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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Calibration.R
\name{Calibration}
\alias{Calibration}
\title{Calibration based on an ensemble inflation (Doblas-Reyes et al. 2005)}
\usage{
Calibration(data)
}
\arguments{
\item{data}{a list of s2dverification objects (lists) as output by the \code{Load} function from the s2dverification package, one for each variable.}
\value{
\code{$calibrated} {An array with the calibrated forecasts with same dimensions that data$mod}
}
\description{
This function applies a variance inflation technique described in Doblas-Reyes et al. (2005) in leave-one-out cross-validation. The calibrated forecasts have an equivalent variance to that of the reference dataset, but at the same time preserve reliability.
}
\examples{
# Creation of sample s2dverification objects. These are not complete
# s2dverification objects though. The Load function returns complete objects.
# Example
mod1 <- 1 : (1 * 3 * 4 * 5 * 6 * 7)
dim(mod1) <- c(dataset = 1, member = 3, sdate = 4, ftime = 5, lat = 6, lon = 7)
obs1 <- 1 : (1 * 1 * 4 * 5 * 6 * 7)
dim(obs1) <- c(dataset = 1, member = 1, sdate = 4, ftime = 5, lat = 6, lon = 7)
lon <- seq(0, 30, 5)
lat <- seq(0, 25, 5)
data1 <- list(mod = mod1, obs = obs1, lat = lat, lon = lon)
a <- Calibration(data1)
str(a)
}
\references{
Doblas-Reyes, F. J., Hagedorn, R., & Palmer, T. N. (2005). The rationale behind the success of multi-model ensembles in seasonal forecasting—II. Calibration and combination. Tellus A: Dynamic Meteorology and Oceanography, 57(3), 234-252.
Torralba, V., Doblas-Reyes, F. J., MacLeod, D., Christel, I., & Davis, M. (2017). Seasonal climate prediction: A new source of information for the management of wind energy resources. Journal of Applied Meteorology and Climatology, 56(5), 1231-1247.
}
\author{
Verónica Torralba, \email{veronica.torralba@bsc.es}
}