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Dynamical-Model-Informed Stochastic Flow Matching for Global Probabilistic Subseasonal Forecasting of Means and Extremes
Abdullah A. Fahad, Manmeet Singh
Physics-based models provide skillful subseasonal forecasts but suffer from systematic biases, weakened teleconnections, and parameterized physics, while very large ensembles remai…
Steering Diffusion Priors with Sparse Observations for High-Resolution Temperature Downscaling
Anirudh Avireddy, Manmeet Singh, Shivanshi Singh +4
Local heatwave hazard depends on fine-scale air temperature, but ground stations are sparse and reanalysis products such as ERA5 cannot resolve the terrain and land-surface contras…
A Physics--ML Multi-Fidelity Strategy for Earth System Model Parameter Optimization: A QG Proof-of-Concept
Abdullah A. Fahad, Manmeet Singh, Donifan Barahona +2
Earth System Models rely on tunable subgrid-scale parameterizations, but optimizing these parameters is computationally expensive, particularly when nonlinear interactions require…
GraphCast Skill and Systematic Biases in Indian Summer Monsoon Forecasts: Evaluation Against ERA5 and IMERG
Somnath Luitel, Parthasarathi Mukhopadhyay, Manmeet Singh +2
The Indian Summer Monsoon (ISM) is one of the most dynamically complex components of the global climate system, yet its accurate prediction remains challenging for both physics-bas…
Aircast-Mars: A Mars Foundation Model for Global Weather Forecasting with HEALPix-Aware Convolutions
Manmeet Singh, Saptarishi Dhanuka, Naveen Sudharsan +3
Foundation models for planetary atmospheres promise fast, lightweight surrogates of expensive general circulation models (GCMs) for mission planning and scientific inquiry. Here we…