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1 Read data

  • Data source: Globally averaged marine surface annual mean data from ESRL-NOAA
co2_atm <- read_table2(
  paste(path_atm_pCO2,
        "co2_annmean_gl.txt",
        sep = ""),
  col_names = FALSE,
  comment = "#"
)

co2_atm <- co2_atm %>% 
  select(-X3)

names(co2_atm) <- c("year", "pCO2")
  • Data source:

Global CO2 concentration (ppm) Prepared by C Le Quéré and M W Jones for the Global Carbon Project, 1 May 2020 This dataset is intended to be used as atmospheric forcing for modelling the evolution of carbon sinks

Data from March 1958 are monthly average from MLO and SPO provided by NOAA’s Earth System Research Laboratory http://www.esrl.noaa.gov/gmd/ccgg/trends/ When no SPO data are available (including prior to 1975), SPO is constructed from the 1976-2014 average MLO-SPO trend and average monthly departure The last year of data are still preliminary, pending recalibrations of reference gases and other quality control checks.

Data prior to March 1958 are estimated with a cubic spline fit to ice core data from Joos and Spahni 2008 Rates of change in natural and anthropogenic radiative forcing over the past 20,000 years PNAS

Annual mean values are calculated for all years.

co2_atm_reccap2 <- read_table2(
  paste0(path_reccap2,
        "global_co2_merged.txt"),
  col_names = c("year", "pCO2"),
  skip = 16
)

co2_atm_reccap2 <- co2_atm_reccap2 %>% 
  mutate(year = as.integer(round(year))) %>% 
  group_by(year) %>% 
  summarise(pCO2 = mean(pCO2, na.rm = TRUE)) %>% 
  ungroup()

2 Time series

ggplot() +
  # geom_path(data = co2_atm_reccap2, aes(year, pCO2, col="reccap2")) +
  geom_point(data = co2_atm_reccap2, aes(year, pCO2, col="reccap2")) +
  # geom_smooth(data = co2_atm_reccap2, aes(year, pCO2, col="reccap2"),
  #             method = "lm", formula = y ~ x + I(x^2)) +
  # geom_path(data = co2_atm, aes(year, pCO2, col="NOAA")) +
  geom_point(data = co2_atm, aes(year, pCO2, col="NOAA")) +
  scale_color_brewer(palette = "Set1") +
  theme(legend.title = element_blank())

Version Author Date
5323d37 jens-daniel-mueller 2022-01-17
90b0670 jens-daniel-mueller 2021-08-06
88967c0 jens-daniel-mueller 2020-12-16
fd1a2c9 jens-daniel-mueller 2020-12-15
58359ac jens-daniel-mueller 2020-11-27
92e10aa Jens Müller 2020-11-27

3 Write clean file

co2_atm %>%
  write_csv(paste(path_preprocessing,
                  "co2_atm.csv",
                  sep = ""))

co2_atm_reccap2 %>%
  write_csv(paste(path_preprocessing,
                  "co2_atm_reccap2.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] geomtextpath_0.1.0 colorspace_2.0-2   marelac_2.1.10     shape_1.4.6       
 [5] ggforce_0.3.3      metR_0.11.0        scico_1.3.0        patchwork_1.1.1   
 [9] collapse_1.7.0     forcats_0.5.1      stringr_1.4.0      dplyr_1.0.7       
[13] purrr_0.3.4        readr_2.1.1        tidyr_1.1.4        tibble_3.1.6      
[17] 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        readxl_1.3.1      
[41] rstudioapi_0.13    jquerylib_0.1.4    generics_0.1.1     farver_2.1.0      
[45] jsonlite_1.7.3     vroom_1.5.7        magrittr_2.0.1     Rcpp_1.0.8        
[49] munsell_0.5.0      fansi_1.0.2        lifecycle_1.0.1    stringi_1.7.6     
[53] whisker_0.4        yaml_2.2.1         MASS_7.3-55        grid_4.1.2        
[57] parallel_4.1.2     promises_1.2.0.1   crayon_1.4.2       haven_2.4.3       
[61] hms_1.1.1          seacarb_3.3.0      knitr_1.37         ps_1.6.0          
[65] pillar_1.6.4       reprex_2.0.1       glue_1.6.0         evaluate_0.14     
[69] getPass_0.2-2      data.table_1.14.2  modelr_0.1.8       vctrs_0.3.8       
[73] tzdb_0.2.0         tweenr_1.0.2       httpuv_1.6.5       cellranger_1.1.0  
[77] gtable_0.3.0       polyclip_1.10-0    assertthat_0.2.1   xfun_0.29         
[81] broom_0.7.11       later_1.3.0        ellipsis_0.3.2