气候变化领域集成服务门户(CCPortal): Evaluating solar radiation forecast uncertainty

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DOI	10.5194/acp-19-1985-2019
	Evaluating solar radiation forecast uncertainty
	Tuononen M.; O'Connor E.J.; Sinclair V.A.
发表日期	2019
ISSN	16807316
起始页码	1985
结束页码	2000
卷号	19 期号:3
英文摘要	The presence of clouds and their characteristics have a strong impact on the radiative balance of the Earth and on the amount of solar radiation reaching the Earth's surface. Many applications require accurate forecasts of surface radiation on weather timescales, for example solar energy and UV radiation forecasts. Here we investigate how operational forecasts of low and mid-level clouds affect the accuracy of solar radiation forecasts. A total of 4 years of cloud and solar radiation observations from one site in Helsinki, Finland, are analysed. Cloud observations are obtained from a ceilometer and therefore we first develop algorithms to reliably detect cloud base, precipitation, and fog. These new algorithms are widely applicable for both operational use and research, such as in-cloud icing detection for the wind energy industry and for aviation. The cloud and radiation observations are compared to forecasts from the Integrated Forecast System (IFS) run operationally and developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We develop methods to evaluate the skill of the cloud and radiation forecasts. These methods can potentially be extended to hundreds of sites globally. Over Helsinki, the measured global horizontal irradiance (GHI) is strongly influenced by its northerly location and the annual variation in cloudiness. Solar radiation forecast error is therefore larger in summer than in winter, but the relative error in the solar radiation forecast is more or less constant throughout the year. The mean overall bias in the GHI forecast is positive (8 W mĝ'2). The observed and forecast distributions in cloud cover, at the spatial scales we are considering, are strongly skewed towards clear-sky and overcast situations. Cloud cover forecasts show more skill in winter when the cloud cover is predominantly overcast; in summer there are more clear-sky and broken cloud situations. A negative bias was found in forecast GHI for correctly forecast clear-sky cases and a positive bias in correctly forecast overcast cases. Temporal averaging improved the cloud cover forecast and hence decreased the solar radiation forecast error. The positive bias seen in overcast situations occurs when the model cloud has low values of liquid water path (LWP). We attribute this bias to the model having LWP values that are too low or the model optical properties for clouds with low LWP being incorrect. © 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
语种	英语
scopus关键词	algorithm; cloud cover; solar radiation; uncertainty analysis; weather forecasting; wind power; winter; Finland; Helsinki; Varsinais-Suomi
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/144642
作者单位	Finnish Meteorological Institute, Helsinki, Finland; Department of Meteorology, University of Reading, Reading, United Kingdom; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland
推荐引用方式 GB/T 7714	Tuononen M.,O'Connor E.J.,Sinclair V.A.. Evaluating solar radiation forecast uncertainty[J],2019,19(3).
APA	Tuononen M.,O'Connor E.J.,&Sinclair V.A..(2019).Evaluating solar radiation forecast uncertainty.Atmospheric Chemistry and Physics,19(3).
MLA	Tuononen M.,et al."Evaluating solar radiation forecast uncertainty".Atmospheric Chemistry and Physics 19.3(2019).