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1 Model Cant

1.1 Reuqired data

1.1.1 This study

Results from this study are referred to as JDM. Unique eras information is subtracted.

cant_inv_JDM <-
  read_csv(paste(path_version_data,
                 "cant_inv.csv",
                 sep = ""))

“True” Cant fields directly inferred from the model output are referred to as M.

tref  <-
  read_csv(paste(path_version_data,
                 "tref.csv",
                 sep = ""))

cant_tref_1 <-
  read_csv(
    paste(
      path_preprocessing,
      "cant_annual_field_",
      params_local$model_runs,
      "/cant_",
      unique(tref$year[1]),
      ".csv",
      sep = ""
    )
  )

cant_tref_1 <- cant_tref_1 %>%
  rename(cant_tref_1 = cant_total) %>%
  select(-year)

cant_tref_2 <-
  read_csv(
    paste(
      path_preprocessing,
      "cant_annual_field_",
      params_local$model_runs,
      "/cant_",
      unique(tref$year[2]),
      ".csv",
      sep = ""
    )
  )

cant_tref_2 <- cant_tref_2 %>%
  rename(cant_tref_2 = cant_total) %>%
  select(-year)

cant_tref_3 <-
  read_csv(
    paste(
      path_preprocessing,
      "cant_annual_field_",
      params_local$model_runs,
      "/cant_",
      unique(tref$year[3]),
      ".csv",
      sep = ""
    )
  )

cant_tref_3 <- cant_tref_3 %>%
  rename(cant_tref_3 = cant_total) %>%
  select(-year)
cant_M_1 <- left_join(cant_tref_1, cant_tref_2) %>%
  mutate(cant = cant_tref_2 - cant_tref_1,
         eras = unique(cant_inv_JDM$eras)[1]) %>%
  select(-c(cant_tref_1, cant_tref_2))

cant_M_2 <- left_join(cant_tref_2, cant_tref_3) %>%
  mutate(cant = cant_tref_3 - cant_tref_2,
         eras = unique(cant_inv_JDM$eras)[2]) %>%
  select(-c(cant_tref_2, cant_tref_3))

cant_M <- full_join(cant_M_1, cant_M_2) %>%
  arrange(lon, lat, depth, basin_AIP)

cant_M <- cant_M %>%
  mutate(cant_pos = if_else(cant <= 0, 0, cant))

rm(cant_tref_1, cant_tref_2, cant_tref_3, cant_M_1, cant_M_2)
cant_inv_M <- m_cant_inv(cant_M)
cant_zonal_M <- m_zonal_mean_section(cant_M)

2 Write csv

cant_M %>%
  write_csv(paste(path_version_data,
                  "cant_M.csv", sep = ""))

cant_inv_M %>%
  write_csv(paste(path_version_data,
                  "cant_inv_M.csv", sep = ""))

cant_zonal_M %>%
  write_csv(paste(path_version_data,
                  "cant_zonal_M", sep = ""))

sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.2

Matrix products: default
BLAS:   /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/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] metR_0.9.0      scico_1.2.0     patchwork_1.1.1 collapse_1.5.0 
 [5] forcats_0.5.0   stringr_1.4.0   dplyr_1.0.2     purrr_0.3.4    
 [9] readr_1.4.0     tidyr_1.1.2     tibble_3.0.4    ggplot2_3.3.3  
[13] tidyverse_1.3.0 workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.5               here_1.0.1               lubridate_1.7.9         
 [4] lattice_0.20-41          assertthat_0.2.1         rprojroot_2.0.2         
 [7] digest_0.6.27            R6_2.5.0                 cellranger_1.1.0        
[10] backports_1.1.10         reprex_0.3.0             evaluate_0.14           
[13] httr_1.4.2               pillar_1.4.7             rlang_0.4.10            
[16] readxl_1.3.1             data.table_1.13.6        rstudioapi_0.13         
[19] whisker_0.4              blob_1.2.1               Matrix_1.2-18           
[22] checkmate_2.0.0          rmarkdown_2.5            RcppEigen_0.3.3.9.1     
[25] munsell_0.5.0            broom_0.7.3              compiler_4.0.3          
[28] httpuv_1.5.4             modelr_0.1.8             xfun_0.20               
[31] pkgconfig_2.0.3          htmltools_0.5.0          tidyselect_1.1.0        
[34] fansi_0.4.1              crayon_1.3.4             dbplyr_1.4.4            
[37] withr_2.3.0              later_1.1.0.1            grid_4.0.3              
[40] jsonlite_1.7.2           gtable_0.3.0             lifecycle_0.2.0         
[43] DBI_1.1.0                git2r_0.27.1             magrittr_2.0.1          
[46] scales_1.1.1             cli_2.2.0                stringi_1.5.3           
[49] fs_1.5.0                 promises_1.1.1           RcppArmadillo_0.10.1.2.2
[52] xml2_1.3.2               ellipsis_0.3.1           generics_0.1.0          
[55] vctrs_0.3.6              tools_4.0.3              glue_1.4.2              
[58] hms_0.5.3                parallel_4.0.3           yaml_2.2.1              
[61] colorspace_2.0-0         rvest_0.3.6              knitr_1.30              
[64] haven_2.3.1