View source: R/CST_BiasCorrection.R
CST_BiasCorrection | R Documentation |
This function applies the simple bias adjustment technique described in Torralba et al. (2017). The adjusted forecasts have an equivalent standard deviation and mean to that of the reference dataset.
CST_BiasCorrection(
exp,
obs,
exp_cor = NULL,
na.rm = FALSE,
memb_dim = "member",
sdate_dim = "sdate",
dat_dim = NULL,
ncores = NULL
)
exp |
An object of class |
obs |
An object of class |
exp_cor |
An object of class |
na.rm |
A logical value indicating whether missing values should be stripped before the computation proceeds, by default it is set to FALSE. |
memb_dim |
A character string indicating the name of the member dimension. By default, it is set to 'member'. |
sdate_dim |
A character string indicating the name of the start date dimension. By default, it is set to 'sdate'. |
dat_dim |
A character string indicating the name of dataset dimension. The length of this dimension can be different between 'exp' and 'obs'. The default value is NULL. |
ncores |
An integer that indicates the number of cores for parallel computations using multiApply function. The default value is NULL. |
An object of class s2dv_cube
containing the bias corrected
forecasts with the dimensions nexp, nobs and same dimensions as in the 'exp'
object. nexp is the number of experiment (i.e., 'dat_dim' in exp), and nobs is
the number of observation (i.e., 'dat_dim' in obs). If dat_dim is NULL, nexp
and nobs are omitted. If 'exp_cor' is provided the returned array will be with
the same dimensions as 'exp_cor'.
Verónica Torralba, veronica.torralba@bsc.es
Torralba, V., F.J. Doblas-Reyes, D. MacLeod, I. Christel and M. Davis (2017). Seasonal climate prediction: a new source of information for the management of wind energy resources. Journal of Applied Meteorology and Climatology, 56, 1231-1247, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1175/JAMC-D-16-0204.1")}. (CLIM4ENERGY, EUPORIAS, NEWA, RESILIENCE, SPECS)
mod1 <- 1 : (1 * 3 * 4 * 5 * 6 * 7)
dim(mod1) <- c(dataset = 1, member = 3, sdate = 4, time = 5, lat = 6, lon = 7)
obs1 <- 1 : (1 * 1 * 4 * 5 * 6 * 7)
dim(obs1) <- c(dataset = 1, member = 1, sdate = 4, time = 5, lat = 6, lon = 7)
lon <- seq(0, 30, 5)
lat <- seq(0, 25, 5)
coords <- list(lat = lat, lon = lon)
exp <- list(data = mod1, coords = coords)
obs <- list(data = obs1, coords = coords)
attr(exp, 'class') <- 's2dv_cube'
attr(obs, 'class') <- 's2dv_cube'
a <- CST_BiasCorrection(exp = exp, obs = obs)
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