UCSD Argo pH Climatology
Pasqualina Vonlanthen, David Stappard & Jens Daniel Müller
31 March, 2024
Last updated: 2024-03-31
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bgc_argo_r_argodata/analysis/
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Task
This script loads the pH climatology as described in Mazloff et al. (2023). The climatology netCDF has previously been downloaded. The lat and lon fields are harmonised to our requirements, i.e -75.5 ≥ lat ≤ -30.5 and 20.5 ≥ lon ≤ 379.5.
Mazloff, M. R., A. Verdy, S. T. Gille, K. S. Johnson, B. D. Cornuelle, and J. Sarmiento (2023), Southern Ocean Acidification Revealed by Biogeochemical-Argo Floats, Journal of Geophysical Research: Oceans, 128(5), e2022JC019530, doi:https://doi.org/10.1029/2022JC019530.
Dependencies
pH climatology - /nfs/kryo/work/datasets/gridded/ocean/interior/observation/ph/mazloff_2023/PH-QCv3-v10r1.nc
Outputs (in BGC preprocessed folder)
ucsd_ph_clim.rds – the pH climatology for the Southern Ocean (30.5° S and south) by 1°x1°, depths (2.1, 6.7…. 1800) and month.
path_argo <- '/nfs/kryo/work/datasets/ungridded/3d/ocean/floats/bgc_argo'
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")
path_mazloff_ph <-"/nfs/kryo/work/datasets/gridded/ocean/interior/observation/ph/mazloff_2023"
fn_mazloff_ph <- "PH-QCv3-v10r1.nc"
fn_mazloff_ph <- paste0(path_mazloff_ph, "/", fn_mazloff_ph)
theme_set(theme_bw())Read data
# # read pH, position and depth data
# nc_pH <- read_ncdf(fn_mazloff_ph, var = c("pH"))
# nc_pH <- as_tibble(nc_pH)
#
# nc_lon <- read_ncdf(fn_mazloff_ph, var = c("longitude"))
# nc_lon <- as_tibble(nc_lon)
#
# nc_lat <- read_ncdf(fn_mazloff_ph, var = c("latitude"))
# nc_lat <- as_tibble(nc_lat)
#
# nc_depth <- read_ncdf(fn_mazloff_ph, var = c("depth"))
# nc_depth <- as_tibble(nc_depth)
#
# nc_pH <- nc_pH %>%
# mutate(ny = ny - 0.5,
# nx = nx - 0.5,
# t = t + 0.5)
#
# # Join each attribute in turn to pH data
# clim_argo_ph <- full_join(nc_pH, nc_lat)
# clim_argo_ph <- full_join(clim_argo_ph, nc_lon)
# clim_argo_ph <- full_join(clim_argo_ph, nc_depth)
#
# clim_argo_ph <- clim_argo_ph %>%
# select(-c(starts_with("n")))
#
# clim_argo_ph <- clim_argo_ph %>%
# filter(pH != 0)
#
# # harmonise data
# clim_argo_ph <- clim_argo_ph %>%
# rename(lat = latitude,
# lon = longitude,
# month = t,
# clim_pH = pH) %>%
# mutate(lat = lat -0.5,
# lon = if_else(lon < 20, lon + 360, lon))
#
# read pH, position and depth data
nc_pH <- read_stars(fn_mazloff_ph) %>%
as_tibble()
nc_lat <- read_ncdf(fn_mazloff_ph, var = c("latitude")) %>% as_tibble()Will return stars object with 46 cells.nc_pH <- full_join(nc_pH %>% rename(ny = y),
nc_lat)Joining with `by = join_by(ny)`# harmonise data
clim_argo_ph <- nc_pH %>%
select(-ny) %>%
rename(lat = latitude,
lon = x,
depth = nz,
month = t,
clim_pH = "PH-QCv3-v10r1.nc") %>%
mutate(depth = round(depth, 2),
lon = if_else(lon < 20, lon + 360, lon),
lat = lat - 0.5)Maps
clim_argo_ph %>%
filter(depth < 30) %>%
ggplot() +
geom_tile(aes(lon, lat, fill = clim_pH)) +
facet_wrap(~depth) +
scale_fill_viridis_c() +
coord_quickmap()
clim_argo_ph %>%
ggplot(aes(clim_pH)) +
geom_histogram() +
facet_wrap(~depth) +
scale_y_log10() +
geom_vline(xintercept = 7.5)`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.Warning: Removed 1319033 rows containing non-finite values (`stat_bin()`).Warning: Transformation introduced infinite values in continuous y-axisWarning: Removed 655 rows containing missing values (`geom_bar()`).
Write data to file
clim_argo_ph %>%
drop_na() %>%
write_rds(file = paste0(path_argo_preprocessed, "/ucsd_ph_clim.rds"))
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] stars_0.6-0 sf_1.0-9 abind_1.4-5 oce_1.7-10
[5] gsw_1.1-1 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] fs_1.5.2 lubridate_1.9.0 httr_1.4.4
[4] rprojroot_2.0.3 tools_4.2.2 backports_1.4.1
[7] bslib_0.4.1 utf8_1.2.2 R6_2.5.1
[10] KernSmooth_2.23-20 DBI_1.1.3 colorspace_2.0-3
[13] withr_2.5.0 tidyselect_1.2.0 processx_3.8.0
[16] compiler_4.2.2 git2r_0.30.1 cli_3.6.1
[19] rvest_1.0.3 RNetCDF_2.6-1 xml2_1.3.3
[22] labeling_0.4.2 sass_0.4.4 scales_1.2.1
[25] classInt_0.4-8 callr_3.7.3 proxy_0.4-27
[28] digest_0.6.30 rmarkdown_2.18 pkgconfig_2.0.3
[31] htmltools_0.5.3 highr_0.9 dbplyr_2.2.1
[34] fastmap_1.1.0 rlang_1.1.1 readxl_1.4.1
[37] rstudioapi_0.15.0 farver_2.1.1 jquerylib_0.1.4
[40] generics_0.1.3 jsonlite_1.8.3 googlesheets4_1.0.1
[43] magrittr_2.0.3 ncmeta_0.3.5 Rcpp_1.0.10
[46] munsell_0.5.0 fansi_1.0.3 lifecycle_1.0.3
[49] stringi_1.7.8 whisker_0.4 yaml_2.3.6
[52] grid_4.2.2 parallel_4.2.2 promises_1.2.0.1
[55] crayon_1.5.2 haven_2.5.1 hms_1.1.2
[58] knitr_1.41 ps_1.7.2 pillar_1.9.0
[61] reprex_2.0.2 glue_1.6.2 evaluate_0.18
[64] getPass_0.2-2 modelr_0.1.10 vctrs_0.6.4
[67] tzdb_0.3.0 httpuv_1.6.6 cellranger_1.1.0
[70] gtable_0.3.1 assertthat_0.2.1 cachem_1.0.6
[73] xfun_0.35 lwgeom_0.2-10 broom_1.0.5
[76] e1071_1.7-12 later_1.3.0 viridisLite_0.4.1
[79] class_7.3-20 googledrive_2.0.0 gargle_1.2.1
[82] units_0.8-0 timechange_0.1.1 ellipsis_0.3.2