Anthropogenic CO2 from 1994 to 2007
Jens Daniel Müller
20 November, 2021
Last updated: 2021-11-20
Checks: 7 0
Knit directory: emlr_obs_preprocessing/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 0908ee5 | jens-daniel-mueller | 2021-11-15 | Build site. |
| Rmd | 651fc9a | jens-daniel-mueller | 2021-11-15 | rerun with Key 2004 |
path_key_2004 <- "/nfs/kryo/work/updata/glodapv1_1/GLODAP_gridded.data/"
path_preprocessing <- paste(path_root, "/observations/preprocessing/", sep = "")library(marelac)Error in get(genname, envir = envir) : object 'testthat_print' not found1 Data source
- Gridded ocean interior fields by Key et al. (2004) downloaded in August 2020 from NOAA/NCEI Ocean Carbon Data System (OCADS)
2 Read files
# read text files
pCFC_12_data <-
read_csv(
paste(path_key_2004,
"CFC.data/pCFC-12.data.txt",
sep = ""),
col_names = FALSE,
na = "-999",
col_types = list(.default = "d")
)
# read respective depth layers and convert to vector
Depth_centers <-
read_file(paste(path_key_2004,
"Depth.centers.txt",
sep = ""))
Depth_centers <- Depth_centers %>%
str_split(",") %>%
as_vector()
# read respective latitudes and convert to vector
Lat_centers <-
read_file(paste(path_key_2004, "Lat.centers.txt",
sep = ""))
Lat_centers <- Lat_centers %>%
str_split(",") %>%
as_vector()
# read respective longitudes and convert to vector
Long_centers <-
read_file(paste(path_key_2004, "Long.centers.txt",
sep = ""))
Long_centers <- Long_centers %>%
str_split(",") %>%
as_vector()
# match lon, lat and depth vectors with Cant value file
names(pCFC_12_data) <- Lat_centers
Long_Depth <-
expand_grid(depth = Depth_centers, lon = Long_centers) %>%
mutate(lon = as.numeric(lon),
depth = as.numeric(depth))
pCFC_12_3d <- bind_cols(pCFC_12_data, Long_Depth)
# adjust file dimensions
pCFC_12_3d <- pCFC_12_3d %>%
pivot_longer(1:180, names_to = "lat", values_to = "pCFC_12") %>%
mutate(lat = as.numeric(lat))
pCFC_12_3d <- pCFC_12_3d %>%
drop_na()
# harmonize coordinates
pCFC_12_3d <- pCFC_12_3d %>%
mutate(lon = if_else(lon < 20, lon + 360, lon))
rm(pCFC_12_data,
Long_Depth,
Depth_centers,
Lat_centers,
Long_centers)3 Apply basin mask
# use only three basin to assign general basin mask
# ie this is not specific to the MLR fitting
basinmask <- basinmask %>%
filter(MLR_basins == "2") %>%
select(lat, lon, basin_AIP)
pCFC_12_3d <- inner_join(pCFC_12_3d, basinmask)4 Calculation
4.1 Column inventory
pCFC_12_inv_layers <- m_pCFC_12_inv(pCFC_12_3d)
pCFC_12_inv <- pCFC_12_inv_layers %>%
filter(inv_depth == params_global$inventory_depth_standard)4.2 Zonal mean section
pCFC_12_zonal <- m_zonal_mean_sd(pCFC_12_3d)5 Plots
5.1 Inventory map
p_map_cant_inv(
df = pCFC_12_inv,
var = "pCFC_12_pos",
breaks = seq(0,max(pCFC_12_inv$pCFC_12_pos),5))5.2 Horizontal plane maps
p_map_climatology(
df = pCFC_12_3d,
var = "pCFC_12")
| Version | Author | Date |
|---|---|---|
| 0908ee5 | jens-daniel-mueller | 2021-11-15 |
5.3 Global section
p_section_global(
df = pCFC_12_3d,
var = "pCFC_12")
| Version | Author | Date |
|---|---|---|
| 0908ee5 | jens-daniel-mueller | 2021-11-15 |
5.4 Sections at regular longitudes
p_section_climatology_regular(
df = pCFC_12_3d,
var = "pCFC_12")
| Version | Author | Date |
|---|---|---|
| 0908ee5 | jens-daniel-mueller | 2021-11-15 |
5.5 Write files
pCFC_12_3d %>%
write_csv(paste(path_preprocessing,
"K04_pCFC_12_3d.csv", sep = ""))
# pCFC_12_inv %>%
# write_csv(paste(path_preprocessing,
# "K04_pCFC_12_inv.csv", sep = ""))
pCFC_12_zonal %>%
write_csv(paste(path_preprocessing,
"K04_pCFC_12_zonal.csv", sep = ""))
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] marelac_2.1.10 shape_1.4.5 ggforce_0.3.3 metR_0.9.0
[5] scico_1.2.0 patchwork_1.1.1 collapse_1.5.0 forcats_0.5.0
[9] stringr_1.4.0 dplyr_1.0.5 purrr_0.3.4 readr_1.4.0
[13] tidyr_1.1.3 tibble_3.1.3 ggplot2_3.3.5 tidyverse_1.3.0
[17] 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] httr_1.4.2 rprojroot_2.0.2 tools_4.0.3
[7] backports_1.1.10 bslib_0.2.5.1 utf8_1.1.4
[10] R6_2.5.0 DBI_1.1.0 colorspace_2.0-2
[13] withr_2.3.0 tidyselect_1.1.0 compiler_4.0.3
[16] git2r_0.27.1 cli_3.0.1 rvest_0.3.6
[19] xml2_1.3.2 isoband_0.2.2 labeling_0.4.2
[22] sass_0.4.0 scales_1.1.1 checkmate_2.0.0
[25] digest_0.6.27 rmarkdown_2.10 oce_1.2-0
[28] pkgconfig_2.0.3 htmltools_0.5.1.1 highr_0.8
[31] dbplyr_1.4.4 rlang_0.4.11 readxl_1.3.1
[34] rstudioapi_0.13 jquerylib_0.1.4 generics_0.1.0
[37] farver_2.0.3 jsonlite_1.7.1 magrittr_1.5
[40] Matrix_1.2-18 Rcpp_1.0.5 munsell_0.5.0
[43] fansi_0.4.1 lifecycle_1.0.0 stringi_1.5.3
[46] whisker_0.4 yaml_2.2.1 MASS_7.3-53
[49] grid_4.0.3 blob_1.2.1 parallel_4.0.3
[52] promises_1.1.1 crayon_1.3.4 lattice_0.20-41
[55] haven_2.3.1 hms_0.5.3 seacarb_3.2.14
[58] knitr_1.33 pillar_1.6.2 reprex_0.3.0
[61] glue_1.4.2 evaluate_0.14 RcppArmadillo_0.10.1.2.0
[64] data.table_1.14.0 modelr_0.1.8 vctrs_0.3.8
[67] tweenr_1.0.2 httpuv_1.5.4 testthat_2.3.2
[70] cellranger_1.1.0 gtable_0.3.0 polyclip_1.10-0
[73] assertthat_0.2.1 xfun_0.25 broom_0.7.9
[76] RcppEigen_0.3.3.7.0 later_1.2.0 viridisLite_0.3.0
[79] ellipsis_0.3.2