BGC-Argo Oxygen Data
Pasqualina Vonlanthen, David Stappard & Jens Daniel Müller
13 May, 2024
Last updated: 2024-05-13
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bgc_argo_r_argodata/analysis/
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Task
Explore BGC-Argo oxygen data through timeseries and climatological maps
Dependencies
doxy_bgc_observed.rds - bgc preprocessed folder, created by doxy_vertical_align. Not this file is written BEFORE the vertical alignment stage.
path_argo <- '/nfs/kryo/work/updata/bgc_argo_r_argodata'
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 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, "/doxy_bgc_observed.rds"))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 %>%
filter(lat <= -30, # keep only data at or south of 30ºS
depth <= 10) # keep only data above or at 10 m depth
# 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
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') +
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 (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 (south of 30ºS)')
Monthly average dissolved oxygen, per year, over the whole region south of 30ºS
# timeseries of monthly oxygen values for each year (separate years on the same plot)
oxy_month %>%
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 (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 %>%
filter(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
# 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)
# 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') +
theme(legend.position = 'right')+
facet_wrap(~month)
Monthly timeseries
Timeseries of monthly mean oxygen for the northeast Pacific
# 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 (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 (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 %>%
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 (NE Pacific)',
col = 'year')
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] oce_1.7-10 gsw_1.1-1 lubridate_1.9.0 timechange_0.1.1
[5] argodata_0.1.0 forcats_0.5.2 stringr_1.5.0 dplyr_1.1.3
[9] purrr_1.0.2 readr_2.1.3 tidyr_1.3.0 tibble_3.2.1
[13] ggplot2_3.4.4 tidyverse_1.3.2 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] httr_1.4.4 sass_0.4.4 jsonlite_1.8.3
[4] modelr_0.1.10 bslib_0.4.1 assertthat_0.2.1
[7] getPass_0.2-2 highr_0.9 googlesheets4_1.0.1
[10] cellranger_1.1.0 yaml_2.3.6 pillar_1.9.0
[13] backports_1.4.1 glue_1.6.2 digest_0.6.30
[16] promises_1.2.0.1 rvest_1.0.3 colorspace_2.0-3
[19] htmltools_0.5.8.1 httpuv_1.6.6 pkgconfig_2.0.3
[22] broom_1.0.5 haven_2.5.1 scales_1.2.1
[25] processx_3.8.0 whisker_0.4 later_1.3.0
[28] tzdb_0.3.0 git2r_0.30.1 googledrive_2.0.0
[31] generics_0.1.3 farver_2.1.1 ellipsis_0.3.2
[34] cachem_1.0.6 withr_2.5.0 cli_3.6.1
[37] magrittr_2.0.3 crayon_1.5.2 readxl_1.4.1
[40] evaluate_0.18 ps_1.7.2 fs_1.5.2
[43] fansi_1.0.3 xml2_1.3.3 tools_4.2.2
[46] hms_1.1.2 gargle_1.2.1 lifecycle_1.0.3
[49] munsell_0.5.0 reprex_2.0.2 callr_3.7.3
[52] compiler_4.2.2 jquerylib_0.1.4 RNetCDF_2.6-1
[55] rlang_1.1.1 grid_4.2.2 rstudioapi_0.15.0
[58] labeling_0.4.2 rmarkdown_2.18 gtable_0.3.1
[61] DBI_1.2.2 R6_2.5.1 knitr_1.41
[64] fastmap_1.1.0 utf8_1.2.2 rprojroot_2.0.3
[67] stringi_1.7.8 Rcpp_1.0.10 vctrs_0.6.4
[70] dbplyr_2.2.1 tidyselect_1.2.0 xfun_0.35