My research resides at the intersection of eco-hydro-climatology, atmospheric dynamics, and digital agriculture, united by a central goal: to understand and predict water cycle variability and translate that understanding into actionable solutions for climate-resilient agriculture. I focus on the South Asian monsoon system, where land–atmosphere feedbacks, ocean forcing, and climate change converge to create profound challenges for food and water security.
A central pillar of my work involves quantifying precipitation recycling and atmospheric moisture transport using WRF-based numerical weather predictions and moisture-budget decompositions. I investigate how land surface conditions and transient atmospheric disturbances control sub-seasonal to seasonal (S2S) monsoon variability, directly informing extended-range forecasts for agricultural planning. Concurrently, I examine how climate change alters extreme events including floods, droughts, and compound extremes, and assess their cascading impacts on cropping systems.
Bridging atmospheric science with on-ground agriculture requires advanced geoinformatics. I integrate remote sensing and GIS to map evapotranspiration, soil moisture, land use, and crop health dynamics. A key focus is plant phenotyping, employing multispectral, thermal imagery to non-destructively assess crop traits such as biomass, water stress, and canopy architecture under variable monsoon conditions. These geospatial insights feed into AI/ML models that predict crop stress, identify optimal sowing windows, and estimate irrigation demand, thereby enabling precision agricultural decisions.
Ultimately, by fusing process-based climate modeling with geospatial intelligence and machine learning, I work toward climate-smart water allocation, improved prediction of monsoon dynamics, real-time crop monitoring, and the development of resilient farming systems in climate-vulnerable regions.
Keywords
Eco-Hydro-Climatology: Precipitation recycling, atmospheric moisture transport, monsoon S2S variability
Numerical Wether Prediction and Modeling: WRF, moisture-budget decomposition, extreme event simulation
Climate Change: Floods, droughts, compound extremes, ocean–land–atmosphere interactions
Geoinformatics & Remote Sensing: Evapotranspiration, soil moisture, land use, crop health
Digital Agriculture: Plant phenotyping, AI/ML for crop stress prediction, sowing windows, irrigation demand
Goal: Climate-smart water allocation and resilient farming systems
Area of Research: Geo informatics applications in agriculture
Area of Research: Impact of Land Surface Feedbacks in Climate Model Simulations over India
Area of Research: Role of local vs remote feedbacks on rainfall variability in Indian Subcontinent.
Area of Research: Agriculture and Climate Modeling