read_data
Victoria Froh & Jens Daniel Müller
30 September, 2024
Last updated: 2024-09-30
Checks: 7 0
Knit directory: oae_ccs_roms/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 5dd4857 | vgfroh | 2024-09-30 | Running the carb function |
| html | a2f17f6 | vgfroh | 2024-09-25 | Build site. |
| Rmd | 7f8a0c8 | vgfroh | 2024-09-25 | Alk and DIC maps of surface at t=1 |
| html | f421914 | vgfroh | 2024-09-19 | Build site. |
| Rmd | f7fc26f | vgfroh | 2024-09-19 | first map but i cleaned up the code |
| html | 5eca06c | vgfroh | 2024-09-19 | Build site. |
| Rmd | c9f35a0 | vgfroh | 2024-09-19 | first map |
| html | 16549e7 | vgfroh | 2024-09-19 | Build site. |
| Rmd | 210c100 | vgfroh | 2024-09-19 | setup project |
| html | 2e8d326 | jens-daniel-mueller | 2024-09-19 | Build site. |
| html | 7591977 | jens-daniel-mueller | 2024-09-19 | Build site. |
| Rmd | a97392c | jens-daniel-mueller | 2024-09-19 | setup project |
Read this
this is the script to open the data
#loading packages
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()library(dplyr)
#For the regridded standard files, path:
path_ROMSv2RG_results <-
"/net/sea/work/loher/ROMS/Alk_enh_formatted_2024_08/"
#currently not working
# opening specific nc file (Columbia site, 1x)
# nc <- nc_open(paste0(path_ROMSv2RG_results,
# "ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc"))
#
# print(nc)
#
# #filtering for just one variable w/ stars package
# nc_alk <- read_ncdf(paste0(path_ROMSv2RG_results,
# "ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc"),
# var = "Alk",
# #ncsub = list( #tried here to subset already but i got weird errors
# #lon = 1:96,
# #lat = 1:88
# #depth = 1
# #time = 1
# #)
# # proxy = FALSE
# )
#
# #trying to filter for surface layer only but it did not actually work
# nc_surface_alk <- nc_alk %>%
# filter(depth == 0)
#
# #slicing for just one timepoint but it also did not actually work
# nc_surface_alk_1 <- nc_surface_alk %>%
# slice(time, 1)
#
# #tried this instead to subset, it works on depth but not time
# nc_alk_subset <- nc_alk[,,1,1, drop = FALSE]
#
# #creating a blank plot and loading in the nc data layer using stars package
# ggplot() +
# geom_stars(data = nc_surface_alk_1, aes(fill = Alk)) +
# labs(title = "Columbia River Surface Alkalinity @ T1",
# x = "Longitude",
# y = "Latitude") +
# theme_minimal()
#
###################
#using tidync instead, which works
nc <- tidync(paste0(path_ROMSv2RG_results,
"ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc"))
# filtering nc file for just the surface @ the first time index for both
# DIC and Alk variable
alk_surface_t1 <- nc %>%
hyper_filter(depth = index == 1, time = index == 1) %>%
hyper_tibble(select_var = c("Alk"), # produces a tibble object
force = TRUE)
dic_surface_t1 <- nc %>%
hyper_filter(depth = index == 1, time = index == 1) %>%
hyper_tibble(select_var = c("DIC"), # produces a tibble object
force = TRUE)
#plotting; st_as_sf converts the proxy to a sf object ie requires loading in
alk_surface_t1_sf <- st_as_sf(alk_surface_t1, coords = c("lon", "lat"), crs = 4326)
ggplot(data = alk_surface_t1_sf) +
geom_sf(aes(color = Alk)) +
labs(title = "Columbia River Surface Alkalinity @ T1",
x = "Longitude", y = "Latitude") +
theme_minimal()
#plotting
dic_surface_t1_sf <- st_as_sf(dic_surface_t1, coords = c("lon", "lat"), crs = 4326)
ggplot(data = dic_surface_t1_sf) +
geom_sf(aes(color = DIC)) +
labs(title = "Columbia River Surface DIC @ T1",
x = "Longitude", y = "Latitude") +
theme_minimal()
| Version | Author | Date |
|---|---|---|
| a2f17f6 | vgfroh | 2024-09-25 |
#how can i make them not look like dots
##########################
#i tried something else so i could get the data but i can't plot this w/ ggplot
# lon <- ncvar_get(nc, "lon", verbose = FALSE) # read lon variable
# lat <- ncvar_get(nc, "lat", verbose = FALSE) # read lat variable
# time <- ncvar_get(nc, "time", verbose = FALSE) # read t (time) variable
# depth <- ncvar_get(nc, "depth", verbose = FALSE) # read depth variable
# print(c(length(lon), length(lat), length(t), length(depth))) # show vector lengths
#
# alk_array <- ncvar_get(nc, "Alk") #pull the alk values from the ncdf4 file
#
# alk_surface_time_1 <- alk_array[, , 1, 1] #pull only the first time point and surface layer
##########################
# Using sea carb:
library(seacarb)Loading required package: oce
Loading required package: gsw
Loading required package: SolveSAPHE#load in temperature and salinity data from tidync file
temp <- nc %>%
hyper_filter(depth = index == 1, time = index == 1) %>%
hyper_tibble(select_var = c("temp"), # produces a tibble object
force = TRUE)
sal <- nc %>%
hyper_filter(depth = index == 1, time = index == 1) %>%
hyper_tibble(select_var = c("salt"), # produces a tibble object
force = TRUE)
# join together the DIC and alk maps into one data frame
merged_surface <- left_join(alk_surface_t1, dic_surface_t1, by = c('lat', 'lon'))
#running carb to produce the pCO2 values, chose an avg temp and sal value
merged_surface <- merged_surface %>%
mutate(
pco2 = carb(
flag = 15,
var1 = Alk * 1e-6,
var2 = DIC * 1e-6,
S=32.8,
T=10,
P=0, #surface = 0
Pt=0, #NA
Sit=0, #NA
kf="pf", #default
k1k2="l", #default
ks="d", #default
)$pCO2 #to just save the pco2 output
)
#save just pco2 and lat/lon data to sf object
pco2_surface <- merged_surface %>% select(pco2, lon, lat) %>%
st_as_sf(coords = c("lon", "lat"), crs = 4326)
#plotting pco2
ggplot(data = pco2_surface) +
geom_sf(aes(color = pco2)) +
labs(title = "Calculated pCO2 for Columbia @ t1",
x = "Longitude", y = "Latitude") +
theme_minimal()
# #to check accuracy: loading in model output pCO2
# model_pco2 <- nc %>% #tidync method; this does not work, "no variables available"
# hyper_filter(time = index == 1) %>%
# hyper_tibble(select_var = c("PCO2OC"), # produces a tibble object
# force = TRUE)
# #trying with ncdf4
# nc2 <- nc_open(paste0(path_ROMSv2RG_results,
# "ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc"))
# model_pco2 <- ncvar_get(nc2, varid = PCO2OC) #also does not work, can't object
# model_pco2 <- model_pco2 %>%
# slice(time, 1) # %>% st_as_sf(coords = c("lon", "lat"), crs = 4326)
#
# #stars; also does not work
# nc3 <- read_ncdf(paste0(path_ROMSv2RG_results,
# "ColumbiaRiver/ColumbiaRiver_2010-2015_1x.nc"),
# var = "PCO2OC",
# ncsub = list( #tried here to subset already but i got weird errors
# time = 1
# ),
# proxy = FALSE
# )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] seacarb_3.3.3 SolveSAPHE_2.1.0 oce_1.7-10 gsw_1.1-1
[5] forcats_0.5.2 stringr_1.5.0 dplyr_1.1.3 purrr_1.0.2
[9] readr_2.1.3 tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.4
[13] tidyverse_1.3.2 stars_0.6-0 sf_1.0-9 abind_1.4-5
[17] 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 jquerylib_0.1.4 generics_0.1.3
[40] farver_2.1.1 jsonlite_1.8.3 googlesheets4_1.0.1
[43] magrittr_2.0.3 ncmeta_0.3.5 Rcpp_1.0.10
[46] munsell_0.5.0 fansi_1.0.3 lifecycle_1.0.3
[49] stringi_1.7.8 whisker_0.4 yaml_2.3.6
[52] grid_4.2.2 parallel_4.2.2 promises_1.2.0.1
[55] crayon_1.5.2 CFtime_1.4.0 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