Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants

Sirch, Tobias; Bugliaro, Luca; Zinner, Tobias; Möhrlein, Matthias; Vazquez-Navarro, Margarita

doi:https://doi.org/10.5194/amt-10-409-2017

Articles | Volume 10, issue 2

https://doi.org/10.5194/amt-10-409-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/amt-10-409-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 2

Research article

|

02 Feb 2017

Research article |

| 02 Feb 2017

Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants

Tobias Sirch, Luca Bugliaro, Tobias Zinner, Matthias Möhrlein, and Margarita Vazquez-Navarro

Download

Final revised paper (published on 02 Feb 2017)
Preprint (discussion started on 21 Sep 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review Comments for "Cloud and DNI Nowcasting with MSG/SEVIRI for the optimised operation of concentrating solar power plants"', Anonymous Referee #2, 12 Oct 2016
- AC1: 'RC1', Tobias Sirch, 13 Oct 2016
- AC2: 'Response to anonymous referee #2', Tobias Sirch, 22 Dec 2016
RC2: 'Review comments on Sirch et al. 'Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants.' Anonymous Referee', Anonymous Referee #3, 02 Dec 2016
- AC3: 'Response to anonymous referee #3', Tobias Sirch, 22 Dec 2016

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.