Joana Mendes, Nosipho Zwane, Brighton Mabasa, H. Tazvinga, Karen Walter, C. Morcrette, Joel Botai
{"title":"分析云层对南非地表短波辐射高分辨率预报的影响","authors":"Joana Mendes, Nosipho Zwane, Brighton Mabasa, H. Tazvinga, Karen Walter, C. Morcrette, Joel Botai","doi":"10.1175/jamc-d-23-0058.1","DOIUrl":null,"url":null,"abstract":"\nWe assess site-specific surface short-wave radiation forecasts from two high resolution configurations of the South African Weather Service numerical weather prediction model, at 4 km and 1.5 km. The models exhibit good skill overall in forecasting surface short-wave radiation, with zero median error for all radiation components. This information is relevant to support a growing Renewable Energy sector in South Africa, particularly for photovoltaics. Further model performance analysis has shown an imbalance between cloud and solar radiation forecasting errors. In addition, cloud over-prediction does not necessarily equate to under-estimating solar radiation. Overcast cloud regimes are predicted too often with an associated positive mean radiation bias, whereas the relative abundance of partly cloudy regimes is under-predicted by the models with mixed radiation biases. Challenges highlighted by the misrepresentation of partly cloudy regimes in solar radiation error attribution may be used to inform improvements to the numerical core, namely the cloud and radiation schemes.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" 22","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Analysis of the Effects of Clouds in High-Resolution Forecasting of Surface Short-wave Radiation in South Africa\",\"authors\":\"Joana Mendes, Nosipho Zwane, Brighton Mabasa, H. Tazvinga, Karen Walter, C. Morcrette, Joel Botai\",\"doi\":\"10.1175/jamc-d-23-0058.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nWe assess site-specific surface short-wave radiation forecasts from two high resolution configurations of the South African Weather Service numerical weather prediction model, at 4 km and 1.5 km. The models exhibit good skill overall in forecasting surface short-wave radiation, with zero median error for all radiation components. This information is relevant to support a growing Renewable Energy sector in South Africa, particularly for photovoltaics. Further model performance analysis has shown an imbalance between cloud and solar radiation forecasting errors. In addition, cloud over-prediction does not necessarily equate to under-estimating solar radiation. Overcast cloud regimes are predicted too often with an associated positive mean radiation bias, whereas the relative abundance of partly cloudy regimes is under-predicted by the models with mixed radiation biases. Challenges highlighted by the misrepresentation of partly cloudy regimes in solar radiation error attribution may be used to inform improvements to the numerical core, namely the cloud and radiation schemes.\",\"PeriodicalId\":15027,\"journal\":{\"name\":\"Journal of Applied Meteorology and Climatology\",\"volume\":\" 22\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Meteorology and Climatology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/jamc-d-23-0058.1\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Meteorology and Climatology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/jamc-d-23-0058.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
An Analysis of the Effects of Clouds in High-Resolution Forecasting of Surface Short-wave Radiation in South Africa
We assess site-specific surface short-wave radiation forecasts from two high resolution configurations of the South African Weather Service numerical weather prediction model, at 4 km and 1.5 km. The models exhibit good skill overall in forecasting surface short-wave radiation, with zero median error for all radiation components. This information is relevant to support a growing Renewable Energy sector in South Africa, particularly for photovoltaics. Further model performance analysis has shown an imbalance between cloud and solar radiation forecasting errors. In addition, cloud over-prediction does not necessarily equate to under-estimating solar radiation. Overcast cloud regimes are predicted too often with an associated positive mean radiation bias, whereas the relative abundance of partly cloudy regimes is under-predicted by the models with mixed radiation biases. Challenges highlighted by the misrepresentation of partly cloudy regimes in solar radiation error attribution may be used to inform improvements to the numerical core, namely the cloud and radiation schemes.
期刊介绍:
The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.