I have a number of coordinates (roughly 20000) for which I need to extract data from a number of NetCDF files each comes roughly with 30000 timesteps (future climate scenarios). Using the solution here is not efficient and the reason is the time spent at each i,j to convert “dsloc” to “dataframe” (look at the code below). ** an example
Tag: cdo-climate
how to spatialy aggregate netcdf fields in python, CDO, or NCO?
I want to regrid population data from 0.05 degrees to 0.1 degrees. Because it is population, I should aggregate (sum) population values for resampling data to a coarser resolution. Although I thought that there going to be a simple answer to this question, I did find any yet. I think my question does not need sample data, but you may
Average a Month’s worth of NetCDF data to one 24hr-day to give the mean diurnal cycle
I hope you’re well — I have multiple files all having one month of hourly data. Below shows the dimensions I want to average each individual files in a way to calculate the hourly average to get the diurnal cycle for each month with array shape (time, lon, lat) of 24 steps. Answer
Change resolution of half-degree netCDF to quarter degree netCDF using nco tools
I can change the resolution of a netCDF file to a coarser one by doing something like this: How do I go the other way? I.e. change resolution of coarser scale netCDF to finer scale? Answer Increasing resolution with NCO requires regridding, available in NCO 4.5.1+. This currently requires you have a SCRIP/ESMF-compliant mapfile, which can be generated from SCRIP-compliant