Subimal Ghosh

Abstract Urban weather and climate modeling is challenged by the highly heterogeneous and dynamic nature of cities. It exhibits a persistent trilemma between spatial granularity, spatiotemporal coverage, and physical interpretability. We articulate this challenge and propose a hybrid framework integrating physics-based models, urban observations, and machine learning.

Abstract Terrestrial vegetation, particularly forests and savannas, is vital for regulating water and carbon cycles; however, its resilience to climate change remains largely unexplored in India. Our study projects that global warming will increase the likelihood of a shift from forest to savanna-like conditions in major Indian forest regions by the late 21st century.

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