UCSD Argo pH Climatology
Pasqualina Vonlanthen & Jens Daniel Müller
29 April, 2022
Last updated: 2022-04-29
Checks: 7 0
Knit directory: bgc_argo_r_argodata/
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| html | e61c08e | pasqualina-vonlanthendinenna | 2022-04-27 | Build site. |
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| html | 968ad85 | pasqualina-vonlanthendinenna | 2022-03-29 | Build site. |
| Rmd | 5432acf | pasqualina-vonlanthendinenna | 2022-03-29 | added january pH climatology |
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| Rmd | b9a42f9 | pasqualina-vonlanthendinenna | 2022-03-29 | added january plots and changed pH anomaly detection to mean |
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| Rmd | 5112b5b | pasqualina-vonlanthendinenna | 2022-03-28 | added code for reading metadata in argo_clim_pH |
| html | b530d31 | pasqualina-vonlanthendinenna | 2022-03-25 | Build site. |
| Rmd | 34e771c | pasqualina-vonlanthendinenna | 2022-03-25 | added commented out sio temp climatology |
| html | 6dd0945 | pasqualina-vonlanthendinenna | 2022-03-25 | Build site. |
| Rmd | 5b93849 | pasqualina-vonlanthendinenna | 2022-03-25 | added climatology pages |
Task
Explore the January climatology of Argo pH of Matt Mazloff, UCSD
library(tidyverse)── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──✓ ggplot2 3.3.5 ✓ purrr 0.3.4
✓ tibble 3.1.6 ✓ dplyr 1.0.7
✓ tidyr 1.1.4 ✓ stringr 1.4.0
✓ readr 2.1.1 ✓ forcats 0.5.1── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()#library(ggOceanMaps)
library(oce)Loading required package: gsw#library(ncdf4)
library(stars)Loading required package: abindLoading required package: sfLinking to GEOS 3.6.2, GDAL 3.2.0, PROJ 7.0.0; sf_use_s2() is TRUEpath_updata <- "/nfs/kryo/work/updata"
path_argo_clim_ph <- paste0(path_updata, "/argo_climatology/pH")
path_argo_clim_temp <- paste0(path_updata, "/argo_climatology/temperature")
path_emlr_utilities <- "/nfs/kryo/work/jenmueller/emlr_cant/utilities/files/"
path_argo <- '/nfs/kryo/work/updata/bgc_argo_r_argodata'
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")
theme_set(theme_bw())Read data
nc_pH <-
read_ncdf(paste0(path_argo_clim_ph,"/PHclim_15March2022_Prelim.nc"),
var = c("pH"))Warning in .get_nc_projection(meta$attribute, rep_var, all_coord_var): No
projection information found in nc file.nc_pH <- as_tibble(nc_pH)
nc_lon <-
read_ncdf(paste0(path_argo_clim_ph,"/PHclim_15March2022_Prelim.nc"),
var = c("longitude"))Warning in .get_nc_projection(meta$attribute, rep_var, all_coord_var): No
projection information found in nc file.nc_lon <- as_tibble(nc_lon)
nc_lat <-
read_ncdf(paste0(path_argo_clim_ph,"/PHclim_15March2022_Prelim.nc"),
var = c("latitude"))Warning in .get_nc_projection(meta$attribute, rep_var, all_coord_var): No
projection information found in nc file.nc_lat <- as_tibble(nc_lat)
nc_depth <-
read_ncdf(paste0(path_argo_clim_ph,"/PHclim_15March2022_Prelim.nc"),
var = c("depth"))Warning in .get_nc_projection(meta$attribute, rep_var, all_coord_var): No
projection information found in nc file.nc_depth <- as_tibble(nc_depth)
nc_pH <- nc_pH %>%
mutate(ny = ny - 0.5,
nx = nx - 0.5)
clim_argo_ph_jan <- full_join(nc_pH, nc_lat)Joining, by = "ny"clim_argo_ph_jan <- full_join(clim_argo_ph_jan, nc_lon)Joining, by = "nx"clim_argo_ph_jan <- full_join(clim_argo_ph_jan, nc_depth)Joining, by = "nz"clim_argo_ph_jan <- clim_argo_ph_jan %>%
select(-c(starts_with("n"), "t"))
clim_argo_ph_jan <- clim_argo_ph_jan %>%
mutate(depth = round(depth))Maps
clim_argo_ph_jan %>%
ggplot() +
geom_tile(aes(longitude, latitude, fill = pH)) +
facet_wrap(~depth) +
scale_fill_viridis_c() +
coord_quickmap()
| Version | Author | Date |
|---|---|---|
| 968ad85 | pasqualina-vonlanthendinenna | 2022-03-29 |
clim_argo_ph_jan %>%
filter(pH != 0) %>%
ggplot() +
geom_tile(aes(longitude, latitude, fill = pH)) +
facet_wrap(~depth) +
scale_fill_viridis_c() +
coord_quickmap()
| Version | Author | Date |
|---|---|---|
| 968ad85 | pasqualina-vonlanthendinenna | 2022-03-29 |
clim_argo_ph_jan %>%
filter(pH != 0) %>%
ggplot(aes(pH)) +
geom_histogram() +
facet_wrap(~depth) +
scale_y_log10() +
geom_vline(xintercept = 7.5)`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.Warning: Transformation introduced infinite values in continuous y-axisWarning: Removed 736 rows containing missing values (geom_bar).
| Version | Author | Date |
|---|---|---|
| 968ad85 | pasqualina-vonlanthendinenna | 2022-03-29 |
Harmonise data
clim_argo_ph_jan <- clim_argo_ph_jan %>%
filter(pH != 0)
# harmonise data
clim_argo_ph_jan <- clim_argo_ph_jan %>%
rename(lat = latitude,
lon = longitude,
clim_pH_jan = pH) %>%
mutate(lon = if_else(lon < 20, lon + 360, lon),
month = 1)Write data to file
clim_argo_ph_jan %>% write_rds(file = paste0(path_argo_preprocessed, "/ucsd_ph_clim_jan.rds"))
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] stars_0.5-5 sf_1.0-5 abind_1.4-5 oce_1.5-0
[5] gsw_1.0-6 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7
[9] purrr_0.3.4 readr_2.1.1 tidyr_1.1.4 tibble_3.1.6
[13] ggplot2_3.3.5 tidyverse_1.3.1 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] fs_1.5.2 lubridate_1.8.0 httr_1.4.2 rprojroot_2.0.2
[5] tools_4.1.2 backports_1.4.1 bslib_0.3.1 utf8_1.2.2
[9] R6_2.5.1 KernSmooth_2.23-20 DBI_1.1.2 colorspace_2.0-2
[13] withr_2.4.3 tidyselect_1.1.1 processx_3.5.2 compiler_4.1.2
[17] git2r_0.29.0 cli_3.1.1 rvest_1.0.2 RNetCDF_2.5-2
[21] xml2_1.3.3 labeling_0.4.2 sass_0.4.0 scales_1.1.1
[25] classInt_0.4-3 callr_3.7.0 proxy_0.4-26 digest_0.6.29
[29] rmarkdown_2.11 pkgconfig_2.0.3 htmltools_0.5.2 highr_0.9
[33] dbplyr_2.1.1 fastmap_1.1.0 rlang_1.0.2 readxl_1.3.1
[37] rstudioapi_0.13 jquerylib_0.1.4 generics_0.1.1 farver_2.1.0
[41] jsonlite_1.7.3 magrittr_2.0.1 ncmeta_0.3.0 Rcpp_1.0.8
[45] munsell_0.5.0 fansi_1.0.2 lifecycle_1.0.1 stringi_1.7.6
[49] whisker_0.4 yaml_2.2.1 grid_4.1.2 parallel_4.1.2
[53] promises_1.2.0.1 crayon_1.4.2 haven_2.4.3 hms_1.1.1
[57] knitr_1.37 ps_1.6.0 pillar_1.6.4 reprex_2.0.1
[61] glue_1.6.0 evaluate_0.14 getPass_0.2-2 modelr_0.1.8
[65] vctrs_0.3.8 tzdb_0.2.0 httpuv_1.6.5 cellranger_1.1.0
[69] gtable_0.3.0 assertthat_0.2.1 xfun_0.29 lwgeom_0.2-8
[73] broom_0.7.11 e1071_1.7-9 later_1.3.0 class_7.3-20
[77] viridisLite_0.4.0 units_0.7-2 ellipsis_0.3.2