Last updated: 2020-11-24

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1 Data source

2 Read ncdfs

AnthCO2_data <-
  read_csv(
    "data/input/GLODAPv1_1/GLODAP_gridded.data/AnthCO2.data/AnthCO2.data.txt",
    col_names = FALSE,
    na = "-999",
    col_types = list(.default = "d")
  )

Depth_centers <-
  read_file("data/input/GLODAPv1_1/GLODAP_gridded.data/Depth.centers.txt")

Depth_centers <- Depth_centers %>%
  str_split(",") %>%
  as_vector()

Lat_centers <-
  read_file("data/input/GLODAPv1_1/GLODAP_gridded.data/Lat.centers.txt")

Lat_centers <- Lat_centers %>%
  str_split(",") %>%
  as_vector()

Long_centers <-
  read_file("data/input/GLODAPv1_1/GLODAP_gridded.data/Long.centers.txt")

Long_centers <- Long_centers %>%
  str_split(",") %>%
  as_vector()

names(AnthCO2_data) <- Lat_centers

Long_Depth <-
  expand_grid(depth = Depth_centers, lon = Long_centers) %>%
  mutate(lon = as.numeric(lon),
         depth = as.numeric(depth))

cant_3d <- bind_cols(AnthCO2_data, Long_Depth)

cant_3d <- cant_3d %>%
  pivot_longer(1:180, names_to = "lat", values_to = "cant") %>%
  mutate(lat = as.numeric(lat))

cant_3d <- cant_3d %>%
  drop_na()

cant_3d <- cant_3d %>%
  mutate(lon = if_else(lon < 20, lon + 360, lon))

rm(AnthCO2_data,
   Long_Depth,
   Depth_centers,
   Lat_centers,
   Long_centers)

3 Apply basin mask

cant_3d <- inner_join(cant_3d, basinmask)

4 Inventory calculation

cant_3d <- cant_3d %>% 
  mutate(cant_pos = if_else(cant <= 0, 0, cant),
         eras = "1800-1994")

cant_inv <- m_cant_inv(cant_3d) 

# cant_inv <- cant_3d %>% 
#   filter(depth <= parameters$inventory_depth) %>% 
#   group_by(lon, lat, basin, basin_AIP) %>% 
#   summarise(cant_inv = sum(layer_inv_pos, na.rm = TRUE) / 1000,
#             cant_inv_incl_neg = sum(layer_inv, na.rm = TRUE) / 1000) %>% 
#   ungroup()

5 Cant plots

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

  • Horizontal planes at 0, 150, 500, 2000m
  • Meridional sections at longitudes: 335.5, 190.5, 70.5

Section locations are indicated as white lines in maps.

5.1 Horizontal plane maps

p_map_climatology_divergent(cant_3d, "cant")

5.2 Sections

p_section_global_divergent(cant_3d, "cant")

5.3 Sections at regular longitudes

p_section_climatology_regular_divergent(cant_3d, "cant")

5.4 Zonal mean section

cant_zonal <- m_zonal_mean_section(cant_3d %>% select(-basin))

5.5 Inventory maps

p_map_cant_pos_inv(
  cant_inv,
  breaks = seq(0,max(cant_inv$cant_pos_inv),5))

5.6 Write files

cant_3d %>% 
  write_csv(here::here("data/interim",
                       "S04_cant_3d.csv"))

cant_inv %>% 
  write_csv(here::here("data/interim",
                       "S04_cant_inv.csv"))

cant_zonal %>% 
  write_csv(here::here("data/interim",
                       "S04_cant_zonal.csv"))

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] metR_0.7.0      scico_1.2.0     patchwork_1.0.1 collapse_1.3.2 
 [5] forcats_0.5.0   stringr_1.4.0   dplyr_1.0.0     purrr_0.3.4    
 [9] readr_1.3.1     tidyr_1.1.0     tibble_3.0.3    ggplot2_3.3.2  
[13] tidyverse_1.3.0 workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] httr_1.4.2        jsonlite_1.7.0    here_0.1          modelr_0.1.8     
 [5] Formula_1.2-3     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   lattice_0.20-41  
[13] glue_1.4.1        digest_0.6.25     promises_1.1.1    checkmate_2.0.0  
[17] rvest_0.3.6       colorspace_1.4-1  sandwich_2.5-1    htmltools_0.5.0  
[21] httpuv_1.5.4      Matrix_1.2-18     pkgconfig_2.0.3   broom_0.7.0      
[25] haven_2.3.1       xtable_1.8-4      scales_1.1.1      whisker_0.4      
[29] later_1.1.0.1     git2r_0.27.1      generics_0.0.2    farver_2.0.3     
[33] ellipsis_0.3.1    withr_2.2.0       cli_2.0.2         magrittr_1.5     
[37] crayon_1.3.4      readxl_1.3.1      evaluate_0.14     fs_1.4.2         
[41] fansi_0.4.1       xml2_1.3.2        tools_4.0.2       data.table_1.13.0
[45] hms_0.5.3         lifecycle_0.2.0   munsell_0.5.0     reprex_0.3.0     
[49] isoband_0.2.2     compiler_4.0.2    lfe_2.8-5.1       rlang_0.4.7      
[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          zoo_1.8-8        
[61] lubridate_1.7.9   knitr_1.30        rprojroot_1.3-2   stringi_1.4.6    
[65] parallel_4.0.2    Rcpp_1.0.5        vctrs_0.3.2       dbplyr_1.4.4     
[69] tidyselect_1.1.0  xfun_0.16