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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.

The sea ice component of the Community Earth System Model version 2 (CESM2) contains new “mushy‐layer” physics that simulates prognostic salinity in the sea ice, with consequent modifications to sea ice thermodynamics and the treatment of melt ponds. The changes to the sea ice model and their influence on coupled model simulations are described here. Two simulations were performed to assess the changes in the vertical thermodynamics formulation with prognostic salinity compared to a constant salinity profile. Inclusion of the mushy layer thermodynamics of Turner et al. (2013, https://doi.org/10.1002/jgrc.20171) in a fully coupled Earth system model produces thicker and more extensive sea ice in the Arctic, with relatively unchanged sea ice in the Antarctic compared to simulations using a constant salinity profile. While this is consistent with the findings of uncoupled ice‐ocean model studies, the role of the frazil and congelation growth is more important in fully coupled simulations. Melt pond drainage is also an important contribution to simulated ice thickness differences as also found in the uncoupled simulations of Turner and Hunke (2015; https://doi.org/10.1002/2014JC010358). However, it is an interaction of the ponds and the snow fraction that impacts the surface albedo and hence the top melt. The changes in the thermodynamics and resulting ice state modify the ice‐ocean‐atmosphere fluxes with impacts on the atmosphere and ocean states, particularly temperature. Plain Language Summary We investigate the role of a new approach for sea ice thermodynamics in the Community Earth System Model, based on mushy‐layer theory. The new approach produces thicker sea ice in the Arctic with subsequent impacts on the atmosphere and ocean. Key Points The choice of sea ice thermodynamics impacts the sea ice mean state The choice of sea ice thermodynamics has a modest impact on the coupled system

The Energy Exascale Earth System Model (E3SM) is a new coupled Earth system model sponsored by the U.S Department of Energy. Here we present E3SM global simulations using active ocean and sea ice that are driven by the Coordinated Ocean‐ice Reference Experiments II (CORE‐II) interannual atmospheric forcing data set. The E3SM ocean and sea ice components are MPAS‐Ocean and MPAS‐Seaice, which use the Model for Prediction Across Scales (MPAS) framework and run on unstructured horizontal meshes. For this study, grid cells vary from 30 to 60 km for the low‐resolution mesh and 6 to 18 km at high resolution. The vertical grid is a structured z‐star coordinate and uses 60 and 80 layers for low and high resolution, respectively. The lower‐resolution simulation was run for five CORE cycles (310 years) with little drift in sea surface temperature (SST) or heat content. The meridional heat transport (MHT) is within observational range, while the meridional overturning circulation at 26.5°N is low compared to observations. The largest temperature biases occur in the Labrador Sea and western boundary currents (WBCs), and the mixed layer is deeper than observations at northern high latitudes in the winter months. In the Antarctic, maximum mixed layer depths (MLD) compare well with observations, but the spatial MLD pattern is shifted relative to observations. Sea ice extent, volume, and concentration agree well with observations. At high resolution, the sea surface height compares well with satellite observations in mean and variability. Key Points The Energy Exascale Earth System Model (E3SM) is a new climate model by the U.S. Department of Energy E3SM ocean and ice components use unstructured horizontal meshes for variable‐resolution simulations The 310‐year E3SM simulations agree well with observations in ocean currents and sea ice coverage

The processes responsible for freshwater flux from the Antarctic Ice Sheet (AIS), ice‐shelf basal melting and iceberg calving, are generally poorly represented in current Earth System Models (ESMs). Here we document the cryosphere configuration of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) v1.2. This includes simulating Antarctic ice‐shelf basal melting, which has been implemented through simulating the ocean circulation within static Antarctic ice‐shelf cavities, allowing for the ability to calculate ice‐shelf basal melt rates from the associated heat and freshwater fluxes. In addition, we added the capability to prescribe forcing from iceberg melt, allowing for realistic representation of the other dominant mass loss process from the AIS. In standard resolution simulations (using a noneddying ocean) under preindustrial climate forcing, we find high sensitivity of modeled ocean/ice shelf interactions to the ocean state, which can result in a transition to a high basal melt regime under the Filchner‐Ronne Ice Shelf (FRIS), presenting a significant challenge to representing the ocean/ice shelf system in a coupled ESM. We show that inclusion of a spatially dependent parameterization of eddy‐induced transport reduces biases in water mass properties on the Antarctic continental shelf. With these improvements, E3SM produces realistic ice‐shelf basal melt rates across the continent that are generally within the range inferred from observations. The accurate representation of ice‐shelf basal melting within a coupled ESM is an important step toward reducing uncertainties in projections of the Antarctic response to climate change and Antarctica's contribution to global sea‐level rise. Plain Language Summary The future of the Antarctic Ice Sheet (AIS) has the potential to have broad impacts on global climate, perhaps most notably in contributing to sea‐level rise. The current generation of Earth System Models (ESMs) do not accurately represent the two primary means in which ice is lost from the AIS, through melting at the base of ice shelves floating on the ocean and the calving of icebergs. This limits our ability to make climate projections that incorporate the impacts of the AIS in a changing climate. Here, we demonstrate a novel capability to model one of those processes, ice‐shelf basal melting, in an ESM. We demonstrate the ability to simulate ice‐shelf basal melt rates across many Antarctic ice shelves that are in line with present day observations. We also find that, for certain ice shelves, modeled ice‐shelf basal melting can experience a rapid transition to high melting far above present‐day estimates, and this simulated high melting can be mitigated through improved ocean physics. Key Points Capabilities have been added to an Earth System Model to model realistic Antarctic ice‐shelf basal melt fluxes and prescribe iceberg forcing Simulated basal melt rates have a strong sensitivity to the ocean mesoscale eddy parameterization For one choice of the mesoscale eddy parameterization, the Filchner‐Ronne Ice Shelf transitions to a high melt regime

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

The extent and thickness of the Arctic sea ice cover has decreased dramatically in the past few decades with minima in sea ice extent in September 2005 and 2007. These minima have not been predicted in the IPCC AR4 report, suggesting that the sea ice component of climate models should more realistically represent the processes controlling the sea ice mass balance. One of the processes poorly represented in sea ice models is the formation and evolution of melt ponds. Melt ponds accumulate on the surface of sea ice from snow and sea ice melt and their presence reduces the albedo of the ice cover, leading to further melt. Toward the end of the melt season, melt ponds cover up to 50% of the sea ice surface. We have developed a melt pond evolution theory. Here, we have incorporated this melt pond theory into the Los Alamos CICE sea ice model, which has required us to include the refreezing of melt ponds. We present results showing that the presence, or otherwise, of a representation of melt ponds has a significant effect on the predicted sea ice thickness and extent. We also present a sensitivity study to uncertainty in the sea ice permeability, number of thickness categories in the model representation, meltwater redistribution scheme, and pond albedo. We conclude with a recommendation that our melt pond scheme is included in sea ice models, and the number of thickness categories should be increased and concentrated at lower thicknesses.

The Southern Ocean overturning circulation is driven by winds, heat fluxes, and freshwater sources. Among these sources of freshwater, Antarctic sea ice formation and melting play the dominant role. Even though iceshelf melt is relatively small in magnitude, it is located close to regions of convection, where it may influence dense water formation. Here, we explore the impacts of ice-shelf melting on Southern Ocean water-mass transformation (WMT) using simulations from the Energy Exascale Earth System Model (E3SM) both with and without the explicit representation of melt fluxes from beneath Antarctic ice shelves. We find that iceshelf melting enhances transformation of Upper Circumpolar Deep Water, converting it to lower density values. While the overall differences in Southern Ocean WMT between the two simulations are moderate, freshwater fluxes produced by ice-shelf melting have a further, indirect impact on the Southern Ocean overturning circulation through their interaction with sea ice formation and melting, which also cause considerable upwelling. We further find that surface freshening and cooling by ice-shelf melting cause increased Antarctic sea ice production and stronger density stratification near the Antarctic coast. In addition, ice-shelf melting causes decreasing air temperature, which may be directly related to sea ice expansion. The increased stratification reduces vertical heat transport from the deeper ocean. Although the addition of ice-shelf melting processes leads to no significant changes in Southern Ocean WMT, the simulations and analysis conducted here point to a relationship between increased Antarctic ice-shelf melting and the increased role of sea ice in Southern Ocean overturning.

A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.

Icepack (v1.1.0) – the column thermodynamics model of the Community Ice CodE (CICE) version 6 – is used to assess how changing the thermodynamics from the Bitz and Lipscomb (1999) physics (hereafter BL99) to the mushy-layer physics impacts the model performance in reproducing in situ landfast ice observations from two ice mass balance (IMB) buoys co-deployed in the landfast ice close to Nain (Labrador) in February 2017. To this end, a new automated surface retrieval algorithm is used to determine the in situ ice thickness, snow depth, basal ice congelation and snow-ice formation from the measured vertical temperature profiles. Icepack simulations are run to reproduce these observations using each thermodynamics scheme, with a particular interest in how the different physics influence the representation of snow-ice formation and ice congelation. Results show that the BL99 parameterization represents well the ice congelation but underrepresents the snow-ice contribution to the ice mass balance. In particular, defining snow-ice formation based on the hydrostatic balance alone does not reproduce the negative freeboards observed for several days in the IMB observations, resulting in an earlier snow-flooding onset, a positive ice thickness bias and reduced snow depth variations. We find that the mushy-layer thermodynamics with default parameters significantly degrades the model performance, overestimating both the congelation growth and snow-ice formation. The simulated thermodynamics response to flooding, however, better represents the observations, and the best results are obtained when allowing for negative freeboards in the mushy-layer physics. We find that the mushy-layer thermodynamics produces a larger variability in congelation rates at the ice bottom interface, alternating between periods of exceedingly fast growth and periods of unrealistic basal melt. This pattern is related to persistent brine dilution in the lowest ice layer by the congelation and brine drainage parameterizations. We also show that the mushy-layer congelation parameterization produces significant frazil formation, which is not expected in a landfast ice context. This behavior is attributed to the congelation parameterization not fully accounting for the conductive heat flux imbalance at the ice–ocean boundary. We propose a modification of the mushy-layer congelation scheme that largely reduces the frazil formation and allows for better tuning of the congelation rates to match the observations. Our results demonstrate that the mushy-layer physics and its parameters can be tuned to closely match the in situ observations, although more observations are needed to better constrain them.

We present MPAS-Seaice, a sea-ice model which uses the Model for Prediction Across Scales (MPAS) framework and spherical centroidal Voronoi tessellation (SCVT) unstructured meshes. As well as SCVT meshes, MPAS-Seaice can run on the traditional quadrilateral grids used by sea-ice models such as CICE. The MPAS-Seaice velocity solver uses the elastic–viscous–plastic (EVP) rheology and the variational discretization of the internal stress divergence operator used by CICE, but adapted for the polygonal cells of MPAS meshes, or alternatively an integral (“finite-volume”) formulation of the stress divergence operator. An incremental remapping advection scheme is used for mass and tracer transport. We validate these formulations with idealized test cases, both planar and on the sphere. The variational scheme displays lower errors than the finite-volume formulation for the strain rate operator but higher errors for the stress divergence operator. The variational stress divergence operator displays increased errors around the pentagonal cells of a quasi-uniform mesh, which is ameliorated with an alternate formulation for the operator. MPAS-Seaice shares the sophisticated column physics and biogeochemistry of CICE and when used with quadrilateral meshes can reproduce the results of CICE. We have used global simulations with realistic forcing to validate MPAS-Seaice against similar simulations with CICE and against observations. We find very similar results compared to CICE, with differences explained by minor differences in implementation such as with interpolation between the primary and dual meshes at coastlines. We have assessed the computational performance of the model, which, because it is unstructured, runs with 70 % of the throughput of CICE for a comparison quadrilateral simulation. The SCVT meshes used by MPAS-Seaice allow removal of equatorial model cells and flexibility in domain decomposition, improving model performance. MPAS-Seaice is the current sea-ice component of the Energy Exascale Earth System Model (E3SM).