Precipitation observation using microwave backhaul links in the alpine and pre-alpine region of Southern Germany

Precipitation observation using microwave backhaul links in the alpine and pre-alpine region of Southern Germany
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DOI:
10.5194/hess-16-2647-2012
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发表时间:
2012-01-01
影响因子:
6.3
通讯作者:
Kunstmann, H.
Kunstmann, H.
中科院分区:
地球科学2区
文献类型:
--
作者:
Chwala, C.;Gmeiner, A.;Kunstmann, H.

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在复杂地形上测量降雨率存在很大的不确定性,因为雨量计受地形学的影响,而气象雷达大多无法观测到山谷。我们应用了一种新的方法来估计近地表降雨率利用衰减数据从商业微波链路在德国南部的高山地区。接收到的信号电平(RSL)数据由发射塔上的小型数据记录器每分钟记录下来,然后通过GSM(全球移动通信系统)发送到数据库服务器。由于无雨期的RSL波动较大,因此确定降水引起的衰减并不简单。为了能够连续处理2010年7月至2010年10月的RSL数据,我们引入了一种利用光谱时间序列分析来检测干湿期的新方法。分析了该方法的性能和局限性,结果表明,在所有五个环节中,干湿期的平均检测错误率都可以降低到10%。然后,根据RSL得出湿/干分类雨率,并与雨量计和天气雷达测量结果进行比较。所得到的相关性对于不同的链路是不同的,链路测量比较的R-2 = 0.81,链路雷达比较的R-2 = 0.85。
Measuring rain rates over complex terrain is afflicted with large uncertainties, because rain gauges are influenced by orography and weather radars are mostly not able to look into mountain valleys. We apply a new method to estimate near surface rain rates exploiting attenuation data from commercial microwave links in the alpine region of Southern Germany. Received signal level (RSL) data are recorded minutely with small data loggers at the towers and then sent to a database server via GSM (Global System for Mobile Communications). Due to the large RSL fluctuations in periods without rain, the determination of attenuation caused by precipitation is not straightforward. To be able to continuously process the RSL data from July 2010 to October 2010, we introduce a new method to detect wet and dry periods using spectral time series analysis. Its performance and limitations are presented, showing that the mean detection error rates of wet and dry periods can be reduced to 10% for all five links. After, the wet/dry classification rain rates are derived from the RSL and compared to rain gauge and weather radar measurements. The resulting correlations differ for different links and reach values of R-2 = 0.81 for the link-gauge comparison and R-2 = 0.85 for the link-radar comparison.