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National assessment reveals widespread wind farm impacts on land surface temperature and vegetation in China. 2026-03

DOI: https://doi.org/10.1016/j.geosus.2026.100460

Learning enhanced ensemble filters. 2026-02

DOI: https://doi.org/10.1016/j.jcp.2025.114550

ClimaLand: A Land Surface Model Designed to Enable Data‐Driven Parameterizations. 2026-01

DOI: https://doi.org/10.1029/2025ms005118

Nesterov acceleration for ensemble Kalman inversion and variants. 2025-08

DOI: https://doi.org/10.1016/j.jcp.2025.114063

Forecast error growth: A dynamic–stochastic model. 2025-07-01

DOI: https://doi.org/10.1063/5.0248102

Forecast error growth: a dynamic–stochastic model. 2025-07

URI: https://centaur.reading.ac.uk/123533/

Learning Enhanced Ensemble Filters. 2025-04

DOI: https://doi.org/10.48550/arxiv.2504.17836

Forecast error growth: A dynamic-stochastic model. 2025-03

DOI: https://doi.org/10.48550/arxiv.2411.06623

Learning Optimal Filters Using Variational Inference. 2025-03

DOI: https://doi.org/10.48550/ARXIV.2406.18066

Inverse Problems and Data Assimilation: A Machine Learning Approach. 2024-10

DOI: https://doi.org/10.48550/ARXIV.2410.10523

High‐Dimensional Covariance Estimation From a Small Number of Samples. 2024-09

DOI: https://doi.org/10.1029/2024MS004417

The South Atlantic Dipole via multichannel singular spectrum analysis. 2024-07-05

URI: https://centaur.reading.ac.uk/117071/ DOI: https://doi.org/10.1038/s41598-024-62089-w ISSN: https://portal.issn.org/resource/ISSN/2045-2322

Improved subseasonal prediction of South Asian monsoon rainfall using data-driven forecasts of oscillatory modes. 2024-04-09

DOI: https://doi.org/10.1073/pnas.2312573121

Filtering dynamical systems using observations of statistics. 2024-03-01

DOI: https://doi.org/10.1063/5.0171827

A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing. 2024-01

DOI: https://doi.org/10.1016/j.solener.2023.112198

A Multi‐Model Ensemble Kalman Filter for Data Assimilation and Forecasting. 2023-01

DOI: https://doi.org/10.1029/2022MS003123

EnsembleKalmanProcesses.jl: Derivative-free ensemble-based model calibration. 2022-12-15

DOI: https://doi.org/10.21105/joss.04869

Towards physics-inspired data-driven weather forecasting: integrating data assimilation with a deep spatial-transformer-based U-NET in a case study with ERA5. 2022-03-16

DOI: https://doi.org/10.5194/gmd-15-2221-2022

Impacts of 319 wind farms on surface temperature and vegetation in the United States. 2022-02-01

DOI: https://doi.org/10.1088/1748-9326/ac49ba

parasweep: a template-based utility for generating, dispatching, and post-processing of parameter sweeps. 2021-01-13

URI: https://centaur.reading.ac.uk/116998/

Advances in Coupled Data Assimilation, Ensemble Forecasting, and Assimilation of Altimeter Observations. 2020-11

DOI: https://doi.org/10.36071/clivar.79.2020 ISSN: https://portal.issn.org/resource/ISSN/1026-0471

Local Atmosphere–Ocean Predictability: Dynamical Origins, Lead Times, and Seasonality. 2019-11-01

DOI: https://doi.org/10.1175/JCLI-D-18-0817.1

Strongly Coupled Data Assimilation in Multiscale Media: Experiments Using a Quasi‐Geostrophic Coupled Model. 2019-06

DOI: https://doi.org/10.1029/2019MS001652

Climate model shows large-scale wind and solar farms in the Sahara increase rain and vegetation. 2018-09-07

DOI: https://doi.org/10.1126/science.aar5629