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Gridpp is a software package to post-process gridded weather forecasts. It consists of a library of commonly-used post-processing methods and a command-line tool that applies these methods to forecast fields in NetCDF files.

Gridpp is written in C++ but offers python bindings to the functions in the library. The tool is used at MET Norway to produce operational weather forecasts for Yr (https://www.yr.no).

Features

• Methods for downscaling a forecast from a coarse grid to a fine grid, such as bilinear or nearest neighbour methods.
• Methods for calibrating a downscaled grid, such as quantile mapping.
• Computationally efficient neighbourhood methods to compute neighbourhood min, mean, max, and any quantile.
• Functions for diagnosing variables, such as relative humidity from temperature and dewpoint temperature.
• Data assimilation methods such as optimal interpolation (OI) to merge observations and gridded forecasts
• Efficient data structures for nearest location lookup in a vector or grid of locations

This wiki includes documentation and examples of how to use the python interface to the gridpp library and the gridpp command-line tool.

API reference

The reference for available functions in the gridpp API is found here.

News

Date	News
Jan 25, 2024	[Version 0.7.0]](https://github.com/metno/gridpp/releases/tag/v0.7.0) released
Oct 14, 2022	Version 0.6.0 released
Nov 9, 2020	Version 0.5.0 released
June 19, 2020	Documentation in this wiki is significantly updated
June 15, 2020	A prototype version of gridpp library v0.4.2 is available.
April 9, 2020	Gridpp is being restructured to offer an API to its core functions.