E3SM/EAM Simulation Data Outputs

Simulation data provided from the Energy Exascale Earth System Model (E3SM) simulation code in association to a paper to be published, Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks. E3SM is a fully coupled Earth model system that combines inde...

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Bibliographic Details
Main Authors: Banesh, Divya, Panda, Nishant, Biswas, Ayan, Van Roekel, Luke, Oyen, Diane, Urban, Nathan, Grosskopf, Michael, Wolfe, Jonathan, Lawrence, Earl
Format: Dataset
Language:unknown
Published: 2021
Subjects:
Sea ice
Online Access:https://zenodo.org/record/5715462
https://doi.org/10.5281/zenodo.5715462
Description
Summary:Simulation data provided from the Energy Exascale Earth System Model (E3SM) simulation code in association to a paper to be published, Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks. E3SM is a fully coupled Earth model system that combines independent components for atmosphere, ocean, land surface, sea ice and land ice. It includes a driver and flux coupler to exchange data across components, resulting in an integrated modeling system. Through the simulations are fully coupled, we focus our analyses on the atmospheric component, the E3SM Atmosphere Model (EAM) to generate the data. EAM data is discretized using a variable resolution spectral element method, allowing for a regionally refined mesh that can be tessellated at higher resolutions in particular regions of interest. EAM consists of the High-Order Methods Modeling Environment Spectral Element dynamical core and the EAM physics and chemistry parameterizations.

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