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Large language models can summarize, aggregate, and convey localized climate-related data to people in a cost-effective and expeditious manner. We have built a simple, proof-of-concept prototype and argue that the approach holds the potential to truly democratize climate information.Large language models can summarize, aggregate, and convey localized climate-related data to people in a cost-effective and expeditious manner. This Comment introduces a simple, proof-of-concept prototype and argues that the approach holds the potential to truly democratize climate information.

A study of the scalability of the Finite-volumE Sea ice–Ocean circulation Model, Version 2.0 (FESOM2), the first mature global model of its kind formulated on unstructured meshes, is presented. This study includes an analysis of the main computational kernels with a special focus on bottlenecks in parallel scalability. Several model enhancements improving this scalability for large numbers of processes are described and tested. Model grids at different resolutions are used on four high-performance computing (HPC) systems with differing computational and communication hardware to demonstrate the model's scalability and throughput. Furthermore, strategies for improvements in parallel performance are presented and assessed. We show that, in terms of throughput, FESOM2 is on a par with state-of-the-art structured ocean models and, in a realistic eddy-resolving configuration (1/10∘ resolution), can achieve about 16 years per day on 14 000 cores. This suggests that unstructured-mesh models are becoming very competitive tools in high-resolution climate modeling. We show that the main bottlenecks of FESOM2 parallel scalability are the two-dimensional components of the model, namely the computations of the external (barotropic) mode and the sea-ice model. It is argued that these bottlenecks are shared with other general ocean circulation models.

Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) show substantial biases in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. Here, we analyze the influence of horizontal resolution in a hierarchy of five multi-resolution simulations with the AWI Climate Model (AWI-CM), the climate model used at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, which employs a sea ice–ocean model component formulated on unstructured meshes. The ocean grid sizes considered range from a nominal resolution of ∼1∘ (CMIP5 type) up to locally eddy resolving. We show that increasing ocean resolution locally to resolve ocean eddies leads to reductions in deep ocean biases, although these improvements are not strictly monotonic for the five different ocean grids. A detailed diagnosis of the simulations allows to identify the origins of the biases. We find that two key regions at the surface are responsible for the development of the deep bias in the Atlantic Ocean: the northeastern North Atlantic and the region adjacent to the Strait of Gibraltar. Furthermore, the Southern Ocean density structure is equally improved with locally explicitly resolved eddies compared to parameterized eddies. Part of the bias reduction can be traced back towards improved surface biases over outcropping regions, which are in contact with deeper ocean layers along isopycnal surfaces. Our prototype simulations provide guidance for the optimal choice of ocean grids for AWI-CM to be used in the final runs for phase 6 of CMIP (CMIP6) and for the related flagship simulations in the High Resolution Model Intercomparison Project (HighResMIP). Quite remarkably, retaining resolution only in areas of high eddy activity along with excellent scalability characteristics of the unstructured-mesh sea ice–ocean model enables us to perform the multi-centennial climate simulations needed in a CMIP context at (locally) eddy-resolving resolution with a throughput of 5–6 simulated years per day.

The key role of the South Atlantic Anticyclone (SAA) on the seasonal cycle of the tropical Atlantic is investigated with a regionally coupled atmosphere–ocean model for two different coupled domains. Both domains include the equatorial Atlantic and a large portion of the northern tropical Atlantic, but one extends southward, and the other northwestward. The SAA is simulated as internal model variability in the former, and is prescribed as external forcing in the latter. In the first case, the model shows significant warm biases in sea surface temperature (SST) in the Angola-Benguela front zone. If the SAA is externally prescribed, these biases are substantially reduced. The biases are both of oceanic and atmospheric origin, and are influenced by ocean–atmosphere interactions in coupled runs. The strong SST austral summer biases are associated with a weaker SAA, which weakens the winds over the southeastern tropical Atlantic, deepens the thermocline and prevents the local coastal upwelling of colder water. The biases in the basins interior in this season could be related to the advection and eddy transport of the coastal warm anomalies. In winter, the deeper thermocline and atmospheric fluxes are probably the main biases sources. Biases in incoming solar radiation and thus cloudiness seem to be a secondary effect only observed in austral winter. We conclude that the external prescription of the SAA south of 20°S improves the simulation of the seasonal cycle over the tropical Atlantic, revealing the fundamental role of this anticyclone in shaping the climate over this region.

We examine the historical evolution and projected changes in the hydrography of the deep basin of the Arctic Ocean in 23 climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The comparison between historical simulations and observational climatology shows that the simulated Atlantic Water (AW) layer is too deep and thick in the majority of models, including the multi‐model mean (MMM). Moreover, the halocline is too fresh in the MMM. Overall our findings indicate that there is no obvious improvement in the representation of the Arctic hydrography in CMIP6 compared to CMIP5. The climate change projections reveal that the sub‐Arctic seas are outstanding warming hotspots, causing a strong warming trend in the Arctic AW layer. The MMM temperature increase averaged over the upper 700 m at the end of the 21st century is about 40% and 60% higher in the Arctic Ocean than the global mean in the SSP245 and SSP585 scenarios, respectively. Salinity in the upper few hundred meters is projected to decrease in the Arctic deep basin in the MMM. However, the spread in projected salinity changes is large and the tendency toward stronger halocline in the MMM is not simulated by all the models. The identified biases and projection uncertainties call for a concerted effort for major improvements of coupled climate models. Plain Language Summary Coupled climate models are crucial tools for understanding and projecting climate change, especially for the Arctic where the climate is changing at unprecedented rates. A cold fresh layer of water (aka halocline) has been protecting sea‐ice at the surface from the warm layer of water (aka Atlantic Water layer) which flows underneath and could potentially accelerate sea ice melting from below. Climate change disturbs this vertical structure by changing the temperature and salinity of the Arctic Ocean (in a process known as Atlantification and Pacification) which may lead to additional sea ice basal melting and accelerate sea ice decline. We examined the simulated temperature and salinity in the Arctic Ocean deep basin in state‐of‐the‐art climate model simulations which provided the basis for the IPCC Assessment Report. We found that although there are persistent inaccuracies in the representation of Arctic temperature and salinity, the Arctic Ocean below 100 m is subject to much stronger warming than the average global ocean. On the other hand, the upper Arctic Ocean salinity is projected to decrease, which on average may strengthen the isolation of sea ice from Atlantic Water heat in the Arctic deep basin area. Key Points A too deep and thick Arctic Atlantic Water layer continues to be a major issue in contemporary climate models contributing to the CMIP6 The Arctic Ocean below the halocline is subject to much stronger warming than the global mean during the 21st century The multi‐model mean upper ocean salinity is projected to decrease in the future but with high uncertainty

The Alfred Wegener Institute Climate Model (AWI‐CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice‐ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max Planck Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI‐CM performs better than the average of CMIP5 models. AWI‐CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea‐ice extent in September over the past 30 years is 20–30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present‐day climate under the strong emission scenario SSP585 are similar to the multi‐model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2°C to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical, and Southern Ocean. Furthermore, in the northern middle latitudes in boreal summer and autumn as well as in the southern middle latitudes, a more zonal atmospheric flow is projected throughout the year. Plain Language Summary The Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) participates for the first time with a global climate model in the Coupled Model Intercomparison Project 6 (CMIP6). The results of CMIP6 and previous model comparison projects feed into the next assessment report of the Intergovernmental Panel on Climate Change (IPCC). The IPCC assessment reports include information on past and expected climate change in the future and is written for policy‐ and decision‐makers as well as for the general public. The main characteristics of the AWI climate model are described and compared to models from previous intercomparison projects. The projected global warming in AWI‐CM is similar to the average warming predicted by climate models in the previous intercomparison project. However, the Arctic sea‐ice extent declines faster than typical previous estimates. Areas that are wet in present‐day climate become wetter, and areas that are dry in present‐day climate become drier in the future—consistent with previous climate model simulations. The ocean currents remain rather stable in the AWI climate projections, which leads to a continued warm Gulf stream and therefore an only slightly reduced warming of the North Atlantic and parts of Europe compared to other middle‐latitude regions. Key Points The paper describes contributions of AWI‐CM, which employs a sea‐ice ocean component formulated on unstructured meshes, to CMIP6 Equilibrium climate sensitivity is similar to average of CMIP5 projections; transient climate response is slightly above average Response patterns are similar to CMIP5 with more pronounced Arctic sea ice loss and a more stable AMOC compared to other systems

This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.

Broad, long-living, ice-free areas in midwinter northeast of Svalbard between 2011 and 2014 are investigated. The formation of these persistent and reemerging anomalies is linked, hypothetically, with the increased seasonality of Arctic sea ice cover, enabling an enhanced influence of oceanic heat on sea ice and, in particular, heat transported by Atlantic Water. The “memory” of ice-depleted conditions in summer is transferred to the fall season through excess heat content in the upper mixed layer, which in turn transfers to midwinter via thinner and younger ice. This thinner ice is more fragile and mobile, thus facilitating the formation of polynyas and leads. When openings in ice cover form along the Atlantic Water pathway, weak density stratification at the mixed layer base supports the development of thermohaline convection, which further entrains warm and salty water from deeper layers. Convection-induced upward heat flux from the Atlantic layer retards ice formation, either keeping ice thickness low or blocking ice formation entirely. Certain stages of this chain of events have been examined in a region north of Svalbard and Franz Joseph Land, between 80° and 83°N and 15° and 60°E, where the top hundred meters of Atlantic inflow through the Fram Strait cools and freshens rapidly. Complementary research methods, including statistical analyses of observations and numerical modeling, are used to support the basic concept that the recently observed retreat of sea ice northeast of Svalbard in winter may be explained by a positive feedback between summer ice decay and the growing influence of oceanic heat on a seasonal time scale.

Sea ice dynamics determine the drift and deformation of sea ice. Nonlinear physics, usually expressed in a viscous‐plastic rheology, makes the sea ice momentum equations notoriously difficult to solve. At increasing sea ice model resolution the nonlinearities become stronger as linear kinematic features (leads) appear in the solutions. Even the standard elastic‐viscous‐plastic (EVP) solver for sea ice dynamics, which was introduced for computational efficiency, becomes computationally very expensive, when accurate solutions are required, because the numerical stability requires very short, and hence more, subcycling time steps at high resolution. Simple modifications to the EVP solver have been shown to remove the influence of the number of subcycles on the numerical stability. At low resolution appropriate solutions can be obtained with only partial convergence based on a significantly reduced number of subcycles as long as the numerical procedure is kept stable. This previous result is extended to high resolution where linear kinematic features start to appear. The computational cost can be strongly reduced in Arctic Ocean simulations with a grid spacing of 4.5 km by using modified and adaptive EVP versions because fewer subcycles are required to simulate sea ice fields with the same characteristics as with the standard EVP. Key Points We explore the performance of new options for EVP solvers at high resolution (4.5 km) A significant reduction of the required number of EVP subcycles leads to a sixfold speedup of the sea ice dynamics This speedup does not lead to a deterioration of the simulated sea ice

In this study we demonstrate the potential of a kinetic energy backscatter scheme for use in global ocean simulations. Ocean models commonly employ (bi)harmonic eddy viscosities causing excessive dissipation of kinetic energy in eddy‐permitting simulations. Overdissipation not only affects the smallest resolved scales but also the generation of eddies through baroclinic instabilities, impacting the entire wave number spectrum. The backscatter scheme returns part of this overdissipated energy back into the resolved flow. We employ backscatter in the FESOM2 multiresolution ocean model with a quasi‐uniform 1/4° mesh. In multidecadal ocean simulations, backscatter increases eddy activity by a factor 2 or more, moving the simulation closer to observational estimates of sea surface height variability. Moreover, mean sea surface height, temperature, and salinity biases are reduced. This amounts to a globally averaged bias reduction of around 10% for each field, which is even larger in the Antarctic Circumpolar Current. However, in some regions such as the coastal Kuroshio, backscatter leads to a slight overenergizing of the flow and, in the Antarctic, to an unrealistic reduction of sea ice. Some of the bias increases can be reduced by a retuning of the model, and we suggest related adjustments to the backscatter scheme. The backscatter simulation is about 2.5 times as expensive as a simulation without backscatter. Most of the increased cost is due to a halving of the time step to accommodate higher simulated velocities. Plain Language Summary The weather of the oceans is determined by so‐called mesoscale eddies, which carry a large portion of the kinetic energy of ocean currents. They are responsible for the transport of heat and dissolved substances; they can affect the large and fast mean currents of the ocean and interact strongly with the atmosphere above. However, these eddies are not well represented in current ocean and climate models. With this study, we apply a new method to better represent the effect of ocean weather in ocean models. We show that this leads to improvements of the simulation of ocean currents and their variability and reduces biases in ocean temperatures and salinity. While increasing the resolution of ocean models also helps to improve the representation of mesoscale eddies, such a resolution increase is computationally expensive. The new backscatter parametrization can help to save computational costs by allowing improved eddy simulations comparable to much higher resolution. Key Points We present a stable ocean kinetic energy backscatter scheme in a global ocean model setup The scheme substantially improves sea surface height variability comparable to much higher resolution Biases in mean sea surface height, temperature, and salinity are also improved