A novel disaggregation algorithm for commercial microwave links (CMLs), named CLEAR (CML Segments with Equal Amounts of Rain), is proposed. CLEAR utilizes a multiplicative random cascade generator to control the splitting of link segments. The evaluation performed both on virtual and real CML data shows that CLEAR outperforms a commonly used benchmark algorithm. Moreover, the stochastic nature of CLEAR allows it to represent uncertainty as an ensemble of rain rate distributions along CML paths.

A common method to retrieve important information about the microphysical structure of rain (DSD retrievals) requires a constrained relationship between the drop size distribution parameters. The most widely accepted empirical relationship is between μ and Λ. The relationship shows variability across the different types of rainfall (convective or stratiform). The new proposed power-law model to represent the μ–Λ relation provides a better physical interpretation of the relationship coefficients.

Knowledge of the raindrop size distribution (DSD) is crucial for understanding rainfall microphysics and quantifying uncertainty in quantitative precipitation estimates. In this study a general overview of the DSD retrieval approach from a polarimetric radar is discussed, highlighting sensitivity to potential sources of errors, either directly linked to the radar measurements or indirectly through the critical modeling assumptions behind the method such as the shape–size (μ–Λ) relationship.

An original dataset of microwave signal attenuation and rainfall variables was collected during 1-year-long field campaign. The monitored 38 GHz dual-polarized commercial microwave link with a short sampling resolution (4 s) was accompanied by five disdrometers and three rain gauges along its path. Antenna radomes were temporarily shielded for approximately half of the campaign period to investigate antenna wetting impacts.

Ground-based rainfall observations across the African continent are sparse. We present a new and inexpensive rainfall measuring instrument (the intervalometer) and use it to derive reasonably accurate rainfall rates. These are dependent on a fundamental assumption that is widely used in parameterisations of the rain drop size distribution. This assumption is tested and found to not apply for most raindrops but is still useful in deriving rainfall rates. The intervalometer shows good potential.