Abstract
Cloud forecast is a crucial component in predicting solar irradiance from numerical weather prediction (NWP) models. Assessing cloud properties from the NWP models requires significant work due to the need for high-quality data, spatial analysis covering model extent, and detailed analysis of model performance for different types of clouds. This study presents an evaluation of the WRF-Solar cloud forecast using the National Solar Radiation Database (NSRDB). We propose an evaluation framework applied to a single model prediction as well as ensemble-based forecasts. Various cloud detection metrics are calculated when comparing with the satellite-derived dataset. The mismatched clouds from the WRF-Solar model are quantified using nine cloud types classified by cloud top height and cloud optical depth. The results based on the WRF-Solar forecasts covering the entire U.S. for the full year of 2018 shows mismatched cloud frequency in the range of 8% - 46% for thick and high-level (deep convective) to thin and low-level (cumulus) clouds.
Original language | American English |
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Number of pages | 6 |
State | Published - 2022 |
Event | 8th World Conference on Photovoltaic Energy Conversion - Milan, Italy Duration: 26 Sep 2022 → 30 Sep 2022 |
Conference
Conference | 8th World Conference on Photovoltaic Energy Conversion |
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City | Milan, Italy |
Period | 26/09/22 → 30/09/22 |
NREL Publication Number
- NREL/CP-5D00-83925
Keywords
- cloud mask forecast
- ensemble forecast
- NSRDB
- WRF-Solar EPS