Speaker
Description
Wireless Commercial Microwave Links (CMLs) can serve as opportunistic environmental sensors, as signal attenuation along links can be exploited to infer precipitation intensity with high spatial resolution and low implementation cost. While rain-induced attenuation has been extensively modeled, the impact of hail on signal propagation remains largely unexplored, despite the significant economic damage severe hailstorms can cause. This study investigates hail's impact on microwave communication links to characterize its effects and improve the understanding of hail events.
The experimental study utilized data collected from two bi-directional CMLs in Kfar Saba, Israel, operating at frequencies between 18 GHz and 38.8 GHz. The methodology involves extracting precipitation-induced signal attenuation by separating total attenuation from baseline losses and wet antenna effects. To evaluate the performance of the standard power-law relationship, A_r (t) = aR^b (t)L, this power law, with the standard coefficients optimized for rain, was applied to both rain and hail periods to estimate precipitation rates from the observed attenuation. These estimates were used to calculate the total accumulated precipitation for each storm event, which was then compared with ground truth measurements from an OTT Parsivel disdrometer to assess the model's accuracy across different precipitation types
Preliminary results from storms between January 2023 and April 2024 show that rain-only events align closely with the standard power-law model, indicating good agreement between CML-based estimates and disdrometer measurements. In contrast, hail points display a wider spread and significant deviations from the standard model. These observations underscore the challenge of using standard rain coefficients for hail and provide the motivation to characterize these deviations as a means for precipitation classification. By refining this characterization, it may become possible to distinguish between rain and hail events, while also exploring the derivation of hail-specific coefficients in the future.