Comparison of rainfall microphysics characteristics derived by numerical weather prediction modelling and dual‐frequency precipitation radar

The understanding of large-scale rainfall microphysical characteristics plays a significant role in meteorology, hydrology and natural hazards managements. Traditional instruments for estimating raindrop size distribution (DSD), including disdrometers ground dual-polarization radars, are available only limited areas. However, the development space-based radars mesoscale numerical weather prediction models would allow DSD estimation on large scale. This study investigated performance research forecasting (WRF) model global precipitation measurement mission (GPM) dual-frequency radar retrieval under different conditions. parameters (Dm Nw), rain rate (R), kinetic energy (KE) reflectivity (Z) were estimated Chilbolton, United Kingdom, by using long-term disdrometer observations validation. energy–rain (KE–R) reflectivity–rain (Z–R) relationships explored disdrometer, WRF GPM. It was found that parameter trends three approaches similar although has larger Dm smaller Nw values. In terms relationship, GPM performs better when both Ku- Ka-band (KuPR KaPR) observe simultaneously (R > 0.5 mm h−1), while shows high accuracy light < h−1). fusion is recommended improved ungauged