Abstract Stratosphere‐troposphere coupling (STC) in the Southern Hemisphere (SH) occurs primarily from austral spring to summer, and the dominant mode of variability in this vertical coupling (the “STC mode”) represents the timing of the seasonal transition of the polar vortex and its subsequent coupling to the Southern Annular Mode (SAM). Because it represents downward coupling over a season, stratospheric winds projected onto the STC mode are useful as a seasonal predictor of spring and summer SH surface climate. However, it is not clear how the STC mode and its connection to seasonal predictability will evolve in response to changes in stratospheric ozone and increases in greenhouse gases. Here, using four large ensemble simulations from 1950 to 2100, we apply a “snapshot EOF” technique in order to track the evolution of the mode in response to prescribed ozone and RCP8.5 greenhouse gas changes. We find that for all large ensembles, the STC mode in late spring strengthens (weakens) during the period of ozone depletion (recovery), and these responses are largest in the model that includes interactive ozone. A majority of the large ensembles further suggest a significant weakening of the mode by 2075 in an extreme RCP8.5 climate, including a decrease in the fraction of variance explained by the mode over time and a decrease in the correlation of the mode with the SAM. The key result is that as ozone recovers and greenhouse gases increase, there is a projected decline in the seasonal predictability of austral surface climate associated with the STC mode.

The role of the stratosphere for decadal surface cooling in subpolar and midlatitude Eurasia over the last few decades despite Arctic amplification is isolated using two sets of simulations in four different coupled ocean-atmosphere climate models. In the first set, the stratosphere is nudged to observations (NUDGED) while allowing for the rest of the atmosphere to evolve freely, while in the second set the ocean-atmosphere system is free-running (FREE) and the stratospheric polar vortex does not exhibit long term trends. By comparing NUDGED to FREE, we attribute to the stratosphere the anomalously cold conditions in the 2000s in high latitude Eurasia, and also the contemporaneous warm conditions in Eastern Canada. Furthermore, anomalously rainy conditions in much of Southern Europe in the 2000s can also be largely attributed to the stratosphere. This cold Eurasia fingerprint from the stratosphere overwhelmed or strongly suppressed the forced signal from anthropogenic emissions in all four models, demonstrating the crucial role the stratosphere has for decadal surface-climate variability even in a warming climate.

Abstract There are notable discrepancies between near‐surface humidity trends in observational products as compared to climate models. Here, we explore the extent to which the discrepancy can be explained by inhomogeneities in the observational record. To do so, we apply a validated changepoint detection algorithm to the residual between two observational products, the ERA5 reanalysis and HadISDH station‐based product, and a climate model simulation whose circulation is constrained to match the observations. Based on synthetic data tests, the approach is likely to identify changepoints in excess of 0.32 g/kg, and rarely identifies a changepoint when none is present. For ERA5, we identify changepoints across 31% of the global land area; qualitatively similar results are found for HadISDH. Correcting the inhomogeneities reduces, but does not eliminate, the previously identified discrepancy between model simulations and the historical record.

Abstract. The process of developing Earth System Models (ESMs) varies across modeling centers globally, but the overarching goal is largely the same – to improve the representation of physically-based processes such that biases in the mean climate state and its variability are minimized. Developers face a number of scientific and technical hurdles to ensure the best use of limited computational resources, storage space, and time. These challenges are particularly pronounced for modes of climate variability that are characterized by high internal variability, like the El Niño Southern Oscillation (ENSO). In this study, we leverage the development of the Community Earth System Model version 3 (CESM3) as a case study to illustrate some of these difficulties as well as to highlight new model developments and their impacts on ENSO. ENSO is a complicated indicator of model performance in that it can be characterized by a wide number of metrics to assess how well (or poorly) it is simulated. This is at odds with the model development process as a whole, which requires that a manageably small number of metrics be selected for model analysis as teams conduct hundreds of simulations to arrive at a single "best" model configuration. Selecting too many metrics runs the risk of dramatically slowing progress in developing a coupled ESM. As a result, we discuss a minimal set of ENSO metrics here that we consider indicative of overall model performance. We find that biases in the spatial extent of ENSO events persisted throughout the development cycle, with sea surface temperature anomalies (SSTa) that extend too far into the West Pacific for all simulations. Other metrics are more sensitive to model changes, including ENSO amplitude and duration. Such metrics are, however, prone to significant internal variability. This is confirmed by temporally sub-sampling long pre-industrial control simulations of previous model versions (CESM1 and CESM2), which also adds critical context to the evaluation of CESM3; any new model version should ideally not be markedly worse than past iterations. Ultimately, CESM3 produces a reasonable ENSO in comparison to previous model versions and relative to observations, but it remains difficult to attribute changes in its representation to individual model changes due to the significant internal variability.

Abstract. Stratospheric aerosol injection has emerged as a candidate climate intervention strategy to partially offset global surface warming. Previous work has demonstrated that lower stratospheric heating drives modifications to the stratospheric thermal profile, circulation, and water vapor, with downstream consequences for surface climate; however, the impact of stratospheric heating has not previously been characterized across a multi-model ensemble. This work presents first results from the Stratospheric Heating Model Intercomparison Project (SHeatMIP), in which an idealized 0.3 K/day tropical lower-stratospheric heating tendency is imposed across five climate models (CESM, GFDL, GISS, MIROC, UKESM). All models show robust increases in lower-stratospheric temperature, water vapor, and polar night jet strength in both hemispheres, with corresponding surface shifts in the subtropical and eddy-driven jets and a polar cap pressure response resembling a positive North Atlantic Oscillation phase. Despite qualitative agreement, inter-model spread is substantial, with differences of 1 K in the cold point temperature adjustment and 0.38 K in the global mean surface temperature response. The surface temperature spread strongly co-varies with the stratospheric water vapor response (R2 = 0.82), implicating water vapor as a key source of surface warming uncertainty. The forced polar vortex response shows strong co-variability with the climatological polar night jet strength (R2=0.98), and projects onto the surface as a polar cap pressure anomaly. The results show that inter-model differences in the response to stratospheric heating may be traceable to the climatological mean state, offering a pathway toward observationally-constrained evaluation of model suitability for SAI research.

Skillful seasonal forecasts of impactful climate events are in high demand yet remain a major challenge. Skill on seasonal timescales will arise from prediction of slowly varying predictable modes and their influence on the weather. The stratosphere provides one such mode, if it can be predicted, and if it exerts a sufficient influence on the troposphere below. Here we introduce a new seasonal hindcast data set with the Community Earth System Model version 2 (CESM2) with a raised atmospheric model lid and enhanced vertical resolution and compare with a companion hindcast set with CESM2's default vertical resolution. The enhanced vertical resolution enables considerably higher prediction skill of the Quasi-biennial Oscillation (QBO). We further use this data set to probe for associated skill in features that are thought to be influenced by the QBO and use it to inform on the uncertainties that could be present in observed QBO connections given the short observational record. This includes connections to the Northern Hemisphere polar vortex, the North Atlantic Oscillation, the Madden Julian Oscillation, the sub-tropical and mid-latitude westerlies in the Pacific sector, tropical precipitation, and the tropical easterly jet. The enhanced QBO skill has little impact on these phenomena. However, the hindcasts do indicate an improved representation of connections between the QBO and the stratospheric polar vortex and tropospheric zonal winds in the Pacific sector with higher resolution but there are indications of a low signal-to-noise problem in QBO teleconnections that, if addressed, could improve prediction skill in some of these features.

Cold extremes continue to have considerable impacts on a wide range of sectors including health, energy, agriculture, and infrastructure. On a global scale, the frequency and intensity of cold extremes are declining due to anthropogenic climate change. This general decreasing trend in cold extremes is well captured by models for the historical period. However, there are strong regional and seasonal differences in cold extreme occurrence that can be attributed to the variability of large-scale dynamical drivers of cold extremes such as sea ice, the polar stratosphere, and ENSO. The uncertain future evolution of these large-scale drivers, as well as shortcomings in our understanding of the links between these drivers and cold extremes, make it difficult to constrain the magnitude and year-to-year variability of the projected decrease in cold extremes. This review reveals a range of unresolved questions pertaining to the dynamical forcing of cold extremes and their evolution in a changing climate.

In recent years a robust weakening of the storm tracks has been identified in reanalysis data. This trend has been linked to coinciding changes in surface temperature extremes and precipitation. Here we use a surface-based metric to quantify regional trends in the boreal summertime low-level extratropical cyclone activity (ECA) and link this to surface impacts. We compare trends over the satellite-era across a single model large ensemble (SPEAR-MED Large Ensemble) and the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations, including full and single forcing simulations and prescribed sea surface temperature simulations. The models successfully capture the hemisphericwide ECA decrease and regional trends over the Pacific, North America, and Europe seen in reanalysis. However, this masks a model-observation discrepancy over the North Atlantic, which is anti-correlated with mean circulation trends. We then re-examine previous links between extratropical cyclones and increasing daily maximum surface temperatures and shifts in precipitation in historical trends. ECA trends cannot account for the magnitudes of daily maximum surface temperature trends over North America or Europe but can explain a large fraction of precipitation trends over the North Atlantic. This suggests other drivers, such as greenhouse gas radiative forcing, are more important in strengthening daily maximum surface temperature trends. In contrast, models struggle to capture the North Atlantic ECA-related trends, primarily because they underestimate ECA trends. This can explain model-observation discrepancies in total precipitation change over the West Atlantic, but not the East Atlantic.

This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data unlocking key research avenues in atmospheric science and provides justification for the resources needed to produce this data. Topics within the CMIP7 Atmosphere Theme centre around processes and feedbacks in atmospheric science such as clouds, aerosols and atmospheric chemistry, atmospheric circulation, temperature variability and extremes, radiative forcings, and Earth system model evaluation. These topics are summarised in this paper as scientific “opportunities” which will be realised through CMIP7 experiments and Earth system model outputs. These opportunities were submitted by a thematic group of atmospheric science community representatives combined with an extended consultation process. The production of these variables will close key gaps and uncertainties identified during previous rounds of CMIP, and will be broadly used by scientific, policy, governmental, industry, and other communities that rely on climate model projections for research and decision making, including supporting the 7th Intergovernmental Panel on Climate Change Assessment Report (AR7). As an author group, we also reflect on the process used to collate this data request and make recommendations to future CMIP governance on implementing a consultation on this scale in the future.

Abstract The springtime variability of the stratospheric polar vortex over Antarctica is an important source of predictability for the Southern Annular Mode (SAM) and associated Southern Hemisphere (SH) regional climate anomalies in austral spring–summer seasons. Variations in the Antarctic spring vortex often result from anomalous meridional shifts of the SH winter stratospheric jet maximum near the stratopause and associated wave–mean flow feedback. In this study, we evaluate 1) the ability of the models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) under historical forcings to simulate the observed dynamical chain of processes linking wintertime upper-stratospheric vortex anomalies to springtime surface climate anomalies; and 2) the influence of this ability on future projections of the SH stratospheric vortex and SAM under the highest greenhouse gas emission scenario [shared socioeconomic pathway (SSP) 5-8.5]. Our results show that many CMIP6 models are deficient in reproducing the observed dynamical evolution of SH vortex anomalies, mainly due to a systematic poleward bias in the mean position of the SH winter stratospheric jet maximum. These biases appear to significantly influence projected changes in the stratospheric zonal circulation and the associated SAM by the end of the twenty-first century. Therefore, model deficiencies in simulating the correct position of the SH winter stratospheric jet near the stratopause and the dynamical evolution of its anomalous meridional shift to a spring polar vortex strength anomaly constitute a key source of uncertainty in projections of the SAM and associated SH climate changes in austral spring. Significance Statement The Southern Annular Mode (SAM) is the leading mode of extratropical circulation variability in the Southern Hemisphere (SH) and significantly influences SH regional climate, ocean circulations, and Antarctic sea ice variations. Austral spring SAM variability is substantially driven by the SH springtime stratospheric polar vortex variability, which often follows anomalous meridional shifts of the preceding winter stratospheric jet and associated wave–mean flow interactions. We show that many climate models do not accurately simulate these stratospheric processes largely due to a systematic poleward bias in the mean position of the SH winter stratospheric jet maximum. These model deficiencies appear to be a key source of uncertainty in future projections of the SAM and associated SH climate changes in austral spring.

Terrestrial ecosystems currently sequester ~25% of anthropogenic carbon (C) emissions and regulate atmospheric carbon dioxide concentrations [CO2] at timescales from seasons to centuries. Previous work has shown that interannual variability in land C uptake (NBP or net biosphere production) is controlled by terrestrial water storage (TWS) and has argued that the NBP – TWS sensitivity is underestimated in Earth system models (ESMs), calling into question ESM-utility for climate change projections. Further, observational analyses have argued that a heightened NBP – TWS sensitivity in recent decades has resulted from climate change, in contrast to ESMs which show no change or a decreasing NBP – TWS sensitivity. However, internal climate variability (ICV) can obscure forced climate trends derived from observational time series. We use four ESM large ensembles to show that observed increase in the NBP – TWS sensitivity falls within the 95% confidence interval of slope changes for all ESMs examined. Further, we show that the observed change in NBP – TWS sensitivity over the last 60 years cannot be confidently distinguished from ICV. The variance across ensemble members when looking at the global NBP – TWS relationship is greatly reduced by leveraging spatially explicit maps that are available in ESM output and increasingly accessible observationally with new remote sensing technologies.

In March 2023, southeastern South America (SESA) experienced a severe heatwave with its maximum intensity exceeding four standard deviations from the climatological mean. The timing of the occurrence was also unusual, as it occurred in the late summer. This study examines the contributing factors to the March 2023 SESA heatwave using a dynamical adjustment approach based on constructed atmospheric circulation analogs from the ERA5 reanalysis. Additionally, we assess changes in March heatwaves in the Coupled Model Intercomparison Project 6 (CMIP6) Shared Socioeconomic Pathways 3-7.0 climate simulations using the same method. The dynamical adjustment indicates that the largest contributors to the heatwave are circulation anomalies (on average 33%, 2.72 degrees C) and thermodynamic effect (58%, 4.75 degrees C), primarily linked to soil-temperature feedback. This result supports that extremely dry soil from the ongoing multi-year drought played a role in amplifying the heatwave intensity. The persistence of the circulation anomalies is also noticeable during the period. The contribution of the long-term temperature trend is 9% (0.78 degrees C). In CMIP6 future simulations, the number of March heatwaves increases, but the relative frequency of March-2023-like dry-hot heatwaves decreases, largely due to projected increases in soil moisture. The contributions of the temperature trends and circulation anomalies are larger, while the thermodynamic effects related to soil-temperature feedback are reduced. The finding suggests that future March heatwaves are driven by increases in temperatures with reduced roles of soil moisture. However, uncertainty exists in future soil moisture projections, indicating the need for more understanding of changes in heatwaves in the region.

The southwestern United States is currently in a multi-decade drought that has developed since a precipitation maximum in the 1980s. While anthropogenic warming has made the drought more severe, it is the decline in winter–spring precipitation that has had a more profound effect on water resources and ecosystems. This precipitation decline is not well understood beyond its attribution to the post-1980 La Niña-like cooling trend in tropical sea surface temperatures, which caused a North Pacific anti-cyclonic atmospheric circulation trend conducive to declining precipitation in the southwestern United States. Using a hierarchy of model simulations, we show that, even under El Niño-like sea surface temperature trends, there is a tendency towards a North Pacific anti-cyclonic circulation trend and declining precipitation in the southwestern United States, counter to the canonical El Niño teleconnection. This unintuitive yet robust circulation change arises from non-additive responses to tropical mean sea surface temperature warming and radiative effects from anthropogenic aerosols. The post-1980 period exhibits the fastest southwestern US soil moisture drying among past and future periods of similar length due to the combination of this forced precipitation decline and anthropogenic warming. While the precipitation trend might reverse due to future projected El Niño-like warming and aerosol emissions reduction, it is unlikely to substantially alleviate the currently projected future drought risk. Climate model simulations suggest that both anthropogenic aerosols and tropical ocean warming have contributed to reduced precipitation over the southwestern United States in recent decades, thus making the current drought more likely than previously thought.

The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, "esm-flat10", has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 - the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as "fast track" simulations.

Stratospheric aerosol injection (SAI) is a proposed climate intervention method aimed at mitigating some of the impacts of anthropogenic global warming by enhancing the atmosphere’s reflectivity, thus reducing solar radiation reaching the Earth’s surface. While SAI’s extreme temperature-reducing effects are well-established, its impact on precipitation extremes remains uncertain, especially in Africa, a region highly vulnerable to climate change. Understanding SAI’s potential effects on precipitation extremes is crucial, as it could increase or decrease variability in precipitation patterns, thereby affecting food security and ecosystems. Our findings indicate that areas projected under SSP2-4.5 to experience intense precipitation, such as parts of West and Central Africa, are projected to experience a reduction in both the frequency and intensity of precipitation, whereas drier areas are expected to receive increased precipitation under the SSP2-4.5 scenario with SAI. Also, the response to this SAI scenario varies considerably across different regions, displaying a high degree of heterogeneity across multiple precipitation extreme indices. These findings underscore the need to explore other scenarios of SAI and for further regional studies to understand SAI’s implications better and to inform climate-policy decisions.

The Caribbean and Central American hydroclimate is understudied and complex in part due to its data sparsity, varied topographies, and multi-faceted interactions with the tropics and mid-latitudes. Recent work developed a refined and comprehensive understanding of the observed hydroclimate that has yet to be explored in global circulation models. This study investigates the simulation of the Caribbean hydroclimate using a suite of station and gridded observational datasets, the Community Earth System Model version 1 (CESM1) at high (0.25 × 0.25°) and low (0.9 × 1.25°) resolution, CESM2 at low (0.9 × 1.25°) resolution, the Coupled Model Intercomparison Project phase 6 (CMIP6) High-Resolution Model Intercomparison Project (HighResMIP), and the Geophysical Fluid Dynamics Laboratory Seamless System for Prediction and Earth System Research (GFDL-SPEAR). The simulated climatologies (1983–2014) of the annual rainfall cycle and total moisture fluxes, and climatological regressions of sea surface temperatures (SST), sea-level pressure (SLP), and zonal/meridional low-level winds onto indices of seasonal Caribbean rainfall totals are calculated to investigate inter-model differences and their comparison to observations. Generally, fully coupled CESM, GFDL-SPEAR-MED, and CMIP6 simulations underestimate precipitation across the Caribbean, with some improvements using high-resolution (< 0.5°) simulations. The underestimations are largest during the Early-Rainy Season (ERS; mid-April to mid-June). Coupled models also show a moisture divergence bias associated with a stronger/west-displaced North Atlantic Subtropical High (NASH), a weaker / southward displaced Intertropical Convergence Zone (ITCZ), and stronger Caribbean Low-Level Jet (CLLJ). Precipitation and large-scale dynamic biases in experiments with observation-based SSTs are smaller, regardless of their spatial resolution, suggesting SST biases in coupled models may contribute to precipitation and circulation biases. The findings emphasize the importance of both high-resolution and accurate simulation of coupled dynamical interactions in global circulation models to accurately simulate the Caribbean’s hydroclimate, and, therefore, provide reliable future climate projections for the region.

The Coupled Model Intercomparison Project (CMIP) coordinates community-based efforts to answer key and timely climate science questions, facilitate delivery of relevant multi-model simulations through shared infrastructure, and support national and international climate assessments. Generations of CMIP have evolved through extensive community engagement from punctuated phasing into more continuous support for the design of experimental protocols, infrastructure for data publication and access, and public delivery of climate information. We identify four fundamental research questions motivating a seventh phase of coupled model intercomparison relating to patterns of sea surface temperature change, changing weather, the water-carbon-climate nexus, and tipping points. Key CMIP7 advances include an expansion of baseline experiments, a focus on CO2-emissions-driven experiments, sustained support for community MIPs, periodic updating of historical forcings and diagnostics requests, and a collection of prioritized experiments, or the "Assessment Fast Track", drawn from community MIPs to support climate research, assessment, and service goals across prediction and projection, characterization, attribution, and process understanding.

The Detection and Attribution Model Intercomparison Project (DAMIP) coordinates single forcing climate model simulations for detection and attribution analysis and other applications. DAMIP simulations were carried out with fifteen climate models as part of CMIP6, and these simulations were used in at least 270 published articles. These simulations were also used directly in at least five chapters of the IPCC Sixth Assessment Working Group I Report, and they underpinned the estimate of anthropogenic attributable warming highlighted in the Summary for Policymakers of that report, and quoted directly in the UNFCCC Glasgow Climate Pact. For CMIP7, natural-only, well-mixed greenhouse gas-only, and aerosol-only simulations have been proposed as fast track DAMIP simulations, and planning of a broader set of experiments is currently underway. This talk will highlight key DAMIP results from CMIP6, and will discuss plans for the CMIP7 version of DAMIP. Comments and suggestions regarding the CMIP7 DAMIP experimental design will be welcomed.