Downscaling

climatologies.R

This script generates monthly climatologies geotiffs. climatologies.R uses the original annual geotiffs to produce climatologies for each month. An arbitrary climatology period may be specified. Common periods include 1961-1990, 1971-2000, and 1958-2001. Periods are chosen based on the climatology period of an alternate higher-resolution data set to which the data here will eventually be downscaled. Climatology geotiffs are created for the climate variables temperature and precipitation, and in some cases sea level pressure. Each mutli-band geotiff contains twelve monthly bands.

climatologies.R is the first preparatory script run as part of the overall downscaling process chain, although climatologies are often used for other unrelated projects as well.

R code

library(raster)
library(parallel)

# Source functions
path.fun <- file.path("/workspace/UA/mfleonawicz/projects/Downscaling/code")
source(file.path(path.fun, "climPrep.R"))
source(file.path(path.fun, "climCalc.R"))

#### Choose datasets (current options: 'cru30' 'cru31' 'cru3101' 'cru322'
#### 'ERA40' 'AR4gcm' 'AR5gcm') #### Note cru3101 will still place
#### precipitation outputs into in a 'CRU31' folder.
dataset <- "cru322"

#### Set year ranges for reference climatology period ####
yrs.clim <- c(1961, 1990)

#### Top level climatology directory ####
dir.create(newDir <- file.path("/Data/Base_Data/Climate/World/Climatologies"), 
    showWarnings = F)

#### Set to TRUE is resampling outputs to a new grid and specify any raster
#### layer as the new grid ####
resample <- F
if (resample) r <- raster(file.path(drive[3], "/Base_Data/Climate/World/ERA40/ERA40_historical_monthly_195709-200208.nc"), 
    varname = "t2m", layer = 1)

dp <- climPrep(dataset, yrs.clim, include.psl = F)  # add include.psl=T if psl is to be included. Only available for ERA40 and historical GCMs.
for (i in 1:length(dp)) assign(names(dp)[i], dp[[i]])
for (k in 1:length(mainDir)) mclapply(1:length(files[[k]]), climCalc, yr1 = yrs.clim[1], 
    yr2 = yrs.clim[2], var = varid[k], scen = scen[k], datID = datID, arID = arID, 
    pq = c(0.01, 0.99), tq = c(0.01, 0.99), setNAs = 0.5, interpNAs = T, mc.cores = length(files[[k]]))