lonlat_temp_st | R Documentation |
This sample data set contains gridded seasonal forecast and corresponding observational data from the Copernicus Climate Change ECMWF-System 5 forecast system, and from the Copernicus Climate Change ERA-5 reconstruction. Specifically, for the 'tas' (2-meter temperature) variable, for the 15 first forecast ensemble members, monthly averaged, for the 3 first forecast time steps (lead months 1 to 4) of the November start dates of 2000 to 2005, for the Mediterranean region (27N-48N, 12W-40E). The data was generated on (or interpolated onto, for the reconstruction) a rectangular regular grid of size 360 by 181.
The 'CST_Start' call used to generate the data set in the infrastructure of the Earth Sciences Department of the Barcelona Supercomputing Center is shown next. Note that 'CST_Start' internally calls 'startR::Start' and then uses 'as.s2dv_cube' that converts the 'startR_array' into 's2dv_cube'.
lonlat_temp_st <- NULL repos_exp <- paste0('/esarchive/exp/ecmwf/system5c3s/monthly_mean/', '$var$_f6h/$var$_$sdate$.nc') sdates <- sapply(2000:2005, function(x) paste0(x, '1101')) lonmax <- 40 lonmin <- -12 latmax <- 48 latmin <- 27 lonlat_temp_st$exp <- CST_Start(dataset = repos_exp, var = 'tas', member = startR::indices(1:15), sdate = sdates, ftime = startR::indices(1:3), lat = startR::values(list(latmin, latmax)), lat_reorder = startR::Sort(decreasing = TRUE), lon = startR::values(list(lonmin, lonmax)), lon_reorder = startR::CircularSort(0, 360), synonims = list(lon = c('lon', 'longitude'), lat = c('lat', 'latitude'), member = c('member', 'ensemble'), ftime = c('ftime', 'time')), return_vars = list(lat = NULL, lon = NULL, ftime = 'sdate'), retrieve = TRUE) dates <- c(paste0(2000, c(11, 12)), paste0(2001, c('01', 11, 12)), paste0(2002, c('01', 11, 12)), paste0(2003, c('01', 11, 12)), paste0(2004, c('01', 11, 12)), paste0(2005, c('01', 11, 12)), 200601) dates <- sapply(dates, function(x) {paste0(x, '01')}) dates <- as.POSIXct(dates, format = ' dim(dates) <- c(ftime = 3, sdate = 6) dates <- t(dates) names(dim(dates)) <- c('sdate', 'ftime') path.obs <- '/esarchive/recon/ecmwf/era5/monthly_mean/$var$_f1h-r1440x721cds/$var$_$date$.nc' lonlat_temp_st$obs <- CST_Start(dataset = path.obs, var = 'tas', date = unique(format(dates, ' ftime = startR::values(dates), ftime_across = 'date', ftime_var = 'ftime', merge_across_dims = TRUE, split_multiselected_dims = TRUE, lat = startR::values(list(latmin, latmax)), lat_reorder = startR::Sort(decreasing = TRUE), lon = startR::values(list(lonmin, lonmax)), lon_reorder = startR::CircularSort(0, 360), synonims = list(lon = c('lon', 'longitude'), lat = c('lat', 'latitude'), ftime = c('ftime', 'time')), transform = startR::CDORemapper, transform_extra_cells = 2, transform_params = list(grid = 'r360x181', method = 'conservative'), transform_vars = c('lat', 'lon'), return_vars = list(lon = NULL, lat = NULL, ftime = 'date'), retrieve = TRUE) library(lubridate) dates_exp <- lonlat_temp_st$exp$attrs$Dates lonlat_temp_st$exp$attrs$Dates <- floor_date(ymd_hms(dates_exp), unit = "months") dim(lonlat_temp_st$exp$attrs$Dates) <- dim(dates_exp) dates_obs <- lonlat_temp_st$obs$attrs$Dates lonlat_temp_st$obs$attrs$Dates <- floor_date(ymd_hms(dates_obs), unit = "months") dim(lonlat_temp_st$obs$attrs$Dates) <- dim(dates_obs)
Nicolau Manubens nicolau.manubens@bsc.es
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