load("../InputData/CRU_SummerData_G5000.RData")

# create a time axis that uses years instead of days. Assume that the data in the CRU
# temperature data file is for every year beginning in January 1801.
# remove the grid cells that are not land - maybe not?
FIdx <- unlist( read.table("../Data/Arc2Kmask1.txt", as.is=T))
FIdx <- union( FIdx, which( colSums(!is.na(Inst.Data)) > 0) )
Inst.Data <- Inst.Data[ , FIdx]
Inst.Locs <- Inst.Locs[ FIdx, ]

Data.timeline <- Inst.Time

# normalise data
# CalTMean  <- colMeans(Inst.Data, na.rm=TRUE)
# CalTSDev  <- apply(Inst.Data, 2, sd, na.rm=TRUE)
CalTMean <- rep(0, ncol( Inst.Data))
CalTSDev <- rep(1, ncol( Inst.Data))

Inst.Data <- t( (t(Inst.Data) - CalTMean) / CalTSDev)

BARCAST.INPUT <- list(Inst.Locs,
                Data.timeline,
                Inst.Data,
                NA*Inst.Data)
names(BARCAST.INPUT)<-c("Master.Locs",
                "Data.timeline",
                "Inst.Data",
                "Prox.Data.1")


save(list=c("BARCAST.INPUT" ,"CalTMean" ,"CalTSDev"), file="../Data/ArcticRecon_2k0_Summer_Inst_CRU_G5000.RData")