Last updated: 2024-09-19

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Knit directory: oae_ccs_roms/

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Read this

this is the script to open the data

# File paths
# /work/loher/ROMS/Alk_enh_formatted_2024_08 ##regridded v2
# /net/sea/work/loher/ROMS/Pactcs30_Alk_enhanced_2024_08 ## original grids v2

#loading packages
library(ncdf4)
library(tidync)
library(stars)
Loading required package: abind
Loading required package: sf
Linking to GEOS 3.11.1, GDAL 3.4.1, PROJ 7.2.1; sf_use_s2() is TRUE
WARNING: different compile-time and runtime versions for GEOS found:
Linked against: 3.11.1-CAPI-1.17.1 compiled against: 3.9.1-CAPI-1.14.2
It is probably a good idea to reinstall sf, and maybe rgeos and rgdal too
library(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()
# setting main path to read files (original grid)
# path_ROMSv2_results <- 
#   "/net/sea/work/loher/ROMS/Pactcs30_Alk_enhanced_2024_08/"

# #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:
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: 12
#filtering for just one variable
nc <- 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.
#slicing for just one timepoint
nc <- nc %>% 
  slice(time, 1
      ) 
#creating a blank plot nad loading in the nc data layer  
ggplot() + 
  geom_stars(data = nc)

Version Author Date
5eca06c vgfroh 2024-09-19 
# 
# #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