An adequate characterization of internal modes of climate variability (MoV) is a prerequisite for both accurate seasonal predictions and climate change detection and attribution. Assessing the fidelity of climate models in simulating MoV is therefore essential; however, doing so is complicated by the large intrinsic variations in MoV and the limited span of the observational record. Large ensembles (LEs) provide a unique opportunity to assess model fidelity in simulating MoV and quantify intermodel contrasts. In this work, these goals are pursued in four recently produced LEs: the versions 1 and 2 LEs. In general, the representation of global coupled modes is found to improve across successive E3SM and CESM versions in conjunction with the fidelity of the base state climate while the patterns of extratropical modes are well simulated across the ensembles. Various persistent shortcomings for all MoV are however identified and discussed. The results both demonstrate the successes of these recent model versions and suggest the potential for continued improvement in the representation of MoV with advances in model physics.

Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM2.5) as major climate forcers. Yet the model performance for PM2.5 components remains little evaluated due in part to lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by fourteen CMIP6 models, including organic carbon (OC, available in 14 models), black carbon (BC, 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM2.5 components. Seven models output total PM2.5 concentrations, and they all underestimate the observed total PM2.5 over eastern China, with GFDL-ESM4 (–1.5 %) and MPI-ESM-1-2-HAM (–1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM2.5 from the available components output, underestimate the total PM2.5 concentrations, partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by –71.2 % to –37.8 % across the 14 models) and the smallest for BC (–47.9 % to –12.1 %). The multi-model mean (MMM) reproduces fairly well the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.75), yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing.

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.

Tropical cyclones (TCs) alter upper-ocean temperature and influence ocean heat content via enhanced turbulent mixing. A better understanding of the role of TCs within the climate system requires a fully coupled modeling framework, where TC-induced ocean responses feed back to the atmosphere and subsequently to the climate mean state and variability. Here, we investigate the impacts of TC wind forcing on the global ocean and the associated feedbacks within the climate system using the fully coupled Community Earth System Model version 1.3 (CESM1.3). Using the low-resolution version of CESM1.3 (1 degrees atmosphere and ocean grid spacing) with no intrinsic TCs, we conduct a suite of sensitivity experiments by inserting TC winds extracted from a high-resolution (0.25 degrees atmosphere grid spacing) TC-permitting simulation into the low-resolution model. Results from the low-resolution TC experiment are compared to a low-resolution control simulation to diagnose TCs' impact. We found that the added TC winds can increase ocean heat content by affecting ocean vertical mixing, air-sea enthalpy fluxes, and cloud amount. The added TCs can influence mean SST, precipitation, ocean subsurface temperature, and ocean mixed layer depth. We found a strengthening of the wind-driven subtropical cells and a weakening of the Atlantic meridional overturning circulation due to the changes of surface buoyancy fluxes. TCs in the model cause anomalous equatorward ocean heat convergence in the deep tropics and an increase of poleward ocean heat transport out of the subtropics. Our modeling results provide new insights into the multiscale interactions between TCs and the coupled climate system.

The Atlantic meridional overturning circulation is an important global-scale oceanic circulation, and its changes may be responsible for past abrupt climate change events. By using two versions of a coupled climate model, here we show that the stability of this circulation depends not only on the background climate, but also on the type of primary external forcing: freshwater vs. greenhouse gases. When freshwater forcing is dominant, hysteresis of this circulation (an abrupt collapse/reactivation) becomes possible only under simulated glacial conditions with closed Bering Strait. Under present day and future conditions, both freshwater and greenhouse gas forcings could collapse this circulation, but only greenhouse gas forcing produced a bi-stable equilibrium state comparable to abrupt climate change. Our results demonstrate that the Bering Strait status (open vs. closed) may facilitate or prohibit the existence of this circulation’s hysteresis, irrespective of the background climate conditions, but is directly related to the primary forcing.

Figure S1: Time series of PI global T2m (K) in the LEs, including their mean (mn

All CESM2 ocean grid coordinates and scalar constants

The potential for multiyear prediction of impactful Earth system change remains relatively underexplored compared to shorter (subseasonal to seasonal) and longer (decadal) timescales. In this study, we introduce a new initialized prediction system using the Community Earth System Model version 2 (CESM2) that is specifically designed to probe potential and actual prediction skill at lead times ranging from 1 month out to 2 years. The Seasonal-to-Multiyear Large Ensemble (SMYLE) consists of a collection of 2-year-long hindcast simulations, with four initializations per year from 1970 to 2019 and an ensemble size of 20. A full suite of output is available for exploring near-term predictability of all Earth system components represented in CESM2. We show that SMYLE skill for El Niño–Southern Oscillation is competitive with other prominent seasonal prediction systems, with correlations exceeding 0.5 beyond a lead time of 12 months. A broad overview of prediction skill reveals varying degrees of potential for useful multiyear predictions of seasonal anomalies in the atmosphere, ocean, land, and sea ice. The SMYLE dataset, experimental design, model, initial conditions, and associated analysis tools are all publicly available, providing a foundation for research on multiyear prediction of environmental change by the wider community.

Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version by default [v1]NCAR Datasets Published in the CloudAuthorsJeffde La BeaujardièreiDBrianBonnlanderSethMcGinnisiDMaxwellGroverAndersonBanihirweiDKevinRaederiDGaryStrandiDSee all authors Jeff de La BeaujardièreiDCorresponding Author• Submitting AuthorNational Center for Atmospheric ResearchiDhttps://orcid.org/0000-0002-1001-9210view email addressThe email was not providedcopy email addressBrian BonnlanderNational Center for Atmospheric Researchview email addressThe email was not providedcopy email addressSeth McGinnisiDNational Center for Atmospheric ResearchiDhttps://orcid.org/0000-0001-8082-834Xview email addressThe email was not providedcopy email addressMaxwell GroverNational Center for Atmospheric Researchview email addressThe email was not providedcopy email addressAnderson BanihirweiDNational Center for Atmospheric ResearchiDhttps://orcid.org/0000-0001-6583-571Xview email addressThe email was not providedcopy email addressKevin RaederiDNational Center for Atmospheric ResearchiDhttps://orcid.org/0000-0002-6166-7154view email addressThe email was not providedcopy email addressGary StrandiDNational Center for Atmospheric ResearchiDhttps://orcid.org/0000-0001-9740-0104view email addressThe email was not providedcopy email address

Low-lying island nations like Indonesia are vulnerable to sea level Height EXtremes (HEXs). When compounded by marine heatwaves, HEXs have larger ecological and societal impact. Here we combine observations with model simulations, to investigate the HEXs and Compound Height-Heat Extremes (CHHEXs) along the Indian Ocean coast of Indonesia in recent decades. We find that anthropogenic sea level rise combined with decadal climate variability causes increased occurrence of HEXs during 2010-2017. Both HEXs and CHHEXs are driven by equatorial westerly and longshore northwesterly wind anomalies. For most HEXs, which occur during December-March, downwelling favorable northwest monsoon winds are enhanced but enhanced vertical mixing limits surface warming. For most CHHEXs, wind anomalies associated with a negative Indian Ocean Dipole (IOD) and co-occurring La Niña weaken the southeasterlies and cooling from coastal upwelling during May-June and November-December. Our findings emphasize the important interplay between anthropogenic warming and climate variability in affecting regional extremes.

The Atlantic Meridional Overturning circulation (AMOC) is an important global scale circulation and changes in AMOC can induce significant regional and global climate impacts. Here we study the stability of AMOC and its influence on global ocean circulation and the surface climate though analyzing a set of sensitivity experiments using the Community Climate System Model version 1 (CESM1). Results show that a collapsed AMOC can induce changes in global ocean circulation, such as reduced (or reversed) Bering Strait transport, weakened Indonesia throughflow and Agulhas current, but strengthened Drake Passage transport. It also changes the global wind pattern and surface temperature, such as a seesaw-like surface temperature change between Northern and Southern Hemispheres, a weakening of Indian-Australia summer monsoon, a southward shift of the Southern ocean westerlies, etc. We also found that AMOC and the Pacific deep meridional overturning circulation (or PMOC) do not form a natural seesaw under modern day climate and geography. A collapsed AMOC (active PMOC) is not stable under modern conditions if there is no additional freshwater (salt) input in the subpolar North Atlantic (Pacific), suggesting that the modern mean state of AMOC (PMOC) does not depend on local haline forcing although its variability and changes do.

Abstract The low-lying coastal and island regions are vulnerable to sea level rise and extreme events. Compounded by marine heatwaves, sea level extremes have devastating impacts on coastal community and marine ecosystems. As long tide gauge records are sparse, sea level extremes around Indonesia are poorly understood, and the Compound Height-Heat EXtreme (C-HHEX) events remain unexplored. Here we combine in situ and satellite observations with model simulations, to investigate the long-lasting (>1 month) sea level extremes and C-HHEXs along Indonesian coasts of the Indian Ocean since the 1960s. We find that 90% (80%) of the extreme sea level (C-HHEX) events, with a maximum monthly sea level anomaly of 0.45m, are clustered in an 8yr period of 2010-2017, due to anthropogenic global sea level rise and decadal enhancement driven by changing surface winds associated with a combined invigoration of the Indian and Pacific Walker Cells, atmospheric overturning circulations in east-west direction. Remote and local surface wind anomalies associated with negative phases of the Indian Ocean Dipole (IOD) - enhanced by La Niña – drive individual C-HHEX events under a precondition of shallow thermocline (a region of subsurface ocean with temperature decreases rapidly downward). By contrast, winds associated with monsoon and its intraseasonal oscillations force the sea level alone events under a deep thermocline condition. We conclude that the shoaling thermocline in eastern Indian Ocean under anthropogenic warming and global sea level rise favorably precondition the ocean for stronger and more frequent sea level extremes and C-HHEXs, increasing the environmental stress on Indonesia.

Major tropical volcanic eruptions have a large impact on climate, but there have only been three major eruptions during the recent relatively well‐observed period. Models are therefore an important tool to understand and predict the impacts of an eruption. This study uses five state‐of‐the‐art decadal prediction systems that have been initialized with the observed state before volcanic aerosols are introduced. The impact of the volcanic aerosols is found by subtracting the results of a reference experiment where the volcanic aerosols are omitted. We look for the robust impact across models and volcanoes by combining all the experiments, which helps reveal a signal even if it is weak in the models. The models used in this study simulate realistic levels of warming in the stratosphere, but zonal winds are weaker than the observations. As a consequence, models can produce a pattern similar to the North Atlantic Oscillation in the first winter following the eruption, but the response and impact on surface temperatures are weaker than in observations. Reproducing the pattern, but not the amplitude, may be related to a known model error. There are also impacts in the Pacific and Atlantic Oceans. This work contributes toward improving the interpretation of decadal predictions in the case of a future large tropical volcanic eruption.

Abstract Simulations of 21st century climate with Community Earth System Model version 2 (CESM2) using the standard atmosphere (CAM6), denoted CESM2(CAM6), and the latest generation of the Whole Atmosphere Community Climate Model (WACCM6), denoted CESM2(WACCM6), are presented, and a survey of general results is described. The equilibrium climate sensitivity (ECS) of CESM2(CAM6) is 5.3°C, and CESM2(WACCM6) is 4.8°C, while the transient climate response (TCR) is 2.1°C in CESM2(CAM6) and 2.0°C in CESM2(WACCM6). Thus, these two CESM2 model versions have higher values of ECS than the previous generation of model, the CESM (CAM5) (hereafter CESM1), that had an ECS of 4.1°C, though the CESM2 versions have lower values of TCR compared to the CESM1 with a somewhat higher value of 2.3°C. All model versions produce credible simulations of the time evolution of historical global surface temperature. The higher ECS values for the CESM2 versions are reflected in higher values of global surface temperature increase by 2,100 in CESM2(CAM6) and CESM2(WACCM6) compared to CESM1 between comparable emission scenarios for the high forcing scenario. Future warming among CESM2 model versions and scenarios diverges around 2050. The larger values of TCR and ECS in CESM2(CAM6) compared to CESM1 are manifested by greater warming in the tropics. Associated with a higher climate sensitivity, for CESM2(CAM6) the first instance of an ice‐free Arctic in September occurs for all scenarios and ensemble members in the 2030–2050 time frame, but about a decade later in CESM2(WACCM6), occurring around 2040–2060.

Abstract. The complexity of each Coupled Model Intercomparison Project grows with every new generation. The Phase 5 effort saw a large increase in the number of experiments that were performed and the number of variables that were requested compared to its previous generation, Phase 3. Many centers were not prepared for the large demand and this stressed the resources of several centers including at the National Center for Atmospheric Research. During Phase 5, we missed several deadlines and we struggled to get the data out to the community for analysis. In preparation for the current generation, Phase 6, we examined the weaknesses in our workflow and addressed the performance issues with new software tools. Through this investment, we were able to publish approximately six times the amount of data to the community compared to the volumes we produced in the previous generation and we were able to accomplish this within one-third of the time, providing an 18 times speedup. This paper discusses the improvements we have made to accomplish this success for Phase 6 and further improvements we hope to make for the next generation.

The complexity of each Coupled Model Intercomparison Project grows with every new generation. The Phase 5 effort saw a dramatic increase in the number of experiments that were performed and the number of variables that were requested compared to its previous generation, Phase 3. The large increase in data volume stressed the resources of several centers including at the National Center for Atmospheric Research. During Phase 5, we missed several deadlines and we struggled to get the data out to the community for analysis. In preparation for the current generation, Phase 6, we examined the weaknesses in our workflow and addressed the performance issues with new software tools. Through this investment, we were able to publish approximately 565 TB of compressed data to the community, with another 30 TB yet to be published. When compared to the volumes we produced in the previous generation, 165 TB of uncompressed data, we were able to provide 6 times the amount of data and we accomplish this within one-third of the time. This provided us with an approximate 18 times faster speedup. While this paper discusses the improvements we have made to our own workflow for the Coupled Model Intercomparison Project Phase 6 (CMIP6), we hope to encourage other centers to evaluate and invest in their own workflows in order to be successful in these types of modeling campaigns.

AbstractWe present an unprecedented set of high‐resolution climate simulations, consisting of a 500‐year pre‐industrial control simulation and a 250‐year historical and future climate simulation from 1850 to 2100. A high‐resolution configuration of the Community Earth System Model version 1.3 (CESM1.3) is used for the simulations with a nominal horizontal resolution of 0.25° for the atmosphere and land models and 0.1° for the ocean and sea‐ice models. At these resolutions, the model permits tropical cyclones and ocean mesoscale eddies, allowing interactions between these synoptic and mesoscale phenomena with large‐scale circulations. An overview of the results from these simulations is provided with a focus on model drift, mean climate, internal modes of variability, representation of the historical and future climates, and extreme events. Comparisons are made to solutions from an identical set of simulations using the standard resolution (nominal 1°) CESM1.3 and to available observations for the historical period to address some key scientific questions concerning the impact and benefit of increasing model horizontal resolution in climate simulations. An emerging prominent feature of the high‐resolution pre‐industrial simulation is the intermittent occurrence of polynyas in the Weddell Sea and its interaction with an Interdecadal Pacific Oscillation. Overall, high‐resolution simulations show significant improvements in representing global mean temperature changes, seasonal cycle of sea‐surface temperature and mixed layer depth, extreme events and in relationships between extreme events and climate modes.

Two high‐resolution versions of a Coupled Earth System Model (CESM1.3: 0.25° atmosphere, 1° ocean; CESM1.1: 0.25° atmosphere, 0.1° ocean) are compared to the standard resolution CESM1.1 and CESM1.3 (1° atmosphere, 1° ocean). The CESM1.3 versions are documented, and the consequences of model resolution, air‐sea coupling, and physics in the atmospheric models are studied with regard to storm tracks in the Southern Hemisphere as represented by 850‐hPa eddy kinetic energy. Increasing the resolution from 1° to 0.25° in the atmosphere (same physics) coupled to the 1° ocean intensifies the strength of the storm tracks closer to observations. The 0.25° atmosphere with the older CESM1.1 physics coupled to the 0.1° ocean has fewer low clouds, warmer Southern Ocean sea surface temperatures, a weaker meridional temperature gradient, and a degraded storm track simulation compared to the 0.25° atmosphere with CESM1.3 physics coupled to the 1° ocean. Therefore, deficient physics in the atmospheric model can negate the gains attained by higher resolution in atmosphere and ocean.