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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 10, 409-429, 2017
http://www.atmos-meas-tech.net/10/409/2017/
doi:10.5194/amt-10-409-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
02 Feb 2017
Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants
Tobias Sirch1, Luca Bugliaro1, Tobias Zinner2, Matthias Möhrlein3, and Margarita Vazquez-Navarro1 1Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
2Meteorologisches Institut, Ludwig-Maximilians-Universität, Munich, Germany
3Nowcast GmbH, Albert-Roßhaupter-Str. 43, Munich, Germany
Abstract. A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellite is presented for a forecast horizon up to 120 min. The basis of the algorithm is an optical flow method to derive cloud motion vectors for all cloudy pixels. To facilitate forecasts over a relevant time period, a classification of clouds into objects and a weighted triangular interpolation of clear-sky regions are used. Low and high level clouds are forecasted separately because they show different velocities and motion directions. Additionally a distinction in advective and convective clouds together with an intensity correction for quickly thinning convective clouds is integrated. The DNI is calculated from the forecasted optical thickness of the low and high level clouds. In order to quantitatively assess the performance of the algorithm, a forecast validation against MSG/SEVIRI observations is performed for a period of 2 months. Error rates and Hanssen–Kuiper skill scores are derived for forecasted cloud masks. For a forecast of 5 min for most cloud situations more than 95 % of all pixels are predicted correctly cloudy or clear. This number decreases to 80–95 % for a forecast of 2 h depending on cloud type and vertical cloud level. Hanssen–Kuiper skill scores for cloud mask go down to 0.6–0.7 for a 2 h forecast. Compared to persistence an improvement of forecast horizon by a factor of 2 is reached for all forecasts up to 2 h. A comparison of forecasted optical thickness distributions and DNI against observations yields correlation coefficients larger than 0.9 for 15 min forecasts and around 0.65 for 2 h forecasts.

Citation: Sirch, T., Bugliaro, L., Zinner, T., Möhrlein, M., and Vazquez-Navarro, M.: Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants, Atmos. Meas. Tech., 10, 409-429, doi:10.5194/amt-10-409-2017, 2017.
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Short summary
A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the geostationary satellite MSG is presented. The basis of the algorithm is an optical flow method to derive cloud motion vectors for low and high level clouds separately. DNI is calculated from the forecasted optical thickness of the clouds. Validation against MSG observations shows good performance: compared to persistence an improvement of forecast horizon by a factor of 2 is reached for 2 h forecasts.
A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the...
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