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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.

Used as back-up registry!

unit, parameter and method mapping tables for marine-data.de/?site=viewer, following https://spaces.awi.de/x/RhAUFg and querries for pangaea

User interface of the UFZ TSM