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ABSTRACT In recent decades, the spread, intensity and frequency of extreme monsoon events over India have increased significantly. The year 2019 witnessed a widespread increase in extreme precipitation. Although oceanic variables have a role, the mechanism of rain formation and detailed cloud properties remain unclear for extremes. Using satellite and reanalysis datasets, we examined the interplay between cloud characteristics and dynamics in extreme and non‐extreme rainfall events for the 2019 monsoon. The study reveals that extreme events depict higher cloud ice (260.84 g/m2) and liquid (209.60 g/m2) mass than non‐extreme events (161.67 and 116.64 g/m 2 ) averaged over central India (CI) due to increased atmospheric moisture availability. Extreme events were associated with greater ice particles of all sizes, while non‐extreme events had lower number densities, primarily concentrated within the 21–35 μm range. These findings underscore the essential role of cloud microphysics in influencing extreme rainfall. The study reveals distinct differences in dynamical features, including atmospheric circulation, specific humidity, outgoing longwave radiation (OLR), and vertical velocity between extreme and non‐extreme events. The average specific humidity over CI is higher (9.01 g/kg) in extreme than non‐extreme (7.93 g/kg). The lower OLR in extreme (197.95 W/m 2 ) than non‐extreme events (210.80 W/m 2 ) indicates enhanced deep convection, which supports more stratiform rain, contributed significantly (~45%) to the total precipitation and significant difference in convective rain during extreme and non‐extreme events. In contrast, the Monsoon Mission Coupled Forecast System version 2.0 (MMCFSv2) model shows that the percentage of convective rainfall does not differ between extreme (76.56%) and non‐extreme (75.5%) events. Our findings deepen our understanding of the complex relationships between ocean and atmospheric dynamics and cloud properties, emphasising their pivotal influence on quantified precipitation forecasts (QPF) to improve extreme rainfall simulation.
Arya et al. (Sun,) studied this question.