Anthropogenic CO2 from 1994 to 2007
Jens Daniel Müller
27 November, 2020
Last updated: 2020-11-27
Checks: 7 0
Knit directory: emlr_obs_preprocessing/
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path_functions <- "/nfs/kryo/work/updata/emlr_cant/utilities/functions/"
path_files <- "/nfs/kryo/work/updata/emlr_cant/utilities/files/"path_gruber_2019 <- "/nfs/kryo/work/updata/cant_gruber_2019/"
path_preprocessing <- "/nfs/kryo/work/updata/emlr_cant/observations/preprocessing/"1 Libraries
Loading libraries specific to the the analysis performed in this section.
library(tidync)2 Data source
- Anthropogenic CO2 estimates (1994-2007) by Gruber et al. (2019) downloaded in August 2020 from NOAA/NCEI Ocean Carbon Data System (OCADS)
3 Read ncdfs
3.1 Public data sets
The publicly available data sets contain only positive Cant estimates.
dcant <- tidync(paste(
path_gruber_2019,
"dcant_emlr_cstar_gruber_94-07_vs1.nc",
sep = ""
))
dcant <- dcant %>% activate(DCANT_01)
dcant <- dcant %>% hyper_tibble()
# harmonize column names and coordinates
dcant <- dcant %>%
rename(lon = LONGITUDE,
lat = LATITUDE,
depth = DEPTH,
cant_pos = DCANT_01) %>%
mutate(lon = if_else(lon < 20, lon + 360, lon))dcant_inv <- tidync(paste(
path_gruber_2019,
"inv_dcant_emlr_cstar_gruber_94-07_vs1.nc",
sep = ""
))
dcant_inv <- dcant_inv %>% activate(DCANT_INV01)
dcant_inv <- dcant_inv %>% hyper_tibble()
# harmonize column names and coordinates
dcant_inv <- dcant_inv %>%
rename(lon = LONGITUDE,
lat = LATITUDE,
cant_pos_inv = DCANT_INV01) %>%
mutate(lon = if_else(lon < 20, lon + 360, lon)) %>%
mutate(eras = "JGOFS_GO")3.2 Raw data
Internally available data sets also contain negative Cant estimates, as they are contained in the “raw” output of the eMLR mapping step.
V101 <- tidync(paste(path_gruber_2019,
"Cant_V101new.nc",
sep = ""))
V101 <- V101 %>% activate(Cant)
V101 <- V101 %>% hyper_tibble()
# harmonize column names and coordinates
V101 <- V101 %>%
rename(lon = longitude,
lat = latitude,
cant = Cant) %>%
filter(cant != -999) %>%
mutate(lon = if_else(lon < 20, lon + 360, lon))4 Apply basin mask
dcant <- inner_join(dcant, basinmask)
dcant_inv <- inner_join(dcant_inv, basinmask)
V101 <- inner_join(V101, basinmask)5 Join pos and all Cant
cant_3d <- inner_join(dcant, V101)
cant_3d <- cant_3d %>%
mutate(eras = "JGOFS_GO")
rm(dcant, V101)6 Zonal mean section
cant_zonal <- m_zonal_mean_section(cant_3d %>% select(-basin))7 Column inventory
7.1 From 3d fields
cant_inv <- m_cant_inv(cant_3d)7.1.1 Cant - all
p_map_cant_inv(
df = cant_inv,
var = "cant_inv",
col = "divergent")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
7.1.2 Cant - pos
p_map_cant_inv(
df = cant_inv,
var = "cant_pos_inv")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
7.2 From pubished inventory data
p_map_cant_inv(
df = dcant_inv,
var = "cant_pos_inv")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
7.3 Published - 3d
cant_offset <- inner_join(
cant_inv %>% rename(cant_re = cant_pos_inv),
dcant_inv %>% rename(cant_pub = cant_pos_inv)
)
cant_offset <- cant_offset %>%
mutate(delta_cant = cant_re - cant_pub)
p_map_cant_inv_offset(df = cant_offset,
var = "delta_cant",
breaks = seq(-3,3,0.25))
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
rm(cant_offset, dcant_inv)8 Cant plots
Below, following subsets of the climatologies are plotted for all relevant parameters:
- Horizontal planes at 0, 150, 500, 2000m
- Meridional sections at longitudes: 335.5, 190.5, 70.5
Section locations are indicated as white lines in maps.
8.1 Horizontal plane maps
8.1.1 All values
p_map_climatology(
df = cant_3d,
var = "cant",
col = "divergent")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
8.1.2 Positive values
p_map_climatology(
df = cant_3d,
var = "cant_pos")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
8.2 Sections basin
8.2.1 All values
p_section_global(
df = cant_3d,
var = "cant",
col = "divergent")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
8.2.2 Positive values
p_section_global(
df = cant_3d,
var = "cant_pos")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
8.3 Sections at regular longitudes
8.3.1 All values
p_section_climatology_regular(
df = cant_3d,
var = "cant",
col = "divergent")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
8.3.2 Positive values
p_section_climatology_regular(
df = cant_3d,
var = "cant_pos")
| Version | Author | Date |
|---|---|---|
| 92e10aa | Jens Müller | 2020-11-27 |
9 Write files
cant_3d %>%
write_csv(paste(path_preprocessing,
"G19_cant_3d.csv",
sep = ""))
cant_inv %>%
write_csv(paste(path_preprocessing,
"G19_cant_inv.csv",
sep = ""))
cant_zonal %>%
write_csv(paste(path_preprocessing,
"G19_cant_zonal.csv",
sep = ""))
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.1
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] tidync_0.2.4 metR_0.9.0 scico_1.2.0 patchwork_1.1.0
[5] collapse_1.4.2 forcats_0.5.0 stringr_1.4.0 dplyr_1.0.2
[9] purrr_0.3.4 readr_1.4.0 tidyr_1.1.2 tibble_3.0.4
[13] ggplot2_3.3.2 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] httr_1.4.2 viridisLite_0.3.0 jsonlite_1.7.1
[4] here_0.1 modelr_0.1.8 assertthat_0.2.1
[7] blob_1.2.1 cellranger_1.1.0 yaml_2.2.1
[10] pillar_1.4.6 backports_1.1.10 lattice_0.20-41
[13] glue_1.4.2 RcppEigen_0.3.3.7.0 digest_0.6.27
[16] promises_1.1.1 checkmate_2.0.0 rvest_0.3.6
[19] colorspace_1.4-1 htmltools_0.5.0 httpuv_1.5.4
[22] Matrix_1.2-18 pkgconfig_2.0.3 broom_0.7.2
[25] haven_2.3.1 scales_1.1.1 whisker_0.4
[28] later_1.1.0.1 git2r_0.27.1 farver_2.0.3
[31] generics_0.0.2 ellipsis_0.3.1 withr_2.3.0
[34] cli_2.1.0 magrittr_1.5 crayon_1.3.4
[37] readxl_1.3.1 evaluate_0.14 fs_1.5.0
[40] ncdf4_1.17 fansi_0.4.1 xml2_1.3.2
[43] RcppArmadillo_0.10.1.0.0 tools_4.0.3 data.table_1.13.2
[46] hms_0.5.3 lifecycle_0.2.0 munsell_0.5.0
[49] reprex_0.3.0 isoband_0.2.2 compiler_4.0.3
[52] RNetCDF_2.4-2 rlang_0.4.8 grid_4.0.3
[55] rstudioapi_0.11 labeling_0.4.2 rmarkdown_2.5
[58] gtable_0.3.0 DBI_1.1.0 R6_2.5.0
[61] ncmeta_0.3.0 lubridate_1.7.9 knitr_1.30
[64] rprojroot_1.3-2 stringi_1.5.3 parallel_4.0.3
[67] Rcpp_1.0.5 vctrs_0.3.4 dbplyr_1.4.4
[70] tidyselect_1.1.0 xfun_0.18