Speaker
Description
Commercial microwave links (CMLs) have emerged as valuable infrastructure for the opportunistic sensing of rain. However, many networks exhibit persistent diurnal signal fluctuations in the absence of precipitation. Their physical origin remains relatively misunderstood, limiting the reliability of CMLs for atmospheric sensing and prompting for additional signal processing to avoid misclassification of signal patterns. These fluctuations have been observed across diverse regions, vendors, frequencies, and deployment configurations, suggesting a systematic atmospheric contribution rather than hardware effects.
In this work, we present preliminary results from a physics-informed analysis exploring the relationship between surface cooling, wind conditions, and channel variability in the context of nocturnal boundary-layer evolution. Using data from operational CML networks, we observe that a substantial portion of the analyzed links exhibit a structured coupling between ambient temperature gradients and channel volatility, which turns into fluctuations of the received signal level. This relationship tends to strengthen under calm wind conditions and is frequently characterized by a temporal lag in which surface cooling precedes enhanced signal variability, consistent with the gradual development of the nocturnal stable boundary layer.
These findings suggest that diurnal channel variability may reflect organized boundary-layer dynamics rather than random fluctuations. The results support the potential of CML networks to function not only for rainfall measurement, but also as distributed sensors of the atmospheric conditions, enhancing their role in opportunistic sensing.