Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-1091-2024
https://doi.org/10.5194/gmd-17-1091-2024
Methods for assessment of models
 | 
09 Feb 2024
Methods for assessment of models |  | 09 Feb 2024

Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME

Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac

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Cited articles

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Ackerman, S. A., Holz, R., Frey, R., Eloranta, E., Maddux, B., and McGill, M.: Cloud detection with MODIS. Part II: validation, J. Atmos. Ocean. Tech., 25, 1073–1086, 2008. a
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Amodei, M. and Stein, J.: Deterministic and fuzzy verification methods for a hierarchy of numerical models, Meteorol. Appl., 16, 191–203, https://doi.org/10.1002/met.101, 2009. a
Antoine, S., Honnert, R., Seity, Y., Vié, B., Burnet, F., and Martinet, P.: Evaluation of an improved AROME configuration for fog forecasts during the SOFOG3D campaign, Weather Forecast., 38, 1605–1620, https://doi.org/10.1175/WAF-D-22-0215.1, 2023. a, b
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
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