Commercial Microwave Links as opportunistic sensors for precipitation in northern Italy: building and validating an operational monitoring network

There is a growing interest in emerging opportunistic sensors for precipitation, motivated by the need to improve its quantitative estimates at the ground. The scopes of this work are to discuss the effort of building a CML-based opportunistic sensing framework from scratch and to present preliminary assessment of the accuracy of CMLs retrieved rainfall rates in Northern Italy. The CML product, obtained by the open-source RAINLINK software package, is evaluated on different scales against the precipitation products operationally used at the Regional Weather Service of Emilia-Romagna (Italy). The results of the 15 min single-link validation with close-by rain gauges show high variability, which can be caused by the complex area physiography and precipitation patterns. Known sources of errors 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 CV of 0.78) to adjusted radar-based precipitation gridded products and better than satellite- 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 POD and accuracy. A widespread underestimation is evident at both grid box (Mean Error of -0.26) and basin-scale (Multiplicative Bias of 0.7), while the number of false alarms is generally low and gets even lower as link coverage increases. Taking into account also delays in the availability of the data (latency of 0.33 hours for CML against 1 hour for the adjusted radar and 24h for the quality-controlled rain gauges), CML appears as a valuable data source in particular from a local operational framework perspective.