Quantitative analysis of radar signatures predicting raindrop characteristics in heavy rainfall, suggesting improved forecasting methods.
Based on 3 years of summertime radar observations in East China, this study quantifies the relationship between polarimetric radar signatures (PRSs) and retrieved raindrop size distributions (RSDs) in heavy‐rainfall‐producing convection. Multiple PRSs, including the 30‐dBZ and 40‐dBZ echo‐tops, the integrated intensities of and columns, the maximum graupel and hail height, as well as the changes in and within the warm‐cloud layer, can to some extent indicate the mean raindrop size, number concentration, and rain rate at the low level (1‐km level). A Multi‐Layer Perceptron model is designed and trained to preliminarily predict these RSD parameters using the PRSs as inputs. These RSD parameters are generally reproduced and the correlations between predicted and observed values are above 0.8. The study clearly demonstrates the quantitative constraints of PRSs on low‐level RSDs in heavy‐rainfall‐producing convection. Such microphysical constraints have potential applications for polarimetric radar in the prediction of RSDs and rainfall intensity.
No takes yet. Share an insight, caveat, or question.
Chen et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: