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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)

Reliable simulation, prediction, and complete theoretical understanding of atmospheric blocking remain challenging despite its significant socio-economic impacts. Generations of climate models have notoriously underestimated blocking frequency, particularly over the Euro-Atlantic sector. Identifying factors controlling blocking frequency and dynamics is therefore essential for improving its simulation. Here, using a cloud-locking experiment, we show that cloud radiative effects (CREs) significantly increase the frequency of Euro-Atlantic blocking. CREs enhance upstream diabatic source of wave activity, both directly through longwave heating and indirectly through their feedback on latent heating, with the latter playing the dominant role. The resulting increase in the upstream diabatic source feeds into local wave activity downstream and promotes blocking formation. Qualitatively similar results are shown by multi-model experiments with radiatively inactive clouds to longwave radiation, albeit with a larger impact from mean-state changes. The results underscore the necessity of accurately representing cloud-radiation interactions in weather and climate models for improved prediction of blocking events. This study uses climate model experiments and shows that radiative heating from the presence of clouds can substantially increase the frequency of Euro-Atlantic atmospheric blocking, highlighting the need to better represent cloud-radiation interactions for improved prediction of extreme weather.

Simulations of the slab ocean configuration of the coupled Energy Exascale Earth System Model (E3SM) were used to isolate the role of poleward ocean heat transport (OHT) in shaping the climate and its response to CO2 forcing. Imposed changes to mean‐state OHT produce compensating changes in atmospheric heat transport (AHT) that are mediated by changes in surface evaporation. A reduction of maximum OHT by 0.56 PW (32%) reduces the global mean surface air temperature by 3.6°C. However, this cooler mean state exhibits 1.2°C more warming under CO2 quadrupling, with the largest differences occurring at high latitudes. The amplified warming arises from stronger surface albedo and lapse rate feedbacks in polar regions and a shortwave cloud feedback in the southern midlatitudes. These results highlight the critical role of mean‐state OHT in modulating mean‐state climate, the partitioning between the OHT and AHT, and climate sensitivity.

Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.

Nudging techniques are commonly employed to constrain atmospheric simulations toward observed states, facilitating model evaluation and sensitivity studies. However, if applied improperly – particularly to thermodynamic variables such as temperature and humidity – nudging can distort physical processes and introduce spurious biases, undermining the credibility of the simulations. This study presents an improved nudging implementation that applies vertically modulated tendencies to reduce adverse impacts on model physics. The framework is tested in version 2 of the Energy Exascale Earth System Model (EAMv2) using a suite of hindcast simulations nudged toward ERA5 reanalysis. We systematically evaluate the individual and combined effects of nudging wind, temperature, and humidity fields on the model's ability to represent large-scale atmospheric states and high-impact weather systems. Results show that the revised strategy – particularly when nudging temperature and humidity at selected levels – enhances hindcast skill by improving agreement with ERA5 without degrading the hydrological cycle or precipitation processes. Additional improvements in surface temperature, outgoing longwave radiation, and precipitation biases are achieved through targeted nudging of land-surface variables. The proposed approach strengthens the representation of large-scale conditions relevant to tropical cyclones, atmospheric rivers, and extratropical cyclones in the low-resolution EAMv2. These findings demonstrate that carefully designed thermodynamic nudging, especially of temperature and humidity, improves the realism of constrained simulations and broadens the utility of nudged EAMv2 for atmospheric modeling, machine learning, and high-impact weather research.

A cloud-resolving model is used to test the hypothesis that radiative cooling by water vapor emission is the primary control on the temperature of tropical anvil clouds. The temperature of ice clouds in the simulation can be increased or decreased by changing only the emissivity of water vapor in the upper troposphere. The effect of the model’s fixed ozone profile on stability creates a pressure-dependent inhibition of convection, leading to a small warming in cloud-top temperature as SST is increased. Increasing stratospheric water vapor also warms the cloud-top temperature slightly. Changing the latent heat of fusion reduces the cloud fraction at high altitudes, but does not significantly change temperature at which cloud fraction peaks in the upper troposphere. The relationship between radiatively driven horizontal mass convergence and cloud fraction that causes cloud temperature to be insensitive to surface temperature is preserved when a large model domain is used so that convection aggregates in a small part of the model domain.

A large set of Green’s function-type experiments is performed with q-flux forcings mimicking the effects of the ocean heat uptake (OHU) to examine the global surface air temperature (SAT) sensitivities to the location of the forcing. The result of the experiments confirms the earlier notion derived from experiments with different model complexities that the global mean SAT is far more sensitive to the oceanic forcing from high latitudes than the tropics. Remarkably, no matter in which latitude the q-flux forcings are placed, the SAT response is always characterized by a feature of polar amplification, implicating that it is intrinsic to our climate system. Considerable zonal asymmetry is also present in the efficacy of the tropical OHU, with the tropical eastern Pacific being much more efficient than the Indian Ocean and tropical Atlantic in driving global SAT warming by exciting the leading neutral mode of the SAT that projects strongly onto global mean warming. Using a radiative kernel, feedback analysis is also conducted to unravel the underlying processes responsible for the spatial heterogeneity in the global OHU efficacy, the polar amplification structures, and the tropical altruism of sharing the warmth with remote latitudes. Warming “altruism” for a q flux at a given latitude is also investigated in terms of the ratio of the induced remote latitudes versus the directly forced local warming. It is found that the tropics are much more altruistic than higher latitudes because of the high-energy transport efficiency of the Hadley circulation.

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a multiple atmosphere multiple land (MAML) framework in the superparamaterized version of E3SM (SP‐E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud‐resolving scale and their interactions with atmosphere. Comparing to the standard SP‐E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., multiple atmosphere single land (MASL)), the impact of MAML on the strength of land‐atmosphere coupling is limited, partly because the current implementation mainly facilitates one‐way coupling between the cloud‐resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP‐E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (P‐E) is primarily driven by the change in large‐scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P‐E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P‐E by decreasing the NGMS. Finally, future development in the MAML framework is discussed. Plain Language Summary Land‐atmosphere interactions such as soil moisture‐precipitation feedback occur at a wide range of spatial scales. For example, spatial variability of surface fluxes such as radiation and precipitation can influence surface latent and sensible heat fluxes, which further influence turbulent mixing processes in the boundary layer and cloud and precipitation. Current global climate models (GCMs) have difficulties in representing land‐atmosphere interactions at scales smaller than the GCM grid (subgrid scales). To meet this challenge, we employ a novel framework, called multiple atmosphere multiple land (MAML), in a superparamaterized version of E3SM (SP‐E3SM) in which a cloud resolving model is embedded within each GCM grid to better resolve clouds and convection. MAML explicitly simulates the subgrid variabilities of land states and fluxes at scale of ∼1 km and provides feedback to the atmosphere. The use of MAML is shown to have a limited effect on the strength of land‐atmosphere coupling due to the current one‐way subgrid land‐atmosphere interaction setup. Despite the limited effect, MAML increases the rainfall in India, Amazon, and Central Africa, which reduces the dry bias in the model. Key Points A multiple atmosphere multiple land (MAML) framework of land‐atmosphere coupling is implemented in the super‐parameterized E3SM (SP‐E3SM) MAML increases precipitation in India, Central Africa, and Amazon by increasing water vapor and hence large‐scale moisture convergence MAML's impact on land‐atmosphere interactions is limited by the current setup of one‐way coupling on cloud‐resolving scales

The effect of cloud‐radiation interactions on cloud properties is examined in the context of a limited‐domain cloud‐resolving model. The atmospheric cloud radiative effect (ACRE) influences the areal extent of tropical high clouds in two distinct ways. The first is through direct radiative destabilization of the elevated cloud layers, mostly as a result of longwave radiation heating the cloud bottom and cooling the cloud top. The second effect is radiative stabilization, whereby cloud radiative heating of the atmospheric column stabilizes the atmosphere to deep convection. In limited area domain simulations, the stabilizing (or indirect) effect is the dominant role of the cloud radiative heating, thus reducing the cloud cover in simulations where ACRE is included compared to those where it is removed. Direct cloud radiative heating increases high cloud fraction, decreases mean cloud optical depth, and increases cloud top temperature. The indirect cloud radiative heating decreases high cloud fraction, but also decreases mean cloud optical depth and increases cloud top temperature. The combination of these effects increases the top‐of‐atmosphere cloud radiative effect. In mock‐Walker circulation experiments, the decrease in high cloud amount owing to radiative stabilization tends to cancel out the increase in high cloud amount owing to the destabilization within the cloud layer. The changes in cloud optical depth and cloud top pressure, however, are similar to those produced in the limited area domain simulations. Key Points: ACRE simultaneously enhances and reduces high cloud amount through two different physical mechanisms. High cloud reduction through indirect cloud heating dominates the cloud response in limited‐domain experiments ACRE produces more high, optically thin clouds relative to high, optically thick clouds, and thus increases TOA CRE

In this study, we analyze the realism with which tropical cyclones (TCs) are simulated in the fully coupled low‐ and high‐resolution Energy Exascale Earth System Model (E3SM) version 1, with a focus on the latter. Compared to the low‐resolution (grid spacing of ∼1°), the representation of TCs improves considerably in the high‐resolution configuration (grid spacing of ∼0.25°). Significant improvements are found in the global TC frequency, TC lifetime maximum intensities, and the relative distribution of TCs among the different basins. However, at both resolutions, spurious TC activity is found in some basins, notably in the subtropical regions. Contrasting the simulated large‐scale TC environment with observations reveals that the model environment is unrealistically conducive for TC development in those regions. Further analysis indicates that these biases are likely related to those in thermodynamic potential intensity, caused by systematic SST biases, and vertical wind shear in the coupled model. TC‐ocean interaction is also examined in the high‐resolution configuration of the model. The salient features of the ocean's response to TC‐induced mixing and the ocean's impact on TC intensification are well‐reproduced. Finally, an evaluation of the influence of El Niño Southern Oscillation (ENSO) on TCs in the high‐resolution configuration of the model reveals that the ENSO‐TC relationship in the model has the right sign and is significant for the North Atlantic and Northwest Pacific, albeit weaker than in observations. In summary, the high‐resolution configuration of the E3SM model simulates TC activity reasonably and hence could be a useful tool for TC‐related research. Plain Language Summary Considering the wide range of spatiotemporal scales governing tropical cyclones (TCs), high‐resolution numerical models that can resolve both small‐scale and large‐scale processes are needed to simulate TCs realistically. In this study, we describe the simulation of TCs in version 1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) model with a focus on results from the high‐resolution configuration (spatial resolution of 0.25° in the atmosphere). When compared to the simulation at the low or standard resolution configuration (spatial resolution of 1° in the atmosphere), the salient features of TCs, such as their frequency distribution among the various basins and their strength, improve considerably in the high‐resolution configuration, underlining the value of high‐resolution modeling. Further, the high‐resolution configuration of the model realistically simulates the interaction between TCs and the ocean beneath them, which is a fundamental aspect of their development. However, our analysis also reveals that systematic errors in the simulated climate can cause misrepresentation of the model TC environment, leading to spurious TC activity in certain regions and a weaker control exerted by El Niño‐Southern Oscillation. Overall, the high‐resolution E3SM well represents the global TC climatology, supporting it as a valuable tool for studying TCs. Key Points Under a variety of metrics, simulated TCs are significantly improved in high‐resolution versus low‐resolution E3SM configurations Spurious TC activity in the model can be well‐explained by errors in the simulation of sea surface temperatures and the vertical wind shear TC‐induced oceanic cooling and the ocean's negative feedback on TCs are well‐simulated in the high‐resolution configuration of the model