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library(tidyverse)
library(lubridate)
library(stars)
library(metR)
library(patchwork)

1 Read source files

Data source: Globally mapped climatologies from Lauvset et al. (2016) downloaded in June 2020 from glodap.info.

Following files were used:

file_list <- list.files(path = "data/GLODAPv2_2016b_Mappedclimatologies", pattern = "*.nc")
print(file_list)
[1] "GLODAPv2.2016b.Cant.nc"        "GLODAPv2.2016b.NO3.nc"        
[3] "GLODAPv2.2016b.oxygen.nc"      "GLODAPv2.2016b.PO4.nc"        
[5] "GLODAPv2.2016b.salinity.nc"    "GLODAPv2.2016b.silicate.nc"   
[7] "GLODAPv2.2016b.TAlk.nc"        "GLODAPv2.2016b.TCO2.nc"       
[9] "GLODAPv2.2016b.temperature.nc"
basinmask <- read_csv(here::here("data/World_Ocean_Atlas_2018/_summarized_files",
                                 "basin_mask_WOA18.csv"))

landmask <- read_csv(here::here("data/World_Ocean_Atlas_2018/_summarized_files",
                                 "land_mask_WOA18.csv"))

2 Plot data and write csv

Below, following subsets of the climatologies are plotted for all relevant parameters:

  • Horizontal planes at 0, 100, 500, 2000m
  • Meridional sections at longitudes:
    • Atlantic: 335.5
    • Pacific: 190.5
    • Indian ocean: 70.5

Section locations are indicated as white lines in maps.

# file <- file_list[1]

for (file in file_list) {
 
clim <- read_stars(here::here("data/GLODAPv2_2016b_Mappedclimatologies",
                          file),
                   quiet = TRUE)

# extract parameter name

parameter <- str_split(file, pattern = "6b.", simplify = TRUE)[2]
parameter <- str_split(parameter, pattern = ".nc", simplify = TRUE)[1]
print(parameter)

# extract parameter

clim <- clim %>% select(all_of(parameter))

#convert to table

clim_tibble <- clim %>% 
  as_tibble()

# harmonize column names

clim_tibble <- clim_tibble %>% 
  rename(lat = y,
         lon = x,
         depth = depth_surface)

# remove NAs

clim_tibble <- clim_tibble %>% 
  drop_na()

# join with basin mask and remove data outside basin mask

clim_tibble <- inner_join(clim_tibble, basinmask)

# write csv file

clim_tibble %>% 
  write_csv(here::here("data/GLODAPv2_2016b_MappedClimatologies/_summarized_files",
                       paste(parameter,".csv", sep = "")))


# plot maps

print(
map_climatology(clim_tibble, parameter)
)

# plot sections

print(
section_climatology(clim_tibble, parameter)
)

print(
section_climatology_shallow(clim_tibble, parameter)
)

}
[1] "Cant"

[1] "NO3"

[1] "oxygen"

[1] "PO4"

[1] "salinity"

[1] "silicate"

[1] "TAlk"

[1] "TCO2"

[1] "temperature"

3 Open tasks

  • none

4 Questions

  • none

sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)

Matrix products: default

locale:
[1] LC_COLLATE=English_Germany.1252  LC_CTYPE=English_Germany.1252   
[3] LC_MONETARY=English_Germany.1252 LC_NUMERIC=C                    
[5] LC_TIME=English_Germany.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] patchwork_1.0.1 metR_0.7.0      stars_0.4-3     sf_0.9-5       
 [5] abind_1.4-5     lubridate_1.7.9 forcats_0.5.0   stringr_1.4.0  
 [9] dplyr_1.0.0     purrr_0.3.4     readr_1.3.1     tidyr_1.1.0    
[13] tibble_3.0.3    ggplot2_3.3.2   tidyverse_1.3.0 workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] httr_1.4.2         jsonlite_1.7.0     viridisLite_0.3.0  here_0.1          
 [5] modelr_0.1.8       assertthat_0.2.1   blob_1.2.1         cellranger_1.1.0  
 [9] yaml_2.2.1         pillar_1.4.6       backports_1.1.8    glue_1.4.1        
[13] digest_0.6.25      promises_1.1.1     checkmate_2.0.0    rvest_0.3.6       
[17] colorspace_1.4-1   htmltools_0.5.0    httpuv_1.5.4       pkgconfig_2.0.3   
[21] broom_0.7.0        haven_2.3.1        scales_1.1.1       whisker_0.4       
[25] later_1.1.0.1      git2r_0.27.1       generics_0.0.2     farver_2.0.3      
[29] ellipsis_0.3.1     withr_2.2.0        cli_2.0.2          magrittr_1.5      
[33] crayon_1.3.4       readxl_1.3.1       evaluate_0.14      fs_1.4.2          
[37] fansi_0.4.1        xml2_1.3.2         lwgeom_0.2-5       class_7.3-17      
[41] tools_4.0.2        data.table_1.13.0  hms_0.5.3          lifecycle_0.2.0   
[45] munsell_0.5.0      reprex_0.3.0       isoband_0.2.2      compiler_4.0.2    
[49] e1071_1.7-3        rlang_0.4.7        classInt_0.4-3     units_0.6-7       
[53] grid_4.0.2         rstudioapi_0.11    labeling_0.3       rmarkdown_2.3     
[57] gtable_0.3.0       DBI_1.1.0          R6_2.4.1           knitr_1.29        
[61] rprojroot_1.3-2    KernSmooth_2.23-17 stringi_1.4.6      parallel_4.0.2    
[65] Rcpp_1.0.5         vctrs_0.3.2        dbplyr_1.4.4       tidyselect_1.1.0  
[69] xfun_0.16