Category: physics.ao-ph
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DAISI: Data Assimilation with Inverse Sampling using Stochastic Interpolants
DAISI: Data Assimilation with Inverse Sampling using Stochastic Interpolants arXiv:2512.00252v1 Announce Type: new Abstract: Data assimilation (DA) is a cornerstone of scientific and engineering applications, combining model forecasts with sparse and noisy observations to estimate latent system states. Classical DA methods, such as the ensemble Kalman filter, rely on Gaussian approximations and heuristic tuning (e.g.,…
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Probabilistic Emulation of the Community Radiative Transfer Model Using Machine Learning
Probabilistic Emulation of the Community Radiative Transfer Model Using Machine Learning arXiv:2504.16192v1 Announce Type: cross Abstract: The continuous improvement in weather forecast skill over the past several decades is largely due to the increasing quantity of available satellite observations and their assimilation into operational forecast systems. Assimilating these observations requires observation operators in the form…