Last updated: 2022-10-23

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Knit directory: emlr_obs_preprocessing/

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Rmd 20ce2b7 jens-daniel-mueller 2022-04-13 added GCB data read-in and rebuild

1 Data source

  • Carbon flux estimates from Global Carbon Budget 2021 by Friedlingstein et al. (2021) downloaded in April 2022 from ICOS
Global_Carbon_Budget <-
  read_excel(
    file_GCB_xlsx,
    sheet = "Global Carbon Budget",
    skip = 20
  )

Historical_Budget <-
  read_excel(
    file_GCB_xlsx,
    sheet = "Historical Budget",
    skip = 15
  )

Fossil_Emissions_by_Category <-
  read_excel(
    file_GCB_xlsx,
    sheet = "Fossil Emissions by Category",
    skip = 8
  )

Ocean_Sink <-
  read_excel(
    file_GCB_xlsx,
    sheet = "Ocean Sink",
    col_types = c(
      "numeric",
      "numeric",
      "numeric",
      "skip",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "skip",
      "numeric",
      "numeric",
      "skip",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric"
    ),
    skip = 27
  )


Terrestrial_Sink <-
  read_excel(
    file_GCB_xlsx,
    sheet = "Terrestrial Sink",
    col_types = c(
      "numeric",
      "numeric",
      "skip",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "numeric",
      "skip",
      "numeric",
      "numeric"
    ),
    skip = 24
  )


Cement_Carbonation_Sink <-
  read_excel(
    file_GCB_xlsx,
    sheet = "Cement Carbonation Sink",
    col_types = c("numeric",
                  "numeric", "skip", "numeric", "numeric"),
    skip = 9
  )

2 Global Carbon Budget

Global_Carbon_Budget <- Global_Carbon_Budget %>% 
  rename(year = Year) %>% 
  pivot_longer(-year,
               names_to = "estimate",
               values_to = "GtC_yr") %>%
  drop_na() %>% 
  arrange(year) %>% 
  group_by(estimate) %>% 
  mutate(GtC = cumsum(GtC_yr)) %>% 
  ungroup()

Global_Carbon_Budget %>% 
  ggplot(aes(year, GtC_yr)) + 
  geom_hline(yintercept = 0) +
  geom_path(col = "red") +
  facet_wrap(~ estimate, ncol = 2)

Version Author Date
e949567 jens-daniel-mueller 2022-04-13 
Global_Carbon_Budget %>% 
  ggplot(aes(year, GtC, col = estimate)) + 
  geom_hline(yintercept = 0) +
  geom_path()

Version Author Date
e949567 jens-daniel-mueller 2022-04-13

3 Historical Budget

Historical_Budget <- 
  Historical_Budget %>% 
  rename(year = Year) %>% 
  pivot_longer(-year,
               names_to = "estimate",
               values_to = "GtC_yr") %>%
  drop_na() %>% 
  arrange(year) %>% 
  group_by(estimate) %>% 
  mutate(GtC = cumsum(GtC_yr)) %>% 
  ungroup()

Historical_Budget %>% 
  ggplot(aes(year, GtC_yr)) + 
  geom_hline(yintercept = 0) +
  geom_path(col = "red") +
  facet_wrap(~ estimate, ncol = 2)

Version Author Date
e949567 jens-daniel-mueller 2022-04-13 
Historical_Budget %>% 
  ggplot(aes(year, GtC, col = estimate)) + 
  geom_hline(yintercept = 0) +
  geom_path()

Version Author Date
e949567 jens-daniel-mueller 2022-04-13

4 Ocean Sink

Ocean_Sink_models <- Ocean_Sink %>%
  select(year, `CESM-ETH`:`MOM6-COBALT (Princeton)`) %>%
  pivot_longer(-year,
               names_to = "product",
               values_to = "GtC_yr") %>% 
  mutate(type = "models")

Ocean_Sink_data_products <- Ocean_Sink %>%
  select(year, Landschutzer:Watson) %>%
  drop_na() %>% 
  pivot_longer(-year,
               names_to = "product",
               values_to = "GtC_yr") %>% 
  mutate(type = "data_products")

Ocean_Sink <- bind_rows(
  Ocean_Sink_models,
  Ocean_Sink_data_products
)

rm(
  Ocean_Sink_models,
  Ocean_Sink_data_products
)

Ocean_Sink <- Ocean_Sink %>% 
  arrange(year) %>% 
  group_by(type, product) %>% 
  mutate(GtC = cumsum(GtC_yr)) %>% 
  ungroup()

Ocean_Sink %>% 
  ggplot(aes(year, GtC_yr, group = product, col = type)) + 
  geom_path() +
  scale_color_brewer(palette = "Set1")

Version Author Date
e949567 jens-daniel-mueller 2022-04-13 
Ocean_Sink %>% 
  ggplot(aes(year, GtC, group = product, col = type)) + 
  geom_path() +
  scale_color_brewer(palette = "Set1")

Version Author Date
e949567 jens-daniel-mueller 2022-04-13

5 Write files

Historical_Budget %>%
  write_csv(paste(path_preprocessing,
                  "GCB_Historical_Budget.csv",
                  sep = ""))

Global_Carbon_Budget %>%
  write_csv(paste(path_preprocessing,
                  "GCB_Global_Carbon_Budget.csv",
                  sep = ""))

Ocean_Sink %>%
  write_csv(paste(path_preprocessing,
                  "Ocean_Sink.csv",
                  sep = ""))

sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.3

Matrix products: default
BLAS:   /usr/local/R-4.1.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.1.2/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] readxl_1.3.1       geomtextpath_0.1.0 colorspace_2.0-2   marelac_2.1.10    
 [5] shape_1.4.6        ggforce_0.3.3      metR_0.11.0        scico_1.3.0       
 [9] patchwork_1.1.1    collapse_1.7.0     forcats_0.5.1      stringr_1.4.0     
[13] dplyr_1.0.7        purrr_0.3.4        readr_2.1.1        tidyr_1.1.4       
[17] tibble_3.1.6       ggplot2_3.3.5      tidyverse_1.3.1    workflowr_1.7.0   

loaded via a namespace (and not attached):
 [1] fs_1.5.2           bit64_4.0.5        lubridate_1.8.0    gsw_1.0-6         
 [5] RColorBrewer_1.1-2 httr_1.4.2         rprojroot_2.0.2    tools_4.1.2       
 [9] backports_1.4.1    bslib_0.3.1        utf8_1.2.2         R6_2.5.1          
[13] DBI_1.1.2          withr_2.4.3        tidyselect_1.1.1   processx_3.5.2    
[17] bit_4.0.4          compiler_4.1.2     git2r_0.29.0       textshaping_0.3.6 
[21] cli_3.1.1          rvest_1.0.2        xml2_1.3.3         labeling_0.4.2    
[25] sass_0.4.0         scales_1.1.1       checkmate_2.0.0    SolveSAPHE_2.1.0  
[29] callr_3.7.0        systemfonts_1.0.3  digest_0.6.29      rmarkdown_2.11    
[33] oce_1.5-0          pkgconfig_2.0.3    htmltools_0.5.2    highr_0.9         
[37] dbplyr_2.1.1       fastmap_1.1.0      rlang_1.0.2        rstudioapi_0.13   
[41] jquerylib_0.1.4    generics_0.1.1     farver_2.1.0       jsonlite_1.7.3    
[45] vroom_1.5.7        magrittr_2.0.1     Rcpp_1.0.8         munsell_0.5.0     
[49] fansi_1.0.2        lifecycle_1.0.1    stringi_1.7.6      whisker_0.4       
[53] yaml_2.2.1         MASS_7.3-55        grid_4.1.2         parallel_4.1.2    
[57] promises_1.2.0.1   crayon_1.4.2       haven_2.4.3        hms_1.1.1         
[61] seacarb_3.3.0      knitr_1.37         ps_1.6.0           pillar_1.6.4      
[65] reprex_2.0.1       glue_1.6.0         evaluate_0.14      getPass_0.2-2     
[69] data.table_1.14.2  modelr_0.1.8       vctrs_0.3.8        tzdb_0.2.0        
[73] tweenr_1.0.2       httpuv_1.6.5       cellranger_1.1.0   gtable_0.3.0      
[77] polyclip_1.10-0    assertthat_0.2.1   xfun_0.29          broom_0.7.11      
[81] later_1.3.0        ellipsis_0.3.2