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This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2xCO2 is slightly higher than previously at 2.7‐‐3.1°C (depending on version), and is a result of lower CO2 radiative forcing and stronger positive feedbacks.

Saltwater intrusion is a critical concern for coastal communities due to its impacts on fresh ecosystems and civil infrastructure. Declining recharge and rising sea level are the two dominant drivers of saltwater intrusion along the land‐ocean continuum, but there are currently no global estimates of future saltwater intrusion that synthesize these two spatially variable processes. Here, for the first time, we provide a novel assessment of global saltwater intrusion risk by integrating future recharge and sea level rise while considering the unique geology and topography of coastal regions. We show that nearly 77% of global coastal areas below 60° north will undergo saltwater intrusion by 2100, with different dominant drivers. Climate‐driven changes in subsurface water replenishment (recharge) is responsible for the high‐magnitude cases of saltwater intrusion, whereas sea level rise and coastline migration are responsible for the global pervasiveness of saltwater intrusion and have a greater effect on low‐lying areas. Plain Language Summary Coastal watersheds around the globe are facing perilous changes to their freshwater systems. Driven by climatic changes in recharge and sea level working in tandem, sea water encroaches into coastal groundwater aquifers and consequently salinizes fresh groundwater, in a process called saltwater intrusion. To assess the vulnerability of coastal watersheds to future saltwater intrusion, we applied projections of sea level and groundwater recharge to a global analytical modeling framework. Nearly 77% of the global coast is expected to undergo measurable salinization by the year 2100. Changes in recharge have a greater effect on the magnitude of salinization, whereas sea level rise drives the widespread extensiveness of salinization around the global coast. Our results highlight the variable pressures of climate change on coastal regions and have implications for prioritizing management solutions. Key Points First global analysis of future saltwater intrusion vulnerability responding to spatially variable recharge and sea level rise is provided Recharge drives the extreme cases of saltwater intrusion, while sea level rise is responsible for its global pervasiveness Nearly 77% of global coastal areas below 60° north will undergo saltwater intrusion by 2100

The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The data set of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We do not find a conclusive result for how cloud clustering changes as the climate warms. Key Points Temperature, humidity, and clouds in radiative‐convective equilibrium vary substantially across models Models agree that self‐aggregation dries the atmosphere and reduces high cloudiness There is no consistency in how self‐aggregation depends on warming

Air‐sea heat and moisture fluxes modulate the surface energy balance and oceanic and atmospheric heat transport across all timescales. Spatial gradients of these fluxes, on a multitude of spatial scales, also have significant impacts on the ocean and atmosphere. Nevertheless, analysis of these gradients, and discussion regarding our ability to represent them, is relatively absent within the community. This letter discusses their importance and presents a wintertime climatology. Their sensitivity to spatiotemporal scale and choice of data set is also examined in the mid‐latitudes. A lead‐lag analysis illustrates that wintertime air‐sea heat flux gradients in the Gulf Stream can precede the North Atlantic Oscillation by ∼1 month. A lack of observations and thus validation of air‐sea heat flux gradients represents a significant gap in our understanding of how air‐sea processes affect weather and climate, and warrants increased attention from the observational and modeling communities. Plain Language Summary The oceans impact both weather and climate by heating and cooling the lower atmosphere. Surface latent (sensible) heat flux is a quantity that measures the exchange of heat associated with evaporation of seawater (an air‐sea temperature difference). In addition to the absolute exchange, the manner in which the exchange varies spatially (the heat flux gradients) is also known to be important for the development of weather systems and longer‐term climate. Despite this, relatively little attention is paid in the literature to variability in these gradients. This study provides a brief overview of their importance and provides a wintertime climatology in these gradients. It is also illustrated that when considering gradients, the importance of specifying the spatial scale over which the gradient is calculated is critical. Although many differences exist between air‐sea heat flux data products in these gradients, there are currently almost no observations to validate them in key areas of interest, which represents a significant deficiency in our understanding of ocean‐atmosphere interactions. This is emphasized by demonstrating that these gradients in the mid‐latitudes can statistically precede variability in the North Atlantic Oscillation, the most important mode of monthly atmospheric variability in the North Atlantic. Key Points Air‐sea heat and moisture flux gradients modulate important oceanic and atmospheric processes across a multitude of spatiotemporal scales Air‐sea heat flux gradient variability can statistically precede mid‐latitude atmospheric variability Notable air‐sea heat and moisture flux gradient inconsistencies exist in data products, yet the ability to validate them remains elusive

Deep and abyssal layer decadal temperature trends from the mid‐1980s to the mid‐2010s are mapped globally using Deep Argo and historical ship‐based Conductivity‐Temperature‐Depth (CTD) instrument data. Abyssal warming trends are widespread, with the strongest warming observed around Antarctic Bottom Water (AABW) formation regions. The warming strength follows deep western boundary currents transporting abyssal waters north and decreases with distance from Antarctica. Abyssal cooling trends are found in the North Atlantic and eastern South Atlantic, regions primarily ventilated by North Atlantic Deep Water (NADW). Deep warming trends are prominent in the Southern Ocean south of about 50°S, the Greenland‐Iceland‐Norwegian (GIN) Seas and the western subpolar North Atlantic, with cooling in the eastern subpolar North Atlantic and the subtropical and tropical western North Atlantic. Globally integrated decadal heat content trends of 21.6 (±6.5) TW in the deep and 12.9 (±1.8) TW in the abyssal layer are more certain than previous estimates. Plain Language Summary Even the deepest waters in the ocean, which sink to the abyss around Antarctica after being cooled and made saltier by heat exchange with the atmosphere and sea ice formation, have been shown to be warming around much of the globe in recent decades. The net warming rate below 2000‐m depth accounts for about 10% of total ocean heat uptake, but uncertainties in prior estimates have been about half the size of the signal owing to sparse sampling in the deep ocean. However, new observations from Deep Argo floats, capable of profiling to the ocean floor in most locations, have improved that situation in some regions. Here we analyze these new observations together with historical observations collected from ships since the 1970s to map decadal ocean temperature trends around the globe. As a result, we use more historical data than previous estimates. We refine the local patterns of warming and cooling in the waters deeper than 2,000 m. We confirm the amplitude of the net warming below 2,000 m estimated in previous studies, and extend the time covered by those estimates. The increased data coverage substantially reduces the uncertainty of the net warming estimate. Key Points Analysis of Deep Argo float and historical ship‐based CTD data reveal global patterns in deep and abyssal layer decadal temperature trends High resolution maps reveal spreading of abyssal warming from Antarctica and cooling from the North Atlantic on sub‐basin spatial scales Globally integrated decadal heat content trends are 21.6 (±6.5) TW in the deep and 12.9 (±1.8) TW in the abyssal layer

Future projections indicate the Atlantic Meridional Overturning Circulation (AMOC) will weaken and shoal in response to global warming, but models disagree widely over the amount of weakening. We analyze projected AMOC weakening in 27 CMIP6 climate models, in terms of changes in three return pathways of the AMOC. The branch of the AMOC that returns through diffusive upwelling in the Indo‐Pacific, but does not later upwell in the Southern Ocean (SO), is particularly sensitive to warming, in part, because shallowing of the deep flow prevents it from entering the Indo‐Pacific via the SO. The present‐day strength of this Indo‐Pacific pathway provides a strong constraint on the projected AMOC weakening. However, estimates of this pathway using four observationally based methods imply a wide range of AMOC weakening under the SSP5‐8.5 scenario of 29%–61% by 2100. Our results suggest that improved observational constraints on this pathway would substantially reduce uncertainty in 21st century AMOC decline. Plain Language Summary The Atlantic Meridional Overturning Circulation (AMOC) is a system of ocean currents that move warm surface waters from the south to the north of the Atlantic Ocean where they cool, sink, and return southward at depth. Changes in the AMOC would have wide‐ranging impacts on our climate. It is predicted to weaken as the climate warms during the 21st century, but the extent of weakening varies among different climate models. We show that AMOC weakening is greatest in models that have a large exchange of water between the AMOC and the Indo‐Pacific Ocean along a specific pathway. The magnitude of this ocean pathway, inferred from four observation‐based estimates of the global overturning circulation, is uncertain. By using these estimates and analyzing the relationship between the aforementioned ocean pathway and AMOC weakening across many climate models, we can predict how the real‐world AMOC will change. Our findings indicate that by 2100, under a high greenhouse gas emission scenario, the AMOC will weaken by 29%–61%. This highlights the importance of reducing differences between observational estimates of the ocean's overturning pathways to reduce uncertainty in future AMOC weakening and to improve the representation of these pathways in climate models. Key Points The magnitude of 21st century Atlantic Meridional Overturning Circulation (AMOC) weakening in CMIP6 models is highly correlated with an AMOC pathway into the Indo‐Pacific Ocean The real‐world “Indo‐Pacific diffusive” AMOC pathway inferred from observation‐based estimates is used to constrain future AMOC weakening Under high‐end greenhouse gas forcing, AMOC weakening based on this emergent constraint relationship ranges from 29% to 61% by 2100

This paper addresses the question of whether the increased occurrence of central Pacific (CP) versus Eastern Pacific (EP) El Niños is consistent with greenhouse gas forced changes in the background state of the tropical Pacific as inferred from global climate change models. Our analysis uses high‐quality satellite and in situ ocean data combined with wind data from atmospheric reanalyses for the past 31 years (1980–2010). We find changes in background conditions that are opposite to those expected from greenhouse gas forcing in climate models and opposite to what is expected if changes in the background state are mediating more frequent occurrences of CP El Niños. A plausible interpretation of these results is that the character of El Niño over the past 31 years has varied naturally and that these variations projected onto changes in the background state because of the asymmetric spatial structures of CP and EP El Niños. Key Points The character of El Nino is changing in ways not expected from climate models Changes in El Nino are projecting onto background conditions The changes probably result from natural variations rather than GHG forcing

Fresh submarine groundwater discharge (FSGD) can deliver significant fluxes of water and solutes from land to sea. In the Arctic, which accounts for ∼34% of coastlines globally, direct observations and knowledge of FSGD are scarce. Through integration of observations and process‐based models, we found that regardless of ice‐bonded permafrost depth at the shore, summer SGD flow dynamics along portions of the Beaufort Sea coast of Alaska are similar to those in lower latitudes. Calculated summer FSGD fluxes in the Arctic are generally higher relative to low latitudes. The FSGD organic carbon and nitrogen fluxes are likely larger than summer riverine input. The FSGD also has very high CO2 making it a potentially significant source of inorganic carbon. Thus, the biogeochemistry of Arctic coastal waters is potentially influenced by groundwater inputs during summer. These water and solute fluxes will likely increase as coastal permafrost across the Arctic thaws. Plain Language Summary Groundwater flows from land to sea, transporting freshwater, organic matter, nutrients, and other solutes that impact coastal ecosystems. However, along coasts of the rapidly‐warming Arctic, there is limited knowledge regarding how much fresh groundwater enters the ocean. Using field observations and numerical models, we show that groundwater flowing from tundra in northern coastal Alaska carries large amounts of freshwater, organic matter, and carbon dioxide to the Arctic lagoons during summer. These inputs are likely significant to coastal biogeochemical cycling and marine food webs. Groundwater discharge and the associated transport of dissolved materials are expected to increase due to longer periods of above‐zero temperatures that thaw frozen soils below the tundra. Key Points Summer fresh submarine groundwater discharge (FSGD) to the Alaskan Beaufort Sea is only 3%–7% of rivers but carries as much organic matter Summer FSGD delivers a median of 116 (interquartile range: 35–405) and 6 (2–21) kg/d per km dissolved organic carbon and nitrogen Fresh groundwater at the beach of Simpson Lagoon (SL) has a median PCO2 of ∼33,000 μatm implying substantial CO2 flux

Sea level rise (SLR) is a long-lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process-based models. However, risk-averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high-end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high-end scenarios. High-end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1-2.6) relative to pre-industrial values our high-end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5-8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long-term benefits of mitigation. However, even a modest 2°C warming may cause multi-meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high-end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high-end SLR.

Severe convective storms are among the most dangerous weather phenomena and accurate forecasts mitigate their impacts. The recently released suite of AI‐based weather models produces medium‐range forecasts within seconds, with a skill similar to state‐of‐the‐art operational forecasts for variables on single levels. However, predicting severe thunderstorm environments requires accurate combinations of dynamic and thermodynamic variables and the vertical structure of the atmosphere. Advancing the assessment of AI‐models toward process‐based evaluations lays the foundation for hazard‐driven applications. We assess the forecast skill of the top‐performing AI‐models GraphCast, Pangu‐Weather and FourCastNet for convective parameters at lead‐times up to 10 days against reanalysis and ECMWF's operational numerical weather prediction model IFS. In a case study and seasonal analyses, we see the best performance by GraphCast and Pangu‐Weather: these models match or even exceed the performance of IFS for instability and shear. This opens opportunities for fast and inexpensive predictions of severe weather environments. Plain Language Summary Over the past year, several global AI‐based weather models were released and produce a similar quality of forecasts as traditional weather models. AI‐models are very fast and computationally cheap to produce forecasts. The evaluation of AI‐models has largely focused on single atmospheric variables at certain heights. To forecast specific phenomena, such as thunderstorms, a combination of variables must be accurate at multiple heights. Here we use the output of AI‐models to derive thunderstorm‐related ingredients. We compare 10‐day‐forecasts between the AI‐models GraphCast, Pangu‐Weather and FourCastNet and a state‐of‐the‐art traditional weather model while using a reanalysis data set as the reference. The example of a tornado outbreak in the southern United States shows that all models are capable of forecasting thunderstorm ingredients multiple days in advance. To obtain a robust assessment, we evaluate the entire thunderstorm season in 2020 in North America, Europe, Argentina, and Australia, where severe thunderstorms occur frequently. Two of the three AI‐models achieve similar or even better results than the traditional weather model while being much cheaper to operate computationally. Forecasting thunderstorm parameters directly, instead of calculating them afterward, is likely to produce even better results. This opens opportunities for rapid and accessible forecasts for severe thunderstorm phenomena. Key Points AI‐based global weather models produce forecasts with sufficient accuracy to derive instability and shear metrics skillfully The best AI‐based weather models are capable of competing with state‐of‐the‐art numerical weather predictions of instability and shear This is a major step toward computationally inexpensive and fast convective outlooks