Satellite observations reveal the role of climate variability in the 2019 extreme rainfall and flood event in Karnataka, India

Multiple with extreme rainfall induced flash flooding pose significant challenges in monsoon dominated regions of India, yet reliable near-real-time monitoring is limited due to sparse ground observations. This study highlights the use of a satellite-based rainfall index (RI), derived from multispectral infrared and water vapor observations, to map short-lived localized multiple with extreme rainfall events with application to the August 2019 flood in Karnataka India. The information of RI integrates brightness temperature information using Meteosat-8 with precipitation estimates from TRMM and GPM-IMERG and is validated independently by using district scale India Meteorological department (IMD) rainfall data. To understand the impact of climatological context on 2019 rainfall event, rainfall anomalies are examined alongside ENSO and Indian Ocean Dipole (IOD) indices using partial correlation analysis over the period of 1998 to 2019. Results attribute statistically consistent co-variability between large-scale climate models and monsoon rainfall variability, with ENSO showing a strong and significant association than IOD. These relationships are interpreted as background climatic modulation rather than direct causal forcing. The study advances satellite-based rainfall monitoring by leveraging high-resolution analysis rainfall episodes with long-term climatological context, offering a transferable frame work for flood early-warning support in data-scarce regions.