There is a growing interest in emerging opportunistic sensors for precipitation, motivated by the need to improve its quantitative estimates at the ground. The scope of this work is to present a preliminary assessment of the accuracy of commercial microwave link (CML) retrieved rainfall rates in Northern Italy. The CML product, obtained by the open-source RAINLINK software package, is evaluated on different scales (single link, 5 km×5 km grid, river basin) against the precipitation products operationally used at Arpae-SIMC, the regional weather service of Emilia-Romagna, in Northern Italy. The results of the 15 min single-link validation with nearby rain gauges show high variability, which can be caused by the complex physiography and precipitation patterns. Known sources of errors (e.g. the attenuation caused by the wetting of the antennas or random fluctuations in the baseline) are particularly hard to mitigate in these conditions without a specific calibration, which has not been implemented. However, hourly cumulated spatially interpolated CML rainfall maps, validated with respect to the established regional gauge-based reference, show similar performance (R² of 0.46 and coefficient of variation, CV, of 0.78) to adjusted radar-based precipitation gridded products and better performance than satellite-based ones. Performance improves when basin-scale total precipitation amounts are considered (R² of 0.83 and CV of 0.48). Avoiding regional-specific calibration therefore does not preclude the algorithm from working but has some limitations in probability of detection (POD) and accuracy. A widespread underestimation is evident at both the grid box scale (mean error of −0.26) and the basin scale (multiplicative bias of 0.7), while the number of false alarms is generally low and becomes even lower as link coverage increases. Also taking into account delays in the availability of the data (latency of 0.33 h for CML against 1 h for the adjusted radar and 24 h for the quality-controlled rain gauges), CML appears as a valuable data source in particular from a local operational framework perspective. Finally, results show complementary strengths for CMLs and radars, encouraging joint exploitation.

中文翻译：

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商业微波链路作为意大利北部运营降雨监测的工具

由于需要改进对地面的定量估计，因此人们对新兴的降水传感器越来越感兴趣。这项工作的范围是对意大利北部商业微波链路（CML）取回的降雨率的准确性进行初步评估。通过开源RAINLINK软件包获得的CML产品，针对不同规模（单链路，5 km×5 km网格，流域），针对艾米利亚的区域气象服务Arpae-SIMC使用的降水产品进行了评估。 -意大利北部的罗马涅（Romagna）。15分钟的结果 使用附近雨量计的单链路验证显示出很大的可变性，这可能是由复杂的生理和降水模式引起的。在没有特定校准的情况下，在这些情况下，已知的错误源（例如，由天线的润湿引起的衰减或基线中的随机波动）尤其难以缓解，这尚未实施。但是，相对于已建立的基于区域量规的参考数据进行验证的每小时累积空间内插CML降雨图，显示出与调整后的基于雷达的降水量格网产品相似的性能（R ²为0.46，变异系数CV为0.78），并且效果更好性能要比基于卫星的性能好。当考虑流域规模的总降水量时，性能会提高（R ²为0.83，CV为0.48）。因此，避免区域特定的校准并不会阻止该算法的工作，但是在检测概率（POD）和准确性方面存在一些限制。在网格箱规模（平均误差为-0.26）和盆地规模（乘积偏差为0.7）上，普遍存在低估的迹象，而虚假警报的数量通常很少，并且随着链路覆盖范围的增加而变得更低。同时也考虑到延迟的数据的可用性的0.33（延迟 ħ对于CML对1个 ħ用于调整雷达和24  ħ对于质量控制的雨量计），CML尤其是从本地操作框架的角度来看，是有价值的数据源。最后，结果显示了CML和雷达的互补优势，鼓励了联合开发。