Cite as:
Urbich, I.; Bendix, J. &amp; M&uuml;ller, R.W. (2018): <b>A Novel Approach for the Short-Term Forecast of the Effective Cloud Albedo</b>. <i>Remote Sensing</i> <b>10</b>, 955.

Resource Description

Title: A Novel Approach for the Short-Term Forecast of the Effective Cloud Albedo
FOR816dw ID: 318
Publication Date: 2018-06-15
License and Usage Rights:
Resource Owner(s):
Individual: Isabel Urbich
Individual: Jörg Bendix
Individual: Richard W. Müller
The increasing use of renewable energies as a source of electricity has led to a fundamental<br/> transition of the power supply system. The integration of ?uctuating weather-dependent energy<br/> sources into the grid already has amajor impact on its load ?ows. As a result, the interest in forecasting<br/> wind and solar radiation with a suf?cient accuracy over short time periods (<4 h) has grown. In this<br/> study, the short-term forecast of the effective cloud albedo based on optical ?ow estimation methods<br/> is investigated. The optical ?ow method utilized here is TV-L1 from the open source library OpenCV.<br/> This method uses a multi-scale approach to capture cloud motions on various spatial scales. After the<br/> clouds are displaced, the solar surface radiation will be calculated with SPECMAGIC NOW, which<br/> computes the global irradiation spectrally resolved from satellite imagery. Due to the high temporal<br/> and spatial resolution of satellite measurements, the effective cloud albedo and thus solar radiation<br/> can be forecasted from 5 min up to 4 h with a resolution of 0.05. The validation results of this method<br/> are very promising, and the RMSE of the 30-min, 60-min, 90-min and 120-min forecast equals 10.47%,<br/> 14.28%, 16.87% and 18.83%, respectively. The paper gives a brief description of the method for the<br/> short-term forecast of the effective cloud albedo. Subsequently, evaluation results will be presented<br/> and discussed.
| forecasting methods | cloud albedo |
Literature type specific fields:
Journal: Remote Sensing
Volume: 10
Page Range: 955
Metadata Provider:
Individual: Jörg Bendix
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