OceanSODA-Argo pH
Pasqualina Vonlanthen & Jens Daniel Müller
02 December, 2021
Last updated: 2021-12-02
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Knit directory: bgc_argo_r_argodata/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| 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. |
| html | 5e2b8a5 | pasqualina-vonlanthendinenna | 2021-11-26 | Build site. |
| 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
)`summarise()` has grouped output by 'year', 'month', 'date', 'lat'. You can override using the `.groups` argument.Join the two datasets
OceanSODA <- OceanSODA %>%
mutate(date = format_ISO8601(date, precision = "ym"))
argo_OceanSODA <- left_join(argo_monthly, OceanSODA) %>%
rename(OceanSODA_ph = ph_total,
OceanSODA_ph_error = ph_total_uncert)Joining, by = c("date", "year", "lon", "lat")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)Joining, by = c("lon", "lat")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()`summarise()` has grouped output by 'lon', 'lat'. You can override using the `.groups` argument.# 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()`summarise()` has grouped output by 'lon', 'lat'. You can override using the `.groups` argument.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)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).
# 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)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()
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)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).
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)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()
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')Warning: Raster pixels are placed at uneven vertical intervals and will be
shifted. Consider using geom_tile() instead.
Warning: Raster pixels are placed at uneven vertical intervals and will be
shifted. Consider using geom_tile() instead.
# 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()`summarise()` has grouped output by 'year', 'month', 'value'. You can override using the `.groups` argument.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')Warning: Removed 23 rows containing missing values (geom_point).
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) +
labs(title = 'oceanSODA pH - Argo pH',
x = 'date',
y = 'offset (pH units)',
col = 'region')
Offset between climatological Argo and climatological OceanSODA pH:
# Offset between climatological argo and climatological OceanSODA pH
argo_OceanSODA_SO_clim %>%
drop_na() %>%
ggplot() +
geom_point(aes(x = month, y = offset_clim), 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)')
Mean offset between climatological OceanSODA pH and climatological Argo pH
mean_offset <- inner_join(argo_OceanSODA_SO_clim, region_masks_all_1x1_SO) %>%
group_by(month, value) %>%
summarise(mean_offset_clim = mean(offset_clim, na.rm = TRUE),
std_offset_clim = sd(offset_clim, na.rm = TRUE))Joining, by = c("lon", "lat")`summarise()` has grouped output by 'month'. You can override using the `.groups` argument.mean_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 = 'clim OceanSODA pH - clim Argo pH',
col = 'region',
fill = '± 1 std') 
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(min(offset_clim, na.rm = TRUE), -0.025, -0.005, 0.000, 0.005, 0.025, 0.035, 0.05, max(offset_clim, na.rm = TRUE)),
labels = c(-0.030, -0.010, -0.0025, 0.0025, 0.010, 0.030, 0.04, 0.055)),
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_discrete() +
# binned_scale(aes(lon, lat, fill = offset_clim),
# scale_name = 'offset',
# palette = scale_fill_divergent_discretised(),
# name = 'offset (pH units)',
# breaks = c(-Inf, -0.025, -0.005, 0.000, 0.005, 0.025, Inf),
# labels = c(-0.030, -0.025, -0.005, 0.00, 0.005, 0.025, 0.030),
# limits = NULL) +
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).
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_discrete()+
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)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()
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] 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] checkmate_2.0.0 scales_1.1.1 classInt_0.4-3
[31] ggOceanMapsData_1.0.1 proxy_0.4-26 digest_0.6.27
[34] rmarkdown_2.10 pkgconfig_2.0.3 htmltools_0.5.1.1
[37] highr_0.8 dbplyr_1.4.4 rlang_0.4.11
[40] readxl_1.3.1 rstudioapi_0.13 farver_2.1.0
[43] jquerylib_0.1.4 generics_0.1.0 jsonlite_1.7.2
[46] magrittr_2.0.1 Rcpp_1.0.7 munsell_0.5.0
[49] fansi_0.5.0 abind_1.4-5 lifecycle_1.0.0
[52] stringi_1.5.3 whisker_0.4 yaml_2.2.1
[55] grid_4.0.3 blob_1.2.1 parallel_4.0.3
[58] promises_1.2.0.1 crayon_1.4.1 lattice_0.20-41
[61] haven_2.3.1 stars_0.5-2 hms_0.5.3
[64] knitr_1.33 pillar_1.6.2 codetools_0.2-16
[67] reprex_0.3.0 glue_1.4.2 evaluate_0.14
[70] data.table_1.14.0 modelr_0.1.8 vctrs_0.3.8
[73] httpuv_1.6.2 cellranger_1.1.0 gtable_0.3.0
[76] assertthat_0.2.1 xfun_0.25 lwgeom_0.2-5
[79] broom_0.7.9 e1071_1.7-8 later_1.3.0
[82] viridisLite_0.4.0 class_7.3-17 units_0.7-2
[85] ellipsis_0.3.2