气候变化领域集成服务门户(CCPortal): Adopting citizen observations in operational weather prediction

CCPortal

DOI	10.1175/BAMS-D-18-0237.1
	Adopting citizen observations in operational weather prediction
	Nipen T.N.; Seierstad I.A.; Lussana C.; Kristiansen J.; Hov Ø.
发表日期	2020
ISSN	00030007
起始页码	E43
结束页码	E57
卷号	101 期号:1
英文摘要	Citizen weather stations are rapidly increasing in prevalence and are becoming an emerging source of weather information. These low-cost consumer-grade devices provide observations in real time and form parts of dense networks that capture high-resolution meteorological information. Despite these benefits, their adoption into operational weather prediction systems has been slow. However, MET Norway recently introduced observations from Netatmo’s network of weather stations in the postprocessing of near-surface temperature forecasts for Scandinavia, Finland, and the Baltic countries. The observations are used to continually correct errors in the weather model output caused by unresolved features such as cold pools, inversions, urban heat islands, and an intricate coastline. Corrected forecasts are issued every hour. Integrating citizen observations into operational systems comes with a number of challenges. First, operational systems must be robust and therefore rely on strict quality control procedures to filter out unreliable measurements. Second, postprocessing methods must be selected and tuned to make use of the high-resolution data that at times can contain conflicting information. Central to resolving these challenges is the need to use the massive redundancy of citizen observations, with up to dozens of observations per square kilometer, and treating the data source as a network rather than a collection of individual stations. We present our experiences with introducing citizen observations into the operational production chain of automated public weather forecasts. Their inclusion shows a clear improvement to the accuracy of short-term temperature forecasts, especially in areas where existing professional stations are sparse. © 2020 American Meteorological Society
语种	英语
scopus关键词	Weather information services; High resolution data; Meteorological information; Near surface temperature; Operational production; Operational systems; Postprocessing methods; Temperature forecasts; Weather information; Weather forecasting
来源期刊	Bulletin of the American Meteorological Society
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/177960
作者单位	Norwegian Meteorological Institute, Oslo, Norway
推荐引用方式 GB/T 7714	Nipen T.N.,Seierstad I.A.,Lussana C.,et al. Adopting citizen observations in operational weather prediction[J],2020,101(1).
APA	Nipen T.N.,Seierstad I.A.,Lussana C.,Kristiansen J.,&Hov Ø..(2020).Adopting citizen observations in operational weather prediction.Bulletin of the American Meteorological Society,101(1).
MLA	Nipen T.N.,et al."Adopting citizen observations in operational weather prediction".Bulletin of the American Meteorological Society 101.1(2020).