We study how and why Earth's climate system responds to various perturbations—ranging from natural variability to human activities—across global and regional scales, including India, Southeast Asia, the Tropics, and the Arctic. Climate change refers to the long-term response to forcings such as atmospheric composition, land use, volcanic eruptions, and solar radiation, typically unfolding over decades to centuries. Climate variability, on the other hand, encompasses fluctuations around the mean climate state, occurring on shorter timescales and often superimposed on long-term changes. Understanding these processes is key to improving future climate projections, particularly by quantifying climate feedbacks, sensitivity, and the efficacy of different forcing agents.

Our approach

To address these challenges our toolbox contains  a spectrum of climate models - simple box models to state-of-the-art Global Climate Models (GCMs). We complement this by evidences from climate observations to enhance & inform our understanding and for model validation. 

Currently, we are configuring GCMs in various modes—fully coupled, atmosphere-only, and other experimental setups—while extensively utilizing CMIP6 datasets. Additionally, we are exploring AI/ML applications in climate science, particularly for analyzing large climate datasets, improving model emulation, and detecting emerging climate signals. 

These efforts aim to advance our understanding of climate variability and change, ultimately informing better adaptation strategies.