Cargando…
Examining the Potential of a Random Forest Derived Cloud Mask from GOES-R Satellites to Improve Solar Irradiance Forecasting
In order for numerical weather prediction (NWP) models to correctly predict solar irradiance reaching the earth’s surface for more accurate solar power forecasting, it is important to initialize the NWP model with accurate cloud information. Knowing where the clouds are located is the first step. Us...
Autores principales: | McCandless, Tyler, Jiménez, Pedro Angel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216221/ https://www.ncbi.nlm.nih.gov/pubmed/34158911 http://dx.doi.org/10.3390/en13071671 |
Ejemplares similares
-
Exploring the Potential of Statistical Modeling to Retrieve the Cloud Base Height from Geostationary Satellites: Applications to the ABI Sensor on Board of the GOES-R Satellite Series
por: Jiménez, Pedro A., et al.
Publicado: (2021) -
Very Short-Term Surface Solar Irradiance Forecasting Based on FengYun-4 Geostationary Satellite
por: Yang, Liwei, et al.
Publicado: (2020) -
Contrasting impacts of forests on cloud cover based on satellite observations
por: Xu, Ru, et al.
Publicado: (2022) -
Assessment of the GOES-16 Clear Sky Mask Product over the Contiguous USA Using CALIPSO Retrievals
por: Jiménez, Pedro A.
Publicado: (2020) -
Debris cloud of India anti-satellite test to Microsat-R satellite
por: Jiang, Yu
Publicado: (2020)