BGC-Argo Oxygen Data
Pasqualina Vonlanthen & Jens Daniel Müller
20 April, 2022
Last updated: 2022-04-20
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Knit directory: bgc_argo_r_argodata/
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| Rmd | 59073c1 | pasqualina-vonlanthendinenna | 2021-11-12 | added NE Pacific oxygen |
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| Rmd | 06b6be7 | pasqualina-vonlanthendinenna | 2021-11-12 | added NE Pacific oxygen |
| html | 284003d | pasqualina-vonlanthendinenna | 2021-11-11 | Build site. |
| Rmd | fb668ef | pasqualina-vonlanthendinenna | 2021-11-11 | added oxygen data page |
| Rmd | f7807db | pasqualina-vonlanthendinenna | 2021-11-11 | added oxygen data page |
Task
Explore BGC-Argo oxygen data through timeseries and climatological maps
path_argo <- '/nfs/kryo/work/updata/bgc_argo_r_argodata'
path_emlr_utilities <- "/nfs/kryo/work/jenmueller/emlr_cant/utilities/files/"Load oxygen data
Load in delayed-mode, adjusted oxygen data from the BGC-Argo synthetic profile files
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")
oxy_merge <-
read_rds(file = paste0(path_argo_preprocessed, "/bgc_merge.rds")) %>%
select(
-c(nitrate_adjusted_error:ph_in_situ_total_adjusted_error),
-c(profile_nitrate_qc, profile_ph_in_situ_total_qc)
)Southern Ocean surface oxygen
Focus on surface oxygen (top 10 m of the watercolumn) in the Southern Ocean, south of 30ºS
# select only best pH data (with QC flag 1) below 30ºS, for the top 10 m of the watercolumn
oxy_surface <- oxy_merge %>%
mutate(depth = swDepth(pres_adjusted, latitude = lat), .before = pres_adjusted) %>%
filter(doxy_adjusted_qc == '1', # keep only 'good' data
lat <= -30, # keep only data at or south of 30ºS
depth <= 10) %>% # keep only data above or at 10 m depth
mutate(
year = year(date), # separate the year and month from the date column
month = month(date), .after = n_prof
)
# check the correct latitudes, QC flags, and depth levels have been filtered
# max(oxy_surface$lat)
# min(oxy_surface$lat)
# table(oxy_surface$doxy_adjusted_qc)
# max(oxy_surface$depth)
# max(oxy_surface$date)
# min(oxy_surface$date)Monthly climatological map
Create a map of climatological monthly oxygen values, from January 2013 to August 2021, for the region south of 30ºS
# average oxygen values in the top 10 m for each month in each 2 x 2º longitude/latitude grid
oxy_mean <- oxy_surface %>%
group_by(lat, lon, month) %>%
summarise(oxy_ave_month = mean(doxy_adjusted))
# read in the map from updata
map <-
read_rds(paste(path_emlr_utilities,
"map_landmask_WOA18.rds",
sep = ""))
# map a monthly climatology of surface oxygen (Jan 2013 - September 2021)
map +
geom_tile(data = oxy_mean,
aes(lon, lat, fill = oxy_ave_month)) +
lims(y = c(-85, -25)) +
scale_fill_gradientn(colors = oceColorsJet(n = oxy_mean$oxy_ave_month)) +
labs(x = 'lon',
y = 'lat',
fill = 'dissolved oxygen \n(µmol kg-1)',
title = 'Monthly average surface dissolved oxygen values (Jan 2013-Sep 2021)') +
theme(legend.position = 'bottom')+
facet_wrap(~month)
Monthly timeseries
Plot a timeseries of monthly-mean dissolved oxygen for the region south of 30ºS for the upper 10 m of the watercolumn
# plot a timeseries of monthly values over the whole southern ocean south of 30ºS
oxy_month <- oxy_surface %>%
group_by(year, month) %>%
summarise(oxy_ave = mean(doxy_adjusted))
# timeseries of monthly pH values over 2013-2021 (separate panels for each month)
oxy_month %>%
ggplot(aes(x = year, y = oxy_ave)) +
facet_wrap(~month) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = seq(2013, 2021, 2))+
labs(x = 'year',
y = 'dissolved O2 (µmol kg-1)',
title = 'monthly mean dissolved oxygen (Jan 2013-Sep 2021, south of 30ºS)')
Monthly average dissolved oxygen, per year (January 2013 - December 2020; plotting only full years), over the whole region south of 30ºS
# timeseries of monthly oxygen values for each year (separate years on the same plot)
oxy_month %>%
filter(year != 2021) %>% # keep only years with full data
ggplot(aes(x = month, y = oxy_ave, group = year, col = as.character(year)))+
geom_line()+
geom_point()+
scale_x_continuous(breaks = seq(1, 12, 1))+
labs(x = 'month',
y = 'dissolved O2 (µmol kg-1)',
title = 'monthly mean dissolved oxygen (Jan 2013-Dec 2020, south of 30ºS)',
col = 'year')
Northeast Pacific surface oxygen
Focus on surface oxygen (upper 10 m) in the north-east Pacific (10ºN - 70ºN, -190ºE, -140ºE)
# select only best oxygen data (with QC flag 1) between 10 and 70ºN, and 190 and 140ºW, for the top 10 m of the watercolumn
oxy_nepacific <- oxy_merge %>%
mutate(depth = swDepth(pres_adjusted, latitude = lat), .before = pres_adjusted) %>%
filter(doxy_adjusted_qc == '1', # keep only 'good' data
between(lat, 10, 70),
between(lon, 190, 240), # keep only data for the NE Pacific
depth <= 10) %>% # keep only data above or at 10 m depth
mutate(
year = year(date), # separate the year and month from the date column
month = month(date), .after = n_prof
)
# longitudes larger than -180ºE are lon-380 Monthly climatological map
Create a map of climatological monthly surface oxygen values, in the north-east Pacific ocean (10ºN - 70ºN, -190ºE, -140ºE), for January 2013 - August 2021
# average oxygen values in the top 10 m for each month in each 2 x 2º longitude/latitude grid
oxy_mean_nepacific <- oxy_nepacific %>%
group_by(lat, lon, month) %>%
summarise(oxy_ave_month = mean(doxy_adjusted))
# map a monthly climatology of surface oxygen (Jan 2013 - August 2021)
map +
geom_tile(data = oxy_mean_nepacific,
aes(lon, lat, fill = oxy_ave_month)) +
lims(y = c(5, 60),
x = c(180, 250)) +
scale_fill_gradientn(colors = oceColorsJet(n = oxy_mean_nepacific$oxy_ave_month)) +
labs(x = 'lon',
y = 'lat',
fill = 'dissolved oxygen \n(µmol kg-1)',
title = 'Monthly average surface dissolved oxygen (Jan 2013-Aug 2021)') +
theme(legend.position = 'right')+
facet_wrap(~month)
Monthly timeseries
Timeseries of monthly mean oxygen for the northeast Pacific from January 2013 to August 2021
# plot a timeseries of monthly values over the whole NE Pacific
oxy_month_nepacific <- oxy_nepacific %>%
group_by(year, month) %>%
summarise(oxy_ave = mean(doxy_adjusted))
# timeseries of monthly pH values over 2013-2021 (separate panels for each month)
oxy_month_nepacific %>%
ggplot(aes(x = year, y = oxy_ave)) +
facet_wrap(~month) +
geom_line() +
geom_point() +
scale_x_continuous(breaks = seq(2013, 2021, 2))+
labs(x = 'year',
y = 'dissolved O2 (µmol kg-1)',
title = 'monthly mean dissolved oxygen (Jan 2013-Aug 2021, NE Pacific)')
Timeseries of monthly surface oxygen, per year, in the NE Pacific
# timeseries of monthly oxygen values for each year (separate years on the same plot)
oxy_month_nepacific %>%
filter(year != 2021) %>% # keep only years with full data
ggplot(aes(x = month, y = oxy_ave, group = year, col = as.character(year)))+
geom_line()+
geom_point()+
scale_x_continuous(breaks = seq(1, 12, 1))+
labs(x = 'month',
y = 'dissolved O2 (µmol kg-1)',
title = 'monthly mean dissolved oxygen (Jan 2013-Dec 2020, NE Pacific)',
col = 'year')
sessionInfo()R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.3
Matrix products: default
BLAS: /usr/local/R-4.1.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.1.2/lib64/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] oce_1.5-0 gsw_1.0-6 lubridate_1.8.0 argodata_0.1.0
[5] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4
[9] readr_2.1.1 tidyr_1.1.4 tibble_3.1.6 ggplot2_3.3.5
[13] tidyverse_1.3.1 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8 getPass_0.2-2 ps_1.6.0 assertthat_0.2.1
[5] rprojroot_2.0.2 digest_0.6.29 utf8_1.2.2 R6_2.5.1
[9] cellranger_1.1.0 backports_1.4.1 reprex_2.0.1 evaluate_0.14
[13] highr_0.9 httr_1.4.2 pillar_1.6.4 rlang_0.4.12
[17] readxl_1.3.1 rstudioapi_0.13 whisker_0.4 callr_3.7.0
[21] jquerylib_0.1.4 rmarkdown_2.11 labeling_0.4.2 munsell_0.5.0
[25] broom_0.7.11 compiler_4.1.2 httpuv_1.6.5 modelr_0.1.8
[29] xfun_0.29 pkgconfig_2.0.3 htmltools_0.5.2 tidyselect_1.1.1
[33] fansi_1.0.2 crayon_1.4.2 tzdb_0.2.0 dbplyr_2.1.1
[37] withr_2.4.3 later_1.3.0 grid_4.1.2 jsonlite_1.7.3
[41] gtable_0.3.0 lifecycle_1.0.1 DBI_1.1.2 git2r_0.29.0
[45] magrittr_2.0.1 scales_1.1.1 cli_3.1.1 stringi_1.7.6
[49] farver_2.1.0 fs_1.5.2 promises_1.2.0.1 xml2_1.3.3
[53] bslib_0.3.1 ellipsis_0.3.2 generics_0.1.1 vctrs_0.3.8
[57] tools_4.1.2 glue_1.6.0 RNetCDF_2.5-2 hms_1.1.1
[61] processx_3.5.2 fastmap_1.1.0 yaml_2.2.1 colorspace_2.0-2
[65] rvest_1.0.2 knitr_1.37 haven_2.4.3 sass_0.4.0