scholarly journals Eurasian Cold Air Outbreaks under Different Arctic Stratospheric Polar Vortex Strengths

2019 ◽  
Vol 76 (5) ◽  
pp. 1245-1264 ◽  
Author(s):  
Jinlong Huang ◽  
Wenshou Tian

Abstract This study analyzes the differences and similarities of Eurasian cold air outbreaks (CAOs) under the weak (CAOW), strong (CAOS), and neutral (CAON) stratospheric polar vortex states and examines the potential links between the polar vortex and Eurasian CAOs. The results indicate that the colder surface air temperature (SAT) over Europe in the earlier stages of CAOW events is likely because the amplitude of the preexisting negative North Atlantic Oscillation pattern is larger in CAOW events than in CAON and CAOS events. Marked by the considerably negative stratospheric Arctic Oscillation signals entering the troposphere, the SAT at midlatitudes over eastern Eurasia in CAOW events is colder than in CAON events. A larger diabatic heating rate related to a positive sensible heat flux anomaly in CAOW events likely offsets, to some degree, the cooling effect caused by the stronger cold advection and makes the differences in area-averaged SAT anomalies over northern Eurasia between the CAOW and CAON events look insignificant in most stages. Massive anomalous waves from the low-latitude western Pacific merge over northeastern Eurasia, then weaken the westerly wind over this region to create favorable conditions for southward advection of cold air masses in the earlier stages of all three types of CAOs. This study further analyzes the interannual relationship between the stratospheric polar vortex strength and the intensity of Eurasian CAOs and finds that climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) relative to the reanalysis dataset tend to underestimate the correlation between them. The relationship between them is strengthening under representative concentration pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) scenarios over the period 2006–60. In addition, the intensity of Eurasian CAOs exhibits a decreasing trend in the past and in the future.

2021 ◽  
Author(s):  
Erik T. Smith ◽  
Scott Sheridan

Abstract Historical and future simulated temperature data from five climate models in the Coupled Model Intercomparing Project Phase 6 (CMIP6) are used to understand how climate change might alter cold air outbreaks (CAOs) in the future. Three different Shared Socioeconomic Pathways (SSPs), SSP 1 – 2.6, SSP 2 – 4.5, and SSP 5 – 8.5 are examined to identify potential fluctuations in CAOs across the globe between 2015 and 2054. Though CAOs may remain persistent or even increase in some regions through 2040, all five climate models show CAOs disappearing by 2054 based on current climate percentiles. Climate models were able to accurately simulate the spatial distribution and trends of historical CAOs, but there were large errors in the simulated interannual frequency of CAOs in the North Atlantic and North Pacific. Fluctuations in complex processes, such as Atlantic Meridional Overturning Circulation, may be contributing to each model’s inability to simulate historical CAOs in these regions.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Jinlong Huang ◽  
Peter Hitchcock ◽  
Amanda C. Maycock ◽  
Christine M. McKenna ◽  
Wenshou Tian

AbstractSevere cold air outbreaks have significant impacts on human health, energy use, agriculture, and transportation. Anomalous behavior of the Arctic stratospheric polar vortex provides an important source of subseasonal-to-seasonal predictability of Northern Hemisphere cold air outbreaks. Here, through reanalysis data for the period 1958–2019 and climate model simulations for preindustrial conditions, we show that weak stratospheric polar vortex conditions increase the risk of severe cold air outbreaks in mid-latitude East Asia by 100%, in contrast to only 40% for moderate cold air outbreaks. Such a disproportionate increase is also found in Europe, with an elevated risk persisting more than three weeks. By analysing the stream of polar cold air mass, we show that the polar vortex affects severe cold air outbreaks by modifying the inter-hemispheric transport of cold air mass. Using a novel method to assess Granger causality, we show that the polar vortex provides predictive information regarding severe cold air outbreaks over multiple regions in the Northern Hemisphere, which may help with mitigating their impact.


2017 ◽  
Vol 98 (1) ◽  
pp. 37-44 ◽  
Author(s):  
Darryn W. Waugh ◽  
Adam H. Sobel ◽  
Lorenzo M. Polvani

Abstract The term polar vortex has become part of the everyday vocabulary, but there is some confusion in the media, general public, and science community regarding what polar vortices are and how they are related to various weather events. Here, we clarify what is meant by polar vortices in the atmospheric science literature. It is important to recognize the existence of two separate planetary-scale circumpolar vortices: one in the stratosphere and the other in the troposphere. These vortices have different structures, seasonality, dynamics, and impacts on extreme weather. The tropospheric vortex is much larger than its stratospheric counterpart and exists year-round, whereas the stratospheric polar vortex forms in fall but disappears in the spring of each year. Both vortices can, in some circumstances, play a role in extreme weather events at the surface, such as cold-air outbreaks, but these events are not the consequence of either the existence or gross properties of these two vortices. Rather, cold-air outbreaks are most directly related to transient, localized displacements of the edge of the tropospheric polar vortex that may, in some circumstances, be related to the stratospheric polar vortex, but there is no known one-to-one connection between these phenomena.


2021 ◽  
Author(s):  
Hilla Afargan-Gerstman ◽  
Iuliia Polkova ◽  
Lukas Papritz ◽  
Paolo Ruggieri ◽  
Martin P. King ◽  
...  

<div> <p>Variability of the stratospheric polar vortex has the potential to influence surface weather by imposing negative North Atlantic Oscillation (NAO) conditions, associated with cold air outbreaks in the Arctic and a southward shift of the extratropical storm track. In particular, the likelihood of cold temperature extremes over the ocean, known as marine cold air outbreaks (MCAOs), have been associated with a range of hazardous conditions, including strong surface winds and the occurrence of extreme cyclones known as Polar Lows (PLs), posing risks for Arctic marine activity and infrastructure. Likewise, winter storms can lead to high damage potential in the extratropics due to their associated extreme winds.</p> </div><div> <p>Skillful predictions of MCAOs and extratropical winter storms on subseasonal timescales have been linked to the strength of the stratospheric polar vortex. Using ERA-Interim reanalysis (1979-2019) and ECMWF forecasts from the S2S Prediction Project database we investigate the stratospheric influence on surface extremes such as MCAOs and high-impact winter storms. Following weak stratospheric vortex extremes, anomalous circulation patterns accompanied by increased storminess over the eastern North Atlantic are found to be strong indicators for enhanced MCAOs in high- and mid-latitudes. Understanding the role of the stratosphere in subseasonal variability and predictability of cold air outbreaks and storm tracks during winter can provide a key for a reliable forecast of severe impacts.</p> </div>


2020 ◽  
Author(s):  
Hilla Afargan-Gerstman ◽  
Iuliia Polkova ◽  
Lukas Papritz ◽  
Paolo Ruggieri ◽  
Martin P. King ◽  
...  

Abstract. Marine cold air outbreaks (MCAOs) in the Arctic are associated with a range of severe weather phenomena, such as polar lows, strong surface winds and intense cooling of the ocean surface. While MCAO frequency has been linked to the strength of the stratospheric polar vortex, a connection to the occurrence of extreme stratospheric events, known as sudden stratospheric warmings (SSWs), has dominantly been investigated with respect to cold extremes over land. Here, the influence of SSW events on MCAOs in the Barents Sea is studied using observational and reanalysis datasets. Overall, more than a half of SSW events lead to more frequent MCAOs in the Barents Sea. SSW events with an enhanced MCAO response in the Barents Sea are associated with a ridge over Greenland and a trough over Scandinavia, leading to an anomalous dipole pattern of 500-hPa geopotential height and strong northerly flow over the Norwegian Sea. As SSW events tend to have a long-term influence on surface weather, these results can shed light on the predictability of MCAOs in the Arctic for winters with SSW events.


2011 ◽  
Vol 24 (19) ◽  
pp. 5108-5124 ◽  
Author(s):  
Liwei Jia ◽  
Timothy DelSole

A new statistical optimization method is used to identify components of surface air temperature and precipitation on six continents that are predictable in multiple climate models on multiyear time scales. The components are identified from unforced “control runs” of the Coupled Model Intercomparison Project phase 3 dataset. The leading predictable components can be calculated in independent control runs with statistically significant skill for 3–6 yr for surface air temperature and 1–3 yr for precipitation, depending on the continent, using a linear regression model with global sea surface temperature (SST) as a predictor. Typically, lag-correlation maps reveal that the leading predictable components of surface air temperature are related to two types of SST patterns: persistent patterns near the continent itself and an oscillatory ENSO-like pattern. The only exception is Europe, which has no significant ENSO relation. The leading predictable components of precipitation are significantly correlated with an ENSO-like SST pattern. No multiyear predictability of land precipitation could be verified in Europe. The squared multiple correlations of surface air temperature and precipitation for nonzero lags on each continent are less than 0.4 in the first year, implying that less than 40% of variations of the leading predictable component can be predicted from global SST. The predictable components describe the spatial structures that can be predicted on multiyear time scales in the absence of anthropogenic and natural forcing, and thus provide a scientific rationale for regional prediction on multiyear time scales.


2015 ◽  
Vol 28 (15) ◽  
pp. 5908-5921 ◽  
Author(s):  
Cheng Qian ◽  
Xuebin Zhang

Abstract The annual cycle is the largest variability for many climate variables outside the tropics. Whether human activities have affected the annual cycle at the regional scale is unclear. In this study, long-term changes in the amplitude of surface air temperature annual cycle in the observations are compared with those simulated by the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Different spatial domains ranging from hemispheric to subcontinental scales in mid- to high-latitude land areas for the period 1950–2005 are considered. Both the optimal fingerprinting and a nonoptimal detection and attribution technique are used. The results show that the space–time pattern of model-simulated responses to the combined effect of anthropogenic and natural forcings is consistent with the observed changes. In particular, models capture not only the decrease in the temperature seasonality in the northern high latitudes and East Asia, but also the increase in the Mediterranean region. A human influence on the weakening in the temperature seasonality in the Northern Hemisphere is detected, particularly in the high latitudes (50°–70°N) where the influence of the anthropogenic forcing can be separated from that of the natural forcing.


2017 ◽  
Vol 30 (12) ◽  
pp. 4463-4475 ◽  
Author(s):  
Liwei Jia ◽  
Xiaosong Yang ◽  
Gabriel Vecchi ◽  
Richard Gudgel ◽  
Thomas Delworth ◽  
...  

This study explores the role of the stratosphere as a source of seasonal predictability of surface climate over Northern Hemisphere extratropics both in the observations and climate model predictions. A suite of numerical experiments, including climate simulations and retrospective forecasts, are set up to isolate the role of the stratosphere in seasonal predictive skill of extratropical near-surface land temperature. It is shown that most of the lead-0-month spring predictive skill of land temperature over extratropics, particularly over northern Eurasia, stems from stratospheric initialization. It is further revealed that this predictive skill of extratropical land temperature arises from skillful prediction of the Arctic Oscillation (AO). The dynamical connection between the stratosphere and troposphere is also demonstrated by the significant correlation between the stratospheric polar vortex and sea level pressure anomalies, as well as the migration of the stratospheric zonal wind anomalies to the lower troposphere.


2020 ◽  
Author(s):  
Zebedee R. J. Nicholls ◽  
Malte Meinshausen ◽  
Jared Lewis ◽  
Robert Gieseke ◽  
Dietmar Dommenget ◽  
...  

Abstract. Here we present results from the first phase of the Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination of reduced complexity climate models (RCMs), which are used to complement and extend the insights from more complex Earth System Models (ESMs), in particular those participating in the Sixth Coupled Model Intercomparison Project (CMIP6). In Phase 1 of RCMIP, with 14 participating models namely ACC2, AR5IR (2 and 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR and WASP, we highlight the structural differences across various RCMs and show that RCMs are capable of reproducing global-mean surface air temperature (GSAT) changes of ESMs and historical observations. We find that some RCMs are capable of emulating the GSAT response of CMIP6 models to within a root-mean square error of 0.2 °C (of the same order of magnitude as ESM internal variability) over a range of scenarios. Running the same model configurations for both RCP and SSP scenarios, we see that the SSPs exhibit higher effective radiative forcing throughout the second half of the 21st Century. Comparing our results to the difference between CMIP5 and CMIP6 output, we find that the change in scenario explains approximately 46 % of the increase in higher end projected warming between CMIP5 and CMIP6. This suggests that changes in ESMs from CMIP5 to CMIP6 explain the rest of the increase, hence the higher climate sensitivities of available CMIP6 models may not be having as large an impact on GSAT projections as first anticipated. A second phase of RCMIP will complement RCMIP Phase 1 by exploring probabilistic results and emulation in more depth to provide results available for the IPCC's Sixth Assessment Report author teams.


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