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A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two‐layer model. Key Points An updated version of the Max Planck Institute for Meteorology Earth System Model (MPI‐ESM1.2) is presented The model includes both code corrections and parameterization improvements Despite this, the model maintains an equilibrium climate sensitivity, which rises with warming

The Younger Dryas (YD), arguably the most widely studied millennial-scale extreme climate event, was characterized by diverse hydroclimate shifts globally and severe cooling at high northern latitudes that abruptly punctuated the warming trend from the last glacial to the present interglacial. To date, a precise understanding of its trigger, propagation, and termination remains elusive. Here, we present speleothem oxygen-isotope data that, in concert with other proxy records, allow us to quantify the timing of the YD onset and termination at an unprecedented subcentennial temporal precision across the North Atlantic, Asian Monsoon-Westerlies, and South American Monsoon regions. Our analysis suggests that the onsets of YD in the North Atlantic (12,870 ± 30 B.P.) and the Asian Monsoon-Westerlies region are essentially synchronous within a few decades and lead the onset in Antarctica, implying a north-to-south climate signal propagation via both atmospheric (decadal-time scale) and oceanic (centennial-time scale) processes, similar to the Dansgaard–Oeschger events during the last glacial period. In contrast, the YD termination may have started first in Antarctica at ∼11,900 B.P., or perhaps even earlier in the western tropical Pacific, followed by the North Atlantic between ∼11,700 ± 40 and 11,610 ± 40 B.P. These observations suggest that the initial YD termination might have originated in the Southern Hemisphere and/or the tropical Pacific, indicating a Southern Hemisphere/tropics to North Atlantic–Asian Monsoon-Westerlies directionality of climatic recovery.

It has been proposed that increasing greenhouse gas (GHG) driven climate tipping point risks may prompt consideration of solar radiation modification (SRM) climate intervention to reduce those risks. Here, we study marine cloud brightening (MCB) SRM interventions in three subtropical oceanic regions using Community Earth System Model 2 experiments. We assess the MCB impact on tipping element‐related metrics to estimate the extent to which such interventions might reduce tipping element risks. Both the pattern and magnitude of the MCB cooling depend strongly on location of the MCB intervention. We find the MCB cooling effect reduces most tipping element impacts; though differences in MCB versus GHG climate response patterns mean MCB is an imperfect remedy. However, MCB applied in certain regions may exacerbate certain GHG tipping element impacts. Thus, it is crucial to carefully consider the pattern of MCB interventions and their teleconnected responses to avoid unintended climate effects. Plain Language Summary Marine cloud brightening (MCB) is a proposal to spray sea salt particles into clouds over oceans to increase the reflection of sunlight by the clouds, thus cooling the surface. If greenhouse gas warming continues, technologies like MCB might be considered to avoid climate change impacts such as climate system tipping points. Here, we use state‐of‐the‐art climate model experiments to analyze the MCB impact on elements of the climate system that may have tipping points. In this model, MCB reduces risks for most tipping elements considered here, such as by reducing coral reef heat stress and increasing Atlantic overturning circulation. However, the impact of MCB depends on where it is applied and in some cases adds to GHG impacts, meaning the location of MCB deployments must be carefully considered to avoid unintended regional climate effects. Key Points The magnitude and pattern of marine cloud brightening (MCB) climate impacts depend strongly on the location of the intervention We find MCB impacts that have qualitative similarities to prior work, but there are discrepancies that suggest key inter‐model uncertainties MCB simulations generally show reduced tipping element risk overall, but certain MCB patterns may exacerbate some tipping element changes

The ability of the climate models submitted to the Coupled Model Intercomparison Project 5 (CMIP5) database to simulate the Northern Hemisphere winter climate following a large tropical volcanic eruption is assessed. When sulfate aerosols are produced by volcanic injections into the tropical stratosphere and spread by the stratospheric circulation, it not only causes globally averaged tropospheric cooling but also a localized heating in the lower stratosphere, which can cause major dynamical feedbacks. Observations show a lower stratospheric and surface response during the following one or two Northern Hemisphere (NH) winters, that resembles the positive phase of the North Atlantic Oscillation (NAO). Simulations from 13 CMIP5 models that represent tropical eruptions in the 19th and 20th century are examined, focusing on the large‐scale regional impacts associated with the large‐scale circulation during the NH winter season. The models generally fail to capture the NH dynamical response following eruptions. They do not sufficiently simulate the observed post‐volcanic strengthened NH polar vortex, positive NAO, or NH Eurasian warming pattern, and they tend to overestimate the cooling in the tropical troposphere. The findings are confirmed by a superposed epoch analysis of the NAO index for each model. The study confirms previous similar evaluations and raises concern for the ability of current climate models to simulate the response of a major mode of global circulation variability to external forcings. This is also of concern for the accuracy of geoengineering modeling studies that assess the atmospheric response to stratosphere‐injected particles. Key Points Large volcanic eruptions cause a major dynamical response in the atmosphere CMIP5 models are assessed for their ability to simulate this response No models in the CMIP5 database sufficiently represent this response

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

Purpose of Review This paper reviews recent progress in understanding of the North Pacific Meridional Mode (NPMM) and its influence on the timing, magnitude, flavor, and intensity of the El Niño-Southern Oscillation (ENSO). Recent Findings The NPMM is a seasonally evolving mode of coupled climate variability and features several distinct opportunities to influence ENSO. They include: (1) A Wind-Evaporation-SST (WES) feedback-driven propagation of surface anomalies onto the equator during boreal spring, (2) Trade Wind Charging (TWC) of equatorial subsurface heat content by NPMM-related surface wind stress curl anomalies in boreal winter and early spring, (3) The reflection of NPMM-forced ocean Rossby waves off the western boundary in boreal summer, and (4) A Gill-like atmospheric response associated with anomalous deep convection in boreal summer and fall. The South Pacific Meridional Mode (SPMM) also significantly modulates ENSO, and its interactions with the NPMM may contribute to ENSO diversity. Together, the NPMM and SPMM are also important components of Tropical Pacific Decadal Variability; however, future research is needed to improve understanding on these timescales. Summary Since 1950, the boreal spring NPMM skillfully predicts about 15–30% of observed winter ENSO variability. Improving simulated NPMM-ENSO relationships in forecast models may reduce ENSO forecasting error. Recent studies have begun to explore the influence of anthropogenic climate change on the NPMM-ENSO relationship; however, the results are inconclusive.

Since the early 1990s the Pacific Walker circulation shows a multi‐decadal strengthening, which contradicts future model projections. Whether this trend, evident in many climate indices especially before the 2015 El Niño, reflects the coupled ocean‐atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature trends during 1980–2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere‐Indo‐West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat‐like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central‐eastern equatorial Pacific but warming in the western Pacific and tropical Indian Ocean. Together with the PDO, this pattern drives the Walker circulation strengthening in the equatorial band. Historical simulations appear to underestimate this pattern, contributing to the models' inability to replicate the Walker cell strengthening. Plain Language Summary This paper investigates the observed changes in the tropical Pacific during the satellite era, including the recent decadal strengthening of the atmospheric zonal circulation—the Walker cell. We aim to understand the extent to which these changes represent a forced response to rising CO2 concentrations versus natural variability. We apply an approach in which we decompose the observed sea surface temperature trends into three components—a pattern associated with the Pacific Decadal Oscillation, which is part of natural variability, a uniform warming pattern, and a residual pattern. This residual pattern shows a remarkable resemblance to a forced ocean thermostat‐like transient response generated in some of the climate models, characterized by equatorial Pacific (EP) cooling, and a broad warming of the Northern Hemisphere, and the Indian Ocean and West Pacific. These results challenge studies arguing that the recent strengthening of the Pacific Walker cell can be explained simply by multi‐decadal natural variability in the tropics. Furthermore, the inability of climate models at large to fully capture this forced pattern with historical forcing puts into focus the reliability of future projections of climate change in the tropical Pacific, specifically the timing of emergence of the eastern EP warming. Key Points A multi‐decadal strengthening of the Pacific Walker cell is observed in a wide range of indices, especially after 1990 A Northern Hemisphere ‐ Indo West Pacific warming sea surface temperature pattern, which differs from the Pacific Decadal Oscillation, is evident since 1980 This pattern resembles a forced response to abrupt CO2 forcing, emerging in a subset of climate models, and contributes to the Walker circulation strenthening

Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi‐scenario, and multi GCM‐ RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature (4.3±0.7K)$(4.3\\pm 0.7\\,\\mathrm{K})$and substantial bottom warming (1.7±0.7K)$(1.7\\pm 0.7\\,\\mathrm{K})$ , longer stratification periods (+55 days) and disappearance of ice cover leading to a shift in mixing regime. Increased insufficient cooling during warmer winters points to the vulnerability of Lake Sevan to climate change. Our workflow leverages the strengths of multiple models at several levels of the model chain to provide a more robust projection and at the same time a better uncertainty estimate that accounts for the contributions of the different model levels to overall uncertainty. Although for specific variables, for example, summer bottom temperature, single lake models may perform better, the full ensemble provides a robust estimate of thermal dynamics that has a high transferability so that our workflow can be a blueprint for climate impact studies in other systems. Plain Language Summary Lakes are threatened by climate change because of effects related to the increasing temperature, long stratification, and ice disappearance. One of the best tools to predict these effects on lakes is numerical modeling of lakes that benefit from climate modeling. Climate modeling is normally done globally or in the so‐called general circulation model (GCM) or more detailed simulations on regional levels (RCM) like the CORDEX data set. In this study, we used the CORDEX data, which employed several climate models from several regions (domains) for several climatic scenarios (emissions scenarios) to force multiple lake models. This approach gave us an extensive prediction about various possible outputs. We applied this approach to Lake Sevan (Armenia), a large mountain lake. Our study predicted for the worst‐case scenario, an increase of the surface temperature by almost 4.3 K by the end of the 21st century, 1.75 K for bottom temperature, a total disappearance of ice cover, and about 55 extra days of stratification, showing its vulnerability for climate change. This optimized workflow uses the strength of a wide variety of models on the climate and lake levels to better understand the impact of climate change and quantify the sources of uncertainty in the workflow. Key Points Dual multi‐model ensemble of climate data and lake models is used for robust projections of climate change impacts Variance decomposition effectively identified the sources of uncertainty and contributions of different models to the overall uncertainty Significant warming, longer stratification periods, and loss of ice cover are predicted for Lake Sevan by the end of the 21st century

North Atlantic sea surface temperatures (NASST), particularly in the subpolar region, are among the most predictable in the world's oceans. However, the relative importance of atmospheric and oceanic controls on their variability at multidecadal timescales remain uncertain. Neural networks (NNs) are trained to examine the relative importance of oceanic and atmospheric predictors in predicting the NASST state in the Community Earth System Model 1 (CESM1). In the presence of external forcings, oceanic predictors outperform atmospheric predictors, persistence, and random chance baselines out to 25‐year leadtimes. Layer‐wise relevance propagation is used to unveil the sources of predictability, and reveal that NNs consistently rely upon the Gulf Stream‐North Atlantic Current region for accurate predictions. Additionally, CESM1‐trained NNs successfully predict the phasing of multidecadal variability in an observational data set, suggesting consistency in physical processes driving NASST variability between CESM1 and observations. Plain Language Summary North Atlantic sea surface temperatures, particularly in the subpolar region, are among the most predictable locations in the world's oceans. However, it remains uncertain if processes in the atmosphere or ocean are more important for driving temperature fluctuations in this region occurring over multiple decades. We use a machine learning approach to predict the sea surface temperature state from climate model outputs, given snapshots of atmospheric or oceanic variables. Ocean variables lead to more accurate predictions relative to atmospheric variables and standard prediction baselines out to 25 years ahead if processes that drive the trends in climate, such as human‐induced warming, are present in the data. These successful predictions arise consistently from the same region near the Gulf Stream‐North Atlantic Current region. Despite being trained on climate models, the neural networks can predict the timing of observed positive and negative states of real‐world sea surface temperatures, suggesting that there is potential for using model output to train neural networks at predicting the actual North Atlantic sea surface variability. Key Points Neural networks outperform persistence forecasts in predicting extreme states of North Atlantic sea surface temperature out to 25 years An explainable neural network technique reveals successful predictions rely consistently on the Transition Zone region Neural networks trained on climate model output predict the phasing of multidecadal variability on an observation‐based data set

Anthropogenic aerosols (AER) and greenhouse gases (GHG)—the leading drivers of the forced historical change—produce different large‐scale climate response patterns, with correlations trending from negative to positive over the past century. To understand what caused the time‐evolving comparison between GHG and AER response patterns, we apply a low‐frequency component analysis to historical surface ocean changes from CESM1 single‐forcing large‐ensemble simulations. While GHG response is characterized by its first leading mode, AER response consists of two distinct modes. The first one, featuring long‐term global AER increase and global cooling, opposes GHG response patterns up to the mid‐twentieth century. The second one, featuring multidecadal variations in AER distributions and interhemispheric asymmetric surface ocean changes, appears to reinforce the GHG warming effect over recent decades. AER thus can have both competing and synergistic effects with GHG as their emissions change temporally and spatially. Plain Language Summary Anthropogenically forced climate change over the past century has been mainly caused by two types of emissions: greenhouse gases (GHG) and aerosols (AER). In general, sulfate aerosols from industrial sources can reflect shortwave radiation to yield a cooling effect opposite to the GHG warming effect. However, model simulations isolating GHG and AER forcings show that the large‐scale climate effect of AER does not always dampen the GHG effect. Instead, over recent decades, AER have produced surface ocean response patterns more like the GHG response. Using a novel low‐frequency statistical decomposion, we find that aerosols have driven two distinct modes of climate change patterns over the historical period. The first mode is associated with global aerosol increase, resulting in global‐wide cooling damping the GHG‐induced warming. The second mode is associated with the shift in aerosol emissions from north America/western Europe to southeast Asia, which drives regional changes enhancing the GHG effect. Our results highlight the importance of considering the temporal and spatial evolutions of AER emissions in assessing GHG and AER climate effects and attributing historical anthropogenic climate changes to GHG and AER forcings. Key Points Over the past century, GHG forced response is characterized by a single dominant mode while AER response consists of two distinct modes Monotonic global aerosol increases, mainly from Southeast Asia emissions, produce a global aerosol cooling mode opposing greenhouse warming Important in recent decades, geographic redistribution of AER emissions produces a second aerosol mode that reinforces greenhouse warming