = region_masks_all_2x2 %>%
filter(region == 'southern',
value != 0),
aes(x = lon,
y = lat,
fill = value)) +
labs(title = 'Southern Ocean RECCAP regions',
fill = 'region')
# plot timeseries of monthly OceanSODA pH
argo_OceanSODA_SO_clim_regional <- argo_OceanSODA_SO %>%
select(year, month, value, OceanSODA_ph, argo_ph_month) %>%
pivot_longer(c(OceanSODA_ph,argo_ph_month),
values_to = "ph",
names_to = "data_source") %>%
group_by(year, month, value, data_source) %>% # compute regional mean OceanSODA pH for the three biomes
summarise(ph = mean(ph, na.rm = TRUE)) %>%
ungroup()argo_OceanSODA_SO_clim_regional %>%
ggplot(aes(x = year,
y = ph,
col = value)) +
facet_grid(month ~ data_source) +
geom_line() +
geom_point() +
labs(x = 'year',
y = 'pH in situ (total scale)',
title = 'monthly mean pH (Apr 2014-Aug 2021, Southern Ocean)',
col = 'region')argo_OceanSODA_SO_clim_regional %>%
filter(year != 2014,
year != 2021,
value != 0) %>%
ggplot(aes(x = month,
y = ph,
group = year,
col = as.character(year)))+
geom_line()+
geom_point()+
scale_x_continuous(breaks = seq(1, 12, 2))+
facet_grid(value~data_source)+
labs(x = 'month',
y = 'pH in situ (total scale)',
title = 'monthly mean OceanSODA pH (Jan 2015-Dec 2020, Southern Ocean)',
col = 'year')
Comparison between Argo and OceanSODA pH
Calculate the difference between Argo and OceanSODA pH values
Offset between in-situ monthly pH:
argo_OceanSODA_SO <- argo_OceanSODA_SO %>%
mutate(offset = OceanSODA_ph - argo_ph_month)
argo_OceanSODA_SO %>%
drop_na() %>%
ggplot() +
geom_hline(yintercept = 0, size = 1)+
geom_point(aes(x = date, y = offset, col = value), size = 0.7, pch = 19) +
scale_x_discrete(breaks = c('2014-01', '2015-01', '2016-01', '2017-01', '2018-01', '2019-01', '2020-01'))+
labs(title = 'oceanSODA pH - Argo pH',
x = 'date',
y = 'offset (pH units)',
col = 'region')
argo_OceanSODA_SO %>%
drop_na() %>%
ggplot(aes(x = OceanSODA_ph, y = argo_ph_month))+
# geom_point(pch = 19, size = 0.7)+
geom_bin2d(aes(x = OceanSODA_ph, y = argo_ph_month), size = 0.3, bins = 60)+
lims(x = c(7.8, 8.25),
y = c(7.8, 8.25)) +
geom_abline(slope = 1, intercept = 0)+
facet_wrap(~value)+
labs(x = 'OceanSODA pH (total scale)',
y = 'Argo pH (total scale)',
col = 'region',
title = 'Southern Ocean regional pH')
| Version | Author | Date |
|---|---|---|
| 7f3cfe7 | pasqualina-vonlanthendinenna | 2021-12-17 |
Mean offset between in-situ OceanSODA pH and in-situ Argo pH
mean_insitu_offset <- argo_OceanSODA_SO %>%
group_by(date, value) %>%
summarise(mean_offset = mean(offset, na.rm = TRUE),
std_offset = sd(offset, na.rm = TRUE))
mean_insitu_offset %>%
drop_na() %>%
ggplot() +
geom_hline(yintercept = 0, size = 1, col = 'red')+
geom_point(aes(x = date, y = mean_offset, group = value, col = value), size = 0.7, pch = 19) +
geom_line(aes(x = date, y = mean_offset, group = value, col = value))+
geom_ribbon(aes(x = date,
ymin = mean_offset-std_offset,
ymax = mean_offset+std_offset,
group = value,
fill =value),
alpha = 0.2)+
scale_x_discrete(breaks = c('2014-01', '2015-01', '2016-01', '2017-01', '2018-01', '2019-01', '2020-01'))+
# facet_wrap(~year)+
labs(title = 'Mean offset (in situ oceanSODA pH - in situ Argo pH)',
x = 'date',
y = 'offset (pH units)',
col = 'region',
fill = '± 1 std')
Offset between climatological Argo and climatological OceanSODA pH:
# Offset between climatological argo and climatological OceanSODA pH
argo_OceanSODA_SO_clim <- inner_join(argo_OceanSODA_SO_clim, region_masks_all_1x1_SO)argo_OceanSODA_SO_clim %>%
drop_na() %>%
ggplot() +
geom_point(aes(x = month, y = offset_clim, col = value), size = 0.7, pch = 19) +
geom_hline(yintercept = 0, size = 1, col = 'red')+
scale_x_continuous(breaks = seq(1, 12, 1))+
labs(title = 'clim oceanSODA pH - clim Argo pH',
x = 'month',
y = 'offset (pH units)',
col = 'region')Mean offset between climatological OceanSODA pH and climatological Argo pH
mean_clim_offset <- argo_OceanSODA_SO_clim %>%
group_by(month, value) %>%
summarise(mean_offset_clim = mean(offset_clim, na.rm = TRUE),
std_offset_clim = sd(offset_clim, na.rm = TRUE))
mean_clim_offset %>%
ggplot()+
geom_point(aes(x = month, y = mean_offset_clim, col = value))+
geom_line(aes(x = month, y = mean_offset_clim, col = value))+
geom_hline(yintercept = 0, col = 'red') +
geom_ribbon(aes(x = month,
ymin = mean_offset_clim - std_offset_clim,
ymax = mean_offset_clim + std_offset_clim,
group = value,
fill = value),
alpha = 0.2) +
scale_x_continuous(breaks = seq(1, 12, 1)) +
labs(x = 'month',
y = 'mean offset (pH units)',
title = 'Mean offset (clim OceanSODA pH - clim Argo pH)',
col = 'region',
fill = '± 1 std') 
Mapped offset between climatological OceanSODA pH and climatological Argo pH
# bin the offsets for better plotting
# plot the offsets on a map of the Southern Ocean
argo_OceanSODA_SO_clim_2x2 <- argo_OceanSODA_SO_clim_2x2 %>%
mutate(offset_clim_binned =
cut(offset_clim,
breaks = c(-Inf, -0.025, -0.005, 0.000, 0.005, 0.025, 0.035, 0.05, Inf))) %>% # bin the offsets into intervals (create a discrete variable instead of continuous)
# offset_clim_binned = as.factor(as.character(offset_clim_binned))) %>%
drop_na()
map +
geom_tile(data = argo_OceanSODA_SO_clim_2x2,
aes(lon, lat, fill = offset_clim_binned)) +
lims(y = c(-85, -30)) +
scale_fill_brewer(palette = 'RdBu', drop = FALSE) +
labs(x = 'lon',
y = 'lat',
fill = 'offset (pH units)',
title = 'clim OceanSODA ph - clim Argo pH') +
theme(legend.position = 'right')+
facet_wrap(~month, ncol = 2)
| Version | Author | Date |
|---|---|---|
| 7f3cfe7 | pasqualina-vonlanthendinenna | 2021-12-17 |
| 123e5db | pasqualina-vonlanthendinenna | 2021-12-07 |
| 38a5110 | pasqualina-vonlanthendinenna | 2021-12-03 |
| 6a5024e | pasqualina-vonlanthendinenna | 2021-12-02 |
| 10ddefb | jens-daniel-mueller | 2021-11-30 |
| 3dc093a | pasqualina-vonlanthendinenna | 2021-11-30 |
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
basemap(limits = -32, data = argo_OceanSODA_SO_clim_2x2) + # change to polar projection
geom_spatial_tile(data = argo_OceanSODA_SO_clim_2x2,
aes(x = lon,
y = lat,
fill = offset_clim_binned),
linejoin = 'mitre',
col = 'transparent',
detail = 60)+
scale_fill_brewer(palette = 'RdBu', drop = FALSE)+
theme(legend.position = 'right')+
labs(x = 'lon',
y = 'lat',
fill = 'offset (pH units)',
title = 'clim Ocean SODA pH - clim Argo pH')+
facet_wrap(~month, ncol = 2)
| Version | Author | Date |
|---|---|---|
| 7f3cfe7 | pasqualina-vonlanthendinenna | 2021-12-17 |
| 123e5db | pasqualina-vonlanthendinenna | 2021-12-07 |
| 38a5110 | pasqualina-vonlanthendinenna | 2021-12-03 |
| 6a5024e | pasqualina-vonlanthendinenna | 2021-12-02 |
| 10ddefb | jens-daniel-mueller | 2021-11-30 |
| 3dc093a | pasqualina-vonlanthendinenna | 2021-11-30 |
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
Basin separation
Each RECCAP biome (1, 2, 3) is separated into basins (Atlantic, Pacific, Indian)
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(lon, lat, basin_AIP)
argo_OceanSODA_SO <- inner_join(argo_OceanSODA_SO, basinmask)
argo_OceanSODA_SO <- argo_OceanSODA_SO %>%
unite(biome_basin, value, basin_AIP, sep = '_', remove = FALSE)# plot timeseries of monthly OceanSODA pH
argo_OceanSODA_SO_clim_subregional <- argo_OceanSODA_SO %>%
group_by(year, month, value, basin_AIP) %>% # compute regional mean OceanSODA pH for the three biomes
summarise(ph = mean(OceanSODA_ph, na.rm = TRUE)) %>%
ungroup()
# plot a timeseries of monthly average OceanSODA pH, per region and per basin
argo_OceanSODA_SO_clim_subregional %>%
filter(year != 2014,
year != 2021) %>%
ggplot(aes(x = month,
y = ph,
group = year,
col = as.character(year)))+
geom_line()+
geom_point()+
scale_x_continuous(breaks = seq(1, 12, 2))+
facet_grid(value~basin_AIP)+
labs(x = 'month',
y = 'pH in situ (total scale)',
title = 'monthly mean OceanSODA pH (Jan 2015-Dec 2020, Southern Ocean basins)',
col = 'year')
argo_OceanSODA_SO_clim_subregional %>%
ggplot(aes(x = year,
y = ph,
col = value)) +
facet_grid(month ~ basin_AIP) +
geom_line() +
geom_point() +
labs(x = 'year',
y = 'pH in situ (total scale)',
title = 'monthly mean pH (Apr 2014-Aug 2021, Southern Ocean basins)',
col = 'region')
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.2
Matrix products: default
BLAS: /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/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] metR_0.9.0 ggOceanMaps_0.4.3 ggspatial_1.1.5
[4] lubridate_1.7.9 argodata_0.0.0.9000 forcats_0.5.0
[7] stringr_1.4.0 dplyr_1.0.5 purrr_0.3.4
[10] readr_1.4.0 tidyr_1.1.3 tibble_3.1.3
[13] ggplot2_3.3.5 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] smoothr_0.1.2 fs_1.5.0 sf_1.0-2
[4] RColorBrewer_1.1-2 httr_1.4.2 rprojroot_2.0.2
[7] tools_4.0.3 backports_1.1.10 bslib_0.2.5.1
[10] utf8_1.2.2 rgdal_1.5-18 R6_2.5.1
[13] KernSmooth_2.23-17 rgeos_0.5-5 DBI_1.1.1
[16] colorspace_2.0-2 raster_3.4-5 withr_2.4.2
[19] sp_1.4-4 tidyselect_1.1.0 compiler_4.0.3
[22] git2r_0.27.1 cli_3.0.1 rvest_0.3.6
[25] RNetCDF_2.4-2 xml2_1.3.2 labeling_0.4.2
[28] sass_0.4.0 checkmate_2.0.0 scales_1.1.1
[31] classInt_0.4-3 ggOceanMapsData_1.0.1 proxy_0.4-26
[34] digest_0.6.27 rmarkdown_2.10 pkgconfig_2.0.3
[37] htmltools_0.5.1.1 highr_0.8 dbplyr_1.4.4
[40] rlang_0.4.11 readxl_1.3.1 rstudioapi_0.13
[43] farver_2.1.0 jquerylib_0.1.4 generics_0.1.0
[46] jsonlite_1.7.2 magrittr_2.0.1 Rcpp_1.0.7
[49] munsell_0.5.0 fansi_0.5.0 abind_1.4-5
[52] lifecycle_1.0.0 stringi_1.5.3 whisker_0.4
[55] yaml_2.2.1 grid_4.0.3 blob_1.2.1
[58] parallel_4.0.3 promises_1.2.0.1 crayon_1.4.1
[61] lattice_0.20-41 haven_2.3.1 stars_0.5-2
[64] hms_0.5.3 knitr_1.33 pillar_1.6.2
[67] codetools_0.2-16 reprex_0.3.0 glue_1.4.2
[70] evaluate_0.14 data.table_1.14.0 modelr_0.1.8
[73] vctrs_0.3.8 httpuv_1.6.2 cellranger_1.1.0
[76] gtable_0.3.0 assertthat_0.2.1 xfun_0.25
[79] lwgeom_0.2-5 broom_0.7.9 e1071_1.7-8
[82] later_1.3.0 viridisLite_0.4.0 class_7.3-17
[85] units_0.7-2 ellipsis_0.3.2