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Abstract: On seasonal time scales, vapor pressure deficit (VPD) is a known predictor of burned area in the southwestern United States (“the Southwest”). VPD increases with atmospheric warming due to the exponential relationship between temperature and saturation vapor pressure. Another control on VPD is specific humidity, such that increases in specific humidity can counteract temperature-driven increases in VPD. Unexpectedly, despite the increased capacity of a warmer atmosphere to hold water vapor, near-surface specific humidity decreased from 1970 to 2019 in much of the Southwest, particularly in spring, summer, and fall. Here, we identify declining near-surface humidity from 1970 to 2019 in the southwestern United States with both reanalysis and in situ station data. Focusing on the interior Southwest in the months preceding the summer forest fire season, we explain the decline in terms of changes in atmospheric circulation and moisture fluxes between the surface and the atmosphere. We find that an early spring decline in precipitation in the interior region induced a decline in soil moisture and evapotranspiration, drying the lower troposphere in summer. This prior season precipitation decline is in turn related to a trend toward a Northern Hemisphere stationary wave pattern. Finally, using fixed humidity scenarios and the observed exponential relationship between VPD and burned forest area, we estimate that with no increase in temperature at all, the humidity decline alone would still lead to nearly one-quarter of the observed VPD-induced increase in burned area over 1984–2019. Significance Statement: Burned forest area has increased significantly in the southwestern United States in recent decades, driven in part by an increase in atmospheric aridity [vapor pressure deficit (VPD)]. Increases in VPD can be caused by a combination of increasing temperature and decreasing specific humidity. As the atmosphere warms with climate change, its capacity to hold moisture increases. Despite this, there is a decrease in near-surface air humidity in the interior southwestern United States over 1970–2019, which during the summer is likely caused by a decline in early spring precipitation leading to limited soil moisture and evaporation in spring and summer. We estimate that this declining humidity alone, without an increase in temperature, would cause about one-quarter of the VPD-induced increase in burned forest area in this region over 1984–2019.

Arid and semi-arid regions of the world are particularly vulnerable to greenhouse gas-driven hydroclimate change. Climate models are our primary tool for projecting the future hydroclimate that society in these regions must adapt to, but here, we present a concerning discrepancy between observed and model-based historical hydroclimate trends. Over the arid/semi-arid regions of the world, the predominant signal in all model simulations is an increase in atmospheric water vapor, on average, over the last four decades, in association with the increased water vapor-holding capacity of a warmer atmosphere. In observations, this increase in atmospheric water vapor has not happened, suggesting that the availability of moisture to satisfy the increased atmospheric demand is lower in reality than in models in arid/semi-arid regions. This discrepancy is most clear in locations that are arid/semi-arid year round, but it is also apparent in more humid regions during the most arid months of the year. It indicates a major gap in our understanding and modeling capabilities which could have severe implications for hydroclimate projections, including fire hazard, moving forward.

Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs).

AbstractUnderstanding the roles of land surface conditions and atmospheric circulation on continental daily temperature variance is key to improving predictions of temperature extremes. Evaporative resistance (rs, hereafter), a function of the land cover type, reflects the ease with which water can be evaporated or transpired and is a strong control on land–atmosphere interactions. This study explores the effects of rs perturbations on summer daily temperature variance using the Simple Land Interface Model (SLIM) by mimicking, for rs only, a global land cover conversion from forest to crop/grassland. Decreasing rs causes a global cooling. The cooling is larger in wetter areas and weaker in drier areas, and primarily results from perturbations in shortwave radiation (SW) and latent heat flux (LH). Decreasing rs enhances cloud cover due to greater land surface evaporation and thus reduces incoming SW over most land areas. When rs decreases, wetter areas experience strong evaporative cooling, while drier areas become more moisture-limited and thus experience less cooling. Thermal advection further shapes the temperature response by damping the combined impacts of SW and LH. Temperature variance increases in drier areas and decreases in wetter areas as rs decreases. The temperature variance changes can be largely explained from changes in the combined variance of SW and LH, including an important contribution of changes in the covariance of SW and LH. In contrast, the effects of changes in thermal advection variance mainly affect the Northern Hemisphere midlatitudes.Significance StatementThis study aims to better understand processes governing daily near-surface air temperature variance over land. We use an idealized modeling framework to explore the effects of land surface evaporative resistance (a parameter that controls how hard it is to evaporate water from the surface) on summer daily temperature variance. We find that a uniform decrease of evaporative resistance across the global land surface causes changes in the temperature variance that can be predicted from changes in the combined variance of shortwave radiation and latent heat flux. The variance of horizontal advection is important in altering the temperature variance in the Northern Hemisphere midlatitudes. Our findings shed light on predicting the characteristics of temperature variability as a function of surface conditions.

AbstractAn ‘emergent constraint’ (EC) is a statistical relationship, across a model ensemble, between a measurable aspect of the present day climate (the predictor) and an aspect of future projected climate change (the predictand). If such a relationship is robust and understood, it may provide constrained projections for the real world. Here, Coupled Model Intercomparison Project 6 (CMIP6) models are used to revisit several ECs that were proposed in prior model intercomparisons with two aims: (1) to assess whether these ECs survive the partial out-of-sample test of CMIP6 and (2) to more rigorously quantify the constrained projected change than previous studies. To achieve the latter, methods are proposed whereby uncertainties can be appropriately accounted for, including the influence of internal variability, uncertainty on the linear relationship, and the uncertainty associated with model structural differences, aside from those described by the EC. Both least squares regression and a Bayesian Hierarchical Model are used. Three ECs are assessed: (a) the relationship between Southern Hemisphere jet latitude and projected jet shift, which is found to be a robust and quantitatively useful constraint on future projections; (b) the relationship between stationary wave amplitude in the Pacific-North American sector and meridional wind changes over North America (with extensions to hydroclimate), which is found to be robust but improvements in the predictor in CMIP6 result in it no longer substantially constrains projected change in either circulation or hydroclimate; and (c) the relationship between ENSO teleconnections to California and California precipitation change, which does not appear to be robust when using historical ENSO teleconnections as the predictor.

Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.

To improve understanding of ocean processes impacting monthly sea surface temperature (SST) variability, we analyze a Community Earth System Model, version 2, hierarchy in which models vary only in their degree of ocean complexity. The most realistic ocean is a dynamical ocean model, as part of a fully coupled model (FCM). The next most realistic ocean, from a mechanically decoupled model (MDM), is like the FCM but excludes anomalous wind stress–driven ocean variability. The simplest ocean is a slab ocean model (SOM). Inclusion of a buoyancy coupled dynamic ocean as in the MDM, which includes temperature advection and vertical mixing absent in the SOM, leads to dampening of SST variance everywhere and reduced persistence of SST anomalies in the high latitudes and equatorial Pacific compared to the SOM. Inclusion of anomalous wind stress–driven ocean dynamics as in the FCM leads to higher SST variance and longer persistence time scales in most regions compared to the MDM. The net role of the dynamic ocean, as an overall dampener or amplifier of anomalous SST variance and persistence, is regionally dependent. Notably, we find that efforts to reduce the complexity of the ocean models in the SOM and MDM configurations result in changes in the magnitude of the thermodynamic forcing of SST variability compared to the FCM. These changes, in part, stem from differences in the seasonally varying mixed layer depth and should be considered when attempting to quantify the relative contribution of certain ocean mechanisms to differences in SST variability between the models. [ABSTRACT FROM AUTHOR]

Climate change projections show amplified warming associated with dry conditions over tropical land. We compare two perspectives explaining this amplified warming: one based on tropical atmospheric dynamics and the other focusing on soil moisture and surface fluxes. We first compare the full spatiotemporal distribution of changes in key variables in the two perspectives under a quadrupling of CO2 using daily output from the CMIP6 simulations. Both perspectives center around the partitioning of the total energy/energy flux into the temperature and humidity components. We examine the contribution of this temperature/humidity partitioning in the base climate and its change under warming to rising temperatures by deriving a diagnostic linearized perturbation model that relates the magnitude of warming to 1) changes in the total energy/energy flux, 2) the base-climate temperature/humidity partitioning, and 3) changes in the partitioning under warming. We show that the spatiotemporal structure of warming in CMIP6 models is well predicted by the inverse of the base-climate partition factor, which we term the base-climate sensitivity: conditions that are drier in the base climate have a higher base-climate sensitivity and experience more warming. On top of this relationship, changes in the partition factor under intermediate (between wet and dry) surface conditions further enhance or dampen the warming. We discuss the mechanistic link between the two perspectives by illustrating the strong relationships between lower-tropospheric temperature lapse rates, a key variable for the atmospheric perspective, and surface fluxes, a key component of the land surface perspective. Significance Statement: Understanding what conditions give rise to the largest magnitude of warming in response to rising CO2 concentrations is not only scientifically important but also critical from a climate impact standpoint. Two main perspectives, one focusing on atmospheric dynamics and the other focusing on land surface processes, have been proposed to explain the stronger warming associated with drier conditions in the tropics. Here, we compare and contrast these two perspectives. We demonstrate that amplified warming in CMIP6 models can largely be predicted from base-climate dryness alone in both perspectives but is further modified based on changes in the partitioning of energy between temperature and moisture. We highlight the spatiotemporal conditions where assumptions in the two perspectives hold and where deviations occur within CMIP6 climate models. [ABSTRACT FROM AUTHOR]

Change over recent decades in the world's five Mediterranean Climate Regions (MCRs) of quantities of relevance to water resources, ecosystems and fire are examined for all seasons and placed in the context of changes in large‐scale circulation. Near‐term future projections are also presented. It is concluded that, based upon agreement between observational data sets and modelling frameworks, there is strong evidence of radiatively‐driven drying of the Chilean MCR in all seasons and southwest Australia in winter. Observed drying trends in California in fall, southwest southern Africa in fall, the Pacific Northwest in summer and the Mediterranean in summer agree with radiatively‐forced models but are not reproduced in a model that also includes historical sea surface temperature (SST) forcing, raising doubt about the human‐origin of these trends. Observed drying in the Mediterranean in winter is stronger than can be accounted for by radiative forcing alone and is also outside the range of the SST‐forced ensemble. It is shown that near surface vapour pressure deficit (VPD) is increasing almost everywhere but that, surprisingly, this is contributed to in the Southern Hemisphere subtropics to mid‐latitudes by a decline in low‐level specific humidity. The Southern Hemisphere drying, in terms of precipitation and specific humidity, is related to a poleward shift and strengthening of the westerlies with eddy‐driven subsidence on the equatorward side. Model projections indicate continued drying of Southern Hemisphere MCRs in winter and spring, despite ozone recovery and year‐round drying in the Mediterranean. Projections for the North American MCR are uncertain, with a large contribution from internal variability, with the exception of drying in the Pacific Northwest in summer. Overall the results indicate continued aridification of MCRs other than in North America with important implications for water resources, agriculture and ecosystems. [ABSTRACT FROM AUTHOR]

Multidecadal variability in the North Atlantic jet stream in general circulation models (GCMs) is compared with that in reanalysis products of the twentieth century. It is found that almost all models exhibit multidecadal jet stream variability that is entirely consistent with the sampling of white noise year-to-year atmospheric fluctuations. In the observed record, the variability displays a pronounced seasonality within the winter months, with greatly enhanced variability toward the late winter. This late winter variability exceeds that found in any GCM and greatly exceeds expectations from the sampling of atmospheric noise, motivating the need for an underlying explanation. The potential roles of both external forcings and internal coupled ocean–atmosphere processes are considered. While the late winter variability is not found to be closely connected with external forcing, it is found to be strongly related to the internally generated component of Atlantic multidecadal variability (AMV) in sea surface temperatures (SSTs). In fact, consideration of the seasonality of the jet stream variability within the winter months reveals that the AMV is far more strongly connected to jet stream variability during March than the early winter months or the winter season as a whole. Reasoning is put forward for why this connection likely represents a driving of the jet stream variability by the SSTs, although the dynamics involved remain to be understood. This analysis reveals a fundamental mismatch between late winter jet stream variability in observations and GCMs and a potential source of long-term predictability of the late winter Atlantic atmospheric circulation.

The role of sampling variability in ENSO composites of winter surface air temperature and precipitation over North America during the period 1920–2013 is assessed for observations and ensembles of coupled model simulations in which sea surface temperature anomalies in the tropical eastern Pacific are nudged to those of the real world. The individual members of each model ensemble show a surprising amount of diversity in their ENSO composites, despite being constructed from the same observed set of 18 El Niño and 14 La Niña events. For a given model, this ensemble spread can only be due to sampling variability, that is, aliasing of internal variability that is unrelated to ENSO, which in turn is shown to arise from internal atmospheric dynamics rather than coupled ocean–atmosphere processes. Analogous ensemble spread is evident in 2000 synthetic ENSO composites based on observations using random sampling techniques. These synthetic composites provide information on the range of spatial patterns and amplitudes associated with imperfect estimation of the forced ENSO signal in the observational record. In some locations, the amplitude of the estimated ENSO signal can vary by more than a factor of two. This observational uncertainty necessitates an approach to model assessment that considers not only the model’s forced response to ENSO, given by its ensemble-mean ENSO composite, but also its representation of internal variability unrelated to ENSO. Such an approach is used to reveal fidelities and shortcomings in the Community Earth System Model, version 1.

Application of random sampling techniques to composite differences between 18 El Niño and 14 La Niña events observed since 1920 reveals considerable uncertainty in both the pattern and amplitude of the Northern Hemisphere extratropical winter sea level pressure (SLP) response to ENSO. While the SLP responses over the North Pacific and North America are robust to sampling variability, their magnitudes can vary by a factor of 2; other regions, such as the Arctic, North Atlantic, and Europe are less robust in their SLP patterns, amplitudes, and statistical significance. The uncertainties on the observed ENSO composite are shown to arise mainly from atmospheric internal variability as opposed to ENSO diversity. These observational findings pose considerable challenges for the evaluation of ENSO teleconnections in models. An approach is proposed that incorporates both pattern and amplitude uncertainty in the observational target, allowing for discrimination between true model biases in the forced ENSO response and apparent model biases that arise from limited sampling of non-ENSO-related internal variability. Large initial-condition coupled model ensembles with realistic tropical Pacific sea surface temperature anomaly evolution during 1920–2013 show similar levels of uncertainty in their ENSO teleconnections as found in observations. Because the set of ENSO events in each of the model composites is the same (and identical to that in observations), these uncertainties are entirely attributable to sampling fluctuations arising from internal variability, which is shown to originate from atmospheric processes. The initial-condition model ensembles thus inform the interpretation of the single observed ENSO composite and vice versa.

This study evaluates the representation of the composite-mean surface response to sudden stratospheric warmings (SSWs) in 28 CMIP6 models. Most models can reproduce the magnitude of the SLP response over the Arctic, although the simulated Arctic SLP response varies from model to model. Regarding the structure of the SLP response, most models exhibit a basin-symmetric negative Northern Annular Mode (NAM)-like response with a cyclonic Pacific SLP response, whereas the reanalysis shows a highly basin-asymmetric negative NAO-like response without a robust Pacific center. We then explore the drivers of these model biases and spread by applying a multiple linear regression (MLR). The results show that the polar cap temperature anomalies at 100 hPa (ΔT100) modulate the magnitude of both the Arctic SLP response and the cyclonic Pacific SLP response. Apart from ΔT100, the intensity and latitudinal location of the climatological eddy-driven jet in the troposphere also affect the magnitude of the Arctic SLP response. The compensation of model biases in these two tropospheric metrics and the good model representation of ΔT100 explain the good agreement between the ensemble mean and the reanalysis on the magnitude of the Arctic SLP response, as indicated by the fact that the ensemble mean lies well within the reanalysis uncertainty range and that the reanalysis mean sits well within the model distribution. The Niño-3.4 SST anomalies and North Pacific SST dipole anomalies together with ΔT100 modulate the cyclonic Pacific SLP response. In this case, biases in both oceanic drivers work in the same direction and lead to the cyclonic Pacific SLP response in models that are not present in the reanalysis. Significance Statement: Sudden stratospheric warmings (SSWs) represent an important source of skill for forecasting winter weather on subseasonal-to-seasonal time scales. To what extent SSWs could be used to improve the prediction of surface weather depends on how well stratosphere–troposphere coupling associated with SSWs is represented in climate models. Therefore, we evaluate the representation of stratosphere–troposphere coupling associated with SSWs in 28 state-of-the-art climate models. The representation is found to diverge widely among climate models, and some are biased noticeably from the reanalysis. The models' spread and bias are largely driven by five major factors and can be reduced substantially by making bias corrections to these factors. [ABSTRACT FROM AUTHOR]

We analyze the sources for spread in the response of the Northern Hemisphere wintertime stratospheric polar vortex (SPV) to global warming in Climate Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) model projections. About half of the intermodel spread in SPV projections by CMIP6 models, but less than a third in CMIP5 models, can be attributed to the intermodel spread in stationary planetary wave driving. In CMIP6, SPV weakening is mostly driven by increased upward wave flux from the troposphere, while SPV strengthening is associated with increased equatorward wave propagation away from the polar stratosphere. We test hypothesized factors contributing to changes in the upward and equatorward planetary wave fluxes and show that an across‐model regression using projected global warming rates, strengthening of the subtropical jet and basic state lower stratospheric wind biases as predictors can explain nearly the same fraction in the CMIP6 SPV spread as the planetary wave driving (r = 0.67). The dependence of the SPV spread on the model biases in the basic state winds offers a possible emergent constraint; however, a large uncertainty prevents a substantial reduction of the projected SPV spread. The lack of this dependence in CMIP5 further calls for better understanding of underlying causes. Our results improve understanding of projected SPV uncertainty; however, further narrowing of the uncertainty remains challenging. Plain Language Summary: Previous studies showed that changes in the strength of the Northern Hemisphere wintertime stratospheric polar vortex can affect near‐surface weather on various timescales. However, climate models do not agree on whether the polar vortex will weaken or strengthen during the 21st century. Here, we use Climate Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) experiments to better understand how the polar vortex will respond to future greenhouse gas emissions. We show that changes in the propagation of large‐scale atmospheric waves can explain nearly half of the spread in the vortex strength projections by the end of the 21st century by CMIP6 models. Increased upward propagation of the waves to the stratosphere leads to vortex weakening while increased equatorward propagation within the stratosphere leads to strengthening. We identify three factors associated with projected changes in the vortex strength across CMIP6 models: projected rates of global warming, projected rates of subtropical jet stream strengthening and model errors in lower stratospheric winds in the past climate. Stronger global warming rates and stronger past lower stratospheric winds are associated with vortex strengthening, while larger strengthening of the subtropical jet stream is associated with weakening. However, these relationships are weak in CMIP5 models. Key Points: About half of the projected stratospheric polar vortex (SPV) uncertainty in Climate Model Intercomparison Project Phase 6 (CMIP6) can be attributed to stationary planetary wave drivingProjected polar vortex weakening and strengthening are linked to increased upward and equatorward wave propagation respectivelyA relationship is found between past lower stratospheric wind biases and SPV projections across CMIP6 models [ABSTRACT FROM AUTHOR]

Canonical understanding based on general circulation models (GCMs) is that the atmospheric circulation response to midlatitude sea‐surface temperature (SST) anomalies is weak compared to the larger influence of tropical SST anomalies. However, the ∼100‐km horizontal resolution of modern GCMs is too coarse to resolve strong updrafts within weather fronts, which could provide a pathway for surface anomalies to be communicated aloft. Here, we investigate the large‐scale atmospheric circulation response to idealized Gulf Stream SST anomalies in Community Atmosphere Model (CAM6) simulations with 14‐km regional grid refinement over the North Atlantic, and compare it to the responses in simulations with 28‐km regional refinement and uniform 111‐km resolution. The highest resolution simulations show a large positive response of the wintertime North Atlantic Oscillation (NAO) to positive SST anomalies in the Gulf Stream, a 0.4‐standard‐deviation anomaly in the seasonal‐mean NAO for 2°C SST anomalies. The lower‐resolution simulations show a weaker response with a different spatial structure. The enhanced large‐scale circulation response results from an increase in resolved vertical motions with resolution and an associated increase in the influence of SST anomalies on transient‐eddy heat and momentum fluxes in the free troposphere. In response to positive SST anomalies, these processes lead to a stronger and less variable North Atlantic jet, as is characteristic of positive NAO anomalies. Our results suggest that the atmosphere responds differently to midlatitude SST anomalies in higher‐resolution models and that regional refinement in key regions offers a potential pathway to improve multi‐year regional climate predictions based on midlatitude SSTs. Plain Language Summary: Variations in the ocean surface temperature (SST) influence the atmospheric circulation and thus climate over land. Canonical understanding is that tropical SSTs are more important than SSTs in midlatitudes. However, this understanding is based on climate models that don't resolve processes at scales less than 100 km. Here, we show that by increasing the atmospheric model resolution to resolve features on smaller scales, such as weather fronts, we find a larger atmospheric circulation response to midlatitude SST anomalies in the North Atlantic. North Atlantic SST anomalies can be predicted multiple years in advance, and a larger atmospheric circulation response to these predictable SST anomalies therefore implies increased predictability of climate over the surrounding land regions. Key Points: There is a large circulation response to idealized Gulf Stream sea‐surface temperature (SST) anomalies in an atmospheric model with 14‐km regional grid refinementThis response is weaker or absent in simulations with 28‐km or coarser resolution, which do not fully resolve mesoscale frontal processesTransient‐eddy fluxes of heat and momentum are modified as fronts pass over warm SSTs, leading to a large‐scale circulation response [ABSTRACT FROM AUTHOR]

Contributions of the resolved waves and parameterized gravity waves to changes in the quasi‐biennial oscillation (QBO) in a future simulation (2015–2100) under the SSP370 scenario are investigated using the Community Earth System Model 2 (CESM2) with enhanced vertical resolution and are compared with those from four CESM2 historical simulations (1979–2014). The maximum QBO amplitude of the future simulation is 26.0 m s−1, which is slightly less than that of the historical simulations (27.4–29.3 m s−1). However, the QBO period in the future simulation is much shorter: 21.6 months in the early‐future (2015–2050) and 12 months in the late‐future (2065–2100) period, than in the historical simulations (23.5–30.9 months). The shortened QBO period in the future is primarily due to increases in both resolved wave forcing and parameterized gravity wave drag (GWD) in the stratosphere, with a more significant contribution by the GWD. As convective activity becomes stronger in the future simulation, the momentum flux of parameterized convective gravity waves at the cloud top increases, resulting in stronger GWD in the stratosphere. The increases in the magnitude of westward GWD dominate those of eastward GWD in the stratosphere. This is due to a significant increase in westward momentum flux in the troposphere, especially during the descending easterly QBO, and enhanced westerlies in the lowermost stratosphere, which introduces a westward anomaly. For the resolved waves, Kelvin wave forcing is a key contributor to increased eastward forcing in the future simulation, with relatively minor contributions by other equatorial planetary waves. Plain Language Summary: The quasi‐biennial oscillation (QBO) is a phenomenon in which easterly and westerly winds alternately descend in the equatorial stratosphere roughly every 28 months. The QBO affects various atmospheric phenomena not only at the equator but in mid‐ and high‐latitudes, such as the Madden‐Julian Oscillation, the subtropical jet, and the polar vortex and associated teleconnections. There is a debate over how the QBO cycle will be altered under future climate change. A future climate modeling experiment with a version of the Community Earth System Model 2 that represents the QBO is performed, and it is found that the QBO period decreases to 12 months in the future simulation. There are two main reasons for this change: First, strengthened convection in the equatorial region leads to enhanced convective gravity wave momentum flux, resulting in stronger gravity wave drag in the stratosphere. Second, an increase in eastward forcing by equatorial Kelvin waves strengthens the overall eastward planetary wave forcing. These increases in both gravity wave drag and Kelvin wave forcing contribute to a speeding up of the QBO cycle in the future climate. Key Points: Momentum budget analysis in a warming climate simulation is performed to diagnose the cause of changes in the quasi‐biennial oscillation (QBO)'s periodIncreasing westward parameterized gravity wave drag speeds up the easterly phase of the QBO in a warming climateIncreasing Kelvin wave forcing and eastward parameterized gravity wave drag speed up the westerly phase of the QBO [ABSTRACT FROM AUTHOR]

Climate simulation uncertainties arise from internal variability, model structure, and external forcings. Model intercomparisons (such as the Coupled Model Intercomparison Project; CMIP) and single-model large ensembles have provided insight into uncertainty sources. Under the Community Earth System Model (CESM) project, large ensembles have been performed for CESM2 (a CMIP6-era model) and CESM1 (a CMIP5-era model). We refer to these as CESM2-LE and CESM1-LE. The external forcing used in these simulations has changed to be consistent with their CMIP generation. As a result, differences between CESM2-LE and CESM1-LE ensemble means arise from changes in both model structure and forcing. Here we present new ensemble simulations which allow us to separate the influences of these model structural and forcing differences. Our new CESM2 simulations are run with CMIP5 forcings equivalent to those used in the CESM1-LE. We find a strong influence of historical forcing uncertainty due to aerosol effects on simulated climate. For the historical period, forcing drives reduced global warming and ocean heat uptake in CESM2-LE relative to CESM1-LE that is counteracted by the influence of model structure. The influence of the model structure and forcing vary across the globe, and the Arctic exhibits a distinct signal that contrasts with the global mean. For the 21st century, the importance of scenario forcing differences (SSP3–7.0 for CESM2-LE and RCP8.5 for CESM1-LE) is evident. The new simulations presented here allow us to diagnose the influence of model structure on 21st century change, despite large scenario forcing differences, revealing that differences in the meridional distribution of warming are caused by model structure. Feedback analysis reveals that clouds and their impact on shortwave radiation explain many of these structural differences between CESM2 and CESM1. In the Arctic, albedo changes control transient climate evolution differences due to structural differences between CESM2 and CESM1. [ABSTRACT FROM AUTHOR]

Many studies have focused on understanding the drivers of soil moisture droughts in Europe when the events have already intensified. Still, how atmospheric circulation changes throughout the entire life cycle of droughts, particularly during the transition periods to drought initiation and termination, has not been thoroughly investigated. Therefore, this study investigates temporal characteristics and atmospheric circulation associated with onsets (a transition period from a normal condition to drought) and terminations (a transition period from drought to a normal condition) of soil moisture droughts in Europe during 1980–2020. The typical duration, preferred seasons of occurrence, and atmospheric circulation during onsets and terminations are examined. The regions of study are central (CEU) and Mediterranean (MED) Europe, and soil moisture from ERA5-Land, GLEAM version 3, SoMo.ml, Noah-LSM, and a simulation from the Community Land Model version 5 (CLM-TRENDY) are utilized. Our findings indicate that the duration of onsets and terminations depends on the dataset: the five soil moisture datasets exhibit different mean duration of onsets and terminations, with ERA5-Land showing shorter and GLEAM longer duration across Europe. Nevertheless, within the same dataset, onsets and terminations exhibit similar durations, implying that onsets and terminations can occur at the same speed. Regarding the preferred seasons for onsets and terminations, onsets occur more during the wet seasons, specifically summer in CEU and autumn and winter in MED. Nevertheless, the frequencies of occurrence during these seasons only slightly exceed that during other seasons. Terminations tend to occur more during the driest seasons. For atmospheric circulation, onsets come with large-scale anticyclonic atmospheric circulation patterns. Terminations do not exhibit a dominant mean circulation pattern over the region where terminations occur but instead show geopotential height anomalies with reduced magnitudes in Europe and a high-pressure system over the North Atlantic. The anticyclonic circulation during onsets is anomalously persistent and shows linkages with the North Atlantic Oscillation (NAO). Positive NAO occurs much more frequently during onsets compared to other drought phases. This finding implies an important role for this large-scale mode of variability in initiating dry periods by reducing soil moisture and its potential to serve as an early warning for droughts during the period prior to the events. [ABSTRACT FROM AUTHOR]

The variability of the summer North Pacific Subtropical High (NPSH) has substantial socioeconomic impacts. However, state‐of‐the‐art climate models significantly disagree on the response of the NPSH to anthropogenic warming. Inter‐model spread in NPSH projections originates from models' inconsistency in simulating tropical precipitation changes. This inconsistency in precipitation changes is partly due to inter‐model spread in tropical sea surface temperature (SST) changes, but it can also occur independently of uncertainty in SST changes. Here, we show that both types of precipitation uncertainty influence the NPSH via the Matsuno‐Gill wave response, but their relative impact varies by region. Through the modulation of low cloud fraction, inter‐model spread of the NPSH can have a further impact on extra‐tropical land surface temperature. The teleconnection between tropical precipitation and the NPSH is examined through a series of numerical experiments. Plain Language Summary: The North Pacific Subtropical High (NPSH) is a semi‐permanent high‐pressure system located in the subtropical North Pacific. The variability in the summer NPSH has a significant impact on the monsoon and typhoons over East Asia and the hydroclimate of California. However, future projections of the NPSH using state‐of‐the‐art climate models remain highly uncertain. By evaluating how much individual models deviate from the multi‐model mean at different locations, we find four hot spots of high uncertainty in NPSH projections. Our analysis further reveals that the primary source of model variance in changes in the NPSH is tropical precipitation, which can be attributed to both inter‐model SST‐driven and non‐inter‐model SST‐driven factors. Through numerical experiments, we demonstrate that the teleconnection between tropical precipitation and the NPSH is achieved through wave propagation. Key Points: Model spread in the response of the summer North Pacific Subtropical High (NPSH) to CO2 stems from model spread in simulating tropical processesModel spread in tropical sea surface temperature (SST) changes modulates the NPSH by influencing tropical precipitationModel spread in tropical precipitation changes independent of model spread in SST changes also adds to the uncertainty of the NPSH response [ABSTRACT FROM AUTHOR]

It has been demonstrated that decadal variations in the North Atlantic Oscillation (NAO) can be predicted by current forecast models. While Atlantic Multidecadal Variability (AMV) in sea surface temperatures (SSTs) has been hypothesised as the source of this skill, the validity of this hypothesis and the pathways involved remain unclear. We show, using reanalysis and data from two forecast models, that the decadal predictability of the NAO can be entirely accounted for by the predictability of decadal variations in the speed of the North Atlantic eddy-driven jet, with no predictability of decadal variations in the jet latitude. The sub-polar North Atlantic (SPNA) is identified as the only obvious common source of an SST-based signal across the models and reanalysis, and the predictability of the jet speed is shown to be consistent with a forcing from the SPNA visible already within a single season. The pathway is argued to be tropospheric in nature, with the SPNA-associated heating extending up to the mid-troposphere, which alters the meridional temperature gradient around the climatological jet core. The relative roles of anthropogenic aerosol emissions and the Atlantic Meridional Overturning Circulation (AMOC) at generating predictable SPNA variability are also discussed. The analysis is extensively supported by the novel use of a set of seasonal hindcasts spanning the 20th century and forced with prescribed SSTs. [ABSTRACT FROM AUTHOR]

The observed stratospheric quasi‐biennial oscillation (QBO) and the tropospheric Madden‐Julian oscillation (MJO) are strongly connected in boreal winter, with stronger MJO activity when lower‐stratospheric winds are easterly. However, the current generation of climate models with internally generated representations of the QBO and MJO do not simulate the observed QBO‐MJO connection, for reasons that remain unclear. This study builds on prior work exploring the QBO‐MJO link in climate models whose stratospheric winds are relaxed toward reanalysis, reducing stratospheric biases in the model and imposing a realistic QBO. A series of ensemble experiments are performed using four state‐of‐the‐art climate models capable of representing the MJO over the period 1980–2015, each with similar nudging in the stratosphere. In these four models, nudging leads to a good representation of QBO wind and temperature signals, however no model simulates the observed QBO‐MJO relationship. Biases in MJO vertical structure and cloud‐radiative feedbacks are investigated, but no conclusive model bias or mechanism is identified that explains the lack of a QBO‐MJO connection. Plain Language Summary: Observations show a strong link between the stratospheric quasi‐biennial oscillation (QBO)—the alternation of tropical stratospheric zonal winds between easterly and westerly phases—and the Madden‐Julian oscillation (MJO), an eastward propagating phenomenon in the tropical troposphere in which the circulation and convection are coupled. Stronger MJO activity is observed when lower‐stratospheric winds are easterly. This coupling is intriguing for many reasons, but most practically because it suggests that the stratosphere can potentially enhance surface weather and inform subseasonal climate prediction. However, current climate models do not show this observed connection. One reason may be related to biases in how models simulate stratospheric winds, which can be corrected for in an artificial way by relaxing the model simulated winds to better match observationally constrained data sets. One recent study, however, showed that correcting for this bias using this approach in one climate model still fails to produce credible QBO‐MJO coupling. Here we expand that analysis to include four climate models and find that no model produces a robust QBO‐MJO relationship like that seen in observations. Our results show that properly representing the QBO winds and temperatures via nudging is therefore not sufficient for reproducing the observed relationship. Furthermore, while biases in how models represent cloud processes may still be a likely culprit, any definitive model bias or missing mechanism remains elusive. Key Points: The link between the quasi‐biennial oscillation (QBO) and Madden‐Julian oscillation (MJO) is explored in four climate models with nudged stratospheric winds and free‐evolving tropospheresNo model shows as strong of a QBO‐MJO connection as in observationsModel biases in cloud‐radiative feedbacks and MJO vertical velocity are diagnosed, but neither conclusively explains the lack of a QBO‐MJO connection [ABSTRACT FROM AUTHOR]

Single-forcing large ensembles are a relatively new tool for quantifying the contributions of different anthropogenic and natural forcings to the historical and future projected evolution of the climate system. This study introduces a new single-forcing large ensemble with the Community Earth System Model, version 2 (CESM2), which can be used to separate the influences of greenhouse gases, anthropogenic aerosols, biomass burning aerosols, and all remaining forcings on the evolution of the Earth system from 1850 to 2050. Here, the forced responses of global near-surface temperature and associated drivers are examined in CESM2 and compared with those in a single-forcing large ensemble with CESM2's predecessor, CESM1. The experimental design, the imposed forcing, and the model physics all differ between the CESM1 and CESM2 ensembles. In CESM1, an "all-but-one" approach was used whereby everything except the forcing of interest is time evolving, while in CESM2 an "only" approach is used, whereby only the forcing of interest is time evolving. This experimental design choice is shown to matter considerably for anthropogenic aerosol-forced change in CESM2, due to state dependence of cryospheric albedo feedbacks and nonlinearity in the Atlantic meridional overturning circulation (AMOC) response to forcing. This impact of experimental design is, however, strongly dependent on the model physics and/or the imposed forcing, as the same sensitivity to experimental design is not found in CESM1, which appears to be an inherently less nonlinear model in both its AMOC behavior and cryospheric feedbacks. [ABSTRACT FROM AUTHOR]

. Climate simulation uncertainties arise from internal variability, model structure, and external forcings. Model intercomparisons (such as the Coupled Model Intercomparison Project; CMIP) and single-model large ensembles have provided insight on uncertainty sources. Under the Community Earth System Model (CESM) project, large ensembles have been performed for CESM2 (a CMIP6-era model) and CESM1 (a CMIP5-era model). We refer to these as CESM2-LE and CESM1-LE. The external forcing used in these simulations changed to be consistent with their CMIP generation. As a result, differences between CESM2-LE and CESM1-LE ensemble means arise from changes in both model structure and forcing. Here we present new ensemble simulations which allow us to separate the influences of these model structural and forcing differences. Our new CESM2 simulations are run with CMIP5 forcings equivalent to those used in the CESM1-LE. We find a strong influence of historical forcing uncertainty due to aerosol effects on simulated climate. For the historical period, forcing drives reduced global warming and ocean heat uptake in CESM2-LE relative to CESM1-LE that is counteracted by the influence of model structure. The influence of model structure and forcing vary across the globe and the Arctic exhibits a distinct signal that contrasts with the global mean. For the 21st century, the importance of scenario forcing differences (SSP3-7.0 for CESM2-LE and RCP8.5 for CESM1-LE) is evident. The new simulations presented here allow us to diagnose the influence of model structure on 21st century change despite large scenario forcing differences, revealing that differences in the meridional distribution of warming are caused by model structure. Feedback analysis reveals that clouds and their impact on shortwave radiation explain many of these structural differences between CESM2 and CESM1. In the Arctic, albedo changes control transient climate evolution differences due to structural differences between CESM2 and CESM1. [ABSTRACT FROM AUTHOR]