read_data
Victoria Froh & Jens Daniel Müller
19 September, 2024
Last updated: 2024-09-19
Checks: 7 0
Knit directory: oae_ccs_roms/
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| Rmd | a97392c | jens-daniel-mueller | 2024-09-19 | setup project |
Read this
this is the script to open the data
# Testing file
# /work/loher/ROMS/Alk_enh_formatted_2024_08 ##regridded v2
# /net/sea/work/loher/ROMS/Pactcs30_Alk_enhanced_2024_08 ## original grids v2
# setting main path to read files
# path_ROMSv2_results <-
# "/net/sea/work/loher/ROMS/Pactcs30_Alk_enhanced_2024_08/"
library(ncdf4)
library(tidync)
library(stars)Loading required package: abindLoading required package: sfLinking to GEOS 3.11.1, GDAL 3.4.1, PROJ 7.2.1; sf_use_s2() is TRUEWARNING: different compile-time and runtime versions for GEOS found:Linked against: 3.11.1-CAPI-1.17.1 compiled against: 3.9.1-CAPI-1.14.2It is probably a good idea to reinstall sf, and maybe rgeos and rgdal toolibrary(tidyverse)── Attaching packages
───────────────────────────────────────
tidyverse 1.3.2 ──✔ ggplot2 3.4.4 ✔ purrr 1.0.2
✔ tibble 3.2.1 ✔ dplyr 1.1.3
✔ tidyr 1.3.0 ✔ stringr 1.5.0
✔ readr 2.1.3 ✔ forcats 0.5.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()# #reading/opening a specific nc file
# nc <- nc_open(paste0(path_ROMSv2_results,
# "Pactcs30_Alk_enhanced_ColumbiaRiver_1x/avg/ColumbiaRiver_1x_2010_monthly.nc"))
#
# print(nc)
# #loading nc file into tidync
# columbia1x_interior <-
# tidync(paste0(path_ROMSv2_results,
# "Pactcs30_Alk_enhanced_ColumbiaRiver_1x/avg/ColumbiaRiver_1x_2010_monthly.nc"))
#
# # filtering nc to a subset of dimensions, then producing a table of certain
# # variables within the subset
# sub_columbia1x_interior <- columbia1x_interior %>%
# hyper_filter(s_rho = s_rho <= 100) %>%
# hyper_tibble(select_var = c("Alk", "DIC"),
# force = TRUE)
#
# #read in ALK and DIC info from the nc file
# testtable <- read_ncdf(paste0(
# path_ROMSv2_results,"Pactcs30_Alk_enhanced_ColumbiaRiver_1x/avg/ColumbiaRiver_1x_2010_monthly.nc"),
# var = c("Alk", "DIC"), make_units = FALSE)
# # compile into a table
# testtable <- testtable %>% as_tibble()
# # extract the year and month from the time stamp
# testtable <- testtable %>% mutate(year = year(time), month = month(time))
#
# ######
#For the regridded standard files:
path_ROMSv2RG_results <-
"/net/sea/work/loher/ROMS/Alk_enh_formatted_2024_08/"
#reading/opening a specific nc file
nc <- nc_open(paste0(path_ROMSv2RG_results,
"ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc"))
print(nc)File /net/sea/work/loher/ROMS/Alk_enh_formatted_2024_08/ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc (NC_FORMAT_NETCDF4):
9 variables (excluding dimension variables):
float Alk[lon,lat,depth,time] (Chunking: [96,88,1,1])
long_name: averaged Alkalinity
units: mMol m-3
missing_value: NaN
_FillValue: NaN
float DIC[lon,lat,depth,time] (Chunking: [96,88,1,1])
long_name: averaged Dissolved inorganic carbon
units: mMol C m-3
missing_value: NaN
_FillValue: NaN
float PO4[lon,lat,depth,time] (Chunking: [96,88,1,1])
long_name: averaged Phosphate
units: mMol P m-3
missing_value: NaN
_FillValue: NaN
float SiO3[lon,lat,depth,time] (Chunking: [96,88,1,1])
long_name: averaged Silicate
units: mMol Si m-3
missing_value: NaN
_FillValue: NaN
float salt[lon,lat,depth,time] (Chunking: [96,88,1,1])
long_name: averaged salinity
units: PSU
missing_value: NaN
_FillValue: NaN
float temp[lon,lat,depth,time] (Chunking: [96,88,1,1])
long_name: averaged potential temperature
units: Celsius
missing_value: NaN
_FillValue: NaN
float FG_CO2[lon,lat,time] (Chunking: [96,88,1])
long_name: averaged Air-sea flux of CO2
units: mmol/m2/s
missing_value: NaN
_FillValue: NaN
float PCO2OC[lon,lat,time] (Chunking: [96,88,1])
long_name: averaged PCO2OC
units: not looked up yet
missing_value: NaN
_FillValue: NaN
float pCO2air[lon,lat,time] (Chunking: [96,88,1])
long_name: averaged Atmospheric pCO2
units: ppm
missing_value: NaN
_FillValue: NaN
4 dimensions:
time Size:1096 *** is unlimited ***
standard_name: time
calendar: 365_day
axis: T
long_name: Averaged time since 2010-01-01
units: days since 2010-01-01
lon Size:96
standard_name: longitude
long_name: longitude
units: degrees_east
axis: X
lat Size:88
standard_name: latitude
long_name: latitude
units: degrees_north
axis: Y
depth Size:16
axis: Z
long_name: depth
units: m
remark: positive down
5 global attributes:
CDI: Climate Data Interface version 2.2.1 (https://mpimet.mpg.de/cdi)
Conventions: CF-1.6
history: Tue Aug 20 20:38:27 2024: cdo --history -s -P 12 -f nc4 -selvar,Alk,DIC,PO4,salt,SiO3,temp -remapbil,/net/sea/work/loher/ROMS/Alk_enh_formatted_2024_08/griddes_ColumbiaRiver /nfs/sea/work/loher/ROMS/Pactcs30_Alk_enhanced_2024_08/Pactcs30_Alk_enhanced_ColumbiaRiver_1x/avg/z_pactcs30_2010-2015_avg.00000.nc /net/sea/work/loher/ROMS/Alk_enh_formatted_2024_08/ColumbiaRiver/pactcs30_2010-2015_avg.00000_1x.nc
CDO: Climate Data Operators version 2.2.0 (https://mpimet.mpg.de/cdo)
cdo_openmp_thread_number: 12nc <- read_ncdf(paste0(path_ROMSv2RG_results,
"ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc"),
var = "FG_CO2")Will return stars object with 9259008 cells.
No projection information found in nc file.
Coordinate variable units found to be degrees,
assuming WGS84 Lat/Lon.nc <- nc %>%
slice(time, 1
)
ggplot() +
geom_stars(data = nc)
#
# #loading nc file into tidync
# columbia1x_regrid <-
# tidync(paste0(path_ROMSv2RG_results,
# "ColumbiaRiver/pactcs30_2010-2015_avg.01092_1x.nc"))
#
# # filtering nc to a subset of dimensions, then producing a table of certain
# # variables within the subset ie only top depth on the last day, Alk
# alk_columbia1x_regrid <- columbia1x_regrid %>%
# hyper_filter(depth = depth <= 0, time = index == 16
# ) %>%
# hyper_tibble(select_var = c("Alk"),
# force = TRUE)
# #plotting basic on map
# alk_C_sf <- st_as_sf(alk_columbia1x_regrid, coords = c("lon", "lat"), crs = 4326)
# ggplot(data = alk_C_sf) + geom_sf(aes(color = Alk)) + theme_minimal() +
# labs(title = "Columbia River Final Alkalinity",
# x = "Longitude", y = "Latitude")
#
# #repeat for DIC
# dic_columbia1x_regrid <- columbia1x_regrid %>%
# hyper_filter(depth = depth <= 0, time = index == 16
# ) %>%
# hyper_tibble(select_var = c("DIC"),
# force = TRUE)
# dic_C_sf <- st_as_sf(dic_columbia1x_regrid, coords = c("lon", "lat"), crs = 4326)
# ggplot(data = dic_C_sf) + geom_sf(aes(color = DIC)) + theme_minimal() +
# labs(title = "Columbia River Final DIC",
# x = "Longitude", y = "Latitude")
#
#
#
#
# ## This section: what does it do/what is the point
# #read in ALK and DIC info from the nc file
# testtable <- read_ncdf(paste0(
# path_ROMSv2RG_results,"ColumbiaRiver/pactcs30_2010-2015_avg.01092_1x.nc"),
# var = c("Alk"), make_units = FALSE)
# # compile into a table
# testtable <- testtable %>% as_tibble()
# # extract the year and month from the time stamp
# testtable <- testtable %>% mutate(year = year(time), month = month(time))vhjgvj
sessionInfo()R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.5
Matrix products: default
BLAS: /usr/local/R-4.2.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.2.2/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] forcats_0.5.2 stringr_1.5.0 dplyr_1.1.3 purrr_1.0.2
[5] readr_2.1.3 tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.4
[9] tidyverse_1.3.2 stars_0.6-0 sf_1.0-9 abind_1.4-5
[13] tidync_0.4.0 ncdf4_1.19 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] fs_1.5.2 lubridate_1.9.0 httr_1.4.4
[4] rprojroot_2.0.3 tools_4.2.2 backports_1.4.1
[7] bslib_0.4.1 utf8_1.2.2 R6_2.5.1
[10] KernSmooth_2.23-20 DBI_1.1.3 colorspace_2.0-3
[13] withr_2.5.0 tidyselect_1.2.0 processx_3.8.0
[16] compiler_4.2.2 git2r_0.30.1 cli_3.6.1
[19] rvest_1.0.3 RNetCDF_2.6-1 xml2_1.3.3
[22] labeling_0.4.2 sass_0.4.4 scales_1.2.1
[25] classInt_0.4-8 callr_3.7.3 proxy_0.4-27
[28] digest_0.6.30 rmarkdown_2.18 pkgconfig_2.0.3
[31] htmltools_0.5.3 highr_0.9 dbplyr_2.2.1
[34] fastmap_1.1.0 rlang_1.1.1 readxl_1.4.1
[37] rstudioapi_0.15.0 PCICt_0.5-4.3 jquerylib_0.1.4
[40] generics_0.1.3 farver_2.1.1 jsonlite_1.8.3
[43] googlesheets4_1.0.1 magrittr_2.0.3 ncmeta_0.3.5
[46] Rcpp_1.0.10 munsell_0.5.0 fansi_1.0.3
[49] lifecycle_1.0.3 stringi_1.7.8 whisker_0.4
[52] yaml_2.3.6 grid_4.2.2 parallel_4.2.2
[55] promises_1.2.0.1 crayon_1.5.2 haven_2.5.1
[58] hms_1.1.2 knitr_1.41 ps_1.7.2
[61] pillar_1.9.0 reprex_2.0.2 glue_1.6.2
[64] evaluate_0.18 getPass_0.2-2 modelr_0.1.10
[67] vctrs_0.6.4 tzdb_0.3.0 httpuv_1.6.6
[70] cellranger_1.1.0 gtable_0.3.1 assertthat_0.2.1
[73] cachem_1.0.6 xfun_0.35 lwgeom_0.2-10
[76] broom_1.0.5 e1071_1.7-12 later_1.3.0
[79] class_7.3-20 googledrive_2.0.0 gargle_1.2.1
[82] units_0.8-0 timechange_0.1.1 ellipsis_0.3.2