The Atlantic Meridional Overturning Circulation (AMOC) plays a crucial role in the global climate system. Various studies report both ongoing and projected reductions in AMOC strength, with important implications for climate and society. While Stratospheric Aerosol Injection (SAI) has been proposed to mitigate some impacts of a warming climate, model simulations disagree whether it could also be successful in ameliorating the projected AMOC decline. Using SAI sensitivity simulations with the Community Earth System Model, we demonstrate that whether SAI could restore AMOC depends on the details of SAI realization, particularly its latitude(s). Specifically, Northern-hemispheric SAI initially impacts upper-ocean densities in the North Atlantic through changes in surface heat flux and temperature, ultimately preventing AMOC decline. On the other hand, Southern-hemispheric SAI does not substantially impact AMOC strength even though global mean cooling is achieved. We show that different processes play different roles in determining the AMOC response between the initial (~10-15 years) and longer timescales, with the former dominated by the direct SAI effect and the latter influenced by feedbacks from AMOC adjustments. These processes may also offset each other, leading to a relatively stable evolution of AMOC under each SAI realization and a small, yet substantially different, subset of potential AMOC responses. Overall, our results demonstrate the potential for SAI to help avoid climatic tipping points, but also highlight the need to understand the dependence of the outcomes on the specific SAI realization as well as for a better process-based understanding of the many factors influencing such outcomes.

A Variable-Resolution, global configuration of the Community Earth System Model (VR-CESM) in which the atmosphere and land are the only active components is employed to investigate the climate of the Euro-Mediterranean region. Two variable-resolution grids with regionally-refined resolutions of 0.25° and 0.125° over the study domain, respectively, are used. The fidelity of these VR-CESM simulations is evaluated considering the near-surface air temperature and precipitation fields for the 2000-2014 period in comparison to available observation-based datasets and those of a coarse resolution (quasi-uniform 1°) control simulation. Our analysis shows that, as a global model, VR-CESM is a promising alternative to regional climate models to advance our understanding of the Euro-Mediterranean climate. The improvements obtained are mainly related to a better representation of the complex topography of the region with higher resolution. Increasing the regional resolution to 0.25° generally yields considerable improvements over the control simulation, however some persistent biases remain. Doubling the highest resolution to 0.125° leads to only modest improvements, primarily in the representation of small-scale processes including representation of extreme events that are of substantial relevance for the present and future of the regional climate.

In the face of a changing climate, the understanding, predictions and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, a reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support the next generation of climate services.

Ocean warming is a key factor impacting future changes in climate. Here we investigate vertical structure changes in globally averaged ocean heat content (OHC) in high- (HR) and low-resolution (LR) future climate simulations with the Community Earth System Model (CESM). Compared with observation-based estimates, the simulated OHC anomalies in the upper 700 m and 2000 m during 1960-2020 are more realistic in CESM-HR than -LR. Under RCP8.5 scenario, the net surface heat into the ocean is very similar in CESM-HR and -LR However, CESM-HR has a larger increase in OHC in the upper 250 m compared to CESM-LR, but a smaller increase below 250 m. This difference can be traced to differences in eddy-induced vertical heat transport between CESM-HR and -LR in the historical period. Moreover, our results suggest that with the same heat input, upper-ocean warming is likely to be underestimated by most non-eddy-resolving climate models.

The mixing of tracers by mesoscale eddies, parameterized in many ocean general circulation models (OGCMs) as a diffusive-advective process, contributes significantly to the distribution of tracers in the ocean. In the ocean interior, diffusive contribution occurs mostly along the direction parallel to local neutral density surfaces. However, near the surface of the ocean, small-scale turbulence and the presence of the boundary itself break this constraint and the mesoscale transport occurs mostly along a plane parallel to the ocean surface (horizontal). Although this process is easily represented in OGCMs with geopotential vertical coordinates, the representation is more challenging in OGCMs that use a general vertical coordinate, where surfaces can be tilted with respect to the horizontal. We propose a method for representing the diffusive horizontal mesoscale fluxes within the surface boundary layer of general vertical coordinate OGCMs. The method relies on regridding/remapping techniques to represent tracers in a geopotential grid. Horizontal fluxes are calculated on this grid and then remapped back to the native grid, where fluxes are applied. The algorithm is implemented in an ocean model and tested in idealized and realistic settings. Horizontal diffusion can account for up to 10\% of the total northward heat transport in the Southern Ocean and Western boundary current regions of the Northern Hemisphere. It also reduces the vertical stratification of the upper ocean, which results in an overall deepening of the surface boundary layer depth. Lastly, enabling horizontal diffusion leads to meaningful reductions in the near-surface global bias of potential temperature and salinity.

Multiple 50-member ensemble simulations with the Community Earth System Model version 2 are performed to estimate the coupled climate responses to the 2019-2020 Australian wildfires and COVID-19 pandemic policies. The climate response to the pandemic is found to be weak generally, with net top-of-atmosphere radiative anomalies of +0.23+-0.14 W m/2driving a gradual global warming of 0.05+-0.04 K by the end of 2022. While regional anomalies are detectible in aerosol burdens and clear-sky radiation, few significant anomalies exist in other fields due to internal variability. In contrast, the simulated response to Australian wildfires is a strong and rapid cooling, peaking at -0.95+-0.15 W m/2 in late 2019 with an anomalous global cooling of 0.06+-0.04 K by mid-2020. Transport of fire aerosols throughout the Southern Hemisphere increases albedo and drives a strong interhemispheric radiative contrast, with simulated responses that are consistent generally with those to a Southern Hemisphere volcanic eruption.

Fundamental understanding of the climate responses to solar variability is obscured by the large and complex climate variability. This long-standing issue is addressed here by examining climate responses under an extreme quiet sun (EQS) scenario, obtained by making the sun void of all magnetic fields. It is used to drive a coupled climate model with whole atmosphere and ocean components. The simulations reveal robust responses, and elucidate aspects of the responses to changes of troposphere/surface forcing and stratospheric forcing that are similar and those that are different. Planetary waves (PWs) play a key role in both regional climate and the mean circulation changes. Intermediate scale stationary waves and regional climate respond to solar forcing changes in the troposphere and stratosphere in a similar way, due to similar subtropical wind changes in the upper troposphere. The patterns of these changes are similar to those found in a warming climate, but with opposite signs. Responses of the largest scale PW during NH and SH winters differ, leading to hemispheric differences in the interplay between dynamical and radiative processes. The analysis exposes remarkable general similarities between climate responses in EQS simulations and those under nominal solar minimum conditions, even though the latter may not always appear to be statistically significant.

Inter-annual to decadal variability in the strength of the land and ocean carbon sinks impede accurate predictions of year-to-year atmospheric carbon dioxide (CO2) growth rate. Such information is crucial to verify the effectiveness of fossil fuel emissions reduction measures. Using a multi-model framework comprising prediction systems based on Earth system models, we find a predictive skill for the global ocean carbon sink of up to 6 years. Longer regional predictability horizons and robust spatial patterns are found across single models. On land, a predictive skill of up to 2 years is primarily maintained in the tropics and extra-tropics enabled by the initialization of the physical climate variables towards observations. We further show that anomalies of atmospheric CO2 growth rate inferred from natural variations of the land and ocean carbon sinks are predictable at lead time of 2 years and the skill is limited by the land carbon sink predictability horizon.

Rapid Arctic warming and sea ice decline in recent decades might have profound impacts on midlatitude weather and climate. This study uses a high-top atmospheric general circulation model - Whole Atmosphere Community Climate Model version 6 (WACCM6) - to investigate the atmospheric responses to the Arctic sea ice reduction, including impacts on mid-latitude blocking and cyclones. The high-top configuration (top layer at about 100 km or 0.001 hPa) together with the finer vertical resolution (70 layers) in WACCM6 allow more realistic representation of stratosphere-troposphere interactions. The sea ice impact during 1979-2015 is obtained by comparing ensemble simulations forced by daily observational sea ice concentration (SIC) and sea surface temperature (SST) to simulations where the time-varying SIC is replaced by a daily SIC climatology. A series of SIC-SST adjustments are performed to minimize unrealistic SIC and SST forcings used in the simulations. Each ensemble consists of 30 members with slightly different atmospheric initial conditions in order to separate forced atmospheric responses from internal model spread.

The mixing of tracers by mesoscale eddies, parameterized in many ocean general circulation models (OGCMs) as a diffusive process, contributes significantly to the distribution of tracers in the ocean. In the ocean interior, such processes occur mostly along the direction parallel to the local neutral density surface. However, near boundaries, small-scale turbulence breaks this constraint and the mesoscale transport occurs mostly along a plane parallel to the boundary (i.e., laterally near the surface of the ocean). Although this process is easily represented in OGCMs with geopotential vertical coordinates, the representation is more challenging in OGCMs that use a general vertical coordinate, where surfaces can be tilted with respect to the horizontal. We propose a method for representing the diffusive lateral mesoscale fluxes within the surface boundary layer of general vertical coordinate OGCMs. The method relies on regridding/remapping techniques to represent tracers in a geopotential grid. Lateral fluxes are calculated in this grid and then remapped back to the native grid, where fluxes are applied. The algorithm is implemented in an ocean model and tested in idealized and realistic settings. Lateral diffusion reduces the vertical stratification of the upper ocean, which results in an overall deepening of the surface boundary layer depth. Although the impact on certain global metrics is not significant, enabling lateral diffusion leads to a small but meaningful reduction in the near-surface global bias of potential temperature and salinity.

This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air-sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy-resolving high-resolution (HR) and eddy-parameterized low-resolution (LR) ocean components. Here, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co-variability over scales between 50-10000 km and 60 days-80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper-ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ~2000-2500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R1, ~600-2000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean-driven variability also shows a surprising temporal persistence, from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that induced by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.

Fundamental understanding of the climate responses to solar variability is obscured by the large and complex climate variability. This long-standing issue is addressed here by examining climate responses under an extreme solar minimum (ESM) scenario, obtained by making the sun void of all magnetic fields. It is used to drive a whole atmosphere climate model with coupled ocean. The simulations reveal robust responses in the coupled climate system, and elucidate similarities and differences of responses to bottom-up and top-down forcing. Planetary waves (PWs) play a key role in both regional climate and the mean circulation changes. Responses of the largest scale PW during NH and SH winters differ, leading to hemispheric differences in the interplay between dynamical and radiative processes. The analysis exposes remarkable general similarities between climate responses in ESM simulations and those under nominal solar minimum conditions, even though the latter may not appear to be statistically significant.