inst/workflow.R

In AgronomicForecastingLab/GEFS_pSIMS:

library(pSIMSMetMaker)
library(tidyverse)
setwd("/mnt/iccp_storage/hamzed/Scripts/GEFS_pSIMS/inst")
sites.path <- system.file("", 'pSIMS_extent.RData', package = "pSIMSMetMaker")
load(sites.path)
#------------------------------------------------- ERA - NEEDS LOGIN
#Login setup
#Create a free CDS user account by self registering.
#Once your user account has been verified you can get your personal user ID and key by visiting the user profile.
#This information is required to be able to retrieve data via the ecmwfr package
#https://github.com/bluegreen-labs/ecmwfr

job::job({
     i <- 3
    user <- "10027"
    wf_set_key(user = user, key = "e5d0082f-ae4d-44d6-a1e0-3b581282033f", 'cds')

    sites <- pSIMS.extent %>%
      dplyr::filter(name %in% c('0024/0045', '0024/0046', '0025/0046'))
    # Request ERA5 data
    era5_data <- era5_tile_request(user, "2020-01-01", "2020-12-31",
                                   sites$xmin[i], sites$xmax[i], sites$ymin[i], sites$ymax[i],
                                   fname=paste0(gsub("/", "_", sites$name[i]),".nc"))
    # Reformat ERA5 data
    era5_data_refmt <- reformat_ERA_data(era5_data)
    #Aggregate the ERA5 data
    era5_data_Agg <- ERA5_aggregate(era5_data_refmt)

    pSIMSMetMaker::write_met(era5_data_Agg[[1]], paste0('clim_', gsub("/", "_", sites$name[i]), '.tile.nc4'))
  }, import = c(pSIMS.extent))




#
# #--------------------------------------------------- NOAA gets
# # Request NOAA GEFS data
# gefs_data <- noaa_gefs_request(sites[1:4,])
# # Reformat NOAA GEFS data
# gefs_data_refmt <- reformat_NOAA_data(gefs_data)
# # Aggregate NOAA GEFS data
# gefs_data_agg <- noaa_gefs_aggregate(gefs_data_refmt)
#
# # Bind ERA5 and NOAA data together
# noaa_era_bind <- bind_NOAA_ERA(gefs_data_agg, era5_data_Agg)