This sample data contain gridded seasonal forecast and corresponding observational data from ECMWF-System 5 forecast system and ERA-5 reconstruction. Specifically, for the monthly mean 2-meter temperature ("tas") variable, the first 3 ensemble members, the first 5 forecast time steps from November initial month, year 2000 to 2005, the Iberian Peninsula region (35N-45N, 10W-5E).
The package "startR" is used to load the data from the data esarchive in the Earth Sciences Department of Barcelona Supercomputing Center.
# 1. Load libraries and define common variables
library(startR)
library(CSTools)
sdates <- sapply(2000:2005, function(x) paste0(x, '1101'))
lonmax <- 5
lonmin <- -10
latmax <- 45
latmin <- 35
# 2. Load exp
repos_exp <- paste0('/esarchive/exp/ecmwf/system5c3s/monthly_mean/',
'$var$_f6h/$var$_$sdate$.nc')
exp <- Start(dat = repos_exp,
var = 'tas',
member = indices(1:3),
sdate = sdates,
time = indices(1:5),
lat = values(list(latmin, latmax)),
lat_reorder = Sort(decreasing = FALSE),
lon = values(list(lonmin, lonmax)),
lon_reorder = CircularSort(-180, 180),
synonims = list(lon = c('lon', 'longitude'),
lat = c('lat', 'latitude'),
member = c('member', 'ensemble')),
return_vars = list(lat = NULL, lon = NULL, time = 'sdate'),
retrieve = TRUE)
# 3. Load obs
exp_time <- attr(exp, "Variables")$common$time
obs_date <- array(format(exp_time, "
path_obs <- '/esarchive/recon/ecmwf/era5/monthly_mean/$var$_f1h-r1440x721cds/$var$_$date$.nc'
obs <- Start(dat = path_obs,
var = 'tas',
date = obs_date,
split_multiselected_dims = TRUE,
lat = values(list(latmin, latmax)),
lat_reorder = Sort(decreasing = FALSE),
lon = values(list(lonmin, lonmax)),
lon_reorder = CircularSort(-180, 180),
synonims = list(lon = c('lon', 'longitude'),
lat = c('lat', 'latitude')),
transform = CDORemapper,
transform_extra_cells = 2,
transform_params = list(grid = 'r360x181',
method = 'conservative'),
transform_vars = c('lat', 'lon'),
return_vars = list(lon = NULL, lat = NULL, time = 'date'),
retrieve = TRUE)
# 4. Check data
obs_time <- attr(obs,"Variables")$common$time
identical(format(obs_time, "
#[1] TRUE
exp_lat <- attr(exp, "Variables")$common$lat
exp_lon <- attr(exp, "Variables")$common$lon
obs_lat <- attr(obs, "Variables")$common$lat
obs_lon <- attr(obs, "Variables")$common$lon
all.equal(exp_lat, obs_lat, check.attributes = F)
#[1] TRUE
all.equal(exp_lon, obs_lon, check.attributes = F)
#[1] TRUE
# 5. Combine into one object
map_temp <- list()
map_temp$exp <- exp
map_temp$obs <- obs