no code implementations • 7 Jul 2014 • Tanja Zerenner, Victor Venema, Petra Friederichs, Clemens Simmer
We apply multi-objective Genetic Programming (GP) to a training data set of high-resolution atmospheric model runs to learn equations or short programs that reconstruct the fine-scale fields (e. g., 400 m resolution) of the near-surface atmospheric state variables from the coarse atmospheric model output (e. g., 2. 8 km resolution).
