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Hi, everyone, these are the codes. The console didn't report any error, but, the plot showed : Error using packet 1 subscript out of bounds. At the same time, only VALUE.obs and CDX.hist were displayed, and CDX.raw and CDX.cal were not dispalyed. Who wold like to help me with this problem?
library(transformeR)
library(downscaleR)
library(visualizeR)
library(climate4R.datasets)
data(VALUE_Iberia_pr)
y <- VALUE_Iberia_pr
data("CORDEX_Iberia_pr")
x <- CORDEX_Iberia_pr
data("CORDEX_Iberia_pr.rcp85")
newdata <- CORDEX_Iberia_pr.rcp85
cal <- biasCorrection(y = y, x = x,
newdata = newdata,
precipitation = TRUE,
method = "eqm",
extrapolation = "constant",
window = c(30, 15),
wet.threshold = 0.1)
In the bias correction step the Cordex (rotated grid) data are interpolated (nearest neighbor) on the Value_Iberia_pr grid in order bias correction to be performed.Try before extracting CDX.hist and CDX.rae to interpolate on the same grid (Value iberia) and then use substGrid with lonlim kai latlim to extract the station data
Hi, everyone, these are the codes. The console didn't report any error, but, the plot showed : Error using packet 1 subscript out of bounds. At the same time, only VALUE.obs and CDX.hist were displayed, and CDX.raw and CDX.cal were not dispalyed. Who wold like to help me with this problem?
library(transformeR)
library(downscaleR)
library(visualizeR)
library(climate4R.datasets)
data(VALUE_Iberia_pr)
y <- VALUE_Iberia_pr
data("CORDEX_Iberia_pr")
x <- CORDEX_Iberia_pr
data("CORDEX_Iberia_pr.rcp85")
newdata <- CORDEX_Iberia_pr.rcp85
cal <- biasCorrection(y = y, x = x,
newdata = newdata,
precipitation = TRUE,
method = "eqm",
extrapolation = "constant",
window = c(30, 15),
wet.threshold = 0.1)
time series plotting for Igueldo station
VALUE.obs <- subsetGrid(y, station.id = "000234") # observation.
CDX.cal <- subsetGrid(cal, station.id = "000234") # CORDEX RCP8.5 corrected
CDX.hist <- interpGrid(x, getGrid(VALUE.obs)) # CORDEX historical
CDX.raw <- interpGrid(newdata, getGrid(VALUE.obs)) # CORDEX RCP8.5
temporalPlot(VALUE.obs, CDX.hist, CDX.cal, CDX.raw,
cols = c("black", "red", "green", "red"))
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