Climatology of extreme precipitation spells induced by cloudburst-like events during the Indian Summer Monsoon

• Published in: Journal of hydrology: X 2025-01, Vol.26, p.100197, Article 100197
• Main Authors: Raghuvanshi, Akash Singh, Trigo, Ricardo M., Agarwal, Ankit
• Format: Article
• Language: English
• Subjects: CloudBurst-like events; CMORPH; Extreme precipitation; IMDAA; IMERG; Indian summer monsoon
• ISSN: 2589-9155; 2589-9155
• DOI: 10.1016/j.hydroa.2024.100197

[Display omitted] •Reanalysis product fall short in capturing hourly precipitation extremes compared to satellite-based products.•CMORPH data capture Extreme Precipitation Spells induced by Cloudburst-like (EPS-CBL) events compared to IMERG data.•From 2000 to 2022, CMORPH and IMERG show rising EPS-CBL events in hilly region, while IMDAA shows a decline.•Diurnal variability in Cloudburst-like (CBL) events driving Extreme Precipitation Spells (EPS) is evident during the ISM. This study enhances existing understanding of extreme precipitation spells induced by cloudburst-like (EPS-CBL) events in India, emphasizing climatology and geographical distribution often overlooked by traditional observations. EPS-CBL is defined as continuous rainfall exceeding 200 mm/day and intermittent extreme rates above 30 mm/hour or the 99.9th percentile threshold, differing from definitions proposed by the IMD and other studies. Our findings reveal significant biases in various precipitation products compared to IMD data. CMORPH consistently outperforms other datasets by capturing more extreme events and showing significant rising trends in regions influenced by orographic effects, such as the Himalayan foothills and the Western Ghats. Although IMERG aligns well with IMD overall, it exhibits variability in extreme events, while IMDAA tends to underestimate these extremes, especially in complex terrains. Analysis of EPS-CBL trends from 2000 to 2022 highlights regional differences across datasets. Both CMORPH and IMERG show an increase in EPS-CBL events in the hilly region, while IMDAA indicates a decline. Understanding EPS-CBL climatology provides valuable insights for modeling studies exploring the underlying mechanisms of these events.