气候变化领域集成服务门户(CCPortal): Rainfall estimation from a German-wide commercial microwave link network: Optimized processing and validation for 1 year of data

CCPortal

DOI	10.5194/hess-24-2931-2020
	Rainfall estimation from a German-wide commercial microwave link network: Optimized processing and validation for 1 year of data
	Graf M.; Chwala C.; Chwala C.; Polz J.; Kunstmann H.; Kunstmann H.
发表日期	2020
ISSN	1027-5606
起始页码	2931
结束页码	2950
卷号	24 期号:6
英文摘要	Rainfall is one of the most important environmental variables. However, it is a challenge to measure it accurately over space and time. During the last decade, commercial microwave links (CMLs), operated by mobile network providers, have proven to be an additional source of rainfall information to complement traditional rainfall measurements. In this study, we present the processing and evaluation of a German-wide data set of CMLs. This data set was acquired from around 4000 CMLs distributed across Germany with a temporal resolution of 1min. The analysis period of 1 year spans from September 2017 to August 2018. We compare and adjust existing processing schemes on this large CML data set. For the crucial step of detecting rain events in the raw attenuation time series, we are able to reduce the amount of misclassification. This was achieved by using a new approach to determine the threshold, which separates a rolling window standard deviation of the CMLs' signal into wet and dry periods. For the compensation for wet antenna attenuation, we compare a time-dependent model with a rain-rate-dependent model and show that the rain-rate-dependent model performs better for our data set. We use RADOLAN-RW, a gridded gauge-adjusted hourly radar product from the German Meteorological Service (DWD) as a precipitation reference, from which we derive the path-averaged rain rates along each CML path. Our data processing is able to handle CML data across different landscapes and seasons very well. For hourly, monthly, and seasonal rainfall sums, we found good agreement between CML-derived rainfall and the reference, except for the winter season due to non-liquid precipitation. We discuss performance measures for different subset criteria, and we show that CML-derived rainfall maps are comparable to the reference. This analysis shows that opportunistic sensing with CMLs yields rainfall information with good agreement with gauge-adjusted radar data during periods without non-liquid precipitation. © 2020 Author(s).
语种	英语
scopus关键词	Antennas; Data handling; Radar; Rain gages; Environmental variables; Misclassifications; Opportunistic sensing; Performance measure; Rainfall estimations; Rainfall measurements; Temporal resolution; Time-dependent models; Rain; antenna; data acquisition; data assimilation; microwave radiometer; optimization; precipitation intensity; rainfall; signal processing; temporal record; Germany
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159383
作者单位	Graf, M., Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany; Chwala, C., Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany, Department of Regional Climate and Hydrology, Institute of Geography, University Augsburg, Augsburg, Germany; Chwala, C., Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany, Department of Regional Climate and Hydrology, Institute of Geography, University Augsburg, Augsburg, Germany; Polz, J., Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany; Kunstmann, H., Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany; Kunstmann, H., Department of Regional Climate and Hydrology, Institute of Geography, University ...
推荐引用方式 GB/T 7714	Graf M.,Chwala C.,Chwala C.,et al. Rainfall estimation from a German-wide commercial microwave link network: Optimized processing and validation for 1 year of data[J],2020,24(6).
APA	Graf M.,Chwala C.,Chwala C.,Polz J.,Kunstmann H.,&Kunstmann H..(2020).Rainfall estimation from a German-wide commercial microwave link network: Optimized processing and validation for 1 year of data.Hydrology and Earth System Sciences,24(6).
MLA	Graf M.,et al."Rainfall estimation from a German-wide commercial microwave link network: Optimized processing and validation for 1 year of data".Hydrology and Earth System Sciences 24.6(2020).