#' Sample Of Experimental And Observational Climate Data In Function Of Longitudes And Latitudes
#'
#' 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.
#' 
#' It is recommended to use the data set as follows:
#'\code{
#' require(zeallot)
#' c(exp, obs) %<-% CSTools::lonlat_data
#'}
#'
#' The `CST_Load` 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_Load` internally calls `s2dverification::Load`, which would require a configuration file (not provided here) expressing the distribution of the 'system5c3s' and 'era5' NetCDF files in the file system.
#'\code{
#' library(CSTools)
#' require(zeallot)
#'
#' startDates <- c('20001101', '20011101', '20021101',
#'                 '20031101', '20041101', '20051101')
#'
#' lonlat_data <- 
#'   CST_Load(
#'     var = 'tas', 
#'     exp = 'system5c3s', 
#'     obs = 'era5', 
#'     nmember = 15,
#'     sdates = startDates,
#'     leadtimemax = 3,
#'     latmin = 27, latmax = 48,
#'     lonmin = -12, lonmax = 40, 
#'     output = 'lonlat',
#'     nprocs = 1
#'   )
#'}
#'
#' @name lonlat_data
#' @docType data
#' @author Nicolau Manubens \email{nicolau.manubens@bsc.es}
#' @keywords data
NULL

#' Sample Of Experimental Precipitation Data In Function Of Longitudes And Latitudes
#'
#' This sample data set contains a small cutout of gridded seasonal precipitation forecast data from the Copernicus Climate Change ECMWF-System 5 forecast system, to be used to demonstrate downscaling. Specifically, for the 'pr' (precipitation) variable, for the first 6 forecast ensemble members, daily values, for all 31 days in March following the forecast starting dates in November of years 2010 to 2012, for a small 4x4 pixel cutout in a region in the North-Western Italian Alps (44N-47N, 6E-9E). The data resolution is 1 degree..
#' 
#' It is recommended to use the data set as follows:
#'\code{
#' require(zeallot)
#' exp %<-% lonlat_prec 
#'}
#'
#' The `CST_Load` call used to generate the data set in the infrastructure of the Marconi machine at CINECA is shown next, working on files which were extracted from forecast data available in the MEDSCOPE internal archive.
#'
#'\code{
#' library(CSTools)
#' require(zeallot)
#'
#' infile <- list(path = '../medscope/nwalps/data/$VAR_NAME$_$START_DATE$_nwalps.nc')
#' exp <- CST_Load('prlr', exp = list(infile), obs = NULL,
#'                 sdates = c('20101101', '20111101', '20121101'),
#'                 leadtimemin = 121, leadtimemax = 151,
#'                 latmin = 44, latmax = 47,
#'                 lonmin = 5, lonmax = 9,
#'                 nmember = 25,
#'                 storefreq = "daily", sampleperiod = 1,
#'                 output = "lonlat"
#'                )$exp
#'}
#'
#' @name lonlat_prec
#' @docType data
#' @author Jost von Hardenberg \email{j.vonhardenberg@isac.cnr.it}
#' @keywords data
NULL

#' Sample Of Experimental And Observational Climate Data Averaged Over A Region
#'
#' This sample data set contains area-averaged 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).
#' 
#' It is recommended to use the data set as follows:
#'\code{
#' require(zeallot)
#' c(exp, obs) %<-% CSTools::areave_data
#'}
#'
#' The `CST_Load` 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_Load` internally calls `s2dverification::Load`, which would require a configuration file (not provided here) expressing the distribution of the 'system5c3s' and 'era5' NetCDF files in the file system.
#'\code{
#' library(CSTools)
#' require(zeallot)
#'
#' startDates <- c('20001101', '20011101', '20021101',
#'                 '20031101', '20041101', '20051101')
#'
#' areave_data <-  
#'   CST_Load(
#'     var = 'tas', 
#'     exp = 'system5c3s', 
#'     obs = 'era5', 
#'     nmember = 15,
#'     sdates = startDates,
#'     leadtimemax = 3,
#'     latmin = 27, latmax = 48,
#'     lonmin = -12, lonmax = 40, 
#'     output = 'areave',
#'     nprocs = 1
#'   )
#'}
#'
#' @name areave_data
#' @docType data
#' @author Nicolau Manubens \email{nicolau.manubens@bsc.es}
#' @keywords data
NULL
