Published in JAMES, 2024
Citation: Mansfield, L. A., & Sheshadri, A. (2024). Uncertainty quantification of a machine learning subgrid-scale parameterization for atmospheric gravity waves. Journal of Advances in Modeling Earth Systems, 16, e2024MS004292. https://doi.org/10.1029/2024MS004292
Published in JAMES, 2024
Citation: King, R. C., Mansfield, L. A., & Sheshadri, A. (2024). Bayesian history matching applied to the calibration of a gravity wave parameterization. Journal of Advances in Modeling Earth Systems, 16, e2023MS004163. https://doi.org/10.1029/2023MS004163
Published in Journal of Advances in Modeling Earth Systems, 2023
Citation: Mansfield, L. A., Gupta, A., Burnett, A. C., Green, B., Wilka, C., & Sheshadri, A. (2023). Updates on model hierarchies for understanding and simulating the climate system: A focus on data-informed methods and climate change impacts. Journal of Advances in Modeling Earth Systems, 15, e2023MS003715. https://doi.org/10.1029/2023MS003715
Published in Journal of Advances in Modeling Earth Systems, 2022
Citation: Mansfield, L. A., & Sheshadri, A. (2022). Calibration and uncertainty quantification of a gravity wave parameterization: A case study of the Quasi-Biennial Oscillation in an intermediate complexity climate model. Journal of Advances in Modeling Earth Systems, 14, e2022MS003245. https://doi.org/10.1029/2022MS003245
Published in University of Reading, 2021
Citation: Mansfield, L.A., Machine Learning, Emulation and Bayesian Dimension Reduction for Climate Change Projection, University of Reading, UK
Published in npj Climate and Atmospheric Science volume 3, 44, 2020
Citation: Mansfield, L.A., Nowack, P.J., Kasoar, M. et al. Predicting global patterns of long-term climate change from short-term simulations using machine learning. npj Clim Atmos Sci 3, 44 (2020). https://www.nature.com/articles/s41612-020-00148-5