6 citations · 17 across the 5 of their papers we have counts for
5 papers
Retrofitting Earth System Models with Cadence-Limited Neural Operator Updates
Aniruddha Bora, Shixuan Zhang, Khemraj Shukla +3
Coarse resolution, imperfect parameterizations, and uncertain initial states and forcings limit Earth-system model (ESM) predictions. Traditional bias correction via data assimilat…
Statistics of extreme events in coarse-scale climate simulations via machine learning correction operators trained on nudged datasets
Alexis-Tzianni Charalampopoulos, Shixuan Zhang, Bryce Harrop +2
This work presents a systematic framework for improving the predictions of statistical quantities for turbulent systems, with a focus on correcting climate simulations obtained by…
Learning bias corrections for climate models using deep neural operators
Aniruddha Bora, Khemraj Shukla, Shixuan Zhang +3
Numerical simulation for climate modeling resolving all important scales is a computationally taxing process. Therefore, to circumvent this issue a low resolution simulation is per…
CondiDiag1.0: A flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)
Hui Wan, Kai Zhang, Philip J. Rasch +4
Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes such as the resolved and unresolved fluid dynamics, radiative…
Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1
Hui Wan, Shixuan Zhang, Philip J. Rasch +3
This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System…