Analysis of cant estimates

workflowr

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Last updated: 2021-06-04

Checks: 7 0

Knit directory: emlr_obs_v_XXX/

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---

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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/analysis_anomalous_changes.Rmd) and HTML (docs/analysis_anomalous_changes.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
html	1c87a03	jens-daniel-mueller	2021-06-04	Build site.
Rmd	b48d553	jens-daniel-mueller	2021-06-04	clean anomalous changes
html	a656287	jens-daniel-mueller	2021-06-04	Build site.
Rmd	0e89bd2	jens-daniel-mueller	2021-06-04	clean anomalous changes
html	7e8d839	jens-daniel-mueller	2021-06-03	Build site.
Rmd	a81f578	jens-daniel-mueller	2021-06-03	include anomalous changes
html	207339d	jens-daniel-mueller	2021-06-03	Build site.
html	315710b	jens-daniel-mueller	2021-06-03	include anomalous changes
html	d612df8	jens-daniel-mueller	2021-06-03	Build site.
Rmd	b8fb70c	jens-daniel-mueller	2021-06-03	include anomalous changes
html	406d740	jens-daniel-mueller	2021-06-03	Build site.
Rmd	98e5d73	jens-daniel-mueller	2021-06-03	include anomalous changes
html	7802dd6	jens-daniel-mueller	2021-06-03	Build site.
Rmd	dced077	jens-daniel-mueller	2021-06-03	include anomalous changes
html	a496b5f	jens-daniel-mueller	2021-06-03	Build site.
Rmd	90863c0	jens-daniel-mueller	2021-06-03	include anomalous changes

---

1 Version ID

The results displayed on this site correspond to the Version_ID: v_XXX

2 Data sources

Required are:

• Cant from Sabine 2004 (S04)

• Cant from Gruber 2019 (G19)

• annual mean atmospheric pCO₂

• Mean eMLR-Cant per grid cell (lat, lon, depth)

cant_3d_tref <- read_csv(paste(path_version_data,
                               "cant_3d_tref.csv",
                               sep = ""))

cant_3d <-
  read_csv(paste(path_version_data,
                 "cant_3d.csv",
                 sep = ""))

co2_atm <-
  read_csv(paste(path_preprocessing,
                 "co2_atm.csv",
                 sep = ""))

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

m_zonal_mean_section <- function(df) {

  df_zonal_mean_section <- df %>%
    fselect(-lon) %>% 
    fgroup_by(lat, depth, basin_AIP) %>% {
      add_vars(fgroup_vars(.,"unique"),
               fmean(., keep.group_vars = FALSE) %>% add_stub(pre = FALSE, "_mean"),
               fsd(., keep.group_vars = FALSE) %>% add_stub(pre = FALSE, "_sd"))
    }
  
  return(df_zonal_mean_section)

}

3 Calculate ss Cant

# calculate delta cant as the difference between total cant at tref
# this includes the G19 anomaly
cant_3d_tref_wide <- cant_3d_tref %>%
  pivot_wider(names_from = era,
              values_from = "cant_pos") %>% 
  mutate(delta_cant_pos_G19 = `2010-2019` - `2000-2009`) %>% 
  drop_na()

# join with basinmask
cant_3d_tref_wide <- inner_join(basinmask, cant_3d_tref_wide)

# extract atm pCO2 at reference year
co2_atm_tref <- right_join(co2_atm, tref %>% rename(year = median_year)) %>% 
  select(-year) %>% 
  rename(pCO2_tref = pCO2)

# atm pCO2 at tref 1,2,3
pCO2_to <- params_local$preind_atm_pCO2
pCO2_t1 <- co2_atm_tref$pCO2_tref[1]
pCO2_t2 <- co2_atm_tref$pCO2_tref[2]

# ratio of atm pCO2 changes between eras
delta_pCO2_ratio <- 
  (pCO2_t2 - pCO2_t1) /
  (pCO2_t1 - pCO2_to)

rm(pCO2_to)
rm(pCO2_t1)
rm(pCO2_t2)

# alpha for ss projection
alpha = delta_pCO2_ratio * 0.94 * 0.94

# calculate cstar for reference year
cant_3d_tref_wide <- cant_3d_tref_wide %>%
  rename(cant_pos_t1 = `2010-2019`,
         cant_pos_t2 = `2000-2009`) %>%
  mutate(delta_cant_pos_ss = alpha * cant_pos_t1)

4 Zonal mean sections

4.1 delta Cant

4.1.1 G19 and ss projections

# calculate zonal mean section
cant_tref_section <- cant_3d_tref_wide %>%
  group_by(data_source) %>%
  nest() %>%
  mutate(section = map(.x = data, ~m_zonal_mean_section(.x))) %>%
  select(-data) %>%
  unnest(section)


cant_tref_section_long <- cant_tref_section %>%
  pivot_longer(
    cols = c(delta_cant_pos_G19_mean, delta_cant_pos_ss_mean),
    values_to = "delta_cant",
    names_to = "estimate",
    names_prefix = "delta_cant_pos_"
  )

cant_tref_section_long %>% 
  group_by(basin_AIP, data_source, estimate) %>%
  group_split() %>% 
  map( ~ p_section_zonal(
    df = .x,
    var = "delta_cant",
    plot_slabs = "n",
    subtitle_text = paste("Basin:", .x$basin_AIP, "| Data:", .x$data_source, "| Estimate:", .x$estimate)
  ))

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Past versions of zonal_section_plots_cant_pos-1.png

Version	Author	Date
1c87a03	jens-daniel-mueller	2021-06-04
a656287	jens-daniel-mueller	2021-06-04

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Version	Author	Date
1c87a03	jens-daniel-mueller	2021-06-04
a656287	jens-daniel-mueller	2021-06-04

4.1.2 ss vs true

# calculate section of anomalous changes
cant_tref_section <- cant_tref_section %>%
  mutate(delta_cant_pos_anomalous = delta_cant_pos_G19_mean - delta_cant_pos_ss_mean)

cant_tref_section %>%
  group_by(basin_AIP, data_source) %>%
  group_split() %>%
  map( ~ p_section_zonal(
    df = .x,
    col = "divergent",
    var = "delta_cant_pos_anomalous",
    plot_slabs = "n",
    breaks = params_global$breaks_cant_offset,
    subtitle_text = paste(.x$basin_AIP, .x$data_source)
  ))

[[1]]

Past versions of zonal_section_plots_delta_cant_pos-1.png

Version	Author	Date
a656287	jens-daniel-mueller	2021-06-04

[[2]]

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a656287	jens-daniel-mueller	2021-06-04

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a656287	jens-daniel-mueller	2021-06-04

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Version	Author	Date
a656287	jens-daniel-mueller	2021-06-04

4.1.3 ss vs eMLR

cant_3d_anom <- inner_join(cant_3d, cant_3d_tref_wide)

cant_3d_anom <- cant_3d_anom %>% 
  mutate(delta_cant_pos_emlr_ss = cant_pos - delta_cant_pos_ss)

cant_anom_section <- cant_3d_anom %>%
  select(lon, lat, depth, basin_AIP, data_source, delta_cant_pos_emlr_ss) %>% 
  group_by(data_source) %>%
  nest() %>%
  mutate(section = map(.x = data, ~m_zonal_mean_section(.x))) %>%
  select(-data) %>%
  unnest(section)

cant_anom_section %>%
  group_by(basin_AIP, data_source) %>%
  group_split() %>%
  map( ~ p_section_zonal(
    df = .x,
    col = "divergent",
    var = "delta_cant_pos_emlr_ss_mean",
    plot_slabs = "n",
    breaks = params_global$breaks_cant_offset,
    subtitle_text = paste(.x$basin_AIP, .x$data_source)
  ))

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Past versions of anomalous_change_emlr-1.png

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7e8d839	jens-daniel-mueller	2021-06-03

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7e8d839	jens-daniel-mueller	2021-06-03

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7e8d839	jens-daniel-mueller	2021-06-03

Session information

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_1.0.5     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_0.1                 lattice_0.20-41         
 [4] lubridate_1.7.9          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_1.13.2        rstudioapi_0.11         
[19] whisker_0.4              blob_1.2.1               Matrix_1.2-18           
[22] checkmate_2.0.0          rmarkdown_2.5            labeling_0.4.2          
[25] RcppEigen_0.3.3.7.0      munsell_0.5.0            broom_0.7.5             
[28] compiler_4.0.3           httpuv_1.5.4             modelr_0.1.8            
[31] xfun_0.18                pkgconfig_2.0.3          htmltools_0.5.0         
[34] tidyselect_1.1.0         fansi_0.4.1              crayon_1.3.4            
[37] dbplyr_1.4.4             withr_2.3.0              later_1.1.0.1           
[40] grid_4.0.3               jsonlite_1.7.1           gtable_0.3.0            
[43] lifecycle_1.0.0          DBI_1.1.0                git2r_0.27.1            
[46] magrittr_1.5             scales_1.1.1             cli_2.1.0               
[49] stringi_1.5.3            farver_2.0.3             fs_1.5.0                
[52] promises_1.1.1           RcppArmadillo_0.10.1.2.0 xml2_1.3.2              
[55] ellipsis_0.3.1           generics_0.0.2           vctrs_0.3.5             
[58] tools_4.0.3              glue_1.4.2               hms_0.5.3               
[61] parallel_4.0.3           yaml_2.2.1               colorspace_1.4-1        
[64] isoband_0.2.2            rvest_0.3.6              knitr_1.30              
[67] haven_2.3.1