Home

Gridpp a is a tool for performing statistical post-processing of 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 (deterministic or ensemble)
• 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
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.