Our lab focuses on the dynamics of the Indian summer monsoon, exploring its variability, long-term changes, and impacts using advanced climate models, multi-source spaceborne data analysis, and physics-guided machine learning approaches. We deep-dive into fundamental processes such as monsoon low-pressure systems, synoptic dry air intrusions, and polar-tropical climate teleconnections, while developing hybrid AI-based predictive frameworks to expand forecasting leads and optimize regional atmospheric climate resilience.
Investigating the core physical mechanics governing the Indian summer monsoon, mapping sub-seasonal precipitation oscillations, tracking structural breakout bounds, and identifying the thermodynamic parameters driving changes across scales.
Quantifying global thermal atmospheric acceleration impacts on tropical climate signatures. We isolate downscaled regional projection variants to track ongoing modifications in flash flood metrics and long-term drought severity projections.
Developing physics-constrained neural computing operators for faster sub-seasonal forecast conversions, building deep numerical simulation emulators, and optimizing severe tropical cyclone detection frameworks.
Active external grants and completed portfolios funding our investigative journeys.