Last updated: 2021-04-16

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Knit directory: emlr_obs_v_XXX/

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1 Data sources

Cant estimates from this sensitivity case:

Mean and SD per grid cell (lat, lon, depth)
Zonal mean and SD (basin, lat, depth)
Inventories (lat, lon)

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

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

cant_inv <- bind_rows(cant_inv, cant_inv_mod_truth)

The following analysis is restricted to the standard inventory depth of 3000 m.

cant_inv <- cant_inv %>%
  filter(inv_depth == params_global$inventory_depth_standard)

2 Cant - positive

In a first series of plots we explore the distribution of Cant, taking only positive estimates into account (positive here refers to the mean cant estimate across MLR model predictions available for each grid cell). Negative values were set to zero before calculating mean sections and inventories.

Column inventory of positive cant between the surface and m water depth per horizontal grid cell (lat x lon).

cant_inv_bias <- cant_inv %>%
  filter(data_source %in% c("mod", "mod_truth")) %>%
  select(lat, lon, data_source, cant_pos_inv) %>%
  pivot_wider(names_from = data_source,
              values_from = cant_pos_inv) %>%
  mutate(cant_pos_bias = mod - mod_truth) %>% 
  drop_na()

p_map_cant_inv(
    df = cant_inv_bias,
    var = "cant_pos_bias",
    col = "divergent",
    subtitle_text = "data_source: mod - mod_truth")

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
0a6099c	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
6a3a689	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
7831fd3	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
ecfaacf	jens-daniel-mueller	2021-04-07

cant_inv %>%
  group_split(data_source) %>%
  map(
    ~ p_map_cant_inv(
    df = .x,
    var = "cant_pos_inv",
    subtitle_text = paste("data_source:", unique(.x$data_source))
  ))

[[1]]

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
0a6099c	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13
062160b	jens-daniel-mueller	2021-04-12
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
7831fd3	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
ecfaacf	jens-daniel-mueller	2021-04-07


[[2]]

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
9f31fe3	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13
062160b	jens-daniel-mueller	2021-04-12


[[3]]

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
0a6099c	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13

3 Cant - all

In a second series of plots we explore the distribution of all Cant, taking positive and negative estimates into account.

Column inventory of all Cant between the surface and 3000m water depth per horizontal grid cell (lat x lon).

cant_inv_bias <- cant_inv %>%
  filter(data_source %in% c("mod", "mod_truth")) %>%
  select(lat, lon, data_source, cant_inv) %>%
  pivot_wider(names_from = data_source,
              values_from = cant_inv) %>%
  mutate(cant_bias = mod - mod_truth) %>% 
  drop_na()

p_map_cant_inv(
    df = cant_inv_bias,
    var = "cant_bias",
    col = "divergent",
    subtitle_text = "data_source: mod - mod_truth")

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
0a6099c	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
6a3a689	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
7831fd3	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
ecfaacf	jens-daniel-mueller	2021-04-07

cant_inv %>%
  group_split(data_source) %>%
  map(~ p_map_cant_inv(
    df = .x,
      var = "cant_inv",
      col = "divergent",
    subtitle_text = paste("data_source:", unique(.x$data_source))
  ))

[[1]]

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
0a6099c	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13
062160b	jens-daniel-mueller	2021-04-12
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
7831fd3	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
ecfaacf	jens-daniel-mueller	2021-04-07


[[2]]

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
9f31fe3	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13
062160b	jens-daniel-mueller	2021-04-12


[[3]]

Version	Author	Date
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
0a6099c	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
4780722	jens-daniel-mueller	2021-04-13

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] gt_0.2.2         kableExtra_1.3.1 marelac_2.1.10   shape_1.4.5     
 [5] scales_1.1.1     metR_0.9.0       scico_1.2.0      patchwork_1.1.1 
 [9] collapse_1.5.0   forcats_0.5.0    stringr_1.4.0    dplyr_1.0.5     
[13] purrr_0.3.4      readr_1.4.0      tidyr_1.1.2      tibble_3.0.4    
[17] ggplot2_3.3.3    tidyverse_1.3.0  workflowr_1.6.2 

loaded via a namespace (and not attached):
 [1] fs_1.5.0                 lubridate_1.7.9          gsw_1.0-5               
 [4] webshot_0.5.2            httr_1.4.2               rprojroot_2.0.2         
 [7] tools_4.0.3              backports_1.1.10         R6_2.5.0                
[10] DBI_1.1.0                colorspace_1.4-1         withr_2.3.0             
[13] tidyselect_1.1.0         compiler_4.0.3           git2r_0.27.1            
[16] cli_2.1.0                rvest_0.3.6              xml2_1.3.2              
[19] labeling_0.4.2           checkmate_2.0.0          digest_0.6.27           
[22] rmarkdown_2.5            oce_1.2-0                pkgconfig_2.0.3         
[25] htmltools_0.5.0          dbplyr_1.4.4             rlang_0.4.10            
[28] readxl_1.3.1             rstudioapi_0.13          generics_0.0.2          
[31] farver_2.0.3             jsonlite_1.7.1           magrittr_1.5            
[34] Matrix_1.2-18            Rcpp_1.0.5               munsell_0.5.0           
[37] fansi_0.4.1              lifecycle_1.0.0          stringi_1.5.3           
[40] whisker_0.4              yaml_2.2.1               grid_4.0.3              
[43] blob_1.2.1               parallel_4.0.3           promises_1.1.1          
[46] crayon_1.3.4             lattice_0.20-41          haven_2.3.1             
[49] hms_0.5.3                seacarb_3.2.14           knitr_1.30              
[52] pillar_1.4.7             reprex_0.3.0             glue_1.4.2              
[55] evaluate_0.14            RcppArmadillo_0.10.1.2.0 data.table_1.13.2       
[58] modelr_0.1.8             vctrs_0.3.5              httpuv_1.5.4            
[61] testthat_2.3.2           cellranger_1.1.0         gtable_0.3.0            
[64] assertthat_0.2.1         xfun_0.18                broom_0.7.5             
[67] RcppEigen_0.3.3.7.0      later_1.1.0.1            viridisLite_0.3.0       
[70] ellipsis_0.3.1           here_0.1

Analysis of cant estimates

Jens Daniel Müller

16 April, 2021

1 Data sources

2 Cant - positive

3 Cant - all