GC076
Solar Radiation Monitoring and Forecast from Satellite Observations and Models: Physical and Machine Learning Perspectives
Session ID#: 81059
Session Description:
Solar energy is a clean and renewable source, which is beneficial for climate change mitigation and sustainable development. The monitoring and forecasting of solar radiation are required to better operate solar plants, especially when integrated with the electric grid. There is an increasing need for solar radiation datasets to be available at high spatial and temporal resolutions. The new generation satellites provide observations with continuously improved spatial and temporal resolutions and help improve the accuracy and usability of solar radiation assessment for solar radiation monitoring and forecast. This session will focus on the algorithm development and applications of solar radiation monitoring, assessment, and forecasting, with physical and machine learning methods. This session aims to help both scientists and engineers to gain information on inform about the data availability and to improve solar radiation forecasts for solar plants monitoring and operation.
Index Terms:
0360 Radiation: transmission and scattering [ATMOSPHERIC COMPOSITION AND STRUCTURE]
1640 Remote sensing [GLOBAL CHANGE]
1922 Forecasting [INFORMATICS]
1952 Modeling [INFORMATICS]
Primary Convener: Tao He, Wuhan University, School of Remote Sensing and Information Engineering, Wuhan, China
Conveners: Pietro Elia Campana, Mälardalen university, Västerås, Sweden and Yi Zhang, University of Maryland College Park, Department of Geographical Sciences, College Park, MD, United States
Primary Liaison: Tao He, Wuhan University, School of Remote Sensing and Information Engineering, Wuhan, China
Improving the MERRA-2 derived solar irradiance forecasts incorporating an efficient physically based models for estimating solar irradiance and an cloud transmittance formula (488349)
Wenmin Qin, Wuhan, Hubei, China, Lunche Wang, China University of Geosciences Wuhan, Wuhan, China and Aiwen Lin Sr, Wuhan university, Wuhan, China
Developing a Parameterization for Solar Variability in WRF-Solar Version 2 (Invited) (519451)
Laura Riihimaki1,2, Larry K Berg3, Joseph Sedlar2,4, Ying Liu5 and Kathleen O Lantz1,2, (1)Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States, (2)NOAA, ESRL Global Monitoring Division, Boulder, CO, United States, (3)Pacific Northwest National Laboratory, Atmospheric Sciences & Global Change Division, Richland, WA, United States, (4)CIRES, University of Colorado Boulder, Boulder, CO, United States, (5)Pacific Northwest National Laboratory, Richland, WA, United States
Short-Term Solar Irradiance Forecasts Using Sky Images and Radiative Transfer Model (535430)
Du Juan1, Qilong Min2, Penglin Zhang1, Jun Yang3 and Bangsheng Yin4, (1)Wuhan University, Wuhan, China, (2)University at Albany, State University of New York, Albany, United States, (3)Chinese Academy of Meteorological Sciences, Beijing, China, (4)University at Albany, State University of New York, Albany, NY, United States
Computing the 1-minute diffuse component of solar radiation using deep learning (547828)
Pietro Elia Campana1, Fu Cheng2, Sandra M. Andersson3, Tomas Landelius3 and Bengt Stridh4, (1)Mälardalen university, Västerås, Sweden, (2)University of Zurich, Zurich, Switzerland, (3)Swedish Meteorological and Hydrological Institute, Norrköping, Sweden, (4)Mälardalen University, Vasteras, Sweden
Optimization-based surface shortwave radiation estimating from multiple geostationary sensors (565709)
Yi Zhang1, Shunlin Liang2, Tao He3, Dongdong Wang1 and Yunyue Yu4, (1)University of Maryland College Park, Department of Geographical Sciences, College Park, MD, United States, (2)Univ Maryland, College Park, MD, United States, (3)Wuhan University, Wuhan, China, (4)NOAA, STAR, College Park, MD, United States
Spatial and temporal variability in surface irradiance at ultraviolet wavelengths from ground-based observations across the United States (569850)
Zhibin Sun1, Maosi Chen1, Chelsea A Corr1, Yan-An Liu2 and Wei Gao1, (1)Colorado State University, UV-B Monitoring and Research Program, Natural Resource Ecology Laboratory, Fort Collins, CO, United States, (2)East China Normal University, Key Laboratory of Geographic Information Science (Ministry of Education), Shanghai, China
