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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.
pH climatology - /nfs/kryo/work/datasets/gridded/ocean/interior/observation/ph/mazloff_2023/PH-QCv3-v10r1.nc
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 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)
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`.
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_1.2.2 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_0.5.8.1 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