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This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid-latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3K. In E3SMv2, ECS is reduced to 4.0K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single-forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol-related forcing.

This paper describes the first implementation of the Δx = 3.25 km version of the Energy Exascale Earth System Model (E3SM) global atmosphere model and its behavior in a 40‐day prescribed‐sea‐surface‐temperature simulation (January 20 through February 28, 2020). This simulation was performed as part of the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains (DYAMOND) Phase 2 model intercomparison. Effective resolution is found to be ∼6× the horizontal dynamics grid resolution despite using a coarser grid for physical parameterizations. Despite this new model being in an immature and untuned state, moving to 3.25 km grid spacing solves several long‐standing problems with the E3SM model. In particular, Amazon precipitation is much more realistic, the frequency of light and heavy precipitation is improved, agreement between the simulated and observed diurnal cycle of tropical precipitation is excellent, and the vertical structure of tropical convection and coastal stratocumulus look good. In addition, the new model is able to capture the frequency and structure of important weather events (e.g., tropical cyclones, extratropical cyclones including atmospheric rivers, and cold air outbreaks). Interestingly, this model does not get rid of the erroneous southern branch of the intertropical convergence zone nor the tendency for strongest convection to occur over the Maritime Continent rather than the West Pacific, both of which are classic climate model biases. Several other problems with the simulation are identified, underscoring the fact that this model is a work in progress.

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110-km grid spacing), ocean and sea ice (60km in the midlatitudes and 30km at the equator and poles), and river transport (55km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima simulations consisting of a long preindustrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between preindustrial (1850) and present day, the trajectory of the warming diverges from observations in the second half of the twentieth century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERFari+aci=−1.65W/m2) and high equilibrium climate sensitivity (ECS=5.3K).

Author(s): Rasch, PJ; Xie, S; Ma, PL; Lin, W; Wang, H; Tang, Q; Burrows, SM; Caldwell, P; Zhang, K; Easter, RC; Cameron-Smith, P; Singh, B; Wan, H; Golaz, JC; Harrop, BE; Roesler, E; Bacmeister, J; Larson, VE; Evans, KJ; Qian, Y; Taylor, M; Leung, LR; Zhang, Y; Brent, L; Branstetter, M; Hannay, C; Mahajan, S; Mametjanov, A; Neale, R; Richter, JH; Yoon, JH; Zender, CS; Bader, D; Flanner, M; Foucar, JG; Jacob, R; Keen, N; Klein, SA; Liu, X; Salinger, AG; Shrivastava, M; Yang, Y | Abstract: The Energy Exascale Earth System Model Atmosphere Model version 1, the atmospheric component of the Department of Energy's Energy Exascale Earth System Model is described. The model began as a fork of the well-known Community Atmosphere Model, but it has evolved in new ways, and coding, performance, resolution, physical processes (primarily cloud and aerosols formulations), testing and development procedures now differ significantly. Vertical resolution was increased (from 30 to 72 layers), and the model top extended to 60 km (~0.1 hPa). A simple ozone photochemistry predicts stratospheric ozone, and the model now supports increased and more realistic variability in the upper troposphere and stratosphere. An optional improved treatment of light-absorbing particle deposition to snowpack and ice is available, and stronger connections with Earth system biogeochemistry can be used for some science problems. Satellite and ground-based cloud and aerosol simulators were implemented to facilitate evaluation of clouds, aerosols, and aerosol-cloud interactions. Higher horizontal and vertical resolution, increased complexity, and more predicted and transported variables have increased the model computational cost and changed the simulations considerably. These changes required development of alternate strategies for tuning and evaluation as it was not feasible to “brute force” tune the high-resolution configurations, so short-term hindcasts, perturbed parameter ensemble simulations, and regionally refined simulations provided guidance on tuning and parameterization sensitivity to higher resolution. A brief overview of the model and model climate is provided. Model fidelity has generally improved compared to its predecessors and the CMIP5 generation of climate models.

Generating finite-element meshes is a serious bottleneck for large parallel simulations. When mesh generation is limited to serial machines and element counts approach a billion, this bottleneck becomes a roadblock. Pamgen is a parallel mesh generation library that allows on-the-fly scalable generation of hexahedral and quadrilateral finite element meshes for several simple geometries. It has been used to generate more that 1.1 billion elements on 17,576 processors. Pamgen generates an unstructured finite element mesh on each processor at the start of a simulation. The mesh is specified by commands passed to the library as a 'C'-programming language string. The resulting mesh geometry, topology, and communication information can then be queried through an API. pamgen allows specification of boundary condition application regions using sidesets (element faces) and nodesets (collections of nodes). It supports several simple geometry types. It has multiple alternatives for mesh grading. It has several alternatives for the initial domain decomposition. Pamgen makes it easy to change details of the finite element mesh and is very useful for performance studies and scoping calculations.