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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 (60 km in the midlatitudes and 30 km at the equator and poles), and river transport (55 km) 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 = −1.65 W/m2) and high equilibrium climate sensitivity (ECS = 5.3 K). Plain Language Summary The U.S. Department of Energy funded the development of a new state‐of‐the‐art Earth system model for research and applications relevant to its mission. The Energy Exascale Earth System Model version 1 (E3SMv1) consists of five interacting components for the global atmosphere, land surface, ocean, sea ice, and rivers. Three of these components (ocean, sea ice, and river) are new and have not been coupled into an Earth system model previously. The atmosphere and land surface components were created by extending existing components part of the Community Earth System Model, Version 1. E3SMv1's capabilities are demonstrated by performing a set of standardized simulation experiments described by the Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima protocol at standard horizontal spatial resolution of approximately 1° latitude and longitude. The model reproduces global and regional climate features well compared to observations. Simulated warming between 1850 and 2015 matches observations, but the model is too cold by about 0.5 °C between 1960 and 1990 and later warms at a rate greater than observed. A thermodynamic analysis of the model's response to greenhouse gas and aerosol radiative affects may explain the reasons for the discrepancy. Key Points This work documents E3SMv1, the first version of the U.S. DOE Energy Exascale Earth System Model The performance of E3SMv1 is documented with a set of standard CMIP6 DECK and historical simulations comprising nearly 3,000 years E3SMv1 has a high equilibrium climate sensitivity (5.3 K) and strong aerosol‐related effective radiative forcing (‐1.65 W/m2)

The Arctic coastal margin receives a disproportionately large fraction of the global river discharge. The bio-geochemistry of the river water as it empties into the marine environment reflects inputs and processes that occur as the water travels from its headwaters. Climate-induced changes to Arctic vegetation and permafrost melt may impact river chemistry. Understanding the impact of river nutrients on coastal marine production, and how this may change in the future, are important for resource managers and community members who monitor and rely on coastal food resources. Using the Energy Exascale Earth System Model we explore the impact of timing and river nutrient concentrations on primary production in each coastal Arctic region and then assess how this influences secondary production and particle fluxes supporting the benthic food web. Our results indicate that while the concentration of Arctic river nitrogen can have a significant impact on annual average nitrogen and primary production in the coastal Arctic, with production increases of up to 20% in the river influenced interior Seas, the timing of the river nutrient inputs into the marine environment appears less important. Bloom timing and partitioning between small and large phytoplankton were minimally impacted by both river nutrient concentration and timing, suggesting that in general, coastal Arctic ecosystem dynamics will continue to be primarily driven by light availability, rather than nutrients. Under a doubling river nutrient scenario, the percentage increase in the POC flux to the benthos on river influenced Arctic coastal shelves was 2-4 times the percentage increase in primary production, suggesting changes to the river nutrient concentration has the potential to modify the Arctic food web structure and dynamics. Generally, the nutrient-induced changes to primary production were smaller than changes previously simulated in response to ice reduction and temperature increase. However, in the Laptev Sea, the production increase resulting from a doubling of river nutrients exceeded the production increase simulated with an atmospheric warming scenario. Dissolved organic carbon is presently poorly represented in the model so its impact on production is hard to simulate. Applying established relationships between modeled DOC, total DOC, and light absorption we illustrate that DOC could play a very important role in modulating production. Our findings highlight the importance of developing more realistic river nutrient and discharge forcing for Earth System Models such that their impact on the critical Arctic coastal domain can be more adequately resolved.

We present the analysis of global sympagic primary production (PP) from 300 years of pre-industrial and historical simulations of the E3SMv1.1-BGC model. The model includes a novel, eight-element sea ice biogeochemical component, MPAS-Seaice zbgc, which is resolved in three spatial dimensions and uses a vertical transport scheme based on internal brine dynamics. Modeled ice algal chlorophyll-a concentrations and column-integrated values are broadly consistent with observations, though chl-a profile fractions indicate that upper ice communities of the Southern Ocean are underestimated. Simulations of polar integrated sea ice PP support the lower bound in published estimates for both polar regions with mean Arctic values of 7.5 and 15.5 TgC/a in the Southern Ocean. However, comparisons of the polar climate state with observations, using a maximal bound for ice algal growth rates, suggest that the Arctic lower bound is a significant underestimation driven by biases in ocean surface nitrate, and that correction of these biases supports as much as 60.7 TgC/a of net Arctic PP. Simulated Southern Ocean sympagic PP is predominantly light-limited, and regional patterns, particularly in the coastal high production band, are found to be negatively correlated with snow thickness.

An ice ecosystem model was coupled to a global dynamic sea ice model to assess large‐scale variability of primary production and ice algal biomass within arctic sea ice. The component models are the Physical Ecosystem Model (PhEcoM) ice ecosystem model and the Los Alamos Sea Ice Model (CICE). Simulated annual arctic sea ice primary production was 15.1 Tg C; within the range of 9 to 73 Tg C estimated using in situ data. The amount of C fixed was >3 Tg C month−1 for March, April, and May. The Bering Sea, Arctic Ocean basins, and the Canadian Archipelago/Baffin Bay were the most productive regions on an annual basis, contributing approximately 24, 18, and another 18%, respectively. High production in the Bering Sea was due to high daily production rates, while the large sea ice coverage in the Canadian Archipelago/Baffin Bay and, in particular, the Arctic Ocean basins resulted in their considerable contribution to sea ice primary production. The simulated trends, patterns, and seasonality of ice algae agree reasonably well with very limited observations. In the model, ice growth rate controls the availability of nutrients to sea ice algae, such that ocean nutrient supply is of secondary importance to ice algal growth. The numerical model results suggest that ice melt rate, which determines the proportional rate of ice algal release, controls the termination of the bloom on large scales. The model described advances the role of sea ice algae in biogeochemical cycling within global climate models. Key Points Simulation results are reasonable compared with in situ observations First large‐scale modeling of pan‐Arctic sea ice primary production High annual production is due to either high daily rates or large ice coverage

Emissions‐driven (prognostic CO2) simulations are essential for representing two‐way carbon‐climate feedback in Earth System Models. We present an emissions‐driven land–atmosphere coupled biogeochemistry (BGC) configuration (BGCLNDATM_progCO2) in version 2.1 of the Energy Exascale Earth System Model (E3SMv2.1). This is the first E3SM configuration that performs land‐atmosphere emission‐hindcasts. Here, we document its implementation, evaluate the model's performance against observations and other models, and propose a structured evaluation protocol for such emissions‐driven simulations. We conducted transient historical simulations (1850–2014) with BGCLNDATM_progCO2 and compare them to reference simulations—a land‐atmosphere coupled simulation without BGC and a standalone land simulation with BGC, both using prescribed CO2 concentrations—and to observations. BGCLNDATM_progCO2 overestimates atmospheric CO2 concentrations by 11–23 ppm yet stays within the 40‐ppm spread CMIP6 emission‐driven models and retains physical climate properties comparable to the reference runs. The CO2 biases are partly attributed to underrepresented oceanic CO2 uptake and inadequate representations of some terrestrial processes. In general, introducing prognostic CO2 did not change physical climate metrics at the global scale but had larger regional effects, particularly over land where spatially heterogeneous CO2 and prognostic leaf area index influenced surface energy balance. Finally, we propose a general evaluation protocol including spin‐up assessment, atmospheric CO2 benchmarking, physical climate evaluation, and land biogeochemical analysis to support scientific rigor and facilitate inter‐model comparisons. The new configuration lays the groundwork for future enhancements, including improved terrestrial biogeochemical processes, integrated marine biogeochemistry, and additional human–Earth system interactions. These developments advance E3SM toward fully coupled emissions‐driven simulations, enabling more accurate carbon–climate feedback projections and informing mitigation policy by providing physically consistent carbon‐budget metrics for mitigation scenarios. Plain Language Summary Understanding the impact of carbon dioxide (CO2) emissions on climate is vital for predicting future changes and crafting effective policies. Earth System Models (ESMs) are essential tools for simulating Earth's climate and assessing various influencing factors. In this study, we extended the Energy Exascale Earth System Model (E3SM)'s capabilities so that CO2 levels are calculated directly from human and natural emissions instead of being prescribed as a single global value. This extension allows for a more realistic representation of CO2 exchange between the atmosphere and land. We conducted historical simulations from 1850 to 2014 using this new development and compared results with observations and other models. Our model slightly overestimates atmospheric CO2 levels compared to measurements but is comparable to other models in capturing key climate features. To help other researchers build and test similar “emission‐driven” models, we created a step‐by‐step evaluation framework that checks CO2 behavior, climate variables, and land‐atmosphere interactions. Our work advances E3SM modeling by accurately representing how CO2 emissions affect Earth's systems. This enhancement lays the groundwork for modeling interactions between human‐Earth interactions, thereby enabling future studies that can inform mitigation and adaption. Key Points Implemented emissions‐driven land–atmosphere biogeochemistry in E3SMv2.1 (BGCLNDATM_progCO2), enabling prognostic CO2 simulations Established a structured evaluation protocol ensuring scientific rigor and facilitating inter‐model comparisons of model performance Emissions‐driven BGCLNDATM_progCO2 simulations maintain a physical climate similar to reference runs with prescribed CO2 concentrations

We document the configuration, tuning, and evaluation of a modified version of the Community Earth System Model version 1 (Hurrell et al., 2013, https://doi.org/10.1175/BAMS-D-12), introduced here as E3SMv0‐HiLAT, intended for study of high‐latitude processes. E3SMv0‐HiLAT incorporates changes to the atmospheric model affecting aerosol transport to high northern latitudes and to reduce shortwave cloud bias over the Southern Ocean. An updated sea ice model includes biogeochemistry that is coupled to an extended version of the ocean model's biogechemistry. This enables cloud nucleation to depend on the changing marine emissions of aerosol precursors, which may be expected in scenarios with strongly changing sea ice extent, oceanic stratification and associated nutrient availability, and atmospheric state. An evaluation of the basic preindustrial state of E3SMv0‐HiLAT is presented in order to ensure that its climate is adequate to support future experimentation. Additional capability is not achieved without some cost, relative to the extraordinarily well‐tuned model from which it was derived. In particular, a reduction of bias in cloud forcing achieved over the Southern Hemisphere also allows for greater Southern Ocean sea ice extent, a tendency that has been partially but not fully alleviated through experimentation and tuning. The most interesting change in the behavior of the model may be its response to greenhouse gas forcing: While the climate sensitivity is found to be essentially unchanged from that of Community Earth System Model version 1, the adjusted radiative forcing has increased from within one standard deviation above that of Coupled Model Intercomparison Project Phase 5 models to nearly two standard deviations. Key Points New Earth system model configuration features improved treatment of sea ice and aerosols Extended marine biogeochemistry enables cloud nucleation to depend on prognostic marine emissions Climate sensitivity is little changed, but adjusted radiative forcing is stronger in modified model

Rivers of the Arctic will become ever more important for the global climate, since they carry a majority of continental dissolved organic carbon flux into the rapidly changing polar ocean. Aqueous organics comprise a wide array of functional groups, several of which are likely to impact coastal and open water biophysical properties. Light attenuation, interfacial films, aerosol formation, gas release and momentum exchange can all be cited. We performed Lagrangian kinetic modeling for the evolution of riverine organic chemistry as the molecules in question make their way from the highlands to Arctic outlets. Classes as diverse as the proteins, sugars, lipids, re-condensates, humics, bio-tracers and small volatiles are all included. Our reduced framework constitutes an idealized northward flow driving a major hydrological discharge rate and primarily representing the Russian Lena. Mountainous, high solute and tundra sources are all simulated, and they meet up at several points between soil and delta process reactors. Turnover rates are parameterized beginning with extrapolated coastal values imposed along a limited tributary network, with connections between different terrestrial sub-ecologies. Temporal variation of our total dissolved matter most closely resembles the observations when we focus on the restricted removal and low initial carbon loads, suggesting relatively slow transformation along the water course. Thus, channel combinations and mixing must play a dominant role. Nevertheless, microbial and photochemical losses help determine the final concentrations for most species. Chemical evolution is distinct for the various functionalities, with special contributions from pre- and post-reactivity in soil and delta waters. Several functions are combined linearly to represent the collective chromophoric dissolved matter, characterized here by its absorption. Tributaries carry the signature of lignin phenols to segregate tundra versus taiga sources, and special attention is paid to the early then marine behaviors of low molecular weight volatiles. Heteropolycondensates comprise the largest percentage of reactive carbon in our simulations due to recombination/accumulation, and they tend to be preeminent at the mouth. Outlet concentrations of individual structures such as amino acids and absorbers lie above threshold values for biophysical influence, on the monolayer and light attenuation. The extent of coastal spreading is examined through targeted regional box modeling, relying on salinity and color for calibration. In some cases, plumes reach the scale of peripheral arctic seas, and amplification is expected during upcoming decades. Conclusions are mapped from the Lena to other boreal discharges, and future research questions are outlined regarding the bonding type versus mass release as permafrost degrades. Dynamic aqueous organic coupling is recommended for polar system models, from headwaters to coastal diluent.

We apply principles of Gibbs phase plane chemistry across the entire ocean-atmosphere interface to investigate aerosol generation and geophysical transfer issues. Marine surface tension differences comprise a tangential pressure field controlling trace gas fluxes, primary organic inputs, and sea spray salt injections, in addition to heat and momentum fluxes. Mapping follows from the organic microlayer composition, now represented in ocean system models. Organic functional variations drive the microforcing, leading to (1) reduced turbulence and (by extension) laminar gas-energy diffusion; plus (2) altered bubble film mass emission into the boundary layer. Interfacial chemical behaviors are, therefore, closely reviewed as the background. We focus on phase transitions among two dimensional “solid, liquid, and gaseous” states serving as elasticity indicators. From the pool of dissolved organic carbon (DOC) only proteins and lipids appear to occupy significant atmospheric interfacial areas. The literature suggests albumin and stearic acid as the best proxies, and we distribute them through ecodynamic simulation. Consensus bulk distributions are obtained to control their adsorptive equilibria. We devise parameterizations for both the planar free energy and equation of state, relating excess coverage to the surface pressure and its modulus. Constant settings for the molecular surrogates are drawn from laboratory study and successfully reproduce surfactant solid-to-gas occurrence in compression experiments. Since DOC functionality measurements are rare, we group them into super-ecological province tables to verify aqueous concentration estimates. Outputs are then fed into a coverage, tension, elasticity code. The resulting two dimensional pressure contours cross a critical range for the regulation of precursor piston velocity, bubble breakage, and primary aerosol sources plus ripple damping. Concepts extend the water-air adsorption theory currently embodied in our OCEANFILMS aerosol emissions package, and the two approaches could be inserted into Earth System Models together. Uncertainties in the logic include kinetic and thermochemical factors operating at multiple scales.

A numerical mechanism connecting ice algal ecodynamics with the buildup of organic macromolecules is tested within modeled pan-Arctic brine channels. The simulations take place offline in a reduced representation of sea ice geochemistry. Physical driver quantities derive from the global sea ice code CICE, including snow cover, thickness and internal temperature. The framework is averaged over ten boreal biogeographic zones. Computed nutrient-light-salt limited algal growth supports grazing, mortality and carbon flow. Vertical transport is diffusive but responds to pore structure. Simulated bottom layer chlorophyll maxima are reasonable, though delayed by about a month relative to observations due to uncertainties in snow variability. Upper level biota arise intermittently during flooding events. Macromolecular concentrations are tracked as proxy proteins, polysaccharides, lipids and refractory humics. The fresh biopolymers undergo succession and removal by bacteria. Baseline organics enter solely through cell disruption, thus the internal carbon content is initially biased low. By including exudation, agreement with dissolved organic or individual biopolymer data is achieved given strong release coupled to light intensity. Detrital carbon then reaches hundreds of micromolar, sufficient to support structural changes to the ice matrix.

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 5.3 K. In E3SMv2, ECS is reduced to 4.0 K 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. Plain Language Summary The U.S. Department of Energy recently released version two of its Energy Exascale Earth System Model (E3SM). E3SMv2 experienced a significant evolution in many of its model components (most notably the atmosphere and sea ice models), and its supporting software infrastructure. In this work, we document the computational performance of E3SMv2 and analyze its ability to reproduce the observed climate. To accomplish this, we utilize the standard Diagnosis and Evaluation and Characterization of Klima experiments augmented with historical simulations for the period 1850–2015. We find that E3SMv2 is nearly twice as fast as its predecessor and more accurately reproduces the observed climate in a number of metrics, most notably clouds and precipitation. We also find that the model's simulated response to increasing carbon dioxide (the equilibrium climate sensitivity) is much more realistic. Unfortunately, E3SMv2 underestimates the global mean surface temperature compared to observations during the second half of historical period. Using sensitivity experiments, where forcing agents (carbon dioxide, aerosols) are selectively disabled in the model, we determine that correcting this problem would require a strong reduction in the impact of aerosols. Key Points E3SMv2 is nearly twice as fast as E3SMv1 with a simulated climate that is improved in many metrics (e.g., precipitation and clouds) Climate sensitivity is substantially lower with a more plausible equilibrium climate sensitivity of 4.0 K (compared to an unlikely value of 5.3 K in E3SMv1) E3SMv2 underestimates the warming in the late historical period due to excessive aerosol‐related forcing