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The teleconnection between the quasi-biennial oscillation (QBO) and the Arctic stratospheric polar vortex, or the Holton–Tan (HT) relationship, may change in a warmer climate or one with stratospheric aerosol intervention (SAI) compared to the present-day climate (PDC). Our results from an Earth system model indicate that, under both global warming (based on RCP8.5 emission scenario) and SAI scenarios, the HT relationship weakens in early winter (November–December), although it is closer to PDC under SAI than under the RCP8.5 scenario. In contrast, the HT relationship in the middle to late winter period (January–February) does not change considerably in response to either RCP8.5 or SAI scenarios compared to PDC. While the weakening of the HT relationship under the RCP8.5 scenario is likely due to the weaker QBO wind amplitudes at the Equator, another physical mechanism must be responsible for the weaker HT relationship under SAI scenarios, since the amplitude of the QBO wind is comparable to the PDC. The strength of the polar vortex does not change under the RCP8.5 scenario compared to PDC, but it becomes stronger under SAI; we attribute the weakening of the HT relationship under SAI to a stronger polar vortex. In general, the changes in the HT relationship cannot be explained by changes to the critical line; the changes in the residual circulation (particularly due to the gravity wave contributions) are important in explaining the changes in the HT relationship under RCP8.5 and SAI scenarios.

Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. A detailed assessment of responses and impacts of such an intervention is needed with multiple global models to support societal decisions regarding the use of these approaches to help address climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI). The protocol and simulations are aimed at enabling community assessment of responses of the Earth system to solar climate intervention. ARISE-SAI simulations are designed to be more policy-relevant than existing large ensembles or multi-model simulation sets. We describe in detail the first set of ARISE-SAI simulations, ARISE-SAI-1.5, which utilize a moderate emissions scenario, introduce stratospheric aerosol injection at ∼21.5 km in the year 2035, and keep global mean surface air temperature near 1.5 ∘C above the pre-industrial value utilizing a feedback or control algorithm. We present the detailed setup, aerosol injection strategy, and preliminary climate analysis from a 10-member ensemble of these simulations carried out with the Community Earth System Model version 2 with the Whole Atmosphere Community Climate Model version 6 as its atmospheric component.

The skill of NOAA’s official monthly U.S. precipitation forecasts (issued in the middle of the prior month) has historically been low, having shown modest skill over the southern United States, but little or no skill over large portions of the central United States. The goal of this study is to explain the seasonal and regional variations of the North American subseasonal (weeks 3–6) precipitation skill, specifically the reasons for its successes and its limitations. The performances of multiple recent-generation model reforecasts over 1999–2015 in predicting precipitation are compared to uninitialized simulation skill using the atmospheric component of the forecast systems. This parallel analysis permits attribution of precipitation skill to two distinct sources: one due to slowly evolving ocean surface boundary states and the other to faster time-scale initial atmospheric weather states. A strong regionality and seasonality in precipitation forecast performance is shown to be analogous to skill patterns dictated by boundary forcing constraints alone. The correspondence is found to be especially high for the North American pattern of the maximum monthly skill that is achieved in the reforecast. The boundary forcing of most importance originates from tropical Pacific SST influences, especially those related to El Niño–Southern Oscillation. We discuss physical constraints that may limit monthly precipitation skill and interpret the performance of existing models in the context of plausible upper limits. Significance Statement Skillful subseasonal precipitation predictions have societal benefits. Over the United States, however, NOAA’s official U.S. monthly precipitation forecast skill has been historically low. Here we explore origins for skill of North American week-3 to week-6 precipitation predictions. Skill arising from initial weather states is compared to that arising from ocean surface boundary states alone. The monthly and seasonally varying pattern of U.S. monthly precipitation skill is appreciably derived from boundary constraints, linked especially with El Niño–Southern Oscillation. Forecasts of opportunity are identified, despite the low skill of monthly precipitation forecasts on average. Potential limits of monthly precipitation skill are explored that provide insight on the juxtaposition of “skill deserts” over the central United States with high skill regions over western North America.

Based on 20-day control forecasts by the 9-km Integrated Forecasting System (IFS) at the European Centre for Medium-Range Weather Forecasts (ECMWF) for selected periods of summer and winter events, this study investigates global distributions of gravity wave momentum fluxes resolved by the highest-resolution-ever global operational numerical weather prediction model. Two supplementary datasets, including 18-km ECMWF IFS experiments and the 30-km ERA5, are included for comparison. In the stratosphere, there is a clear dominance of westward momentum fluxes over the winter extratropics with strong baroclinic instability, while eastward momentum fluxes are found in the summer tropics. However, meridional momentum fluxes, locally as important as the above zonal counterpart, show different behaviors of global distribution characteristics, with northward and southward momentum fluxes alternating with each other especially at lower altitudes. Both events illustrate conclusive evidence that stronger stratospheric fluxes are found in the ECMWF forecast with finer resolution, and that ERA5 datasets have the weakest signals in general, regardless of whether regridding is applied. In the troposphere, probability distributions of vertical motion perturbations are highly asymmetric with more strong positive signals especially over latitudes covering heavy rainfall, likely caused by convective forcing. With the aid of precipitation accumulation, a simple filtering method is proposed in an attempt to eliminate those tropospheric asymmetries by convective forcing, before calculating tropospheric wave-induced fluxes. Furthermore, this research demonstrates promising findings that the proposed filtering method could help in reducing the potential uncertainties with respect to estimating tropospheric wave-induced fluxes. Finally, absolute momentum flux distributions with proposed approaches are presented, for further assessment in the future.

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.

In the tropical stratosphere, deep layers of eastward and westward winds encircle the globe and descend regularly from the upper stratosphere to the tropical tropopause. With a complete cycle typically lasting almost 2.5 years, this quasi-biennial oscillation (QBO) is arguably the most predictable mode of atmospheric variability that is not linked to the changing seasons. The QBO affects climate phenomena outside the tropical stratosphere, including ozone transport, the North Atlantic Oscillation and the Madden–Julian Oscillation, and its high predictability could enable better forecasts of these phenomena if models can accurately represent the coupling processes. Climate and forecasting models are increasingly able to simulate stratospheric oscillations resembling the QBO, but exhibit common systematic errors such as weak amplitude in the lowermost tropical stratosphere. Uncertainties about the waves that force the oscillation, particularly the momentum fluxes from small-scale gravity waves excited by deep convection, make its simulation challenging. Improved representation of the processes governing the QBO is expected to lead to better forecasts of the oscillation and its impacts, increased understanding of unusual events such as the two QBO disruptions observed since 2016, and more reliable future projections of QBO behaviour under climate change.

Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry [CESM2(WACCM6)]. Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment’s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available. Significance Statement We describe here the design and prediction skill of two subseasonal prediction systems based on two configurations of the Community Earth System Model, version 2 (CESM2): CESM2 with the Community Atmosphere Model, version 6 [CESM2(CAM6)] and CESM 2 with Whole Atmosphere Community Climate Model, version 6 [CESM2(WACCM6)] as its atmospheric component. These two systems provide a foundation for community-model based subseasonal prediction research. The CESM2(WACCM6) system provides a novel capability to explore the predictability of the stratosphere, mesosphere, and lower thermosphere. Both CESM2(CAM6) and CESM2(WACCM6) demonstrate subseasonal surface prediction skill comparable to that of the NOAA CFSv2 model, and a little lower than that of the ECMWF forecasting system. CESM2 reforecasts provide a comprehensive dataset for predictability research of multiple aspects of the Earth system, including the whole atmosphere up to 140 km, land, and sea ice. Weekly real-time forecasts, reforecasts, and models are publicly available.

This study focuses on assessing the representation and predictability of North American weather regimes, which are persistent large-scale atmospheric patterns, in a set of initialized subseasonal reforecasts created using the Community Earth System Model, version 2 (CESM2). The k-means clustering was used to extract four key North American (10°–70°N, 150°–40°W) weather regimes within ERA5 reanalysis, which were used to interpret CESM2 subseasonal forecast performance. Results show that CESM2 can recreate the climatology of the four main North American weather regimes with skill but exhibits biases during later lead times with overoccurrence of the West Coast high regime and underoccurrence of the Greenland high and Alaskan ridge regimes. Overall, the West Coast high and Pacific trough regimes exhibited higher predictability within CESM2, partly related to El Niño. Despite biases, several reforecasts were skillful and exhibited high predictability during later lead times, which could be partly attributed to skillful representation of the atmosphere from the tropics to extratropics upstream of North America. The high predictability at the subseasonal time scale of these case-study examples was manifested as an “ensemble realignment,” in which most ensemble members agreed on a prediction despite ensemble trajectory dispersion during earlier lead times. Weather regimes were also shown to project distinct temperature and precipitation anomalies across North America that largely agree with observational products. This study further demonstrates that unsupervised learning methods can be used to uncover sources and limits of subseasonal predictability, along with systematic biases present in numerical prediction systems. Significance Statement North American weather regimes are large-scale atmospheric patterns that can persist for several days. Their skillful subseasonal (2 weeks or greater) prediction can provide valuable lead time to prepare for temperature and precipitation anomalies that can stress energy and water resources. The purpose of this study was to assess the climatological representation and subseasonal predictability of four key North American weather regimes using a research subseasonal prediction system and clustering analysis. We found that the Pacific trough and West Coast high regimes exhibited higher predictability than other regimes and that skillful representation of conditions across the tropics and extratropics can increase predictability during later lead times. Future work will quantify causal pathways associated with high predictability.

Atmospheric gravity waves (GWs), or buoyancy waves, transport momentum and energy through Earth’s atmosphere. GWs are important at nearly all levels of the atmosphere, though, the momentum they transport is particularly important in general circulation of the middle and upper atmosphere. Primary sources of atmospheric GWs are flow over mountains, moist convection, and imbalances in jet/frontal systems. Secondary GWs can also be generated as a result of dissipation of a primary GWs. Gravity waves typically have horizontal wavelengths of 10’s to 100’s of kilometers, though, they can have scales of 1’s to 1000’s of kilometers as well. Current effective resolutions of climate models, and even numerical weather prediction models, do not resolve significant portions of the momentum- and energy-flux-carrying GW spectrum, and so parameterizations are necessary to represent under- and unresolved GWs in most current models. Here, an overview of GWs generated by orography, convection, jet/front systems, primary wave breaking, and secondary wave generation is provided. The basic theory of GW generation, propagation, and dissipation relevant to parameterization is presented. Conventionally used GW parameterizations are then reviewed. Lastly, we describe uncertainties and parameter tuning in current parameterizations and discuss known processes that are currently missing.

Model dependence in simulated responses to stratospheric aerosol injection (SAI) is a major uncertainty surrounding the potential implementation of this solar climate intervention strategy. We identify and aim to understand the drivers of large differences in the aerosol mass latitudinal distributions between two recently produced climate model SAI large ensembles using two models from the same modeling center despite using similar climate targets and controller algorithms. Using a hierarchy of recently produced simulations, we identify three main contributors to the differences including (1) the rapid adjustment of clouds and rainfall to elevated levels of carbon dioxide, (2) the low-frequency dynamical responses in the Atlantic meridional overturning circulation, and (3) the contrasts in future background forcing scenarios. Each uncertainty is unlikely to be significantly narrowed over the likely timeframe of a potential SAI deployment if a 1.5 ∘C target of global warming over preindustrial conditions is to be met.

Simulating whole atmosphere dynamics, chemistry, and physics is computationally expensive. It can require high vertical resolution throughout the middle and upper atmosphere, as well as a comprehensive chemistry and aerosol scheme coupled to radiation physics. An unintentional outcome of the development of one of the most sophisticated and hence computationally expensive model configurations is that it often excludes a broad community of users with limited computational resources. Here, we analyze two configurations of the Community Earth System Model Version 2, Whole Atmosphere Community Climate Model Version 6 (CESM2(WACCM6)) with simplified “middle atmosphere” chemistry at nominal 1 and 2 degree horizontal resolutions. Using observations, a reanalysis, and direct model comparisons, we find that these configurations generally reproduce the climate, variability, and climate sensitivity of the 1 degree nominal horizontal resolution configuration with comprehensive chemistry. While the background stratospheric aerosol optical depth is elevated in the middle atmosphere configurations as compared to the comprehensive chemistry configuration, it is comparable between all configurations during volcanic eruptions. For any purposes other than those needing an accurate representation of tropospheric organic chemistry and secondary organic aerosols, these simplified chemistry configurations deliver reliable simulations of the whole atmosphere that require 35% to 86% fewer computational resources at nominal 1 and 2 degree horizontal resolution, respectively.

This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid-latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3K. In E3SMv2, ECS is reduced to 4.0K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single-forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol-related forcing.

The teleconnection between the Quasi-Biennial Oscillation (QBO) and the Arctic stratospheric polar vortex, or the Holton-Tan (HT) relationship may change in a warmer climate or one with stratospheric aerosol intervention (SAI) as compared to present day climate (PDC). Our results from an Earth system model indicate that, under both global warming (based on RCP8.5 emission scenario) and SAI scenarios, the HT relationship weakens, although it is closer to PDC under SAI than under the RCP8.5 scenario. Such weakening of the HT relationship is more pronounced in early winter (Nov–Dec) compared to the mid-late winter period (Jan–Feb). While the high-latitude responses of temperature to the QBO anomalies are statistically significant under PDC, the responses are not statistically significant in the RCP8.5 and SAI scenarios. While the weakening of the HT relationship under RCP8.5 scenario is likely due to the weaker QBO wind amplitudes at the equator, another physical mechanism must be responsible for the weaker HT relationship under SAI scenario, since the amplitude of the QBO wind is comparable to the PDC. The strength of the polar vortex does not change under the RCP8.5 scenario compared to PDC, but it becomes stronger under SAI; we attribute the weakening of the HT relationship under SAI to such stronger polar vortex. In general, the changes in the HT relationship cannot be solely explained by changes to the critical line; the changes in the residual circulation (particularly due to the gravity wave contributions) are important too in explaining the changes in the HT relationship under RCP8.5 and SAI scenarios.

Extreme weather events have been demonstrated to be increasing in frequency and intensity across the globe and are anticipated to increase further with projected changes in climate. Solar climate intervention strategies, specifically stratospheric aerosol injection (SAI), have the potential to minimize some of the impacts of a changing climate while more robust reductions in greenhouse gas emissions take effect. However, to date little attention has been paid to the possible responses of extreme weather and climate events under climate intervention scenarios. We present an analysis of 16 extreme surface temperature and precipitation indices, as well as associated vegetation responses, applied to the Geoengineering Large Ensemble (GLENS). GLENS is an ensemble of simulations performed with the Community Earth System Model (CESM1) wherein SAI is simulated to offset the warming produced by a high-emission scenario throughout the 21st century, maintaining surface temperatures at 2020 levels. GLENS is generally successful at maintaining global mean temperature near 2020 levels; however, it does not completely offset some of the projected warming in northern latitudes. Some regions are also projected to cool substantially in comparison to the present day, with the greatest decreases in daytime temperatures. The differential warming–cooling also translates to fewer very hot days but more very hot nights during the summer and fewer very cold days or nights compared to the current day. Extreme precipitation patterns, for the most part, are projected to reduce in intensity in areas that are wet in the current climate and increase in intensity in dry areas. We also find that the distribution of daily precipitation becomes more consistent with more days with light rain and fewer very intense events than currently occur. In many regions there is a reduction in the persistence of long dry and wet spells compared to present day. However, asymmetry in the night and day temperatures, together with changes in cloud cover and vegetative responses, could exacerbate drying in regions that are already sensitive to drought. Overall, our results suggest that while SAI may ameliorate some of the extreme weather hazards produced by global warming, it would also present some significant differences in the distribution of climate extremes compared to the present day.

There is a growing demand for understanding sources of predictability on subseasonal to seasonal (S2S) time scales. Predictability at subseasonal time scales is believed to come from processes varying slower than the atmosphere such as soil moisture, snowpack, sea ice, and ocean heat content. The stratosphere as well as tropospheric modes of variability can also provide predictability at subseasonal time scales. However, the contributions of the above sources to S2S predictability are not well quantified. Here we evaluate the subseasonal prediction skill of the Community Earth System Model, version 1 (CESM1), in the default version of the model as well as a version with the improved representation of stratospheric variability to assess the role of an improved stratosphere on prediction skill. We demonstrate that the subseasonal skill of CESM1 for surface temperature and precipitation is comparable to that of operational models. We find that a better-resolved stratosphere improves stratospheric but not surface prediction skill for weeks 3–4.

Model dependence in simulated responses to stratospheric aerosol injection (SAI) is a major uncertainty surrounding the potential implementation of this solar climate intervention strategy. We identify large differences in the aerosol mass latitudinal distributions between two recently produced climate model SAI large ensembles, despite using similar climate targets and controller algorithms, with the goal of understanding the drivers of such differences. Using a hierarchy of recently produced simulations, we identify three main contributors including: 1) the rapid adjustment of clouds and rainfall to elevated levels of carbon dioxide, 2) the associated low-frequency dynamical responses in the Atlantic Meridional Overturning Circulation, and 3) the contrasts in future climate forcing scenarios. Each uncertainty is unlikely to be significantly narrowed over the likely timeframe of a potential SAI deployment if a 1.5 C target is to be met. The results thus suggest the need for significant flexibility in climate intervention deployment to account for these large uncertainties in the climate system response.

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere., Weather and Climate Dynamics, 3 (3), ISSN:2698-4016, ISSN:2698-4008

Artificial injections of sulfur dioxide (SO2) into the stratosphere show in several model studies an impact on stratospheric dynamics. The quasi-biennial oscillation (QBO) has been shown to slow down or even vanish under higher SO2 injections in the equatorial region. But the impact is only qualitatively but not quantitatively consistent across the different studies using different numerical models. The aim of this study is to understand the reasons behind the differences in the QBO response to SO2 injections between two general circulation models, the Whole Atmosphere Community Climate Model (WACCM-110L) and MAECHAM5-HAM. We show that the response of the QBO to injections with the same SO2 injection rate is very different in the two models, but similar when a similar stratospheric heating rate is induced by SO2 injections of different amounts. The reason for the different response of the QBO corresponding to the same injection rate is very different vertical advection in the two models, even in the control simulation. The stronger vertical advection in WACCM results in a higher aerosol burden and stronger heating of the aerosols and, consequently, in a vanishing QBO at lower injection rate than in simulations with MAECHAM5-HAM. The vertical velocity increases slightly in MAECHAM5-HAM when increasing the horizontal resolution. This study highlights the crucial role of dynamical processes and helps to understand the large uncertainties in the response of different models to artificial SO2 injections in climate engineering studies.

It is well known that the stratospheric quasi-biennial oscillation (QBO) is forced by equatorial waves with different horizontal/vertical scales, including Kelvin waves, mixed Rossby–gravity (MRG) waves, inertial gravity waves (GWs), and mesoscale GWs, but the relative contribution of each wave is currently not very clear. Proper representation of these waves is critical to the simulation of the QBO in general circulation models (GCMs). In this study, the vertical resolution in the Beijing Climate Center Atmospheric General Circulation Model (BCC-AGCM) is increased to better represent large-scale waves, and a mesoscale GW parameterization scheme, which is coupled to the convective sources, is implemented to provide unresolved wave forcing of the QBO. Results show that BCC-AGCM can spontaneously generate the QBO with realistic periods, amplitudes, and asymmetric features between westerly and easterly phases. There are significant spatiotemporal variations of parameterized convective GWs, largely contributing to a great degree of variability in the simulated QBO. In the eastward wind shear of the QBO at 20 hPa, forcing provided by resolved waves is 0.1–0.2 m s−1 day−1 and forcing provided by parameterized GWs is ~0.15 m s−1 day−1. On the other hand, westward forcings by resolved waves and parameterized GWs are ~0.1 and 0.4–0.5 m s−1 day−1, respectively. It is inferred that the eastward forcing of the QBO is provided by both Kelvin waves and mesoscale convective GWs, whereas the westward forcing is largely provided by mesoscale GWs. MRG waves barely contribute to the formation of the QBO in the model.

Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere–troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could further benefit these rapidly evolving predictions., Atmospheric Chemistry and Physics, 22 (4), ISSN:1680-7375, ISSN:1680-7367

Major disruptions of the winter season, high-latitude, stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research. We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortices in sub-seasonal to seasonal forecast models. Based on a set of controlled, subseasonal, ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models, and fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts.

Geoscientific Model Development, 15 (13), ISSN:1991-9603, ISSN:1991-959X

The impact of the stratospheric quasi‐biennial oscillation (QBO) on the prediction of the tropospheric Madden‐Julian oscillation (MJO) is evaluated in reforecasts from nine models participating in subseasonal prediction projects, including the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) projects. When MJO prediction skill is analyzed for December to February, MJO prediction skill is higher in the easterly phase of the QBO than the westerly phase, consistent with previous studies. However, the relationship between QBO phase and MJO prediction skill is not statistically significant for most models. This insignificant QBO‐MJO skill relationship is further confirmed by comparing two subseasonal reforecast experiments with the Community Earth System Model v1 using both a high‐top (46‐level) and low‐top (30‐level) version of the Community Atmosphere Model v5. While there are clear differences in the forecasted QBO between the two model top configurations, a negligible change is shown in the MJO prediction, indicating that the QBO in this model may not directly control the MJO prediction and supporting the insignificant QBO‐MJO skill relationship found in SubX and S2S models., Key Points The QBO‐MJO prediction skill relationship is mostly insignificant in nine subseasonal reforecastsThe QBO‐MJO prediction skill relationship is sensitive to the choice of QBO eventsThe insignificant QBO‐MJO skill relationship is supported by comparing reforecasts by a high‐top and low‐top version of CESM1

The Whole Atmosphere Community Climate Model version 6 (WACCM6) is a major update of the whole atmosphere modeling capability in the Community Earth System Model (CESM), featuring enhanced physical, chemical and aerosol parameterizations. This work describes WACCM6 and some of the important features of the model. WACCM6 can reproduce many modes of variability and trends in the middle atmosphere, including the Quasi‐Biennial Oscillation, Stratospheric Sudden Warmings and the evolution of Southern Hemisphere springtime ozone depletion over the 20th century. WACCM6 can also reproduce the climate and temperature trends of the 20th century throughout the atmospheric column. The representation of the climate has improved in WACCM6, relative to WACCM4. In addition, there are improvements in high latitude climate variability at the surface and sea ice extent in WACCM6 over the lower top version of the model (CAM6) that come from the extended vertical domain and expanded aerosol chemistry in WACCM6, highlighting the importance of the stratosphere and tropospheric chemistry for high latitude climate variability.

Over recent years there have been parallel advances in the development of stratosphere resolving numerical models, our understanding of stratosphere-troposphere interaction and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing new and improved capability in long range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal and decadal climate predictions. We end with an outlook towards the future of climate forecasts and identify areas for improvement that could further benefit these rapidly evolving predictions.

Simulating the complex aerosol microphysical processes in a comprehensive Earth System Model can be very computationally intensive and therefore many models utilize a modal approach, where aerosol size distributions are represented by observations-derived lognormal functions. This approach has been shown to yield satisfactory results in a large array of applications, but there may be cases where the simplification in this approach may produce some shortcomings. In this work we show specific conditions under which the current approximations used in modal approaches might yield some incorrect answers. Using results from the Community Earth System Model v1 (CESM1) Geoengineering Large Ensemble (GLENS) project, we analyze the effects in the troposphere of a continuous increasing load of sulfate aerosols in the stratosphere, with the aim of counteracting the surface warming produced by non-mitigated increasing greenhouse gases concentration between 2020–2100. We show that the simulated results pertaining to the evolution of sea salt and dust aerosols in the upper troposphere are not realistic due to internal mixing assumptions in the modal aerosol treatment, which in this case reduces the size, and thus the settling velocities, of those particles and ultimately changes their mixing ratio below the tropopause. The unnatural increase of these aerosol species affects, in turn, the simulation of upper tropospheric ice formation, resulting in an increase in ice clouds that is not due to any meaningful physical mechanisms. While we show that this does not significantly affect the overall results of the simulations, we point to some areas where results should be interpreted with care in modeling simulations using similar approximations: in particular, the evolution of upper tropospheric clouds when large amount of sulfate is present in the stratosphere, as after a large explosive volcanic eruption or in similar stratospheric aerosol injection cases. Finally, we suggest that this could be avoided if sulfate aerosols in the coarse mode, the predominant species in these situation, are treated separately from other aerosol species in the model.

Mesoscale organization of convection is typically not represented in global circulation models, and hence its influence on the global circulation is not accounted for. The heating component of a parameterization that represents the dynamical and physical effects of circulations associated with organized convection, referred to as the multiscale coherent structure parameterization (MCSP), is implemented in the Energy Exascale Earth System Model version 1 (E3SMv1). Numerical simulations are conducted to assess its impact on the simulated climate. Besides E3SMv1 simulations, we performed high‐resolution (2 km) simulations using the Weather Research and Forecasting (WRF) Model to determine the temperature tendencies induced by mesoscale convective systems embedded in deep convection. We tuned the free parameters of the MCSP based on the WRF simulations. MCSP heating enhances Kevin wave spectra in E3SMv1, improves the representation of the Madden‐Julian Oscillation, and reduces precipitation biases over the tropical Pacific.

The quasi‐biennial oscillation (QBO) of the zonal mean wind is a prominent feature of the tropical lower stratosphere and has been shown to influence stratospheric and tropospheric variability. Although observed for many decades, the QBO is difficult to be accurately captured in Earth system models. The newly developed U.S. Department of Energy Energy Exascale Earth System Model, Version 1 (E3SMv1) is capable of resolving stratospheric dynamics as it has a top at 0.1 hPa and 72 levels. The tropical oscillation of the zonal mean zonal wind in the default version of the model is too fast and too strong compared to the observed QBO. Here we evaluate the current simulation of the QBO and present simulations with modified convective gravity wave parameterization parameters that make the oscillation more realistic, especially in terms of the period. Although improvements in the QBO are obtained through modifications to the parameterized gravity waves, we find that the forcing of the QBO from Kelvin and mixed‐Rossby gravity waves is small due to weak sources in the troposphere. The changes to the parameterized convective gravity waves (and QBO) are primarily limited to the tropical stratosphere. Small changes to mean wind and temperature are also found in Northern Hemisphere winter in the uppermost troposphere between 10°N and 60°N. Modifications to parameterized convectively generated gravity waves result in changes in interannual variability, primarily in the Southern Hemisphere, and modest changes in sea level pressure variability over the Pacific are also noted.