Spectral Signatures of Rainfall and Crosswind in Microwave-Link Signals

High-frequency fluctuations in microwave-link received power contain valuable information about atmospheric processes along the propagation path. In addition to well-known turbulence-induced scintillations, raindrop motion can generate a distinct high-frequency signature in both the variance and power spectral density (PSD) of the signal. These rain-induced scintillations contain information related to raindrop size and velocity distributions, but they remain largely unexplored.

In this study, we derived a simple mathematical PSD model that combines turbulence and rainfall contributions, bridging previous turbulence- and rainfall-only models. To isolate the rainfall signature from turbulence, we analyzed a dataset collected in Wageningen using a 2.2 km microwave link operating at 26 GHz with a 20 Hz sampling rate. Variance and PSDs were calculated over 30 s windows under dry and rainy conditions, respectively.

We then examined correlations between signal fluctuation metrics and rainfall characteristics (e.g., path-averaged rainfall rate and moments of the raindrop size distribution measured by disdrometers along the path), as well as nearby crosswind. Differences in spectral power dominance across temporal frequencies were identified: rainfall dominates near 10 Hz (the Nyquist frequency), while crosswind dominates around 2 Hz. The 6th moment of the raindrop size distribution exhibits the highest correlation with signal fluctuation metrics, while the raindrop concentration exhibits the lowest.

These findings highlight the potential to retrieve rainfall characteristics and crosswind from microwave-link observations during rainy events. However, challenges remain, including the low signal-to-noise ratio of the data and the lack of colocated wind and turbulence measurements. Future work should focus on improving measurement setups and advancing the simulation of the combined PSD.