Satellite Data Assimilation in Regional Numerical Weather Prediction as a Key for Better Cloud Cover Forecasts in Tropical Environments

Abstract : Although the high amount of solar irradiance in the tropics is an advantage for a profitable PV production, the local meteorological conditions induce a very high variability which is problematic for a safe and gainful injection into the power grid. This issue is even more critical in non-interconnected territories where network stability is an absolute necessity and the injection of PV power has to be limited. The basis for precise cloud evolution and subsequent irradiance forecasts are high quality atmospheric analyses for NWP. Geostationary meteorological satellites provide valuable observations of cloud properties with high spatiotemporal resolutions and allow a pertinent data assimilation.The shortcoming is that optical and thermal channels of satellite sensors do not provide cloud properties from inside clouds. Different existing data assimilation approaches aim at deriving atmospheric analyses with most realistic cloud features, utilising geostationary satellite observations. The potential of assimilating satellite-derived cloud information in regional NWP with focus on irradiance forecasts in tropical regions has not been evaluated so far. Hence, the present work aims at evaluating the potential of geostationary satellite data assimilation in limited-area models applied to the French tropical oversea territories Reunion Island and French Guiana.
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Communication dans un congrès
European PV Solar Energy Conference and Exhibition, Jun 2016, Munich, Germany. Proceedings of the 32th European PV Solar Energy Conference, 2016
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Contributeur : Frederik Kurzrock <>
Soumis le : lundi 6 mars 2017 - 16:53:44
Dernière modification le : vendredi 26 octobre 2018 - 12:09:29
Document(s) archivé(s) le : mercredi 7 juin 2017 - 15:35:30

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Frederik Kurzrock, Sylvain Cros, Fabrice Chane-Ming, Roland Potthast, Laurent Linguet, et al.. Satellite Data Assimilation in Regional Numerical Weather Prediction as a Key for Better Cloud Cover Forecasts in Tropical Environments. European PV Solar Energy Conference and Exhibition, Jun 2016, Munich, Germany. Proceedings of the 32th European PV Solar Energy Conference, 2016. 〈hal-01483954〉

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