{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T19:43:18Z","timestamp":1780342998883,"version":"3.54.1"},"reference-count":55,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,5,3]],"date-time":"2020-05-03T00:00:00Z","timestamp":1588464000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41805085"],"award-info":[{"award-number":["41805085"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41675017"],"award-info":[{"award-number":["41675017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB1502800"],"award-info":[{"award-number":["2018YFB1502800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Opening Fund of Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, CAS","award":["Grant LPCC2018006"],"award-info":[{"award-number":["Grant LPCC2018006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>An algorithm to forecast very short-term (30\u2013180 min) surface solar irradiance using visible and near infrared channels (AGRI) onboard the FengYun-4A (FY-4A) geostationary satellite was constructed and evaluated in this study. The forecasting products include global horizontal irradiance (GHI) and direct normal irradiance (DNI). The forecast results were validated using data from Chengde Meteorological Observatory for four typical months (October 2018, and January, April, and July 2019), representing the four seasons. Particle Image Velocimetry (PIV) was employed to calculate the cloud motion vector (CMV) field from the satellite images. The forecast results were compared with the smart persistence (SP) model. A seasonal study showed that July and April forecasting is more difficult than during October and January. For GHI forecasting, the algorithm outperformed the SP model for all forecasting horizons and all seasons, with the best result being produced in October; the skill score was greater than 20%. For DNI, the algorithm outperformed the SP model in July and October, with skill scores of about 12% and 11%, respectively. Annual performances were evaluated; the results show that the normalized root mean square error (nRMSE) value of GHI for 30\u2013180 min horizon ranged from 26.78% to 36.84%, the skill score reached a maximum of 20.44% at the 30-min horizon, and the skill scores were all above 0 for all time horizons. For DNI, the maximum skill score was 6.62% at the 180-min horizon. Overall, compared with the SP model, the proposed algorithm is more accurate and reliable for GHI forecasting and slightly better for DNI forecasting.<\/jats:p>","DOI":"10.3390\/s20092606","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T14:00:43Z","timestamp":1588600843000},"page":"2606","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Very Short-Term Surface Solar Irradiance Forecasting Based On FengYun-4 Geostationary Satellite"],"prefix":"10.3390","volume":"20","author":[{"given":"Liwei","family":"Yang","sequence":"first","affiliation":[{"name":"Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions\/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0806-2014","authenticated-orcid":false,"given":"Xiaoqing","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions\/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajia","family":"Hua","sequence":"additional","affiliation":[{"name":"Tangshan Meteorological Service\/CMA, Tangshan 063000, China"},{"name":"Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Shijiazhuang 050000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pingping","family":"Wu","sequence":"additional","affiliation":[{"name":"Weichang Manchu Mongolia Autonmous County Meteorological Bureau\/CMA, Chengde 068450, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenchao","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions\/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongyu","family":"Jia","sequence":"additional","affiliation":[{"name":"College of Geography and Environmental Engineering, Lanzhou City University, Lanzhou 730070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1016\/j.rser.2013.05.014","article-title":"Development of photovoltaic power generation in China: A transition perspective","volume":"25","author":"Liu","year":"2013","journal-title":"Renew. 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