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Downscale.R
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Downscale.R
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library(ncdf4)
library(raster)
library(qmap)
library(akima)
nc.dir <- dir("/media/zizroc/Extra Drive 1/Data/NCEP_Reanalysis_Surface_Flux/2mTemp/", full.names=TRUE)
air2mtemp <- list()
for(i in 1:58){
nc <- nc_open(nc.dir[i])
dname <- "air"
lon <- ncvar_get(nc, "lon")
nlon <- dim(lon)
lat <- ncvar_get(nc, "lat")
nlat <- dim(lat)
t <- ncvar_get(nc, "time")
tunits <- ncatt_get(nc, "time", "units")
nt <- dim(t)
#ts.array <- ncvar_get(nc, dname, start = c(1, 1, k*72999), count = c(dim(lon), dim(lat), 200*365)) #this file is enormous (e.g., reset memory.size)
ts.array <- ncvar_get(nc, dname) #this file is enormous (e.g., reset memory.size)
dlname <- ncatt_get(nc ,dname, "long_name")
dunits <- ncatt_get(nc, dname, "units")
fillvalue <- ncatt_get(nc, dname, "_FillValue")
nc_close(nc)
rm(nc)
gc()
temp.r <- list()
for(j in 1:nt){
tmp <- raster(t(ts.array[130:138, 24:30, j]))
extent(tmp) <- c(lon[130], lon[138], lat[30], lat[24])
temp.r[[j]] <- tmp
}
# if(i==1){Tmp <- temp.r}
# if(i >1){Tmp <- stack(Tmp, temp.r)}
air2mtemp[[i+1947]] <- stack(temp.r)
rm(ts.array, temp.r)
print(i)
}
save(air2mtemp, file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTemp_1948to2016.Rdata")
##
#Maximum temperature
# tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.002.cam.h1.TREFHTMX.18500101-20051231.nc")
# tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.003.cam.h1.TREFHTMX.18500101-20051231.nc")
# tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.004.cam.h1.TREFHTMX.18500101-20051231.nc")
tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.005.cam.h1.TREFHTMX.18500101-20051231.nc")
dname <- "TREFHTMX"
#Variables
lon <- ncvar_get(tmp.nc, "lon")
nlon <- dim(lon)
lat <- ncvar_get(tmp.nc, "lat")
nlat <- dim(lat)
dat <- ncvar_get(tmp.nc, "date") #current date (YYYMMDD)
ndat <- dim(dat)
t <- ncvar_get(tmp.nc, "time")
tunits <- ncatt_get(tmp.nc, "time", "units")
nt <- dim(t)
#k = 1/72999 # for start at t=1
#k = 1 #for start at t=200
#ts.array <- ncvar_get(tmp.nc, dname, start = c(1, 1, k*72999), count = c(dim(lon), dim(lat), 200*365)) #this file is enormous (e.g., reset memory.size)
ts.array <- ncvar_get(tmp.nc, dname) #this file is enormous (e.g., reset memory.size)
dlname <- ncatt_get(tmp.nc ,dname, "long_name")
dunits <- ncatt_get(tmp.nc, dname, "units")
fillvalue <- ncatt_get(tmp.nc, dname, "_FillValue")
nc_close(tmp.nc)
rm(tmp.nc)
gc()
tmax.r <- list()
nt=56940 #1850 to 2005 CE
for(i in 1:nt){
tmp <- raster(t(ts.array[99:102, 71:67, i]))
extent(tmp) <- c(lon[99], lon[102], lat[67], lat[71])
tmax.r[[i]] <- tmp
}
rm(ts.array)
gc()
TREFHTMX.1850to2005.dailyRast <- list()
n=156
#n=200
for(i in 1:n){
index <- seq(i+364*(i-1), i+364*(i-1)+364, 1)
TREFHTMX.1850to2005.dailyRast[[i+1849]] <- tmax.r[index]
}
#save(tmax.r, file="/media/zizroc/Extra Drive 1/Data/R environments/tmax_for_scaling.Rdata")
rm(tmax.r)
#Saves a list of daily GCM values
# save(TREFHTMX.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em002.Rdata")
# save(TREFHTMX.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em003.Rdata")
# save(TREFHTMX.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em004.Rdata")
save(TREFHTMX.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em005.Rdata")
##
#Minimum temperature
# tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.002.cam.h1.TREFHTMN.18500101-20051231.nc")
# tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.003.cam.h1.TREFHTMN.18500101-20051231.nc")
# tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.004.cam.h1.TREFHTMN.18500101-20051231.nc")
tmp.nc <- nc_open("/media/zizroc/Extra Drive 1/Data/CESM/daily/b.e11.BLMTRC5CN.f19_g16.005.cam.h1.TREFHTMN.18500101-20051231.nc")
dname <- "TREFHTMN"
#Variables
lon <- ncvar_get(tmp.nc, "lon")
nlon <- dim(lon)
lat <- ncvar_get(tmp.nc, "lat")
nlat <- dim(lat)
dat <- ncvar_get(tmp.nc, "date") #current date (YYYMMDD)
ndat <- dim(dat)
t <- ncvar_get(tmp.nc, "time")
tunits <- ncatt_get(tmp.nc, "time", "units")
nt <- dim(t)
#k = 1/72999 # for start at t=1
#k = 1 #for start at t=200
#ts.array <- ncvar_get(tmp.nc, dname, start = c(1, 1, k*72999), count = c(dim(lon), dim(lat), 200*365)) #this file is enormous (e.g., reset memory.size)
ts.array <- ncvar_get(tmp.nc, dname) #this file is enormous (e.g., reset memory.size)
dlname <- ncatt_get(tmp.nc ,dname, "long_name")
dunits <- ncatt_get(tmp.nc, dname, "units")
fillvalue <- ncatt_get(tmp.nc, dname, "_FillValue")
nc_close(tmp.nc)
rm(tmp.nc)
gc()
tmin.r <- list()
nt=56940 #1850 to 2005 CE
for(i in 1:nt){
tmp <- raster(t(ts.array[99:102, 71:67, i]))
extent(tmp) <- c(lon[99], lon[102], lat[67], lat[71])
tmin.r[[i]] <- tmp
}
rm(ts.array)
gc()
TREFHTMN.1850to2005.dailyRast <- list()
n=156
#n=200
for(i in 1:n){
index <- seq(i+364*(i-1), i+364*(i-1)+364, 1)
TREFHTMN.1850to2005.dailyRast[[i+1849]] <- tmin.r[index]
}
rm(tmin.r, dname, index, n, nt, dlname, dunits, fillvalue, i, dat, ndat, nlat, nlon, t, tunits, tmp)
#Saves a list of daily GCM values
# save(TREFHTMN.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em002.Rdata")
# save(TREFHTMN.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em003.Rdata")
# save(TREFHTMN.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em004.Rdata")
save(TREFHTMN.1850to2005.dailyRast, file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em005.Rdata")
gc()
###
#This block loads daily rasters for maximum and minimum reference height temperature from the GCM.
#Load the correct ensemble member.
#CESM ensemble member 002
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em002.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em002.Rdata") #TREFHTMN.1850to2005.dailyRast
#CESM ensemble member 003
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em003.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em003.Rdata") #TREFHTMN.1850to2005.dailyRast
#CESM ensemble member 004
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em004.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em004.Rdata") #TREFHTMN.1850to2005.dailyRast
#CESM ensemble member 005
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em005.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em005.Rdata") #TREFHTMN.1850to2005.dailyRast
###
###
#This block reads in Reanalysis 2 data for bias-correction.
load(file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTemp_1948to2016.Rdata") #air2mtemp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/tmax_for_scaling.Rdata") #tmax.r
gcm.ext <- extent(tmax.r[[1]])
cal.ext <- extent(air2mtemp[[1948]][[1]])
air2mtemp.max <- list()
air2mtemp.min <- list()
air2mtemp.ave <- list()
for(i in 1:58){
tmp.max <- list()
tmp.min <- list()
tmp.ave <- list()
for(j in 1:365){
index <- seq(j+3*(j-1), j+3*(j-1)+3, 1)
tmp.max[[j]] <- max(air2mtemp[[i+1947]][[index]])
tmp.min[[j]] <- min(air2mtemp[[i+1947]][[index]])
tmp.ave[[j]] <- mean(air2mtemp[[i+1947]][[index]])
}
air2mtemp.max[[i+1947]] <- tmp.max
air2mtemp.min[[i+1947]] <- tmp.min
air2mtemp.ave[[i+1947]] <- tmp.ave
rm(tmp.max, tmp.min, tmp.ave)
print(i)
}
rm(air2mtemp, index, i, cal.ext)
save(air2mtemp.max, file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTempMax.Rdata")
save(air2mtemp.min, file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTempMin.Rdata")
save(air2mtemp.ave, file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTempAve.Rdata")
gc()
load(file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTempMax.Rdata")
load(file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTempMin.Rdata")
load(file="/media/zizroc/Extra Drive 1/Data/R environments/air2mTempAve.Rdata")
cal.tmax <- list()
cal.tmin <- list()
cal.tave <- list()
for(i in 1:58){ #Calibration set is over 1948 to 2005 period
for(j in 1:365){
tmp1.max <- air2mtemp.max[[i+1947]][[j]]
tmp1.min <- air2mtemp.min[[i+1947]][[j]]
tmp1.ave <- air2mtemp.ave[[i+1947]][[j]]
tmp2.max <- resample(tmp1.max, TREFHTMX.1850to2005.dailyRast[[i+1849+98]][[j]], method="bilinear")
tmp2.min <- resample(tmp1.min, TREFHTMX.1850to2005.dailyRast[[i+1849+98]][[j]], method="bilinear")
tmp2.ave <- resample(tmp1.ave, TREFHTMX.1850to2005.dailyRast[[i+1849+98]][[j]], method="bilinear")
if(j==1){
tmp3.max <- tmp2.max
tmp3.min <- tmp2.min
tmp3.ave <- tmp2.ave
}
if(j>1) {
tmp3.max <- stack(tmp3.max, tmp2.max)
tmp3.min <- stack(tmp3.min, tmp2.min)
tmp3.ave <- stack(tmp3.ave, tmp2.ave)
}
rm(tmp1.max, tmp1.min, tmp1.ave, tmp2.max, tmp2.min, tmp2.ave)
}
cal.tmax[[i+1947]] <- tmp3.max
cal.tmin[[i+1947]] <- tmp3.min
cal.tave[[i+1947]] <- tmp3.ave
rm(tmp3.max, tmp3.min, tmp3.ave)
print(paste("Calibration data rectified to GCM-scale, for year", i+1947, sep=" "))
}
save(cal.tmax, file="/media/zizroc/Extra Drive 1/Data/R environments/calTmax.Rdata")
save(cal.tmin, file="/media/zizroc/Extra Drive 1/Data/R environments/calTmin.Rdata")
save(cal.tave, file="/media/zizroc/Extra Drive 1/Data/R environments/calTave.Rdata")
rm(air2mtemp.max, air2mtemp.min, air2mtemp.ave)
gc()
###
###
#Block loads Reanalysis 2 data for BC.
load(file="/media/zizroc/Extra Drive 1/Data/R environments/calTmax.Rdata") #cal.tmax
load(file="/media/zizroc/Extra Drive 1/Data/R environments/calTmin.Rdata") #cal.tmin
load(file="/media/zizroc/Extra Drive 1/Data/R environments/calTave.Rdata") #cal.tave
###
###
#Calibration Block
#This makes vectorized GCM and GCM-upscaled Reanalysis 2 data for the quantile mapping algorithm.
# cal.Temp.max <- list()
# cal.Temp.min <- list()
# cal.Temp.ave <- list()
# for(j in 1:58){
# tmp.max <- list()
# tmp.min <- list()
# tmp.ave <- list()
# for(i in 1:365){
# # index <- seq(i+3*(i-1), i+3*(i-1)+3, 1)
# tmp.max[[i]] <- max(cal.Temp[[j+1947]][[i]])
# tmp.min[[i]] <- min(cal.Temp[[j+1947]][[i]])
# tmp.ave[[i]] <- mean(cal.Temp[[j+1947]][[i]])
# }
# cal.Temp.max[[j+1947]] <- tmp.max
# cal.Temp.min[[j+1947]] <- tmp.min
# cal.Temp.ave[[j+1947]] <- tmp.ave
# rm(tmp.max, tmp.min, tmp.ave)
# print(j)
# }
gcm.tmax.bias <- list()
gcm.tmin.bias <- list()
cal.tmax.bias <- list()
cal.tmin.bias <- list()
cal.tave.bias <- list()
for(i in 1:365){
gcm.tmax.m <- matrix(nrow=58, ncol=20)
gcm.tmin.m <- matrix(nrow=58, ncol=20)
cal.tmax.m <- matrix(nrow=58, ncol=20)
cal.tmin.m <- matrix(nrow=58, ncol=20)
cal.tave.m <- matrix(nrow=58, ncol=20)
for(j in 1:58){
gcm.tmax.tmp <- TREFHTMX.1850to2005.dailyRast[[j+1849+98]][[i]]
gcm.tmin.tmp <- TREFHTMN.1850to2005.dailyRast[[j+1849+98]][[i]]
cal.tmax.tmp <- cal.tmax[[j+1947]][[i]]
cal.tmin.tmp <- cal.tmin[[j+1947]][[i]]
cal.tave.tmp <- cal.tave[[j+1947]][[i]]
gcm.tmax.m[j,] <- as.vector(gcm.tmax.tmp)
gcm.tmin.m[j,] <- as.vector(gcm.tmin.tmp)
cal.tmax.m[j,] <- as.vector(cal.tmax.tmp)
cal.tmin.m[j,] <- as.vector(cal.tmin.tmp)
cal.tave.m[j,] <- as.vector(cal.tave.tmp)
}
gcm.tmax.bias[[i]] <- gcm.tmax.m
gcm.tmin.bias[[i]] <- gcm.tmin.m
cal.tmax.bias[[i]] <- cal.tmax.m
cal.tmin.bias[[i]] <- cal.tmin.m
cal.tave.bias[[i]] <- cal.tave.m
rm(gcm.tmax.tmp, gcm.tmin.tmp, cal.tmax.tmp, cal.tmin.tmp, cal.tave.tmp, gcm.tmax.m, gcm.tmin.m, cal.tmax.m, cal.tmin.m, cal.tave.m)
print(paste("GCM and calib bias data for day", i, sep=" "))
}
# save(cal.tmax.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/CALIB_Tmax_1948to2005.Rdata")
# save(cal.tmin.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/CALIB_Tmin_1948to2005.Rdata")
# save(cal.tave.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/CALIB_Tave_1948to2005.Rdata")
# #Ensemble member 002
# save(gcm.tmax.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005_em002.Rdata")
# save(gcm.tmin.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005_em002.Rdata")
# #Ensemble member 003
# save(gcm.tmax.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005_em003.Rdata")
# save(gcm.tmin.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005_em003.Rdata")
# #Ensemble member 004
# save(gcm.tmax.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005_em004.Rdata")
# save(gcm.tmin.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005_em004.Rdata")
#Ensemble member 005
save(gcm.tmax.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005_em005.Rdata")
save(gcm.tmin.bias, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005_em005.Rdata")
gc()
#end calibration block
###
###
#Loads vectorized GCM and GCM-upscaled Reanalysis 2 data for quantile mapping algorithm.
load(file="/media/zizroc/Extra Drive 1/Data/R environments/CALIB_Tmax_1948to2005.Rdata")
load(file="/media/zizroc/Extra Drive 1/Data/R environments/CALIB_Tmin_1948to2005.Rdata")
load(file="/media/zizroc/Extra Drive 1/Data/R environments/CALIB_Tave_1948to2005.Rdata")
# #Ensemble member 002
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005.Rdata")
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005.Rdata")
# #Ensemble member 003
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005_em003.Rdata")
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005_em003.Rdata")
# #Ensemble member 004
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005_em004.Rdata")
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005_em004.Rdata")
#Ensemble member 005
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1948to2005_em005.Rdata")
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1948to2005_em005.Rdata")
###
#Tailor the length of the calibration time-series here
# gcm.tmax.bias_calib <- list()
# gcm.tmin.bias_calib <- list()
# cal.temp.bias_calib <- list()
# for(i in 1:12){
# tmp.tmax <- gcm.tmax.bias[[i]][-c(seq(1,9,1)),] #removes the first decade from calibration set
# tmp.tmin <- gcm.tmin.bias[[i]][-c(seq(1,9,1)),]
# tmp.cali <- cal.temp.bias[[i]][-c(seq(1,9,1)),]
#
# gcm.tmax.bias_calib[[i]] <- tmp.tmax[-c(seq(91,110,1)),] #removes the last 2 decades from calibration set
# gcm.tmin.bias_calib[[i]] <- tmp.tmin[-c(seq(91,110,1)),]
# cal.temp.bias_calib[[i]] <- tmp.cali[-c(seq(91,110,1)),]
# }
#If tailoring of calibration time-series is unnecessary, use the following:
gcm.tmax.bias_calib <- gcm.tmax.bias
gcm.tmin.bias_calib <- gcm.tmin.bias
cal.tave.bias_calib <- cal.tave.bias
###
#Quantile Mapping Block - Temperature
#This rescales GCM data distributions to the ranges and means of observation (Reanalysis 2) data.
library(qmap)
BiasCells.tmax <- list()
BiasCells.tmin <- list()
fitQUANT.tave <- list()
for(i in 1:365){
biasQUANT.tave <- list()
biasCells.tmax <- list()
biasCells.tmin <- list()
for(j in 1:20){
mod.tmax <- gcm.tmax.bias_calib[[i]][,j]-272.15
mod.tmin <- gcm.tmin.bias_calib[[i]][,j]-272.15
mod.tave <- (mod.tmax + mod.tmin)/2
obs.tave <- cal.tave.bias_calib[[i]][,j]-272.15
tmp1 <- fitQmapQUANT(obs.tave, mod.tave, wet.day=FALSE, qstep=0.01)
tmp2a <- doQmapQUANT(mod.tmax, tmp1)
tmp2b <- doQmapQUANT(mod.tmin, tmp1)
biasQUANT.tave[[j]] <- tmp1
biasCells.tmax[[j]] <- tmp2a
biasCells.tmin[[j]] <- tmp2b
rm(tmp1, tmp2a, tmp2b, mod.tmax, mod.tmin, mod.tave, obs.tave)
}
fitQUANT.tave[[i]] <- biasQUANT.tave #Assigned to a list to apply to daily GCM
BiasCells.tmax[[i]] <- biasCells.tmax
BiasCells.tmin[[i]] <- biasCells.tmin
rm(biasCells.tmax, biasCells.tmin, biasQUANT.tave)
}
# #Ensemble member 002
# save(fitQUANT.tave, file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT.Rdata")
# save(BiasCells.tmax, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1948to2005.Rdata")
# save(BiasCells.tmin, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1948to2005.Rdata")
# #Ensemble member 003
# save(fitQUANT.tave, file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT_em003.Rdata")
# save(BiasCells.tmax, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1948to2005_em003.Rdata")
# save(BiasCells.tmin, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1948to2005_em003.Rdata")
# #Ensemble member 004
# save(fitQUANT.tave, file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT_em004.Rdata")
# save(BiasCells.tmax, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1948to2005_em004.Rdata")
# save(BiasCells.tmin, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1948to2005_em004.Rdata")
#Ensemble member 005
save(fitQUANT.tave, file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT_em005.Rdata")
save(BiasCells.tmax, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1948to2005_em005.Rdata")
save(BiasCells.tmin, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1948to2005_em005.Rdata")
#end quantile mapping block - temperature
###
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT.Rdata") #fitQUANT.tave
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT_em003.Rdata") #fitQUANT.tave
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT_em004.Rdata") #fitQUANT.tave
load(file="/media/zizroc/Extra Drive 1/Data/R environments/fitQUANT_em005.Rdata") #fitQUANT.tave
###
#Bias Correction Block
#This bias-corrects the complete time-series.
gcm.tmax.bias.1850to2005 <- list()
gcm.tmin.bias.1850to2005 <- list()
for(i in 1:365){
gcm.tmax.m <- matrix(nrow=156, ncol=20)
gcm.tmin.m <- matrix(nrow=156, ncol=20)
for(j in 1:156){
gcm.tmax.tmp <- TREFHTMX.1850to2005.dailyRast[[j+1849]][[i]]
gcm.tmin.tmp <- TREFHTMN.1850to2005.dailyRast[[j+1849]][[i]]
gcm.tmax.m[j,] <- as.vector(gcm.tmax.tmp)
gcm.tmin.m[j,] <- as.vector(gcm.tmin.tmp)
}
gcm.tmax.bias.1850to2005[[i]] <- gcm.tmax.m
gcm.tmin.bias.1850to2005[[i]] <- gcm.tmin.m
rm(gcm.tmax.tmp, gcm.tmin.tmp)
}
# #Ensemble member 002
# save(gcm.tmax.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1850to2005.Rdata")
# save(gcm.tmin.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1850to2005.Rdata")
# #Ensemble member 003
# save(gcm.tmax.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1850to2005_em003.Rdata")
# save(gcm.tmin.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1850to2005_em003.Rdata")
# #Ensemble member 004
# save(gcm.tmax.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1850to2005_em004.Rdata")
# save(gcm.tmin.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1850to2005_em004.Rdata")
#Ensemble member 005
save(gcm.tmax.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMAX_1850to2005_em005.Rdata")
save(gcm.tmin.bias.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCM_TMIN_1850to2005_em005.Rdata")
rm(gcm.tmax.m, gcm.tmin.m)
gc()
BiasCells.tmax.1850to2005 <- list()
BiasCells.tmin.1850to2005 <- list()
for(i in 1:365){
biasCells.tmax <- list()
biasCells.tmin <- list()
for(j in 1:20){
mod.tmax <- gcm.tmax.bias.1850to2005[[i]][,j]-272.15
mod.tmin <- gcm.tmin.bias.1850to2005[[i]][,j]-272.15
tmp1a <- doQmapQUANT(mod.tmax, fitQUANT.tave[[i]][[j]])
tmp1b <- doQmapQUANT(mod.tmin, fitQUANT.tave[[i]][[j]])
biasCells.tmax[[j]] <- tmp1a
biasCells.tmin[[j]] <- tmp1b
rm(tmp1a, tmp1b, mod.tmax, mod.tmin)
}
BiasCells.tmax.1850to2005[[i]] <- biasCells.tmax
BiasCells.tmin.1850to2005[[i]] <- biasCells.tmin
rm(biasCells.tmax, biasCells.tmin)
}
# #Ensemble member 002
# save(BiasCells.tmax.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1850to2005.Rdata")
# save(BiasCells.tmin.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1850to2005.Rdata")
# #Ensemble member 003
# save(BiasCells.tmax.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1850to2005_em003.Rdata")
# save(BiasCells.tmin.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1850to2005_em003.Rdata")
# #Ensemble member 004
# save(BiasCells.tmax.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1850to2005_em004.Rdata")
# save(BiasCells.tmin.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1850to2005_em004.Rdata")
#Ensemble member 005
save(BiasCells.tmax.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMAX_1850to2005_em005.Rdata")
save(BiasCells.tmin.1850to2005, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMbias_TMIN_1850to2005_em005.Rdata")
#Organise data by day interpolate
GCM.tmax.1850to2005.to_interp <- list()
GCM.tmin.1850to2005.to_interp <- list()
for(i in 1:365){
tmp.tmax <- do.call(cbind, BiasCells.tmax.1850to2005[[i]])
tmp.tmin <- do.call(cbind, BiasCells.tmin.1850to2005[[i]])
rownames(tmp.tmax) <- c(1850:2005)
rownames(tmp.tmin) <- c(1850:2005)
GCM.tmax.1850to2005.to_interp[[i]] <- tmp.tmax
GCM.tmin.1850to2005.to_interp[[i]] <- tmp.tmin
rm(tmp.tmax, tmp.tmin)
}
# #Ensemble member 002
# save(GCM.tmax.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax.Rdata")
# save(GCM.tmin.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin.Rdata")
# #Ensemble member 003
# save(GCM.tmax.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_em003.Rdata")
# save(GCM.tmin.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_em003.Rdata")
# #Ensemble member 004
# save(GCM.tmax.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_em004.Rdata")
# save(GCM.tmin.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_em004.Rdata")
#Ensemble member 005
save(GCM.tmax.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_em005.Rdata")
save(GCM.tmin.1850to2005.to_interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_em005.Rdata")
#Interpolate
xmin = -115
xmax = -107.5
ymin = 35.05263
ymax = 42.63158
xo = seq(xmin, xmax, length.out=45)
yo = seq(ymin, ymax, length.out=46)
d1 <- expand.grid(x = xo, y = yo)
x1 = seq(xmin, xmax, length.out=4)
y1 = seq(ymin, ymax, length.out=5)
d2 <- expand.grid(x = x1, y = y1)
load(file="/media/zizroc/Extra Drive 1/Data/R environments/tmpXYZ.Rdata") #tmp.xyz
# tmp.xyz <- rasterToPoints(TREFHTMX.1850to2005.dailyRast[[1850]][[1]])
# save(tmp.xyz, file="/media/zizroc/Extra Drive 1/Data/R environments/tmpXYZ.Rdata")
##
# #Loads GCM data
# #Ensemble member 002
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax.Rdata") #GCM.tmax.1850to2005.to_interp
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin.Rdata") #GCM.tmin.1850to2005.to_interp
# #Ensemble member 003
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_003.Rdata") #GCM.tmax.1850to2005.to_interp
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_003.Rdata") #GCM.tmin.1850to2005.to_interp
# #Ensemble member 004
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_004.Rdata") #GCM.tmax.1850to2005.to_interp
# load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_004.Rdata") #GCM.tmin.1850to2005.to_interp
#Ensemble member 005
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_005.Rdata") #GCM.tmax.1850to2005.to_interp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_005.Rdata") #GCM.tmin.1850to2005.to_interp
##
library(akimia)
GCM.tmax.1850to2005.Interp <- list()
for(j in 1:365){
Tmp <- list()
for(i in 1:156){
# tmp.ak <- interp(tmp.xyz[,1]-360, tmp.xyz[,2], GCM.tmax.1850to2005.to_interp[[j]][i,], xo=seq(min(d1[,1]), max(d1[,1]), length=45), yo=seq(min(d1[,2]), max(d1[,2]), length=46), linear=TRUE)
tmp.ak <- interp(d2[,1], d2[,2], GCM.tmax.1850to2005.to_interp[[j]][i,], xo=seq(min(d1[,1]), max(d1[,1]), length=45), yo=seq(min(d1[,2]), max(d1[,2]), length=46), linear=TRUE)
tmp.ak.ras <- raster(tmp.ak)
Tmp[[i]] <- tmp.ak.ras
}
GCM.tmax.1850to2005.Interp[[j]] <- Tmp
rm(Tmp, tmp.ak, tmp.ak.ras)
print(paste("Chug, chug GCM.tmax: need 365 and I'm at", j, sep=" "))
}
# #Ensemble member 002
# save(GCM.tmax.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMAX.Rdata")
# #Ensemble member 003
# save(GCM.tmax.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMAX_em003.Rdata")
# #Ensemble member 004
# save(GCM.tmax.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMAX_em004.Rdata")
#Ensemble member 005
save(GCM.tmax.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMAX_em005.Rdata")
rm(GCM.tmax.1850to2005.to_interp, GCM.tmax.1850to2005.Interp)
gc()
GCM.tmin.1850to2005.Interp <- list()
for(j in 1:365){
Tmp <- list()
for(i in 1:156){
# tmp.ak <- interp(tmp.xyz[,1]-360, tmp.xyz[,2], GCM.tmin.1850to2005.to_interp[[j]][i,], xo=seq(min(d1[,1]), max(d1[,1]), length=45), yo=seq(min(d1[,2]), max(d1[,2]), length=46), linear=TRUE)
tmp.ak <- interp(d2[,1], d2[,2], GCM.tmin.1850to2005.to_interp[[j]][i,], xo=seq(min(d1[,1]), max(d1[,1]), length=45), yo=seq(min(d1[,2]), max(d1[,2]), length=46), linear=TRUE)
tmp.ak.ras <- raster(tmp.ak)
Tmp[[i]] <- tmp.ak.ras
}
GCM.tmin.1850to2005.Interp[[j]] <- Tmp
rm(Tmp, tmp.ak, tmp.ak.ras)
print(paste("Chug, chug GCM.tmin: need 365 and I'm at", j, sep=" "))
}
# #Ensemble member 002
# save(GCM.tmin.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMIN.Rdata")
# #Ensemble member 003
# save(GCM.tmin.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMIN_em003.Rdata")
# #Ensemble member 004
# save(GCM.tmin.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMIN_em004.Rdata")
#Ensemble member 005
save(GCM.tmin.1850to2005.Interp, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMIN_em005.Rdata")
rm(GCM.tmin.1850to2005.to_interp, GCM.tmin.1850to2005.Interp)
gc()
#end bias-correction block
###
###
#PRISM Block
#Uses PRISM station-based interpolated regression model data for spatial downscaling.
###
xmin = -115
xmax = -107.5
ymin = 35.05263
ymax = 42.63158
prism.ext <- raster()
extent(prism.ext) <- c(xmin, xmax, ymin, ymax)
#The following re-writes PRISM data without aggregating it to GCM-scale
tmax.dir <- dir("/media/zizroc/My Passport/Data/PRISMdata/recent_daily/tmax", full.names=TRUE)
tmin.dir <- dir("/media/zizroc/My Passport/Data/PRISMdata/recent_daily/tmin", full.names=TRUE)
prec.dir <- dir("/media/zizroc/My Passport/Data/PRISMdata/recent_daily/ppt", full.names=TRUE)
pris.ppt <- list()
pris.max.TS <- list()
pris.min.TS <- list()
pris.mean.TS <- list()
difference <- list()
for(i in 1:25){ #from 1981 to 2005 CE
#maximum daily temperatures
bilfiles <- dir(tmax.dir[i], pattern="bil.bil", ignore.case=FALSE, full.name=TRUE)
auxfiles <- dir(tmax.dir[i], pattern="bil.aux", ignore.case=FALSE, full.name=TRUE)
pris.tmax <- bilfiles[!bilfiles %in% auxfiles] #only BIL files
rm(bilfiles, auxfiles)
#minimum daily temperatures
bilfiles <- dir(tmin.dir[i], pattern="bil.bil", ignore.case=FALSE, full.name=TRUE)
auxfiles <- dir(tmin.dir[i], pattern="bil.aux", ignore.case=FALSE, full.name=TRUE)
pris.tmin <- bilfiles[!bilfiles %in% auxfiles] #only BIL files
rm(bilfiles, auxfiles)
# #daily precipitation
# bilfiles <- dir(prec.dir[i], pattern="bil.bil", ignore.case=FALSE, full.name=TRUE)
# auxfiles <- dir(prec.dir[i], pattern="bil.aux", ignore.case=FALSE, full.name=TRUE)
# pris.tmp <- bilfiles[!bilfiles %in% auxfiles] #only BIL files
# rm(bilfiles, auxfiles)
tmp3 <- list()
for(j in 1:365){
tmp1 <- raster(pris.tmax[j])
tmp2 <- crop(tmp1, prism.ext)
tmp3[[j]] <- tmp2
rm(tmp1, tmp2)
}
pris.max.TS[[i]] <- tmp3
rm(tmp3)
tmp3 <- list()
for(j in 1:365){
tmp1 <- raster(pris.tmin[j])
tmp2 <- crop(tmp1, prism.ext)
tmp3[[j]] <- tmp2
rm(tmp1, tmp2)
}
pris.min.TS[[i]] <- tmp3
rm(tmp3)
# pris.mean.TS[[i]] <- (pris.min.TS[[i]] + pris.max.TS[[i]])/2
# difference[[i]] <- pris.max.TS[[i]] - pris.min.TS[[i]]
# for(j in 1:length(pris.tmp)){
# #for(j in 1:1440){
# tmp1 <- raster(pris.tmp[j])
# tmp2 <- crop(tmp1, prism.ext)
# if(j==1){tmp3 <- tmp2}
# if(j>1) {tmp3 <- stack(tmp3, tmp2)}
# rm(tmp1, tmp2)
# }
# pris.ppt[[i]] <- tmp3
# rm(tmp3)
print(paste("PRISM data for year", i+1980, sep=" "))
}
rm(tmax.dir, tmin.dir)
save(pris.max.TS, file="/media/zizroc/Extra Drive 1/Data/R environments/tmaxTS_IIASA.Rdata")
save(pris.min.TS, file="/media/zizroc/Extra Drive 1/Data/R environments/tminTS_IIASA.Rdata")
# save(difference, file="/media/zizroc/Extra Drive 1/Data/R environments/difference.Rdata")
# save(pris.ppt, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISMppt_daily.Rdata")
gc()
####
################################
## Normalisation sub-block ##
################################
#
pris.ave.TS <- list()
pris.dif.TS <- list()
for(i in 1:25){
for(j in 1:365){
pris.ave.TS[[j+(i-1)*364]] <- mean(pris.max.TS[[i]][[j]], pris.min.TS[[i]][[j]])
pris.dif.TS[[j+(i-1)*364]] <- pris.max.TS[[i]][[j]] - pris.min.TS[[i]][[j]]
}
print(i)
}
save(pris.ave.TS, file="/media/zizroc/Extra Drive 1/Data/R environments/TSmean.Rdata")
save(pris.dif.TS, file="/media/zizroc/Extra Drive 1/Data/R environments/TSdiff.Rdata")
#This is the mean PRISM data for each of 365 days over normalisation period (1981-2005 CE)
pris.max.sampl <- list()
pris.min.sampl <- list()
pris.ave.sampl <- list()
pris.dif.sampl <- list()
for(i in 1:365){
tmp.pris.max.sampl <- list()
tmp.pris.min.sampl <- list()
tmp.pris.ave.sampl <- list()
tmp.pris.dif.sampl <- list()
for(j in 1:25){
tmp.pris.max.sampl[[j]] <- pris.max.TS[[j]][[i]]
tmp.pris.min.sampl[[j]] <- pris.min.TS[[j]][[i]]
tmp.pris.ave.sampl[[j]] <- mean(pris.max.TS[[j]][[i]], pris.min.TS[[j]][[i]])
tmp.pris.dif.sampl[[j]] <- pris.max.TS[[j]][[i]] - pris.min.TS[[j]][[i]]
}
pris.max.sampl[[i]] <- tmp.pris.max.sampl
pris.min.sampl[[i]] <- tmp.pris.min.sampl
pris.ave.sampl[[i]] <- tmp.pris.ave.sampl
pris.dif.sampl[[i]] <- tmp.pris.dif.sampl
rm(tmp.pris.max.sampl, tmp.pris.min.sampl, tmp.pris.ave.sampl, tmp.pris.dif.sampl)
print(i)
}
save(pris.max.sampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISmaxSampl.Rdata")
save(pris.min.sampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISminSampl.Rdata")
save(pris.ave.sampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISaveSampl.Rdata")
save(pris.dif.sampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISdifSampl.Rdata")
gc()
###
###
#Loads PRISM data.
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISmaxSampl.Rdata") #pris.max.sampl
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISminSampl.Rdata") #pris.min.sampl
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISaveSampl.Rdata") #pris.ave.sampl
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISdifSampl.Rdata") #pris.dif.sampl
###
#Makes stacks of PRISM rasters for each temperature case from which to randomly draw samples.
#Randomly pull days from each of the 25 years.
pris.max.sampl.day <- list() #single raster for each of 25 years for each of 365 days
pris.min.sampl.day <- list()
pris.ave.sampl.day <- list()
pris.dif.sampl.day <- list()
pris.max.sampl.stk <- list() #raster stack containing all rasters for 25 years for each of 365 days
pris.min.sampl.stk <- list()
pris.ave.sampl.stk <- list()
pris.dif.sampl.stk <- list()
for(i in 1:365){
j = sample(c(1:25), 1) #random sample from 1:25 years generated
pris.max.sampl.day[[i]] <- pris.max.sampl[[i]][[j]]
pris.min.sampl.day[[i]] <- pris.min.sampl[[i]][[j]]
pris.ave.sampl.day[[i]] <- pris.ave.sampl[[i]][[j]]
pris.dif.sampl.day[[i]] <- pris.dif.sampl[[i]][[j]]
pris.max.sampl.stk[[i]] <- stack(pris.max.sampl[[i]])
pris.min.sampl.stk[[i]] <- stack(pris.min.sampl[[i]])
pris.ave.sampl.stk[[i]] <- stack(pris.ave.sampl[[i]])
pris.dif.sampl.stk[[i]] <- stack(pris.dif.sampl[[i]])
print(i)
}
pr.max <- list()
pr.min <- list()
pr.ave <- list()
pr.dif <- list()
for(i in 1:365){
pr.max[[i]] <- mean(pris.max.sampl.stk[[i]])
pr.min[[i]] <- mean(pris.min.sampl.stk[[i]])
pr.ave[[i]] <- mean(pris.ave.sampl.stk[[i]])
pr.dif[[i]] <- mean(pris.dif.sampl.stk[[i]])
}
save(pr.max, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_tmaxStack.Rdata")
save(pr.min, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_tminStack.Rdata")
save(pr.ave, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_taveStack.Rdata")
save(pr.dif, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_tdifStack.Rdata")
rm(pr.max, pr.min, pris.max.sampl.stk, pris.min.sampl.stk, pris.ave.sampl.stk, pris.dif.sampl.stk, pris.max.sampl.day, pris.min.sampl.day, pris.ave.sampl.day, pris.dif.sampl.day, pris.max.sampl, pris.min.sampl, pris.ave.sampl, pris.dif.sampl)
#Dump excess memory
xmin = -115
xmax = -107.5
ymin = 35.05263
ymax = 42.63158
prism.ext <- raster()
extent(prism.ext) <- c(xmin, xmax, ymin, ymax)
#The following re-writes PRISM data without aggregating it to GCM-scale
tmax.dir <- dir("/media/zizroc/My Passport/Data/PRISMdata/recent_daily/tmax", full.names=TRUE)
tmin.dir <- dir("/media/zizroc/My Passport/Data/PRISMdata/recent_daily/tmin", full.names=TRUE)
pris.tmax <- list()
pris.tmin <- list()
for(i in 1:34){ #from 1981 to 2014 CE
#daily maximum temperature
bilfiles <- dir(tmax.dir[i], pattern="bil.bil", ignore.case=FALSE, full.name=TRUE)
auxfiles <- dir(tmax.dir[i], pattern="bil.aux", ignore.case=FALSE, full.name=TRUE)
tmp.tmax <- bilfiles[!bilfiles %in% auxfiles] #only BIL files
rm(bilfiles, auxfiles)
#daily minimum temperature
bilfiles <- dir(tmin.dir[i], pattern="bil.bil", ignore.case=FALSE, full.name=TRUE)
auxfiles <- dir(tmin.dir[i], pattern="bil.aux", ignore.case=FALSE, full.name=TRUE)
tmp.tmin <- bilfiles[!bilfiles %in% auxfiles] #only BIL files
rm(bilfiles, auxfiles)
for(j in 1:365){
tmp1 <- raster(tmp.tmax[j])
tmp2 <- crop(tmp1, prism.ext)
if(j==1){tmp3 <- tmp2}
if(j>1) {tmp3 <- stack(tmp3, tmp2)}
rm(tmp1, tmp2)
}
pris.tmax[[i+1980]] <- tmp3
rm(tmp3)
print(paste("Building PRISM TMAX data for SD. It's", sep=" ", Sys.time(), "and I'm processing year", i+1980, "/ 2014."))
for(j in 1:365){
tmp1 <- raster(tmp.tmin[j])
tmp2 <- crop(tmp1, prism.ext)
if(j==1){tmp3 <- tmp2}
if(j>1) {tmp3 <- stack(tmp3, tmp2)}
rm(tmp1, tmp2)
}
pris.tmin[[i+1980]] <- tmp3
rm(tmp3)
print(paste("Building PRISM TMIN data for SD. It's", sep=" ", Sys.time(), "and I'm processing year", i+1980, "/ 2014."))
}
rm(prec.dir)
save(pris.tmax, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISMtmax_IIASA.Rdata")
save(pris.tmin, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISMtmin_IIASA.Rdata")
gc()
################################
## PRISM resampling sub-block ##
################################
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISMtmax_IIASA.Rdata") #pris.tmax
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISMtmin_IIASA.Rdata") #pris.tmin
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax.Rdata") #GCM.tmax.1850to2005.to_interp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005.Rdata") #TREFHTMN.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin.Rdata") #GCM.tmin.1850to2005.to_interp
#Ensemble member 003
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em003.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_003.Rdata") #GCM.tmax.1850to2005.to_interp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em003.Rdata") #TREFHTMN.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_003.Rdata") #GCM.tmin.1850to2005.to_interp
#Ensemble member 004
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em004.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmax_em004.Rdata") #GCM.tmax.1850to2005.to_interp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em004.Rdata") #TREFHTMN.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcalDay_tmin_em004.Rdata") #GCM.tmin.1850to2005.to_interp
#Create a library of GCM-scaled PRISM raster data
gcm.ext <- extent(TREFHTMX.1850to2005.dailyRast[[1950]][[180]])
tmp.mod <- TREFHTMX.1850to2005.dailyRast[[1950]][[180]]
mod.ext <- c(xmin(gcm.ext)-360, xmax(gcm.ext)-360, ymin(gcm.ext), ymax(gcm.ext))
extent(tmp.mod) <- mod.ext
values(tmp.mod) <- NA
pris.tmax.resampl <- list()
pris.tmin.resampl <- list()
for(i in 1:34){
tmp <- list()
for(j in 1:365){
tmp.obs <- pris.tmax[[i+1980]][[j]]
tmp[[j]] <- resample(tmp.obs, tmp.mod, method="bilinear")
rm(tmp.obs)
}
pris.tmax.resampl[[i+1980]] <- tmp
rm(tmp)
tmp <- list()
for(j in 1:365){
tmp.obs <- pris.tmin[[i+1980]][[j]]
tmp[[j]] <- resample(tmp.obs, tmp.mod, method="bilinear")
rm(tmp.obs)
}
pris.tmin.resampl[[i+1980]] <- tmp
rm(tmp)
print(paste("Building resampled PRISM tmax and tmin lists. It's", sep=" ", Sys.time(), "and I'm processing year", i+1980, "/ 2014."))
}
save(pris.tmax.resampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMAX_1981to2005.Rdata")
save(pris.tmin.resampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMIN_1981to2005.Rdata")
#Ensemble member 003
save(pris.tmax.resampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMAX_1981to2005_em003.Rdata")
save(pris.tmin.resampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMIN_1981to2005_em003.Rdata")
#Ensemble member 004
save(pris.tmax.resampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMAX_1981to2005_em004.Rdata")
save(pris.tmin.resampl, file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMIN_1981to2005_em004.Rdata")
###
#Pattern Selector Block
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMAX_1981to2005.Rdata") #pris.tmax.resampl
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_resampledTMIN_1981to2005.Rdata") #pris.tmin.resampl
library(hydroGOF)
#This selects for the PRISM temp raster whose difference from the GCM raster is a minimum. This PRISM raster is then used as the most similar precipiation distribution to the GCM.
norm <- function(x) sqrt(sum(x^2))
GCM.PRISM.tmax.matches <- list()
for(i in 1:365){
for(j in 1:156){
Tmp <- data.frame()
for(k in 1:34){
tmp.obs <- as.vector(pris.tmax.resampl[[k+1980]][[i]])
tmp.mod <- GCM.tmax.1850to2005.to_interp[[i]][j,]
tmp.cor <- cor(tmp.mod, tmp.obs)
tmp.rms <- rmse(tmp.mod, tmp.obs)
if(is.na(tmp.cor) == TRUE){tmp.cor <- 0}
tmp.all <- cbind(tmp.cor, tmp.rms, k+1980, j+1849, i)
if(k==1){Tmp <- tmp.all}
if(k >1){Tmp <- rbind(Tmp, tmp.all)}
rm(tmp.obs, tmp.mod, tmp.cor, tmp.rms, tmp.all)
}
Tmp <- as.data.frame(Tmp)
names(Tmp) <- c("PEARSON_CORR", "RMSE", "PRISM.YEAR", "GCM.YEAR", "DAY")
Tmp.max <- Tmp[which.max(Tmp[,1]),]
if(Tmp.max[,1] == 0) {Tmp.max <- Tmp[which.min(Tmp[,2]),]} #If the correlation test does not apply, select the row with the lowest RMSE.
if(j==1){TMP.max <- Tmp.max}
if(j >1){TMP.max <- rbind(TMP.max, Tmp.max)}
rm(Tmp.max)
}
GCM.PRISM.tmax.matches[[i]] <- TMP.max
print(paste("Finding similar rasters to GCM. It's", sep=" ", Sys.time(), "and I'm processing day", i, "/ 365."))
rm(TMP.max)
}
save(GCM.PRISM.tmax.matches, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMandPRISMmatchesTMAX.Rdata")
save(GCM.PRISM.tmax.matches, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMandPRISMmatchesTMAX_em003.Rdata")
save(GCM.PRISM.tmax.matches, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMandPRISMmatchesTMAX_em004.Rdata")
GCM.PRISM.tmin.matches <- list()
for(i in 1:365){
for(j in 1:156){
Tmp <- data.frame()
for(k in 1:34){
tmp.obs <- as.vector(pris.tmin.resampl[[k+1980]][[i]])
tmp.mod <- GCM.tmin.1850to2005.to_interp[[i]][j,]
tmp.cor <- cor(tmp.mod, tmp.obs)
tmp.rms <- rmse(tmp.mod, tmp.obs)
if(is.na(tmp.cor) == TRUE){tmp.cor <- 0}
tmp.all <- cbind(tmp.cor, tmp.rms, k+1980, j+1849, i)
if(k==1){Tmp <- tmp.all}
if(k >1){Tmp <- rbind(Tmp, tmp.all)}
rm(tmp.obs, tmp.mod, tmp.cor, tmp.rms, tmp.all)
}
Tmp <- as.data.frame(Tmp)
names(Tmp) <- c("PEARSON_CORR", "RMSE", "PRISM.YEAR", "GCM.YEAR", "DAY")
Tmp.max <- Tmp[which.max(Tmp[,1]),]
if(Tmp.max[,1] == 0) {Tmp.max <- Tmp[which.min(Tmp[,2]),]} #If the correlation test does not apply, select the row with the lowest RMSE.
if(j==1){TMP.max <- Tmp.max}
if(j >1){TMP.max <- rbind(TMP.max, Tmp.max)}
rm(Tmp.max)
}
GCM.PRISM.tmin.matches[[i]] <- TMP.max
print(paste("Finding similar rasters to GCM. It's", sep=" ", Sys.time(), "and I'm processing day", i, "/ 365."))
rm(TMP.max)
}
save(GCM.PRISM.tmin.matches, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMandPRISMmatchesTMIN.Rdata")
save(GCM.PRISM.tmin.matches, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMandPRISMmatchesTMIN_em003.Rdata")
save(GCM.PRISM.tmin.matches, file="/media/zizroc/Extra Drive 1/Data/R environments/GCMandPRISMmatchesTMIN_em004.Rdata")
#end pattern selector block
###
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005.Rdata") #TREFHTMN.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em003.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em003.Rdata") #TREFHTMN.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMX_1850to2005_em004.Rdata") #TREFHTMX.1850to2005.dailyRast
load(file="/media/zizroc/Extra Drive 1/Data/R environments/TREFHTMN_1850to2005_em004.Rdata") #TREFHTMN.1850to2005.dailyRast
###
#Temperature Block
#Makes PRISM-scale max and min temperature bounds from the GCM; i.e., BCSD CESM for TREFHTMX and TREFHTMN.
library(raster)
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_tmaxStack.Rdata") #pr.max
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_tminStack.Rdata") #pr.min
load(file="/media/zizroc/Extra Drive 1/Data/R environments/PRISM_tdifStack.Rdata") #pr.dif
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMAX.Rdata") #GCM.tmin.1850to2005.Interp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMIN.Rdata") #GCM.tmin.1850to2005.Interp
#Ensemble member 003
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMAX_em003.Rdata") #GCM.tmin.1850to2005.Interp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMIN_em003.Rdata") #GCM.tmin.1850to2005.Interp
#Ensemble member 004
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMAX_em004.Rdata") #GCM.tmin.1850to2005.Interp
load(file="/media/zizroc/Extra Drive 1/Data/R environments/GCMcorrByDays_TMIN_em004.Rdata") #GCM.tmin.1850to2005.Interp
#GCM.tmax.1850to2005 <- list()
GCM.tmin.1850to2005 <- list()
for(i in 1:156){
#Tmp.max <- list()
Tmp.min <- list()
for(j in 1:365){
tmp.max <- resample(GCM.tmax.1850to2005.Interp[[j]][[i]], pr.max[[j]], method="bilinear")
tmp.min <- resample(GCM.tmin.1850to2005.Interp[[j]][[i]], pr.min[[j]], method="bilinear")
tmp.av1 <- (tmp.max + tmp.min)/2