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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()

Version Author Date
80c16c2 ds2n19 2023-11-15
710edd4 jens-daniel-mueller 2022-05-11
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`.

Version Author Date
80c16c2 ds2n19 2023-11-15
710edd4 jens-daniel-mueller 2022-05-11

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