david-rayner-gvc / pet_forecast

Create physiological equivalent temperature (PET) forecasts from opendata.dwd.de NWP.

pet_forecast

Create physiological equivalent temperature (PET) forecasts from opendata.dwd.de NWP.

Installation: Not really documented.

• To update the online data you will need to be able to make git push to https://github.com/David-Rayner-GVC/pet_data using ssh. GitPython
• need cdo Climate Data Operators, with eccodes and netcdf4, obviously.
• Python modules netcdf4, GitPython, matplotlib, cdo. Plus xarray, lxml, everything else pretty standard.
• https://github.com/biglimp/PETCalculatorWEB - what, this is not public???
• modify config_RENAME_ME.py to represent your local setup

The script full_workflow:

• download and pre-process NWP files to local netcdf, one file for each variable.
• extract (and publish to GIT) forecast-time-series for a particular locations, based on pet_json
• stash the forecasts in local netcdf files, one per location, for future analysis.

If you just want to retrieve a file from pet_json, use pet_git_integration_lib.RetrieveForecast. You'll need gitpython, but you don't need any authentication.

To-Do

• No checks whether local grid files are up-to-date, they are just downloaded. This can break things if a new forecast is being written (see below)
• no optimization of the time-series extraction, it is just a loop over locations. So the netcdf files are opened/closed/re-opened many times. But hey, that is what file-system caching is for, and it seems to run fast enough.

Things that can go wrong:

• if the download starts before DWD has finished writing out the files for a new forecast, the script will fail with a warning about non-unique time-series. To minimize problems, the script is run at UTC+2 times:

local times for long runs: 6, 12, 18, 24 local times for short runs: 2,8,14,20

(As these are local time, the UTC+ varies with day-light savings)

pet_forecast's Issues

Question about PET calculation

Dear Rayner,
I have read your PET forecast program and i have a question about PET calculation.
There is a module called "petprocessingprognose" in pet_extraction_lib.py file, but i can't find any further information about that module, and it seems to have a lot to do with PET computing.
So where i can get the detail about "petprocessingprognose"?

Thanks