Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 3
Articles | Volume 16, issue 3
https://doi.org/10.5194/gmd-16-1083-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-1083-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 3
Development and technical paper
 | 
10 Feb 2023
Development and technical paper |  | 10 Feb 2023

Optimization of weather forecasting for cloud cover over the European domain using the meteorological component of the Ensemble for Stochastic Integration of Atmospheric Simulations version 1.0

Yen-Sen Lu, Garrett H. Good, and Hendrik Elbern

Supplement

https://doi.org/10.5194/gmd-16-1083-2023-supplement

Data sets

CM SAF ClOud Fractional Cover dataset from METeosat First and Second Generation - Edition 1 (COMET Ed. 1) R. Stöckli, A. Duguay-Tetzlaff, J. Bojanowski, R. Hollmann, P. Fuchs, and M. Werscheck https://doi.org/10.5676/EUM_SAF_CM/CFC_METEOSAT/V001

ECMWF Reanalysis v5 (ERA5) ECMWF https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5

Model code and software

Meteorological component of the Ensemble for Stochastic Integration of Atmospheric Simulations version 1.0 Yen-Sen Lu and Hendrik Elbern https://doi.org/10.5281/zenodo.6637315

hydrogencl/WRF_TOOLS: V0.9.0 (v0.9.0) Y.-S. Lu https://doi.org/10.5281/zenodo.7603301

hydrogencl/SciTool_Py: v0.9.0 (v0.9.0) Y.-S. Lu https://doi.org/10.5281/zenodo.7603323

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Short summary
The Weather Forecasting and Research (WRF) model consists of many parameters and options that can be adapted to different conditions. This expansive sensitivity study uses a large-scale simulation system to determine the most suitable options for predicting cloud cover in Europe for deterministic and probabilistic weather predictions for day-ahead forecasting simulations.
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