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Irrigation supports agricultural production, but widespread use of irrigation can perturb the regional and global water cycle. The one‐way coupled irrigation scheme used in some land surface models and Earth system models assumes that surface water demand is always met and ignores the surface water constraints, leading to overestimation of surface water usage, underestimation of groundwater pumping, and unrealistic simulation of their seasonal variability. To better represent the irrigation processes, a two‐way coupled irrigation scheme is developed within the Energy Exascale Earth System Model (E3SM). The new irrigation scheme simulates irrigation water demand and applies irrigation water in E3SM Land Model (ELM), which is coupled to a river routing model and a water management model (MOSART‐WM) that simulate streamflow, reservoir operations, and irrigation water supply. With two‐way coupling, surface water irrigation is constrained by the available runoff, streamflow, and reservoir storage. Simulations were performed for 1979–2008 at 0.5° spatial resolution to estimate irrigation surface water and groundwater use and their seasonality in global and large river basin scales. Compared to one‐way coupling, the two‐way coupling scheme (1) estimates less surface water withdrawal and less return flow due to the surface water constraint; (2) better represents groundwater recharge and groundwater level decline at global scale; and (3) is able to capture the seasonal dynamics of irrigation water allocations which reflect the local water conditions. The new development is an important step to more realistically account for the interactions between human water use and the terrestrial water cycle in an Earth system model. Plain Language Summary A novel method is developed in the Energy Exascale Earth System Model (E3SM) to better represent the irrigation processes. The old method applies the irrigation water by assuming there is no limitation on the water availability. This will lead to overestimation of irrigation withdrawal in dry conditions. The new development, however, constrains the irrigation withdrawal by evaluating river water availability every computational time step. It is an important step to more realistically represent the interactions between water management and natural hydrologic processes. Compared to the old method, the new method (1) estimates less surface water withdrawal and less return flow due to the surface water constraint; (2) better represents groundwater recharge and groundwater level decline at global scale; and (3) is able to capture the seasonal dynamics of irrigation water allocations which reflect the local water conditions. The new development is an important step to more realistically account for the interactions between human water use and the terrestrial water cycle in an Earth system model. Key Points A two‐way coupled irrigation scheme is developed in E3SM to dynamically constrain surface water withdrawal based on water availability With two‐way coupling, the models estimate less surface water withdrawal and less return flow compared to one‐way coupled simulations With surface water constraint, groundwater recharge, groundwater decline, and the seasonal dynamics of water allocation are better captured

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1‐Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1‐Arctic) historical simulations (1950–2014) with the uniform low‐resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large‐scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high‐resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales. Plain Language Summary Earth system models (ESMs) are essential tools for understanding the climate system and projecting future changes, but standard coarse model resolutions often fail to realistically represent regional processes and topography, particularly in the polar regions, while uniform high‐resolution grids are too computationally expensive. To address this, regionally refined meshes (RRMs) have been developed within ESMs to provide high‐resolution simulations in target areas, improving the accuracy of regional climate simulations while maintaining computational efficiency. This study looks at how well the U.S. DOE's RRM model, E3SMv2.1‐Arctic, performs in simulating Arctic climate. The RRM, which focuses on the Arctic region, is compared to a uniform low‐resolution version, as well as to observations and reanalysis data. The RRM does a better job of simulating important Arctic climate features like precipitation, atmospheric circulation, clouds, sea ice and atmospheric rivers compared to the low‐resolution model. However, it shows some seasonal temperature biases, reducing the cold bias in summer but increasing the warm bias in winter. The RRM also underestimates winter sea ice, consistent with the warm winter bias. While the study demonstrates the advantages of using high‐resolution models to better understand Arctic climate changes, it also notes that some biases remain despite the increased resolution. Key Points Evaluation of atmosphere‐land‐ocean‐ice fully coupled E3SM‐Arctic historical simulations with regionally refined meshes for the Arctic E3SM‐Arctic reduces bias in precipitation, clouds and atmospheric rivers due to better topography compared to its low‐resolution counterpart Higher resolution leads to an increased albedo feedback and more accurate sea ice area, but with faster sea ice melting due to a warm bias

Meltwater from the Greenland Ice Sheet can alter the continental shelf/slope circulation and cross-shelf freshwater fluxes and limit deep convection in adjacent basins through surface freshening. We explore the impacts on the West Greenland Current and eastern Labrador Sea with different vertical distributions of the meltwater forcing. In this study, we present the results from global coupled ocean/sea ice simulations, forced with atmospheric reanalysis, that are mesoscale eddy-active (∼2–3-km horizontal spacing) and eddy-permitting (∼6–7-km horizontal spacing) in the study region. We compare the West Greenland Current in mesoscale eddy-active and eddy-permitting without meltwater to highlight the role of small-scale features. The mesoscale eddy-active configuration is then used to assess the change in the eastern Labrador Sea when meltwater is added to the surface or vertically distributed to account for mixing within fjords. In both simulations with meltwater, the West Greenland and West Greenland Coastal Currents are faster than in the simulation with no meltwater; their mean surface speeds are the highest in the vertical distribution case. In the latter case, there is enhanced baroclinic conversion at the shelf break compared to the simulation with no meltwater. When meltwater is vertically distributed, there is an increase in baroclinic conversion at the shelf break associated with increased eddy kinetic energy. In addition, in the eastern Labrador Sea, the salinity is lower and the meltwater volume is greater when meltwater is vertically distributed. Therefore, the West Greenland Current is sensitive to how meltwater is added to the ocean with implications for the freshening of the Labrador Sea.

This study focuses on the performance of the elastic–viscous–plastic (EVP) dynamical solver within the sea ice model, CICE v6.5.1. The study has been conducted in two steps. First, the standard EVP solver was extracted from CICE for experiments with refactored versions, which are used for performance testing. Second, one refactored version was integrated and tested in the full CICE model to demonstrate that the new algorithms do not significantly impact the physical results.The study reveals two dominant bottlenecks, namely (1) the number of Message Parsing Interface (MPI) and Open Multi-Processing (OpenMP) synchronization points required for halo exchanges during each time step combined with the irregular domain of active sea ice points and (2) the lack of single-instruction, multiple-data (SIMD) code generation.The standard EVP solver has been refactored based on two generic patterns. The first pattern exposes how general finite differences on masked multi-dimensional arrays can be expressed in order to produce significantly better code generation by changing the memory access pattern from random access to direct access. The second pattern takes an alternative approach to handle static grid properties.The measured single-core performance improvement is more than a factor of 5 compared to the standard implementation. The refactored implementation of strong scales on the Intel® Xeon® Scalable Processors series node until the available bandwidth of the node is used. For the Intel® Xeon® CPU Max series, there is sufficient bandwidth to allow the strong scaling to continue for all the cores on the node, resulting in a single-node improvement factor of 35 over the standard implementation. This study also demonstrates improved performance on GPU processors.

A new collaborative organization for sea-ice model development, the CICE Consortium, has devised quality control procedures to maintain the integrity of its numerical codes’ physical representations, enabling broad participation from the scientific community in the Consortium’s open software development environment. Using output from five coupled and uncoupled configurations of the Los Alamos Sea Ice Model, CICE, we formulate quality control methods that exploit common statistical properties of sea-ice thickness, and test for significant changes in model results in a computationally efficient manner. New additions and changes to CICE are graded into four categories, ranging from bit-for-bit amendments to significant, answer-changing upgrades. These modifications are assessed using criteria that account for the high level of autocorrelation in sea-ice time series, along with a quadratic skill metric that searches for hemispheric changes in model answers across an array of different CICE configurations. These metrics also provide objective guidance for assessing new physical representations and code functionality. This article is part of the theme issue ‘Modelling of sea-ice phenomena’.

The Energy Exascale Earth System Model (E3SM) is a state-of-the-science Earth system model (ESM) with the ability to focus horizontal resolution of its multiple components in specific areas. Regionally refined global ESMs are motivated by the need to explicitly resolve, rather than parameterize, relevant physics within the regions of refined resolution, while offering significant computational cost savings relative to the respective cost of configurations with high-resolution (HR) everywhere on the globe. In this paper, we document results from the first Arctic regionally refined E3SM configuration for the ocean and sea-ice components (E3SM-Arctic-OSI), while employing data-based atmosphere, land, and hydrology components. Our aim is an improved representation of the Arctic coupled ocean and sea-ice state, its variability and trends, and the exchanges of mass and property fluxes between the Arctic and the sub-Arctic. We find that E3SM-Arctic-OSI increases the realism of simulated Arctic ocean and sea-ice conditions compared to a similar low-resolution E3SM simulation without the Arctic regional refinement in ocean and sea-ice components (E3SM-LR-OSI). In particular, exchanges through the main Arctic gateways are greatly improved with respect to E3SM-LR-OSI. Other aspects, such as the Arctic freshwater content variability and sea-ice trends, are also satisfactorily simulated. Yet, other features, such as the upper-ocean stratification and the sea-ice thickness distribution, need further improvements, involving either more advanced parameterizations, model tuning, or additional grid refinements. Overall, E3SM-Arctic-OSI offers an improved representation of the Arctic system relative to E3SM-LR-OSI, at a fraction (15 %) of the computational cost of comparable global high-resolution configurations, while permitting exchanges with the lower-latitude oceans that cannot be directly accounted for in Arctic regional models.

During the 42-year period (1979–2020) of satellite measurements, four major winter (December–March) polynyas have been observed north of Greenland: one in December 1986 and three in the last decade, i.e., February of 2011, 2017, and 2018. The 2018 polynya was unparalleled in its magnitude and duration compared to the three previous events. Given the apparent recent increase in the occurrence of these extreme events, this study aims to examine their evolution and causality, in terms of forced versus natural variability. The limited weather station and remotely sensed sea ice data are analyzed combining with output from the fully coupled Regional Arctic System Model (RASM), including one hindcast and two ensemble simulations. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact (i.e., no significant ice melting) on the evolution of the observed winter open-water episodes in the region. Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss in all four polynyas. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds greater than 10 m s−1) blowing persistently over the study region for at least 2 d or more were required over the study region to mechanically redistribute some of the thickest Arctic sea ice out of the region and thus to create open-water areas (i.e., a latent heat polynya). To assess the role of internal variability versus external forcing of such events, we carried out and examined results from the two RASM ensembles dynamically downscaled with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles (initialized 30 years apart: one in December 1985 and another in December 2015), 17 and 16 winter polynyas were produced north of Greenland, respectively. The frequency of polynya occurrence had no apparent sensitivity to the initial sea ice thickness in the study area pointing to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations, and probabilistic forecasts of Arctic events, such as the ones being investigated here and elsewhere.

This paper discusses the sensitivity of tropical cyclone climatology to surface coupling strategy in high-resolution configurations of the Community Earth System Model. Using two supported model setups, we demonstrate that the choice of grid on which the lowest model level wind stress and surface fluxes are computed may lead to differences in cyclone strength in multi-decadal climate simulations, particularly for the most intense cyclones. Using a deterministic framework, we show that when these surface quantities are calculated on an ocean grid that is coarser than the atmosphere, the computed frictional stress is misaligned with wind vectors in individual atmospheric grid cells. This reduces the effective surface drag, and results in more intense cyclones when compared to a model configuration where the ocean and atmosphere are of equivalent resolution. Our results demonstrate that the choice of computation grid for atmosphere–ocean interactions is non-negligible when considering climate extremes at high horizontal resolution, especially when model components are on highly disparate grids.

Meltwater from the Greenland Ice Sheet can alter the continental shelf/slope circulation, cross-shelf freshwater fluxes, and limit deep convection in adjacent basins through surface freshening. We explore the impacts on the West Greenland Current and Eastern Labrador Sea with different vertical distributions of the meltwater forcing. In this study, we present results from global coupled ocean/sea-ice simulations, forced with atmospheric reanalysis, that are mesoscale eddy-active ( 2–3 km horizontal spacing) and eddy-permitting ( 6–7 km horizontal spacing) in the study region. We compare the West Greenland Current in mesoscale eddy-active and eddy-permitting without meltwater to highlight the role of small scale features. Here, the mesoscale eddy-active configuration is then used to assess the change in the Eastern Labrador Sea when meltwater is added to the surface or vertically distributed to account for mixing within fjords. In both simulations with meltwater, the West Greenland and West Greenland Coastal Currents are faster than in the simulation with no meltwater; their mean surface speeds are highest in the vertical distribution case. In the latter case, there is enhanced baroclinic conversion at the shelf break compared to the simulation with no meltwater. When meltwater is vertically distributed, there is an increase in baroclinic conversion at the shelf break associated with increased eddy kinetic energy. In addition, in the Eastern Labrador Sea the salinity is lower and the meltwater volume greater when meltwater is vertically distributed. Therefore, the West Greenland Current is sensitive to how meltwater is added to the ocean with implications for the freshening of the Labrador Sea.

Climate projections depend on scenarios of fossil fuel emissions and land use change, and the Intergovernmental Panel on Climate Change (IPCC) AR5 parallel process assumes consistent climate scenarios across integrated assessment and earth system models (IAMs and ESMs). The CMIP5 (Coupled Model Intercomparison Project Phase 5) project used a novel \"land use harmonization\" based on the Global Land use Model (GLM) to provide ESMs with consistent 1500–2100 land use trajectories generated by historical data and four IAMs. A direct coupling of the Global Change Assessment Model (GCAM), GLM, and the Community ESM (CESM) has allowed us to characterize and partially address a major gap in the CMIP5 land coupling design: the lack of a corresponding land cover harmonization. For RCP4.5, CESM global afforestation is only 22% of GCAM's 2005 to 2100 afforestation. Likewise, only 17% of GCAM's 2040 afforestation, and zero pasture loss, were transmitted to CESM within the directly coupled model. This is a problem because GCAM relied on afforestation to achieve RCP4.5 climate stabilization. GLM modifications and sharing forest area between GCAM and GLM within the directly coupled model did not increase CESM afforestation. Modifying the land use translator in addition to GLM, however, enabled CESM to include 66% of GCAM's afforestation in 2040, and 94% of GCAM's pasture loss as grassland and shrubland losses. This additional afforestation increases CESM vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, which demonstrates that CESM without additional afforestation simulates a different RCP4.5 scenario than prescribed by GCAM. Similar land cover inconsistencies exist in other CMIP5 model results, primarily because land cover information is not shared between models. Further work to harmonize land cover among models will be required to increase fidelity between IAM scenarios and ESM simulations and realize the full potential of scenario-based earth system simulations.