Preindustrial Control Simulations Research Articles

The Impact of Interactive Ocean Dynamics on Atlantic Sea Surface Temperature Variability

Abstract The impact of interactive ocean dynamics on internal variations of Atlantic sea surface temperature (SST) is investigated by comparing preindustrial control simulations of a fully coupled atmosphere–ocean–ice model to the same atmosphere–ice model with the ocean replaced by a motionless slab layer (henceforth slab ocean model). Differences in SST variability between the two models are diagnosed by an optimization technique that finds components whose variance differs as much as possible. This technique reveals that Atlantic SST variability differs significantly between the two models. The two components with the most extreme enhancement of SST variance in the slab ocean model resemble the tripole SST pattern associated with the North Atlantic Oscillation (NAO) and the Atlantic multidecadal variability (AMV) pattern. This result supports previous claims that ocean dynamics are not necessary for the AMV, although ocean dynamics lead to slight increases in the memory of both the AMV and the NAO tripole. The component with the most extreme enhancement of SST variance in the fully coupled model resembles the Atlantic Niño pattern, confirming the ability of our technique to isolate physical modes known to require ocean dynamics. The second component with more variance in the fully coupled model is a mode of subpolar SST variability. Both the reemergence of SST anomalies and changes in ocean heat transport lead to increased SST variance and memory in the subpolar Atlantic. Despite large differences in the mean and variability of SST, atmospheric variability is quite similar between the two models, confirming that most atmospheric variability is generated by internal atmospheric dynamics.

An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles

Abstract. This work assesses a recently produced 21-member climate model large ensemble (LE) based on the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2 (E3SM2). The ensemble spans the historical era (1850 to 2014) and 21st century (2015 to 2100), using the SSP370 pathway, allowing for an evaluation of the model's forced response. A companion 500-year preindustrial control simulation is used to initialize the ensemble and estimate drift. Characteristics of the LE are documented and compared against other recently produced ensembles using the E3SM version 1 (E3SM1) and Community Earth System Model (CESM) versions 1 and 2. Simulation drift is found to be smaller, and model agreement with observations is higher in versions 2 of E3SM and CESM versus their version 1 counterparts. Shortcomings in E3SM2 include a lack of warming from the mid to late 20th century, likely due to excessive cooling influence of anthropogenic sulfate aerosols, an issue also evident in E3SM1. Associated impacts on the water cycle and energy budgets are also identified. Considerable model dependence in the response to both aerosols and greenhouse gases is documented and E3SM2's sensitivity to variable prescribed biomass burning emissions is demonstrated. Various E3SM2 and CESM2 model benchmarks are found to be on par with the highest-performing recent generation of climate models, establishing the E3SM2 LE as an important resource for estimating climate variability and responses, though with various caveats as discussed herein. As an illustration of the usefulness of LEs in estimating the potential influence of internal variability, the observed CERES-era trend in net top-of-atmosphere flux is compared to simulated trends and found to be much larger than the forced response in all LEs, with only a few members exhibiting trends as large as observed, thus motivating further study.

Climate change linked to drought in Southern Madagascar

Southern Madagascar experienced a prolonged drought over the last five years, but whether these conditions are a manifestation of global climate change has been unclear. Here, we document trends beginning as early as 1980 towards a later rainy-season onset across three distinct remotely sensed indicators: precipitation, soil moisture, and vegetation greenness. All three indicators closely covary, particularly over the last decade when satellite observational resolution and accuracy is greatest. Furthermore, observed soil moisture trends early in the rainy season agree with the mean from CMIP6 historical and SSP5-8.5 simulations, but are distinct from pre-industrial control simulations, implicating anthropogenic changes in radiative forcing as the source of the trends. Physically, these models simulate a poleward migration of the mid-latitude jet that leads to a delay in the seasonal steering of storm tracks over Southern Madagascar. Soil moisture trends driven by anthropogenic forcing made the recent drought significantly more likely over 2017–2022 (p < 0.01), and such droughts are expected to become increasingly likely over this century. These results indicate that, although Madagascar has not substantially contributed to global greenhouse gas emissions, farmers in Southern Madagascar will need to adapt to drier conditions early in the rainy season as a consequence of global climate change.

The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2

Abstract. For several decades, a suite of satellite sensors has enabled us to study the global spatiotemporal distribution of phytoplankton through remote sensing of chlorophyll. However, the satellite record has extensive missing data, partially due to cloud cover; regions characterized by the highest phytoplankton abundance are also some of the cloudiest. To quantify potential sampling biases due to missing data, we developed a satellite simulator for ocean chlorophyll in the Community Earth System Model (CESM) that mimics what a satellite would detect if it were present in the model-generated world. Our Chlorophyll Observation Simulator Package (ChlOSP) generates synthetic chlorophyll observations at model runtime. ChlOSP accounts for missing data – due to low light, sea ice, and cloud cover – and it can implement swath sampling. Here, we introduce this new tool and present a preliminary study focusing on long timescales. Results from a 50-year pre-industrial control simulation of CESM–ChlOSP suggest that missing data impact the apparent mean state and variability of chlorophyll. The simulated observations exhibit a nearly −20 % difference in global mean chlorophyll compared with the standard model output, which is the same order of magnitude as the projected change in chlorophyll by the end of the century. Additionally, missing data impact the apparent seasonal cycle of chlorophyll in subpolar regions. We highlight four potential future applications of ChlOSP: (1) refined model tuning; (2) evaluating chlorophyll-based net primary productivity (NPP) algorithms; (3) revised time to emergence of anthropogenic chlorophyll trends; and (4) a test bed for the assessment of gap-filling approaches for missing satellite chlorophyll data.

Investigating Atmospheric Responses to and Mechanisms Governing North Atlantic Sea Surface Temperatures over 10-Year Periods

Abstract North Atlantic sea surface temperature (SST) variability plays a critical role in modulating the climate system. However, characterizing patterns of North Atlantic SST variability and diagnosing the associated mechanisms is challenging because they involve coupled atmosphere–ocean interactions with complex spatiotemporal relationships. Here we address these challenges by applying a time-evolving self-organizing map approach to a long preindustrial coupled control simulation and identify a variety of 10-yr spatiotemporal evolutions of winter SST anomalies, including but not limited to those associated with the North Atlantic Oscillation–Atlantic multidecadal variability (NAO–AMV)-like interactions. To assess mechanisms and atmospheric responses associated with various SST spatiotemporal evolutions, composites of atmospheric and oceanic variables associated with these evolutions are investigated. Results show that transient-eddy activities and atmospheric circulation responses exist in almost all the evolutions that are closely correlated to the details of the SST pattern. In terms of the mechanisms responsible for generating various SST evolutions, composites of ocean heat budget terms demonstrate that contributions to upper-ocean temperature tendency from resolved ocean advection and surface heat fluxes rarely oppose each other over 10-yr periods in the subpolar North Atlantic. We further explore the potential for predictability for some of these 10-yr SST evolutions that start with similar states but end with different states. However, we find that these are associated with abrupt changes in atmospheric variability and are unlikely to be predictable. In summary, this study broadly investigates the atmospheric responses to and the mechanisms governing the North Atlantic SST evolutions over 10-yr periods. Significance Statement Climate variability in the North Atlantic Ocean has wide-ranging impacts on global and regional climate. However, the processes involved include interactions between the ocean and atmosphere that vary across both space and time, making it challenging to characterize and predict. Using a novel machine learning approach, this study identifies various time evolutions of North Atlantic sea surface temperature patterns over 10-yr periods. This includes evolutions with similar start states but different trajectories, which have important implications for predictability. Furthermore, we investigate the mechanisms responsible for these evolutions and how different sea surface temperature patterns affect atmospheric circulation through small-scale atmospheric disturbances. These new insights into the complex ocean–atmosphere interactions over time are critical for improving decadal prediction skill.

Diversity of Lagged Relationships in Global Means of Surface Temperatures and Radiative Budgets for CMIP6 piControl Simulations

Abstract Radiative feedbacks over interannual time scales can be potentially useful for global warming estimation. However, the diversity of the lead–lag relationships in global mean surface temperature (GMST) and net radiation flux at the top of the atmosphere (GMTOA) create uncertainty during the estimation of radiative feedbacks. In this study, key physical processes controlling lead–lag relationships were elucidated by categorizing preindustrial control simulations of CMIP6 into three groups based on cross correlation values of GMTOA against GMST at lag 0 and lag +1 year. The diversity in the lead–lag relationships was primarily caused by the climatological state difference of the atmosphere over the equatorial Pacific, which modulated the strength of convective activity and sensitivity of low-level clouds. Diminished atmospheric stability caused enhanced convective activity, more efficient energy release, and smaller lags. In addition, enhanced stability in the lower atmosphere rendered the low-level clouds more sensitive to sea surface temperature changes and considerably delayed the radiative response. The climatological state difference of the atmosphere resulted from model-inherent atmospheric conditions. These findings suggest that the diversity of lead–lag relationships of GMST and GMTOA over interannual time scales could represent the characteristics of general atmospheric circulation models and possible solutions of the actual atmosphere, which could also affect long-term feedback features.

The role of internal variability and external forcing on southwestern Australian rainfall: prospects for very wet or dry years

The cool-season (May to October) rainfall decline in southwestern Australia deepened during 2001–2020 to become 20.5% less than the 1901–1960 reference period average, with a complete absence of very wet years (i.e., rainfall > 90th percentile). CMIP5 and CMIP6 climate model simulations suggest that approximately 43% of the observed multi-decadal decline was externally-forced. However, the observed 20-year rainfall anomaly in 2001–2020 is outside the range of both preindustrial control and historical simulations of almost all climate models used in this study. This, and the fact that the models generally appear to simulate realistic levels of decadal variability, suggests that 43% might be an underestimate. A large ensemble from one model exhibits drying similar to the observations in 10% of simulations and suggests that the external forcing contribution is indeed larger (66%). The majority of models project further drying over the twenty-first century, even under strong cuts to greenhouse gas emissions. Under the two warmest scenarios, over 70% of the late twenty-first century years are projected to be drier than the driest year simulated during the 1901–1960 period. Our results suggest that few, if any, very wet years will occur during 2023–2100, even if strong cuts to global emissions are made.

Interdecadal Variations of Radiative Feedbacks Associated With the El Niño and Southern Oscillation (ENSO) in CMIP6 Models

AbstractInternally generated radiative feedback at interannual timescales can influence climate sensitivity estimates. This study has clarified the mechanisms of variability in radiative feedback associated with the El Niño and Southern Oscillation based on preindustrial control simulations for Coupled Model Intercomparison Project Phase 6. Radiative feedback showed large modulation with a comparable magnitude to the intermodel uncertainty associated with internal changes in the zonal gradient of the ocean thermocline and sea surface temperature (SST) in the equatorial Pacific on interdecadal timescales. When the interdecadal SST anomalies in the eastern and western equatorial Pacific were simulated as positive and negative, respectively, the statistical properties of the interannual variations were also modified with diminished Walker circulation changes per unit of global mean surface temperature rise. Meanwhile, the enhanced local Hadley circulation led to a middle‐to upper‐level cloud decrease and a low‐level cloud increase in the subtropics, causing enhanced negative radiative feedback as a global average.

Pantropical Indo-Atlantic temperature gradient modulates multi-decadal AMOC variability in models and observations

Interconnections between ocean basins are recognized as an important driver of climate variability. Recent modeling evidence suggests that the North Atlantic climate can respond to persistent warming of the tropical Indian Ocean sea surface temperature (SST) relative to the rest of the tropics (rTIO). Here, we use observational data to demonstrate that multi-decadal changes in pantropical ocean temperature gradients lead to variations of an SST-based proxy of the Atlantic Meridional Overturning Circulation (AMOC). The largest contribution to this temperature gradient-AMOC connection comes from gradients between the Indian and Atlantic Oceans. The rTIO index yields the strongest connection of this tropical temperature gradient to the AMOC. Focusing on the internally generated signal in three observational products reveals that an SST-based AMOC proxy index has closely followed low-frequency changes of rTIO temperature with about 26-year lag since 1870. Analyzing the pre-industrial control simulations of 44 CMIP6 climate models shows that the AMOC proxy index lags simulated mid-latitude AMOC variations by 4 ± 4 years. These model simulations reveal the mechanism connecting AMOC variations to pantropical ocean temperature gradients at a 27 ± 2 years lag, matching the observed time lag in 28 out of the 44 analyzed models. rTIO temperature changes affect the North Atlantic climate through atmospheric planetary waves, impacting temperature and salinity in the subpolar North Atlantic, which modifies deep convection and ultimately the AMOC. Through this mechanism, observed internal rTIO variations can serve as a multi-decadal precursor of AMOC changes with important implications for AMOC dynamics and predictability.

Fingerprinting Low-Frequency Last Millennium Temperature Variability in Forced and Unforced Climate Models

Abstract Constraining unforced and forced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and last millennium Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability at multidecadal and longer time scales. This mismatch suggests that existing simulations underestimate either external or internal drivers of climate variability. In addition, large differences arise across GCMs in both the magnitude and spatial pattern of low-frequency climate variability. Dynamical understanding of forced and unforced variability is expected to contribute to improved interpretations of paleoclimate variability. To that end, we develop a framework for fingerprinting spatiotemporal patterns of temperature variability in forced and unforced simulations. This framework relies on two frequency-dependent metrics: 1) degrees of freedom (≡N) and 2) spatial coherence. First, we use N and spatial coherence to characterize variability across a suite of both preindustrial control (unforced) and last-millennium (forced) GCM simulations. Overall, we find that, at low frequencies and when forcings are added, regional independence in the climate system decreases, reflected in fewer N and higher coherence between local and global mean surface temperature. We then present a simple three-box moist-static-energy-balance model for temperature variability, which is able to emulate key frequency-dependent behavior in the GCMs. This suggests that temperature variability in the GCM ensemble can be understood through Earth’s energy budget and downgradient energy transport, and allows us to identify sources of polar-amplified variability. Finally, we discuss insights the three-box model can provide into model-to-model GCM differences. Significance Statement Forced and unforced temperature variability are poorly constrained and understood, particularly that at time scales longer than a decade. Here, we identify key differences in the time scale–dependent behavior of forced and unforced temperature variability using a combination of numerical climate models and principles of downgradient energy transport. This work, and the spatiotemporal characterizations of forced and unforced temperature variability that we generate, will aid in interpretations of proxy-based paleoclimate reconstructions and improve mechanistic understanding of variability.

The role of internal feedbacks in sustaining multi-centennial variability of the Atlantic Meridional Overturning Circulation revealed by EC-Earth3-LR simulations

A significant multi-centennial climate variability with a distinct peak at approximately 200 years is observed in a pre-industrial (PI) control simulation using the EC-Earth3-LR climate model. This oscillation originates predominately from the North Atlantic and displays a strong association with the Atlantic Meridional Overturning Circulation (AMOC). Our study identifies the interplay between salinity advection feedback and vertical mixing in the subpolar North Atlantic as key roles in providing the continues internal energy source to maintain this multi-centennial oscillation. The perturbation flow of mean subtropical-subpolar salinity gradients serves as positive feedback to sustain the AMOC anomaly, while the mean advection of salinity anomalies and the vertical mixing or convection acts as negative feedback, constraining the AMOC anomaly. Notably, this low-frequency variability persists even in a warmer climate with weakened AMOC, emphasizing the robustness of the salinity advection feedback mechanism.

Mechanisms of Tibetan Plateau Warming Amplification in Recent Decades and Future Projections

Abstract Earth’s surface warming by external forcing depends on location. Warming amplification, or greater surface warming than the global average, occurs in the Arctic and high-elevation regions, including the Tibetan Plateau (TP). We examined the major drivers of TP warming amplification in recent decades (1979–2020) and under future climate scenarios (2061–2100) by applying local energy budget diagnosis of multiple radiative kernels based on state-of-the-art reanalysis datasets and coupled model simulations. From 1979 to 2020, both the snow–albedo feedback and cloud–radiation feedback strongly affected the seasonality of TP warming (summer vs winter). Snow cover and albedo decreased significantly in winter but showed only small changes in summer. TP total and low-level cloud cover increased in summer, causing cooling, and decreased in winter, causing warming. During winter, TP warming amplification (1.84 from 1979 to 2020) is weaker than Arctic amplification (3.64) because the positive contribution of the surface albedo feedback to TP warming is not as strong as the dual warming effects of the lapse rate feedback and surface heat flux observed in the Arctic. Our attribution analyses based on the preindustrial control (piControl) and Historical simulations of phase 6 of the Coupled Model Intercomparison Project confirmed that TP warming is caused by external forcing. Because the external forcing associated with anthropogenic activity is increasing, TP warming will continue to the end of the twenty-first century. Under likely future warming scenarios, winter TP warming amplification is still less than in the Arctic due to the effects of the lapse rate feedback and surface heat flux. Significance Statement Over the Tibetan Plateau, warming amplification, which refers to greater surface warming than the global average (∼75% more warming than the global average from 1979 to 2020), has resulted in melting permafrost, retreating glaciers, and decreasing biodiversity. This study quantified the relative effects of eight physical processes on the warming amplification over the Tibetan Plateau. In the boreal winter, the reduction in snow cover and albedo are the leading contributors (about 49%) to Tibetan Plateau warming, meaning that melting snow exposes darker ground that absorbs more sunlight than snow does. In a warmer future climate, continued melting snow cover is projected to further enhance Tibetan Plateau warming amplification.

How does tropospheric VOC chemistry affect climate? An investigation of preindustrial control simulations using the Community Earth System Model version 2

Abstract. Because of their computational expense, models with comprehensive tropospheric chemistry have typically been run with prescribed sea surface temperatures (SSTs), which greatly limits the model's ability to generate climate responses to atmospheric forcings. In the past few years, however, several fully coupled models with comprehensive tropospheric chemistry have been developed. For example, the Community Earth System Model version 2 with the Whole Atmosphere Community Climate Model version 6 as its atmospheric component (CESM2-WACCM6) has implemented fully interactive tropospheric chemistry with 231 chemical species as well as a fully coupled ocean. Earlier versions of this model used a “SOAG scheme” that prescribes bulk emission of a single gas-phase precursor to secondary organic aerosols (SOAs). In contrast, CESM2-WACCM6 simulates the chemistry of a comprehensive range of volatile organic compounds (VOCs) responsible for tropospheric aerosol formation. Such a model offers an opportunity to examine the full climate effects of comprehensive tropospheric chemistry. To examine these effects, 211-year preindustrial control simulations were performed using the following two configurations: (1) the standard CESM2-WACCM6 configuration with interactive chemistry over the whole atmosphere (WACtl) and (2) a simplified CESM2-WACCM6 configuration using a SOAG scheme in the troposphere and interactive chemistry in the middle atmosphere (MACtl). The middle-atmospheric chemistry is the same in both configurations, and only the tropospheric chemistry differs. Differences between WACtl and MACtl were analyzed for various fields. Regional differences in annual mean surface temperature range from −4 to 4 K. In the zonal average, there is widespread tropospheric cooling in the extratropics. Longwave forcers are shown to be unlikely drivers of this cooling, and possible shortwave forcers are explored. Evidence is presented that the climate response is primarily due to increased sulfate aerosols in the extratropical stratosphere and cloud feedbacks. As found in earlier studies, enhanced internal mixing with SOAs in WACtl causes widespread reductions of black carbon (BC) and primary organic matter (POM), which are not directly influenced by VOC chemistry. These BC and POM reductions might further contribute to cooling in the Northern Hemisphere. The extratropical tropospheric cooling results in dynamical changes, such as equatorward shifts of the midlatitude jets, which in turn drive extratropical changes in clouds and precipitation. In the tropical upper troposphere, cloud-driven increases in shortwave heating appear to weaken and expand the Hadley circulation, which in turn drives changes in tropical and subtropical precipitation. Some of the climate responses are quantitatively large enough in some regions to motivate future investigations of VOC chemistry's possible influences on anthropogenic climate change.

Climate Response to Atlantic Meridional Energy Transport Variations

Abstract The climate responses to Atlantic meridional overturning circulation (AMOC) fluctuations are investigated in a hierarchy of sensitivity experiments. We modify the baroclinic component of the North Atlantic Ocean currents online in an atmosphere–ocean general circulation model to reproduce typical AMOC multidecadal variability found in a preindustrial control simulation in the same model. An analogous experiment is also conducted using a slab-ocean experiment. The responses to a strong AMOC include a widespread warming in the Northern Hemisphere and a northward shift of the intertropical convergence zone over the Atlantic Ocean. The driving mechanism of climate responses is then investigated with the changes in the energy flows in the ocean and atmosphere. The large-scale atmospheric changes in the tropics are organized by an anomalous cross-equatorial Hadley circulation transporting energy southward and moisture and heat northward. Changes in the Indo-Pacific Ocean circulation and heat transport, driven by the wind stress associated with the abnormal Hadley cell, damp the atmospheric responses. The lack of Indo-Pacific transport and ocean heat storage leads to amplified atmospheric changes in the slab-ocean experiments, which are further amplified by a positive feedback due to the interhemispheric antisymmetric changes in low cloud cover.

Multi-decadal variation of ENSO forecast skill since the late 1800s

Diagnosing El Niño-Southern Oscillation (ENSO) predictability within operational forecast models is hindered by computational expense and the need for initialization with three-dimensional fields generated by global data assimilation. We instead examine multi-year ENSO predictability since the late 1800s using the model-analog technique, which has neither limitation. We first draw global coupled model states from pre-industrial control simulations, from the Coupled Model Intercomparison Project Phase 6, that are chosen to initially match observed monthly sea surface temperature and height anomalies in the Tropics. Their subsequent 36-month model evolution are the hindcasts, whose 20th century ENSO skill is comparable to twice-yearly hindcasts generated by a state-of-the-art European operational forecasting system. Despite the so-called spring predictability barrier, present throughout the record, there is substantial second-year ENSO skill, especially after 1960. Overall, ENSO exhibited notably high values of both amplitude and skill towards the end of the 19th century, and again in recent decades.

Understanding the Drivers of Atlantic Multidecadal Variability Using a Stochastic Model Hierarchy

Abstract The relative importance of ocean and atmospheric dynamics in generating Atlantic multidecadal variability (AMV) remains an open question. Comparisons between climate models with a slab ocean (SLAB) and fully dynamic ocean components (FULL) are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper-ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy-resolving preindustrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence, and power spectra. Furthermore, the unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. The stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

No changes in overall AMOC strength in interglacial PMIP4 time slices

Abstract. The Atlantic Meridional Overturning Circulation (AMOC) is a key mechanism of poleward heat transport and an important part of the global climate system. How it responded to past changes in forcing, such as those experienced during Quaternary interglacials, is an intriguing and open question. Previous modelling studies suggest an enhanced AMOC in the mid-Holocene compared to the preindustrial period. In earlier simulations from the Palaeoclimate Modelling Intercomparison Project (PMIP), this arose from feedbacks between sea ice and AMOC changes, which were dependent on resolution. Here we present an initial analysis of recently available PMIP4 simulations for three experiments representing different interglacial conditions – one 127 000 years ago within the Last Interglacial (127 ka, called lig127k), one in the middle of the Holocene (midHolocene, 6 ka), and a preindustrial control simulation (piControl, 1850 CE). Both lig127k and midHolocene have altered orbital configurations compared to piControl. The ensemble mean of the PMIP4 models shows the strength of the AMOC does not markedly change between the midHolocene and piControl experiments or between the lig127k and piControl experiments. Therefore, it appears orbital forcing itself does not alter the overall AMOC. We further investigate the coherency of the forced response in AMOC across the two interglacials, along with the strength of the signal, using eight PMIP4 models which performed both interglacial experiments. Only two models show a stronger change with the stronger forcing, but those models disagree on the direction of the change. We propose that the strong signals in these two models are caused by a combination of forcing and the internal variability. After investigating the AMOC changes in the interglacials, we further explored the impact of AMOC on the climate system, especially on the changes in the simulated surface temperature and precipitation. After identifying the AMOC's fingerprint on the surface temperature and rainfall, we demonstrate that only a small percentage of the simulated surface climate changes could be attributed to the AMOC. Proxy records of sedimentary Pa/Th ratio during the two interglacial periods both show a similar AMOC strength compared to the preindustrial, which fits nicely with the simulated results. Although the overall AMOC strength shows minimal changes, future work is required to explore whether this occurs through compensating variations in the different components of AMOC (such as Iceland–Scotland overflow water). This line of evidence cautions against interpreting reconstructions of past interglacial climate as being driven by AMOC, outside of abrupt events.

Circulation and Soil Moisture Contributions to Heatwaves in the United States

Abstract Extreme heat events are a threat to human health, productivity, and food supply, so understanding their drivers is critical to adaptation and resilience. Anticyclonic circulation and certain quasi-stationary Rossby wave patterns are well known to coincide with heatwaves, and soil moisture deficits amplify extreme heat in some regions. However, the relative roles of these two factors in causing heatwaves is still unclear. Here we use constructed circulation analogs to estimate the contribution of atmospheric circulation to heatwaves in the United States in the Community Earth System Model version 1 (CESM1) preindustrial control simulations. After accounting for the component of the heatwaves explained by circulation, we explore the relationship between the residual temperature anomalies and soil moisture. We find that circulation explains over 85% of heatwave temperature anomalies in the eastern and western United States but only 75%–85% in the central United States. In this region, there is a significant negative correlation between soil moisture the week before the heatwave and the strength of the heatwave that explains additional variance. Further, for the hottest central U.S. heatwaves, positive temperature anomalies and negative soil moisture anomalies are evident over a month before heatwave onset. These results provide evidence that positive land–atmosphere feedbacks may be amplifying heatwaves in the central United States and demonstrate the geographic heterogeneity in the relative importance of the land and atmosphere for heatwave development. Analysis of future circulation and soil moisture in the CESM1 Large Ensemble indicates that, over parts of the United States, both may be trending toward greater heatwave likelihood.

A modeling framework to understand historical and projected ocean climate change in large coupled ensembles

Abstract. The ocean responds to climate change through modifications of heat, freshwater and momentum fluxes at its boundaries. Disentangling the specific role of each of these contributors in shaping the changes of the thermohaline structure of the ocean is central for our process understanding of climate change and requires the design of specific numerical experiments. While it has been partly addressed by modeling studies using idealized CO2 forcings, the time evolution of these individual contributions during historical and projected climate change is however lacking. Here, we propose a novel modeling framework to isolate these contributions in coupled climate models for which large ensembles of historical and scenario simulations are available. The first step consists in reproducing a coupled pre-industrial control simulation with an ocean-only configuration, forced by prescribed fluxes at its interface, diagnosed from the coupled model. In a second step, we extract the external forcing perturbations from the historical+scenario ensemble of coupled simulations, and we add them to the prescribed fluxes of the ocean-only configuration. We then successfully replicate the ocean's response to historical and projected climate change in the coupled model during 1850–2100. In a third step, this full response is decomposed in sensitivity experiments in which the forcing perturbations are applied individually to the heat, freshwater and momentum fluxes. Passive tracers of temperature and salinity are implemented to discriminate the addition of heat and freshwater flux anomalies from the redistribution of pre-industrial heat and salt content in response to ocean circulation changes. Here, we first present this general framework and then apply it to the IPSL-CM6A-LR model and its ocean component NEMO3.6. This framework brings new opportunities to precisely explore the mechanisms driving historical and projected ocean changes within single climate models.

The tropical route of quasi-biennial oscillation (QBO) teleconnections in a climate model

Abstract. The influence of the quasi-biennial oscillation (QBO) on tropical climate is demonstrated using 500-year pre-industrial control simulations from the Met Office Hadley Centre model. Robust precipitation responses to the phase of the QBO are diagnosed in the model, which show zonally asymmetric patterns that resemble the El Niño–Southern Oscillation (ENSO) impacts. These patterns are found because the frequency of ENSO events for each QBO phase is significantly different in these simulations, with more El Niño events found under the westerly phase of the QBO (QBOW) and more La Niña events for the easterly phase (QBOE). The QBO–ENSO relationship is non-stationary and subject to decadal variability in both models and observations. In addition, regression analysis shows that there is a QBO signal in precipitation that is independent of ENSO. No evidence is found to suggest that these QBO–ENSO relationships are caused by ENSO modulating the QBO in the simulations. A relationship between the QBO and a dipole of precipitation in the Indian Ocean is also found in models and observations in boreal fall, characterised by a wetter western Indian Ocean and drier conditions in the eastern part for QBOW and the opposite under QBOE conditions. The Walker circulation is significantly weaker during QBOW compared to QBOE, which could explain the observed and simulated zonally asymmetric precipitation responses at equatorial latitudes, as well as the more frequent El Niño events during QBOW. Further work, including targeted model experiments, is required to better understand the mechanisms causing these relationships between the QBO and tropical convection.