Publications

How far can we downscale? Resolution limits and physical interpretability of diffusion models for African precipitation

Jangho Lee and Sara Shamekh

Machine Learning: Earth, 2026

Data-Driven Modeling of Stratiform and Convective Rain Area

Sara Shamekh, Pedro Angulo-Umana, and Paul A. O'Gorman

Journal of the Atmospheric Sciences, 2026

Wavelet Flow Matching for Multi-Scale Physics Emulation

Gabriele Accarino, Juan Nathaniel, Carla Roesch, Pierre Gentine, Sara Shamekh, Duncan Watson-Parris, and Viviana Acquaviva

arXiv:2605.16573, 2026

Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning

Savannah L. Ferretti, Jerry Lin, Sara Shamekh, Jane W. Baldwin, Michael S. Pritchard, and Tom Beucler

arXiv:2603.10305, 2026

Representing subgrid-scale cloud effects in a radiation parameterization using machine learning: MLe-radiation v1.0

Katharina Hafner, Sara Shamekh, Guillaume Bertoli, Axel Lauer, Robert Pincus, Julien Savre, and Veronika Eyring

Geoscientific Model Development, 19, 3875–3891, 2026

Strictly Constrained Generative Modeling via Split Augmented Langevin Sampling

Matthieu Blanke, Yongquan Qu, Sara Shamekh, and Pierre Gentine

arXiv:2505.18017, 2025

CuMoLoS-MAE: A Masked Autoencoder for Remote Sensing Data Reconstruction

Anurup Naskar, Nathanael Wong Zhixin, and Sara Shamekh

arXiv:2508.14957, 2025

Towards a Unified Data-Driven Boundary Layer Momentum Flux Parameterization for Ocean and Atmosphere

Renaud Falga, Sara Shamekh, and Laure Zanna

arXiv:2511.01766, 2025

PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models

Yongquan Qu, Matthieu Blanke, Sara Shamekh, and Pierre Gentine

arXiv:2508.00325, 2025

ClimSim-Online: A large multi-scale dataset and framework for hybrid physics-ML climate emulation

Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter Hannah, Liran Peng, Jerry Lin, et al. (incl. Sara Shamekh)

Journal of Machine Learning Research, 26(142), 1–85, 2025

WaveSim: A Wavelet-based Multi-scale Similarity Metric for Weather and Climate Fields

Gabriele Accarino, Viviana Acquaviva, Sara Shamekh, Duncan Watson-Parris, and David Lawrence

arXiv:2512.14656, 2025

Distilling machine learning's added value: Pareto fronts in atmospheric applications

Tom Beucler, Arthur Grundner, Sara Shamekh, Peter Ukkonen, Matthew Chantry, and Ryan Lagerquist

Artificial Intelligence for the Earth Systems, 4(2), e240078, 2025