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This study provides an overview of the coupled high‐resolution Version 1 of the Energy Exascale Earth System Model (E3SMv1) and documents the characteristics of a 50‐year‐long high‐resolution control simulation with time‐invariant 1950 forcings following the HighResMIP protocol. In terms of global root‐mean‐squared error metrics, this high‐resolution simulation is generally superior to results from the low‐resolution configuration of E3SMv1 (due to resolution, tuning changes, and possibly initialization procedure) and compares favorably to models in the CMIP5 ensemble. Ocean and sea ice simulation is particularly improved, due to better resolution of bathymetry, the ability to capture more variability and extremes in winds and currents, and the ability to resolve mesoscale ocean eddies. The largest improvement in this regard is an ice‐free Labrador Sea, which is a major problem at low resolution. Interestingly, several features found to improve with resolution in previous studies are insensitive to resolution or even degrade in E3SMv1. Most notable in this regard are warm bias and associated stratocumulus deficiency in eastern subtropical oceans and lack of improvement in El Niño. Another major finding of this study is that resolution increase had negligible impact on climate sensitivity (measured by net feedback determined through uniform +4K prescribed sea surface temperature increase) and aerosol sensitivity. Cloud response to resolution increase consisted of very minor decrease at all levels. Large‐scale patterns of precipitation bias were also relatively unaffected by grid spacing. Plain Language Summary The Energy Exascale Earth System Model (E3SM) is a relatively new fully coupled Earth system and climate model used in major international model simulation projects and mission‐defined efforts for the U.S. Department of Energy. This paper describes the first simulation of the model in its high‐resolution configuration. This higher‐resolution version is able to capture the most energetic motions in the ocean, which are poorly represented in standard resolution coupled climate models, as well as the largest of storms in the atmosphere. Evaluation of this simulation confirms the benefits of high resolution found by other models with a few notable exceptions. These discrepancies with other studies are interesting because they provide a richer understanding of how and why resolution affects model bias. Another key finding is that climate and aerosol sensitivity in E3SM is unaffected by resolution change. This affirms the usefulness of coarser‐resolution models for understanding global‐scale climate change. This study also confirms the benefits of increased resolution for studying fine‐scale features such as hurricanes and orographic precipitation. Finally, the high‐resolution version of E3SM is shown to compare favorably to its low‐resolution counterpart and to the models participating in Phase 5 of the Coupled Model Intercomparison Project. Key Points The high‐resolution E3SMv1 model was run for 50 years using 1950 forcing data according to the HighResMIP protocol Higher resolution and associated retuning improved bias relative to coarser versions of E3SMv1, particularly in ocean and sea ice metrics Aerosol and climate sensitivity were relatively unaffected by resolution change; resolution‐related tuning had a larger impact

This study provides comprehensive insight into the notable differences in clouds and precipitation simulated by the Energy Exascale Earth System Model Atmosphere Model version 0 and version 1 (EAMv1). Several sensitivity experiments are conducted to isolate the impact of changes in model physics, resolution, and parameter choices on these differences. The overall improvement in EAMv1 clouds and precipitation is primarily attributed to the introduction of a simplified third‐order turbulence parameterization Cloud Layers Unified By Binormals (along with the companion changes) for a unified treatment of boundary layer turbulence, shallow convection, and cloud macrophysics, though it also leads to a reduction in subtropical coastal stratocumulus clouds. This lack of stratocumulus clouds is considerably improved by increasing vertical resolution from 30 to 72 layers, but the gain is unfortunately subsequently offset by other retuning to reach the top‐of‐atmosphere energy balance. Increasing vertical resolution also results in a considerable underestimation of high clouds over the tropical warm pool, primarily due to the selection for numerical stability of a higher air parcel launch level in the deep convection scheme. Increasing horizontal resolution from 1° to 0.25° without retuning leads to considerable degradation in cloud and precipitation fields, with much weaker tropical and subtropical short‐ and longwave cloud radiative forcing and much stronger precipitation in the intertropical convergence zone, indicating poor scale awareness of the cloud parameterizations. To avoid this degradation, significantly different parameter settings for the low‐resolution (1°) and high‐resolution (0.25°) were required to achieve optimal performance in EAMv1. Plain Language Summary The Energy Exascale Earth System Model (E3SM) is a new and ongoing U.S. Department of Energy (DOE) climate modeling effort to develop a high‐resolution Earth system model specifically targeting next‐generation DOE supercomputers to meet the science needs of the nation and the mission needs of DOE. The increase of model resolution along with improvements in representing cloud and convective processes in the E3SM atmosphere model version 1 has led to quite significant model behavior changes from its earlier version, particularly in simulated clouds and precipitation. To understand what causes the model behavior changes, this study conducts sensitivity experiments to isolate the impact of changes in model physics, resolution, and parameter choices on these changes. Results from these sensitivity tests and discussions on the underlying physical processes provide substantial insight into the model errors and guidance for future E3SM development. Key Points CLUBB along with the companion changes in EAMv1 primarily account for the overall improvements in clouds and precipitation simulation Underestimate of coastal Sc in EAMv1 is due to CLUBB and model tuning; increased vertical resolution partially offsets this degradation The poor scale awareness of EAMv1 requires retuning as resolution increases, which has a large impact on model cloud behavior

Atmospheric chemistry plays a crucial role in Earth system models (ESMs), controlling atmospheric composition and radiative balance; it is highly interactive with the physical climate, biogeochemical cycles, and human systems. However, it often imposes computational challenges in an ESM. Here we develop a full troposphere‐stratosphere interactive chemistry module for the US Department of Energy's Energy Exascale Earth System Model (E3SM). We intentionally build a streamlined module based on E3SM version 2 that interacts with other components and maintains all of major chemical and chemistry‐climate feedbacks. The module incorporates a new, highly efficient tracer advection scheme; linearization of stratospheric chemistry; and abridged tropospheric chemical mechanism with 28 reactive tracers. This new model, E3SM‐chem, can readily perform century‐long climate simulations of ozone, methane, and nitrous oxide based on emission scenarios as well as provide hourly budgets for the gas‐phase radicals that drive aerosol chemistry. We evaluate E3SM‐chem with an atmosphere‐only simulation as in the recent climate model intercomparison project (CMIP6) finding results similar to the other CMIP6 models. For the present‐day, E3SM‐chem matches the standard measurement metrics for stratospheric and tropospheric ozone, surface air quality, other key reactive gases like carbon monoxide, and the methane lifetime. Overall, E3SM‐chem maintains the climate fidelity of the baseline model while adding at most 20% to the computational cost of the atmosphere model. Hence, interactive chemistry can be a default configuration for long climate simulations at resolutions of 1° or finer, which is crucial for producing self‐consistent chemistry‐climate feedbacks that alter the climate system. Plain Language Summary We have developed an interactive atmospheric chemistry module for version 3 of the US Department of Energy's Energy Exascale Earth System Model (E3SM). This new chemistry module significantly enhances E3SM's ability to simulate chemistry‐climate interactions, thereby representing climate processes more accurately. Importantly, these advancements were achieved without compromising the existing climate simulation in quality or computational cost, thus allowing for the capture of self‐consistent chemistry‐climate evolution both in historical periods and future scenario projections allowing atmospheric composition to respond naturally to changing emissions. Key Points A streamlined interactive atmospheric chemistry module has been developed for Earth system model (ESM) version 3 The new module does well on standard atmospheric trace gas metrics while maintaining or improving the existing climate simulation The chemistry package improves E3SM's science capabilities (chemistry‐climate feedbacks, air quality) with minimal added computational cost

Secondary organic aerosols (SOA) are large contributors to fine particle mass loading and number concentration and interact with clouds and radiation. Several processes affect the formation, chemical transformation, and removal of SOA in the atmosphere. For computational efficiency, global models use simplified SOA treatments, which often do not capture the dynamics of SOA formation. Here we test more complex SOA treatments within the global Energy Exascale Earth System Model (E3SM) to investigate how simulated SOA spatial distributions respond to some of the important but uncertain processes affecting SOA formation, removal, and lifetime. We evaluate model predictions with a suite of surface, aircraft, and satellite observations that span the globe and the full troposphere. Simulations indicate that both a strong production (achieved here by multigenerational aging of SOA precursors that includes moderate functionalization) and a strong sink of SOA (especially in the middle upper troposphere, achieved here by adding particle‐phase photolysis) are needed to reproduce the vertical distribution of organic aerosol (OA) measured during several aircraft field campaigns; without this sink, the simulated middle upper tropospheric OA is too large. Our results show that variations in SOA chemistry formulations change SOA wet removal lifetime by a factor of 3 due to changes in horizontal and vertical distributions of SOA. In all the SOA chemistry formulations tested here, an efficient chemical sink, that is, particle‐phase photolysis, was needed to reproduce the aircraft measurements of OA at high altitudes. Globally, SOA removal rates by photolysis are equal to the wet removal sink, and photolysis decreases SOA lifetimes from 10 to ~3 days. A recent review of multiple field studies found no increase in net OA formation over and downwind biomass burning regions, so we also tested an alternative, empirical SOA treatment that increases primary organic aerosol (POA) emissions near source region and converts POA to SOA with an aging time scale of 1 day. Although this empirical treatment performs surprisingly well in simulating OA loadings near the surface, it overestimates OA loadings in the middle and upper troposphere compared to aircraft measurements, likely due to strong convective transport to high altitudes where wet removal is weak. The default improved model formulation (multigenerational aging with moderate fragmentation and photolysis) performs much better than the empirical treatment in these regions. Differences in SOA treatments greatly affect the SOA direct radiative effect, which ranges from −0.65 (moderate fragmentation and photolysis) to −2 W m−2 (moderate fragmentation without photolysis). Notably, most SOA formulations predict similar global indirect forcing of SOA calculated as the difference in cloud forcing between present‐day and preindustrial simulations. Plain language Summary Secondary organic aerosols (SOA) are formed in the atmosphere by oxidation of organic gases emitted from natural biogenic, anthropogenic, and biomass burning sources. In many regions of the atmosphere, SOA greatly contributes to fine particle mass loadings and number concentrations and affects clouds and radiation. Integrating insights from global atmospheric modeling and measurements, we show that strong chemical production achieved here by multigenerational chemistry including moderate fragmentation of SOA precursors and strong chemical sinks represented by particle‐phase photolysis are needed to explain the aircraft‐observed vertical profiles of SOA over multiple regions including North America, equatorial oceans, and the Southern Ocean. Photolysis reduces simulated global SOA lifetimes from 10 to 3 days. Within the same model physics and cloud treatments, we show that changes in SOA chemistry formulations change SOA wet removal lifetimes by a factor of 3. Simulations show that SOA exerts a strong direct radiative forcing in the present day ranging from −0.65 to −2 W m−2. Future measurements and modeling are needed to better constrain the photolytic and heterogeneous chemical removal of SOA at high‐altitude atmospheric conditions. Key Points Gas‐phase multi‐generational aging of SOA precursors is a strong source Loss processes such as gas‐phase fragmentation pathways for SOA products need to be included for a more realistic model representation of OA Both strong sources and sinks are needed to explain global SOA distributions

We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the fingerprint) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

A long-standing discrepancy exists between general circulation models (GCMs) and satellite observations: The multimodel mean temperature of the midtroposphere (TMT) in the tropics warms at approximately twice the rate of observations. Using a large ensemble of simulations from a single climate model, we find that tropical TMT trends (1979–2018) vary widely and that a subset of realizations are within the range of satellite observations. Realizations with relatively small tropical TMT trends are accompanied by subdued sea-surface warming in the tropical central and eastern Pacific. Observed changes in sea-surface temperature have a similar pattern, implying that the observed tropical TMT trend has been reduced by multidecadal variability. We also assess the latest generation of GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). CMIP6 simulations with muted warming over the central and eastern Pacific also show reduced tropical tropospheric warming. We find that 13% of the model realizations have tropical TMT trends within the observed trend range. These simulations are from models with both small and large climate sensitivity values, illustrating that the magnitude of tropical tropospheric warming is not solely a function of climate sensitivity. For global averages, one-quarter of model simulations exhibit TMT trends in accord with observations. Our results indicate that even on 40-y timescales, natural climate variability is important to consider when comparing observed and simulated tropospheric warming and is sufficiently large to explain TMT trend differences between models and satellite data.

Cosmogenic beryllium-10 and beryllium-7, and the ratio of the two (10Be/7Be), are powerful atmospheric tracers of stratosphere–troposphere exchange (STE) processes; however, measurements are sparse for altitudes well above the tropopause. We present a novel high-altitude balloon campaign aimed to measure these isotopes in the mid-stratosphere called Beryllium Isotopes for Resolving Dynamics in the Stratosphere (BIRDIES). BIRDIES targeted gravity waves produced by tropopause-overshooting convection to study their propagation and impact on STE dynamics, including the production of turbulence in the stratosphere. Two custom-designed payloads called FiSH and GASP were flown at altitudes approaching 30 km to measure in situ turbulence and beryllium isotopes (on aerosols), respectively. These were flown on nine high-altitude balloon flights over Kansas, USA, in summer 2022. The atmospheric samples were augmented with a ground-based rainfall collection targeting isotopic signatures of deep convection overshooting. Our GASP samples yielded mostly negligible amounts of both 10Be and 7Be collected in the mid-stratosphere but led to design improvements to increase aerosol capture in low-pressure environments. Observations from FiSH and the precipitation collection were more fruitful. FiSH showed the presence of turbulent velocity, temperature, and acoustic fluctuations in the stratosphere, including length scales in the infra-sonic range and inertial subrange that indicated times of elevated turbulence. The precipitation collection, and subsequent statistical analysis, showed that large spatial datasets of 10Be/7Be can be measured in individual rainfall events with minimum terrestrial contamination. While the spatial patterns in rainfall suggested some evidence for overshooting convection, inter-event temporal variability was clearly observed and predicted with good agreement using the 3D chemical transport model GEOS-CHEM.

Geochemical environments, fates, and effects are modeled for methane released into seawater by the decomposition of climate‐sensitive clathrates. A contemporary global background cycle is first constructed, within the framework of the Parallel Ocean Program. Input from organics in the upper thermocline is related to oxygen levels, and microbial consumption is parameterized from available rate measurements. Seepage into bottom layers is then superimposed, representing typical seabed fluid flow. The resulting CH4 distribution is validated against surface saturation ratios, vertical sections, and slope plume studies. Injections of clathrate‐derived methane are explored by distributing a small number of point sources around the Arctic continental shelf, where stocks are extensive and susceptible to instability during the first few decades of global warming. Isolated bottom cells are assigned dissolved gas fluxes from porous‐media simulation. Given the present bulk removal pattern, methane does not penetrate far from emission sites. Accumulated effects, however, spread to the regional scale following the modeled current system. Both hypoxification and acidification are documented. Sensitivity studies illustrate a potential for material restrictions to broaden the perturbations, since methanotrophic consumers require nutrients and trace metals. When such factors are considered, methane buildup within the Arctic basin is enhanced. However, freshened polar surface waters act as a barrier to atmospheric transfer, diverting products into the deep return flow. Uncertainties in the logic and calculations are enumerated including those inherent in high‐latitude clathrate abundance, buoyant effluent rise through the column, representation of the general circulation, and bacterial growth kinetics.

Probability distribution functions (PDFs) of model inputs that affect the transport and dispersion of a trace gas released from a coastal California nuclear power plant are quantified using ensemble simulations, machine-learning algorithms, and Bayesian inversion. The PDFs are constrained by observations of tracer concentrations and account for uncertainty in meteorology, transport, diffusion, and emissions. Meteorological uncertainty is calculated using an ensemble of simulations of the Weather Research and Forecasting (WRF) model that samples five categories of model inputs (initialization time, boundary layer physics, land surface model, nudging options, and reanalysis data). The WRF output is used to drive tens of thousands of FLEXPART dispersion simulations that sample a uniform distribution of six emissions inputs. Machine-learning algorithms are trained on the ensemble data and used to quantify the sources of ensemble variability and to infer, via inverse modeling, the values of the 11 model inputs most consistent with tracer measurements. We find a substantial ensemble spread in tracer concentrations (factors of 10 to 103), most of which is due to changing emissions inputs (about 80 %), though the cumulative effects of meteorological variations are not negligible. The performance of the inverse method is verified using synthetic observations generated from arbitrarily selected simulations. When applied to measurements from a controlled tracer release experiment, the inverse method satisfactorily determines the location, start time, duration and amount. In a 2 km × 2 km area of possible locations, the actual location is determined to within 200 m. The start time is determined to within 5 min out of 2 h, and the duration to within 50 min out of 4 h. Over a range of release amounts of 10 to 1000 kg, the estimated amount exceeds the actual amount of 146 kg by only 32 kg. The inversion also estimates probabilities of different WRF configurations. To best match the tracer observations, the highest-probability cases in WRF are associated with using a late initialization time and specific reanalysis data products.

Dimethyl sulfide (DMS) is one of the major precursors for aerosols and cloud condensation nuclei in the marine boundary layer over much of the remote ocean. Here we report on coupled climate simulations with a state‐of‐the‐art global ocean biogeochemical model for DMS distribution and fluxes using present‐day and future atmospheric CO2 concentrations. We find changes in zonal averaged DMS flux to the atmosphere of over 150% in the Southern Ocean. This is due to concurrent sea ice changes and ocean ecosystem composition shifts caused by changes in temperature, mixing, nutrient, and light regimes. The largest changes occur in a region already sensitive to climate change, so any resultant local CLAW/Gaia feedback of DMS on clouds, and thus radiative forcing, will be particularly important. A comparison of these results to prior studies shows that increasing model complexity is associated with reduced DMS emissions at the equator and increased emissions at high latitudes. Key Points We show first climate simulations with a next generation DMS model Our simulation shows large poleward shifts in DMS emission by 2100 DMS may be more sensitive to climate change than previously thought