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The Linear Meta-Model optimization (LiMMo) is a Python-tool designed for the objective tuning of regional climate models (RCM) and numerical weather prediction models (NWPM) to gridded observational datasets.

In this approach, the surface 2D output of the RCM/NWPM is approximated using regression method (linear, piecewise-linear, quadratic). A user-defined error norm, which quantifies the difference between the regression approximation and the observations, is then minimized using a gradient-based optimization method.

Base docker container for usage in RODARE tests.

Analysis of HMC Data Professionals Survey 2024

Change repository path since the name of the project changed

Example project used in this workshop. It is an adapted version from another workshop. The original project can be found here.