Region masks
Jens Daniel Müller
20 June, 2022
Last updated: 2022-06-20
Checks: 7 0
Knit directory: RECCAP2_CESM_ETHZ_submission/
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path_basin_mask <-
"/nfs/kryo/work/updata/reccap2/"1 Overview
Three region mask files prepared by Luke Gregor for the analysis within RECCAP2-ocean are available:
RECCAP2_region_masks_all.ncRECCAP2_openocean_1deg.ncRECCAP2_coastal_MARCAT_1deg.nc
Please note that the content of 2. an 3. should be identical to the fields open_ocean and coastal_MARCAT contained in 3. Accordingly, files 2. and 3. are not required for the analysis. In the following, I plot the content of 1.
For the submission, spatially resolved surface fluxes of CO2 should be integrated across the entire open_ocean region for fco2_glob, and across the indices 1-5 of the open_ocean region for fco2_reg,
2 File: region_masks_all
2.1 Seamask
Please note that the seamask provided within 3. is not identical to the open_ocean region and should not be used for data analysis.
region_masks_all <-
read_ncdf(paste(path_basin_mask, "RECCAP2_region_masks_all_v20220620.nc", sep = "")) %>%
as_tibble()
region_masks_all <- region_masks_all %>%
mutate(seamask = as.factor(seamask))
region_masks_all %>%
ggplot(aes(lon, lat, fill = seamask)) +
geom_raster() +
coord_quickmap(expand = 0)
2.2 Regions
Below, the open ocean regions used to calculate fgco2_reg are displayed. Please note that the coastal_marcats regions is covered by the other regions.
region_masks_all_seamask <- region_masks_all %>%
select(lat, lon, seamask)
region_masks_all <- region_masks_all %>%
select(-seamask)
region_masks_all <- region_masks_all %>%
pivot_longer(open_ocean:southern,
names_to = "region",
values_to = "value") %>%
mutate(value = as.factor(value))
region_masks_all %>%
filter(value != 0) %>%
ggplot(aes(lon, lat, fill = region)) +
geom_raster() +
scale_fill_brewer(palette = "Dark2") +
coord_quickmap(expand = 0)
2.3 Sub-regions
Each open ocean region consists of several subregions with indices for further regionalization.
region_masks_all %>%
filter(value != 0) %>%
group_split(region) %>%
map(
~ ggplot() +
geom_raster(data = region_masks_all_seamask %>% filter(seamask == 0),
aes(lon, lat)) +
geom_raster(data = .x,
aes(lon, lat, fill = value)) +
coord_quickmap(expand = 0) +
labs(title = paste("region:", unique(.x$region)))
)[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
3 Write csv file
region_masks_all %>%
write_csv("data/regions/RECCAP2_region_masks_all_clean.cvs")
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] tidync_0.2.4 stars_0.5-5 sf_1.0-5 abind_1.4-5
[5] colorspace_2.0-2 marelac_2.1.10 shape_1.4.6 ggforce_0.3.3
[9] metR_0.11.0 scico_1.3.0 patchwork_1.1.1 collapse_1.7.0
[13] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4
[17] readr_2.1.1 tidyr_1.1.4 tibble_3.1.6 ggplot2_3.3.5
[21] 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] KernSmooth_2.23-20 DBI_1.1.2 withr_2.4.3 tidyselect_1.1.1
[17] processx_3.5.2 bit_4.0.4 compiler_4.1.2 git2r_0.29.0
[21] cli_3.1.1 rvest_1.0.2 RNetCDF_2.5-2 xml2_1.3.3
[25] labeling_0.4.2 sass_0.4.0 scales_1.1.1 checkmate_2.0.0
[29] classInt_0.4-3 proxy_0.4-26 SolveSAPHE_2.1.0 callr_3.7.0
[33] digest_0.6.29 rmarkdown_2.11 oce_1.5-0 pkgconfig_2.0.3
[37] htmltools_0.5.2 highr_0.9 dbplyr_2.1.1 fastmap_1.1.0
[41] rlang_1.0.2 readxl_1.3.1 rstudioapi_0.13 jquerylib_0.1.4
[45] generics_0.1.1 farver_2.1.0 jsonlite_1.7.3 vroom_1.5.7
[49] magrittr_2.0.1 ncmeta_0.3.0 Rcpp_1.0.8 munsell_0.5.0
[53] fansi_1.0.2 lifecycle_1.0.1 stringi_1.7.6 whisker_0.4
[57] yaml_2.2.1 MASS_7.3-55 grid_4.1.2 parallel_4.1.2
[61] promises_1.2.0.1 crayon_1.4.2 haven_2.4.3 hms_1.1.1
[65] seacarb_3.3.0 knitr_1.37 ps_1.6.0 pillar_1.6.4
[69] reprex_2.0.1 glue_1.6.0 evaluate_0.14 getPass_0.2-2
[73] data.table_1.14.2 modelr_0.1.8 vctrs_0.3.8 tzdb_0.2.0
[77] tweenr_1.0.2 httpuv_1.6.5 cellranger_1.1.0 gtable_0.3.0
[81] polyclip_1.10-0 assertthat_0.2.1 xfun_0.29 lwgeom_0.2-8
[85] broom_0.7.11 e1071_1.7-9 later_1.3.0 ncdf4_1.19
[89] class_7.3-20 units_0.7-2 ellipsis_0.3.2