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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]

Projected changes in the Northern Hemisphere stratospheric polar vortex are analyzed using Climate Model Intercomparison Project Phase 6 experiments. Previous studies showed that projections of the wintertime zonally averaged polar vortex strength diverge widely between climate models with no agreement on the sign of change, and that this uncertainty contributes to the regional climate change uncertainty. Here, we show that there remains large uncertainty in the projected strength of the polar vortex in experiments with global warming levels ranging from moderate (SSP245 runs) to large (Abrupt‐4xCO2 runs), and that the uncertainty maximizes in winter. Partitioning of the uncertainty in wintertime polar vortex strength projections reveals that, by the end of the 21st century, model uncertainty contributes half of the total uncertainty, with scenario uncertainty contributing only 10%. Regression analysis shows that up to 20% of the intermodel spread in projected precipitation over the Iberian Peninsula and northwestern US, and 20%–30% in near‐surface temperature over western US and northern Eurasian, can be associated with the spread in vortex strength projections after accounting for global warming. While changes in the magnitude and sign of the zonally averaged vortex strength are uncertain, most models (>95%) predict an eastward shift of the vortex by 8°–20° degrees in longitude relative to its historical location with the magnitude of the shift increasing for larger global warming levels. There is less agreement across models on a latitudinal shift, whose direction and magnitude correlate with changes in the zonally averaged vortex strength so that vortex weakening/strengthening corresponds to a southward/poleward shift. Plain Language Summary: Previous studies showed that changes in the strength of the winds in the Northern Hemisphere wintertime stratosphere, the so‐called polar vortex, can affect near‐surface winds and precipitation 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 6 experiments to better understand how the polar vortex will respond to future greenhouse gas emissions. We show that half of the uncertainty in the vortex strength projections by the end of the 21st century is due to climate model errors (model uncertainty). We show that the uncertainty in the vortex strength projections is linked to the uncertainty in projected precipitation over the Iberian Peninsula and northwestern US and projected near‐surface temperature over the western US and northern Eurasia. Most models predict an eastward shift of the vortex relative to its historical location but we do not detect any influence of the vortex longitudinal shift on surface precipitation and temperatures. There is less agreement across models on a latitudinal shift, whose direction and magnitude correlate with changes in the vortex strength so that vortex weakening/strengthening corresponds to a southward/poleward shift of the vortex. Key Points: Model uncertainty contributes half of the total uncertainty in the projected strength of the Northern winter stratospheric polar vortexUncertainty in the projected polar vortex strength is linked to uncertainty in projected regional surface temperature and precipitationMost climate models project an eastward shift of the Northern winter stratospheric polar vortex [ABSTRACT FROM AUTHOR]

Many recent studies have confirmed that variability in the stratosphere is a significant source of surface sub‐seasonal prediction skill during Northern Hemisphere winter. It may be beneficial, therefore, to think about times in which there might be windows‐of‐opportunity for skillfull sub‐seasonal predictions based on the initial or predicted state of the stratosphere. In this study, we propose a simple, minimal model that can be used to understand the impact of the stratosphere on tropospheric predictability. Our model purposefully excludes state dependent predictability in either the stratosphere or troposphere or in the coupling between the two. Model parameters are set up to broadly represent current sub‐seasonal prediction systems by comparison with four dynamical models from the Sub‐Seasonal to Seasonal Prediction Project database. The model can reproduce the increases in correlation skill in sub‐sets of forecasts for weak and strong lower stratospheric polar vortex states over neutral states despite the lack of dependence of coupling or predictability on the stratospheric state. We demonstrate why different forecast skill diagnostics can give a very different impression of the relative skill in the three sub‐sets. Forecasts with large stratospheric signals and low amounts of noise are demonstrated to also be windows‐of‐opportunity for skillfull tropospheric forecasts, but we show that these windows can be obscured by the presence of unrelated tropospheric signals. Plain Language Summary: For successful forecasts of surface winter conditions between two weeks and one season ahead, the stratosphere has been shown to be a key source of information. Despite many studies examining how well the stratosphere can be predicted in computer‐based forecasting systems, there remains a lack of understanding of which surface forecasts the stratosphere is most important for. This study is an attempt to step back from examining the role of the stratosphere in any particular forecasting system and instead to determine a simple framework that can be used to understand when and how the stratosphere is important. Using our framework we can construct a series of simple experiments that help to understand how important the stratosphere is in the longer range forecasting problem. Our experiments show that forecasts made during periods in which the Arctic stratospheric winds are unusually strong or weak have greater skill, but this does not depend on how unusually weak or strong the stratospheric winds are. The results are particularly important for thinking about the times in which longer range forecasts might be more skillfull than on average, so called windows‐of‐opportunity, and how these depend on the stratosphere. Key Points: We propose a model that demonstrates how forecast skill present in the lowermost stratosphere contributes to tropospheric forecast skillThe model can explain the greater correlation skill in the troposphere for forecasts during weak or strong vortex eventsThe model shows how tropospheric skill arising from the stratosphere can sometimes be confounded by uncorrelated tropospheric signals [ABSTRACT FROM AUTHOR]

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid‐latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter‐model spread of PHT into the Arctic reflects the tug‐of‐war between sea‐ice and surface‐warming effects. Plain Language Summary: A major conundrum in current climate science is to understand what Arctic changes imply for the climate and environment in mid‐latitude regions. The Polar Amplification Model Intercomparison Project (PAMIP) designed a set of climate model experiments to specifically answer this question in a carefully designed, idealized framework. PAMIP's approach is to separate historic and projected climate change into parts associated with Arctic sea ice loss and ocean surface warming and investigate how these two contributions can influence the atmosphere. To isolate these effects, only models can be used, because, in reality, sea ice loss and ocean surface warming are strongly linked together. This letter focuses on what the PAMIP experiments imply for the transport and redistribution of heat and moisture in the atmosphere. In PAMIP, we learn that Arctic sea ice loss causes the atmosphere to reduce the transport of dry and cold air away from the Arctic while ocean warming causes more transport of moist warm air toward the Arctic. These two effects are in a tug‐of‐war, suggesting that climate change can cause a mix of competing impacts on the global energy transport from the tropics to the Arctic. Key Points: Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulationSea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effectThere is more spread amongst models for the effect of sea‐surface warming than for sea ice loss [ABSTRACT FROM AUTHOR]

Abstract: Anthropogenic‐aerosol (AA) radiative forcing modulates multidecadal greenhouse radiative forcing. However, decadal climate responses to AA are poorly characterized given AA forcing uncertainty and internal climate variability. This motivates revisiting a recent claim that AA drove a negative trend in the Pacific Decadal Oscillation and an associated cooling influence in the 10–15 years following the late‐1990's El Niño. The average of a 50‐member initial condition ensemble of the second generation Canadian Earth System Model version 2 that was forced only with AA does not exhibit the negative‐Pacific Decadal Oscillation/slowdown response. However, spurious responses of this kind, that are artifacts of subsetting the large ensemble (LE) in a manner consistent with published literature, can readily be found. This illustrates the caution needed in interpreting regional‐ and decadal‐scale responses to AA and suggests that improved characterization of model uncertainty in AA over the recent period is required. [ABSTRACT FROM AUTHOR]

Extreme variability of the winter- and spring-time stratospheric polar vortex has been shown to affect extratropical tropospheric weather. Therefore, reducing stratospheric forecast error may be one way to improve the skill of tropospheric weather forecasts. In this review, the basis for this idea is examined. A range of studies of different stratospheric extreme vortex events shows that they can be skilfully forecasted beyond 5 days and into the sub-seasonal range (0-30 days) in some cases. Separate studies show that typical errors in forecasting a stratospheric extreme vortex event can alter tropospheric forecast skill by 5-7% in the extratropics on sub-seasonal time-scales. Thus understanding what limits stratospheric predictability is of significant interest to operational forecasting centres. Both limitations in forecasting tropospheric planetary waves and stratospheric model biases have been shown to be important in this context. [ABSTRACT FROM AUTHOR]