Learning bias corrections for climate models using deep neural operators

The GloSea4 ensemble prediction system for seasonal forecasting

Arribas, A.; Glover, M.; Maidens, A.; Peterson, K.; Gordon, M.; MacLachlan, C.; Graham, R.; Fereday, D.; Camp, J.; Scaife, A.; et al. 2011 · 1910

Earlier work this paper cites.

The use of model output statistics (MOS) in objective weather forecasting

Glahn, H. R.; and Lowry, D. A. 1972 · 1972

Earlier work this paper cites.

Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems

Chen, T.; and Chen, H. 1995 · 1995

Earlier work this paper cites.

Global seasonal rainfall forecasts using a coupled ocean–atmosphere model

Stockdale, T. N.; Anderson, D. L.; Alves, J. O. S.; and Balmaseda, M. A. 1998 · 1998

Earlier work this paper cites.

Energy Exascale Earth System Model v1.0

E3SM Project, D. 2018 · 2018

Cited alongside, same era.

Impact of nudging strategy on the climate representativeness and hindcast skill of constrained EAMv1 simulations

Sun, J.; Zhang, K.; Wan, H.; Ma, P.-L.; Tang, Q.; and Zhang, S. 2019 · 2019

Cited alongside, same era.

Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

Lu, L.; Jin, P.; Pang, G.; Zhang, Z.; and Karniadakis, G. E. 2021 · 2021

Cited alongside, same era.

Correcting weather and climate models by machine learning nudged historical simulations

Original

Watt-Meyer, O.; Brenowitz, N. D.; Clark, S. K.; Henn, B.; Kwa, A.; McGibbon, J.; Perkins, W. A.; and Bretherton, C. S. 2021 · 2021

Later among the works it cites.

Learning two-phase microstructure evolution using neural operators and autoencoder architectures

Oommen, V.; Shukla, K.; Goswami, S.; Dingreville, R.; and Karniadakis, G. E. 2022 · 2022

Later among the works it cites.

The ERA5 global reanalysis

Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horányi, A.; Muñoz-Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D.; et al. 2020 · 2049

Closest in time.