Weak Stratospheric Polar Vortex Events Modulated by the Arctic Sea‐Ice Loss

Hoshi, Kazuhira; Ukita, Jinro; Honda, Meiji; Nakamura, Tetsu; Yamazaki, Koji; Miyoshi, Y.; Jaiser, Ralf

doi:10.1029/2018jd029222

Cited by 35 publications

(25 citation statements)

References 43 publications

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“…Early modeling studies found that low sea ice, either pan-Arctic or east of Greenland and extending into the Barents-Kara seas, forced cold temperatures across the NH continents similar to the negative AO temperature pattern 91,92,93,94,95 . However, since then, modeling studies have supported the entire range of atmospheric response, including cold continents 12,69,71,105,106,112,116,120,121 , a disrupted stratospheric polar vortex comparable to observed 69,112,118,121 and weaker and/or delayed relative to observed 51,100 , a negative AO 118,122 , a positive AO 123,124 with mild continental temperatures 125 and finally no robust impact on midlatitude weather 97,98,99,126 .…”

Section: Observational Analysis Versus Modeling Experimentsmentioning

confidence: 99%

Divergent consensuses on Arctic amplification influence on mid-latitude severe winter weather

Cohen¹,

Zhang²

2020

Preprint

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<p>The Arctic has warmed more than twice as fast as the global average since the late 20<sup>th</sup> century, a phenomenon known as Arctic amplification (AA). &#160;Recently, there have been significant advances in understanding the physical contributions to AA and progress has been made in understanding the mechanisms linking AA to mid-latitude weather variability. &#160;Observational studies overwhelmingly support that AA is contributing to winter continental cooling.&#160; While Arctic warming is strongest at the surface, it extends throughout the mid-troposphere. In addition, the sea ice loss and associated warming is not uniform across the Arctic, but rather regionally focused including in the Barents-Kara Seas, a key region for disrupting the polar vortex.&#160; The probability of severe winter weather increases across the Northern Hemisphere continents following polar vortex disruptions.&#160; While some model experiments support the observational evidence, the majority of modeling results show little connection between AA and severe mid-latitude weather. Rather the excess warming generated in the Arctic due to sea ice loss and other mechanisms is not redistributed vertically in model simulations, but rather horizontally suggesting the export of excess heating from the Arctic to lower latitudes. &#160;Divergent conclusions between model and observational studies, and even intra-model studies, continue to obfuscate a clear understanding of how AA is influencing mid-latitude weather.</p>

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Section: Observational Analysis Versus Modeling Experimentsmentioning

confidence: 99%

Divergent consensuses on Arctic amplification influence on mid-latitude severe winter weather

Cohen¹,

Zhang²

2020

Preprint

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“…In recent years, many components of this pathway have been investigated, especially concerning the increased frequency of cold winters over Europe and the emergence of the counter-intuitive "warm Arctic-cold continent" (WACC) pattern over Eurasia (Petoukhov and Semenov, 2010;Vihma, 2014). However, there remains substantial uncertainty about the impact of Arctic sea ice in terms of location (Zhang et al, 2016;Luo et al, 2017;Screen 2017;Kelleher and Screen, 2018), timing (Honda et al, 2009;Overland et al, 2011;Inoue et al, 2012;Suo et al, 2016;Sorokina et al, 2016;King et al, 2016;Screen, 2017;Wegmann et al, 2018a; or whether sea ice can be used as a predictor or forcing at all based on the contrasting results of model studies (McCusker et al, 2016;Collow et al, 2017;Pedersen et al, 2016;Boland et al, 2017;Crasemann et al, 2017;Ruggieri et al, 2017;Garcia-Serrano et al, 2017;Francis, 2017;Screen et al, 2018;Mori et al, 2019;Hoshi et al, 2019;Romanowksy et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Eurasian autumn snow link to winter North Atlantic Oscillation is strongest for Arctic warming periods

et al. 2020

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Abstract. In recent years, many components of the connection between Eurasian autumn snow cover and wintertime North Atlantic Oscillation (NAO) have been investigated, suggesting that November snow cover distribution has strong prediction power for the upcoming Northern Hemisphere winter climate. However, the non-stationarity of this relationship could impact its use for prediction routines. Here we use snow products from long-term reanalyses to investigate interannual and interdecadal links between autumnal snow cover and atmospheric conditions in winter. We find evidence for a negative NAO-like signal after November with a strong west-to-east snow cover gradient, which is valid throughout the last 150 years. This correlation is consistently linked to a weak stratospheric polar vortex state. Nevertheless, decadal evolution of this link shows episodes of decreased correlation strength, which co-occur with episodes of low variability in the November snow index. By contrast, periods with high prediction skill for winter NAO are found in periods of high November snow variability, which co-occur with the Arctic warming periods of the 20th century, namely the early 20th-century Arctic warming between 1920 and 1940 and the ongoing anthropogenic global warming at the end of the 20th century. A strong snow dipole itself is consistently associated with reduced Barents–Kara sea ice concentration, increased Ural blocking frequency and negative temperature anomalies in eastern Eurasia.

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“…Our analysis shows the potential for combining OBP, SSH, and SST satellite data to determine monthly time series of satellite upper ocean OID steric height, heat and freshwater contents for major parts of the southern Barents Sea. This is important for the local ecosystem (Eriksen et al, 2011;Oziel et al, 2017), and the southern Barents Sea is a region where SST is correlated with anomalous winter surface air temperature across Europe and Asia (Blackport et al, 2019;Hoshi et al, 2019). This builds on Volkov et al's (2013) analysis of steric height, thermosteric height, and halosteric height using satellite data.…”

Section: Resultsmentioning

confidence: 99%

“…A significant increase in the temperature of AW entering the Barents Sea also coincided with a sea ice regime shift in the mid‐2000s, increasing the temperature gradient across the Polar Front, limiting the southward extent of winter sea ice, and resulting in warmer and saltier BSW (Barton et al., 2018). The sea ice loss (Hoshi et al., 2019; Petoukhov & Semenov, 2010) and changes in the ocean to atmospheric heat flux (Blackport et al., 2019) in the Barents and Kara Seas have been correlated with anomalous weather conditions in northern Europe, Russia, and Asia. Monitoring the variations and changes in the properties of BSW is thus relevant for understanding the atmospheric and ocean changes, locally in the Barents Sea and beyond.…”

Section: Introductionmentioning

confidence: 99%

Water Mass Properties Derived From Satellite Observations in the Barents Sea

2020

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The Barents Sea is a region of deep water formation where Atlantic Water is converted into cooler, fresher Barents Sea Water. Barents Sea Water properties exhibit variability at seasonal, interannual, and decadal timescales. This variability is transferred to Arctic Intermediate Water, which eventually contributes to the deeper branch of the Atlantic meridional overturning circulation. Variations in Barents Sea Water properties are reflected in steric height (contribution of density to sea‐level variations) that depends on heat and freshwater contents and is a quantity usually derived from in situ observations of water temperature, salinity, and pressure that remain sparse during winter in the Barents Sea. This analysis explores the utility of satellite observations for representing Barents Sea Water properties and identifying trends and sources of variability through novel methods. We present our methods for combining satellite observations of eustatic height (the contribution of mass to sea‐level variations), sea surface height, and sea surface temperature, validated by in situ temperature and salinity profiles, to estimate steric height. We show that sea surface temperature is a good proxy for heat content in the upper part of the water column in the southeastern Barents Sea and that freshwater content can be reconstructed from satellite data. Our analysis indicates that most of the seasonality in Barents Sea Water properties arises from the balance between ocean heat transport and atmospheric heat flux, while its interannual variability is driven by heat and freshwater advection.

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Weak Stratospheric Polar Vortex Events Modulated by the Arctic Sea‐Ice Loss

Cited by 35 publications

References 43 publications

Divergent consensuses on Arctic amplification influence on mid-latitude severe winter weather

Divergent consensuses on Arctic amplification influence on mid-latitude severe winter weather

Eurasian autumn snow link to winter North Atlantic Oscillation is strongest for Arctic warming periods

Water Mass Properties Derived From Satellite Observations in the Barents Sea

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