Reply on RC3

Abstract

Accurate rainfall monitoring is critical for sustainable societies, and yet challenging in many ways. Opportunistic monitoring using commercial microwave links (CML) in telecommunication networks is emerging as a powerful complement to conventional gauges and weather radar. However, CML data are often inaccessible or incomplete, which limits research and application. Here, we aim to reduce this barrier by openly sharing data at 10-second resolution with true coordinates from a pilot study involving 364 bi-directional CMLs in Gothenburg, Sweden. To enable further comparative analyses, we also share high-resolution data from 11 precipitation gauges and the Swedish operational weather radar composite in the area. The article presents an overview of the data, including collection approach, descriptive statistics, and a case study of a high-intensity event. The results show that the data collection was very successful, providing near-complete time series for the CMLs (99.99 %), gauges (100 %) and radar (99.6 %) in the study period (June–August 2015). The bandwidth consumed during CML data collection was small, and hence the telecommunication traffic was not significantly affected by the collection. The gauge records indicate that total rainfall was approximately 260 mm in the study period, with rainfall occurring in 6 % of each 15-minute interval. One of the most intense events was observed on 28 July 2015, during which the Torslanda gauge recorded a peak of 1.1 mm min−1. The variability of the CML data generally followed the gauge dynamics very well. Here we illustrate this for 28 July, where a nearby CML recorded a drop in received signal strength of about 27 dB at the time of the peak. The radar data showed a good distribution of reflectivities for mostly stratiform precipitation, but also contained some values above 40 dBZ, which is commonly seen as an approximate threshold for convective precipitation. Clutter was also found and was mostly prevalent around low reflectivities of −15 dBZ. The data are accessible at https://doi.org/10.5281/zenodo.6673751 (Andersson et al., 2022). We believe this Open sharing of high-resolution data from Microwave links, Radar, and Gauges (OpenMRG) will facilitate research on microwave-based environmental monitoring using CMLs, and support the development of multi-sensor merging algorithms.