OceanSODA-Argo pH
Pasqualina Vonlanthen & Jens Daniel Müller
26 November, 2021
Last updated: 2021-11-26
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Knit directory: bgc_argo_r_argodata/
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Task
Compare BGC-Argo pH data to pH from the OceanSODA surface data product
# load in the necessary libraries
library(tidyverse)── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──✓ ggplot2 3.3.5 ✓ purrr 0.3.4
✓ tibble 3.1.3 ✓ dplyr 1.0.5
✓ tidyr 1.1.3 ✓ stringr 1.4.0
✓ readr 1.4.0 ✓ forcats 0.5.0── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()library(argodata)
library(ggplot2)
library(lubridate)
Attaching package: 'lubridate'The following objects are masked from 'package:base':
date, intersect, setdiff, unionlibrary(ggOceanMaps)Loading required package: ggspatialLoad 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"))
ph_surface_1x1 <- read_rds(file = paste0(path_argo_preprocessed, "/ph_surface_1x1.rds"))
# 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"))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_surface_ph_1x1 <- ph_surface_1x1 %>%
mutate(day = rep(15, length(date)), # change the date format to match OceanSODA
.after = month) %>%
unite(year, month, day,
col = date,
sep = '-',
remove = FALSE) %>%
mutate(date = ymd(date), .before = year) %>%
group_by(date, lat, lon) %>%
mutate(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, day,
lon, lat,
float_serial_no, cycle_number,
argo_temp_month,
argo_psal_month,
argo_ph_month,
coast, region, value)Join the two datasets
argo_OceanSODA_1x1 <- left_join(argo_monthly_surface_ph_1x1, OceanSODA,
by = c('year', 'date', 'lat', 'lon')) %>%
rename(OceanSODA_ph = ph_total,
OceanSODA_ph_error = ph_total_uncert)
argo_OceanSODA_1x1 %>%
write_rds(file = paste0(path_argo_preprocessed, "/argo_OceanSODA_1x1.rds"))Southern Ocean surface pH
The focus here is on Southern Ocean surface pH, south of 30ºS, as defined in the RECCAP biome regions
# keep only Southern Ocean data
argo_OceanSODA_SO_1x1 <- argo_OceanSODA_1x1 %>%
filter(region == 'southern',
value != 0)Monthly climatological OceanSODA pH
Map monthly mean pH from the OceanSODA data product
theme_set(theme_bw())# regrid the data into 2x2º, which is better for mapping
argo_OceanSODA_SO_2x2 <- argo_OceanSODA_SO_1x1 %>%
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)))# read in the map from updata
map <-
read_rds(paste(path_emlr_utilities,
"map_landmask_WOA18.rds",
sep = ""))
# calculate average monthly pH between April 2014 and August 2021
argo_OceanSODA_clim <- argo_OceanSODA_SO_2x2 %>%
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)) `summarise()` has grouped output by 'lon', 'lat'. You can override using the `.groups` argument.map +
geom_tile(data = argo_OceanSODA_clim,
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)Warning: Raster pixels are placed at uneven vertical intervals and will be
shifted. Consider using geom_tile() instead.Warning: Removed 153708 rows containing missing values (geom_raster).
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
# plot the climatological monthly OceanSODA pH on a polar projection
basemap(limits = -32, data = argo_OceanSODA_clim) + # change to polar projection
geom_spatial_tile(data = argo_OceanSODA_clim,
aes(x = lon,
y = lat,
fill = clim_OceanSODA_ph),
linejoin = 'mitre',
col = 'transparent',
detail = 60)+
scale_fill_viridis_c()+
theme(legend.position = 'bottom')+
labs(x = 'lon',
y = 'lat',
fill = 'pH',
title = 'monthly climatological \nOceanSODA pH (Apr 2014 - Aug 2021)')+
facet_wrap(~month)Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
Timeseries of monthly OceanSODA pH
Evolution of monthly surface pH, for the three Southern Ocean RECCAP regions
ggplot() +
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)) +
coord_quickmap(expand = 0) +
labs(title = 'Southern Ocean RECCAP regions',
fill = 'region')Warning: Raster pixels are placed at uneven vertical intervals and will be
shifted. Consider using geom_tile() instead.
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
# plot timeseries of monthly OceanSODA pH
argo_OceanSODA_SO_2x2 %>%
group_by(year, month, value) %>% # compute regional mean OceanSODA pH for the three biomes
mutate(OceanSODA_ph_region = mean(OceanSODA_ph, na.rm = TRUE)) %>%
ggplot(aes(x = year,
y = OceanSODA_ph_region,
col = value)) +
facet_wrap(~month) +
geom_line() +
geom_point() +
labs(x = 'year',
y = 'pH in situ (total scale)',
title = 'monthly mean OceanSODA pH (Apr 2014-Aug 2021, Southern Ocean)',
col = 'region')Warning: Removed 1911 rows containing missing values (geom_point).
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
argo_OceanSODA_SO_2x2 %>%
group_by(year, month, value) %>% # compute regional mean OceanSODA pH for the three biomes
mutate(OceanSODA_ph_region = mean(OceanSODA_ph, na.rm = TRUE)) %>%
filter(year != 2014,
year != 2021,
value != 0) %>%
ggplot(aes(x = month,
y = OceanSODA_ph_region,
group = year,
col = as.character(year)))+
geom_line()+
geom_point()+
scale_x_continuous(breaks = seq(1, 12, 2))+
facet_wrap(~value)+
labs(x = 'month',
y = 'pH in situ (total scale)',
title = 'monthly mean OceanSODA pH (Jan 2015-Dec 2020, Southern Ocean)',
col = 'year')
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
Comparison between Argo and OceanSODA pH
Calculate the difference between Argo and OceanSODA pH values
In-situ monthly pH:
argo_OceanSODA_SO_2x2 <- argo_OceanSODA_SO_2x2 %>%
mutate(offset = OceanSODA_ph - argo_ph_month)
argo_OceanSODA_SO_2x2 %>%
drop_na() %>%
ggplot() +
geom_point(aes(x = offset, y = date, col = value), size = 0.7, pch = 19) +
geom_vline(xintercept = 0, size = 1, col = 'red')+
labs(title = 'oceanSODA pH - Argo pH',
x = 'offset (pH units)',
y = 'date',
col = 'region')
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
Offset between climatological Argo and climatological OceanSODA pH:
# Offset between climatological argo and climatological OceanSODA pH
argo_OceanSODA_clim <- argo_OceanSODA_clim %>%
mutate(offset_clim = clim_OceanSODA_ph - clim_argo_ph)
argo_OceanSODA_clim %>%
drop_na() %>%
ggplot() +
geom_point(aes(x = offset_clim, y = month), size = 0.7, pch = 19) +
geom_vline(xintercept = 0, size = 1, col = 'red')+
scale_y_continuous(breaks = seq(1, 12, 1))+
labs(title = 'clim oceanSODA pH - clim Argo pH',
x = 'offset (pH units)',
y = 'month',
col = 'region')
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
# plot the offsets on a map of the Southern Ocean
map +
geom_tile(data = argo_OceanSODA_clim,
aes(lon, lat, fill = offset_clim)) +
lims(y = c(-85, -30)) +
scale_fill_viridis_c() +
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)Warning: Raster pixels are placed at uneven vertical intervals and will be
shifted. Consider using geom_tile() instead.Warning: Removed 158580 rows containing missing values (geom_raster).
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
basemap(limits = -32, data = argo_OceanSODA_clim) + # change to polar projection
geom_spatial_tile(data = argo_OceanSODA_clim,
aes(x = lon,
y = lat,
fill = offset_clim),
linejoin = 'mitre',
col = 'transparent',
detail = 60)+
scale_fill_viridis_c()+
theme(legend.position = 'bottom')+
labs(x = 'lon',
y = 'lat',
fill = 'offset (pH units)',
title = 'clim Ocean SODA pH - clim Argo pH')+
facet_wrap(~month)Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
Assuming `crs = 4326` in stat_spatial_rect()
| Version | Author | Date |
|---|---|---|
| 3df4daf | pasqualina-vonlanthendinenna | 2021-11-26 |
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] ggOceanMaps_0.4.3 ggspatial_1.1.5 lubridate_1.7.9
[4] argodata_0.0.0.9000 forcats_0.5.0 stringr_1.4.0
[7] dplyr_1.0.5 purrr_0.3.4 readr_1.4.0
[10] tidyr_1.1.3 tibble_3.1.3 ggplot2_3.3.5
[13] 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] httr_1.4.2 rprojroot_2.0.2 tools_4.0.3
[7] backports_1.1.10 bslib_0.2.5.1 utf8_1.2.2
[10] rgdal_1.5-18 R6_2.5.1 KernSmooth_2.23-17
[13] rgeos_0.5-5 DBI_1.1.1 colorspace_2.0-2
[16] raster_3.4-5 withr_2.4.2 sp_1.4-4
[19] tidyselect_1.1.0 compiler_4.0.3 git2r_0.27.1
[22] cli_3.0.1 rvest_0.3.6 RNetCDF_2.4-2
[25] xml2_1.3.2 labeling_0.4.2 sass_0.4.0
[28] scales_1.1.1 classInt_0.4-3 ggOceanMapsData_1.0.1
[31] proxy_0.4-26 digest_0.6.27 rmarkdown_2.10
[34] pkgconfig_2.0.3 htmltools_0.5.1.1 highr_0.8
[37] dbplyr_1.4.4 rlang_0.4.11 readxl_1.3.1
[40] rstudioapi_0.13 farver_2.1.0 jquerylib_0.1.4
[43] generics_0.1.0 jsonlite_1.7.2 magrittr_2.0.1
[46] Rcpp_1.0.7 munsell_0.5.0 fansi_0.5.0
[49] abind_1.4-5 lifecycle_1.0.0 stringi_1.5.3
[52] whisker_0.4 yaml_2.2.1 grid_4.0.3
[55] blob_1.2.1 parallel_4.0.3 promises_1.2.0.1
[58] crayon_1.4.1 lattice_0.20-41 haven_2.3.1
[61] stars_0.5-2 hms_0.5.3 knitr_1.33
[64] pillar_1.6.2 codetools_0.2-16 reprex_0.3.0
[67] glue_1.4.2 evaluate_0.14 modelr_0.1.8
[70] vctrs_0.3.8 httpuv_1.6.2 cellranger_1.1.0
[73] gtable_0.3.0 assertthat_0.2.1 xfun_0.25
[76] lwgeom_0.2-5 broom_0.7.9 e1071_1.7-8
[79] later_1.3.0 viridisLite_0.4.0 class_7.3-17
[82] units_0.7-2 ellipsis_0.3.2