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Watch a lecture exploring machine learning-based parameterization techniques in meteorological modeling, delivered by Aditi Sheshadri at the International Centre for Theoretical Sciences. Delve into advanced concepts related to moist convective dynamics of monsoons, examining how ML approaches can improve the representation of complex atmospheric processes in weather and climate models. Part of a comprehensive program covering geophysical fluid dynamics, convective organization, and monsoon variability, this presentation contributes to understanding modern computational methods for atmospheric modeling. Gain insights into how data-driven approaches are revolutionizing our ability to forecast and understand monsoon systems, cloud formations, and large-scale atmospheric phenomena like the Inter-Tropical Convergence Zone and Madden-Julian oscillation.
