How I’ve Been Processing Climate Data

From a THREDDS server, I’m using the NetcdfSubset portal to obtain a spatial subset of my climate data set of interest. Since the files I need are too big to download from their HTTP server, they instead give me an OPeNDAP URI with the spatial subset info. I then pass that to nccopy from the NetCDF library.

Then, I installed CDO and wrote a script to do the monthly means for all the files: it averages a daily time step file into a monthly averaged (or whatever metric you choose) file.

cdo monmean foo_hourly_or_daily.nc  foo_monthly_mean.nc

Then, I installed nco to flip the axes.

ncpdq -a lat,lon in.nc out.nc

Then, I imported the correctly-oriented files into R.

rm(list = ls())
library(raster)
library(rgdal)
library(ncdf4)
setwd("wherever your files are")
climate <- brick("filename.nc",varname="whatever your climate variable is")

In my case, as I think is common for climate files, longitude was on a 0-360 scale, instead of -180/180.