Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea Ice

Because Eurasian snow water equivalent (SWE) is a key factor affecting the climate in the Northern Hemisphere, understanding the distribution characteristics of Eurasian SWE is important. Through empirical orthogonal function (EOF) analysis, we found that the first and second modes of Eurasian winte...

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Main Authors: Jiajun Feng, Yuanzhi Zhang, Jin Yeu Tsou, Kapo Wong
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/14/2/243
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author Jiajun Feng
Yuanzhi Zhang
Jin Yeu Tsou
Kapo Wong
author_facet Jiajun Feng
Yuanzhi Zhang
Jin Yeu Tsou
Kapo Wong
author_sort Jiajun Feng
collection DOAJ
description Because Eurasian snow water equivalent (SWE) is a key factor affecting the climate in the Northern Hemisphere, understanding the distribution characteristics of Eurasian SWE is important. Through empirical orthogonal function (EOF) analysis, we found that the first and second modes of Eurasian winter SWE present the distribution characteristics of an east–west dipole and north–south dipole, respectively. Moreover, the distribution of the second mode is caused by autumn Arctic sea ice, with the distribution of the north–south dipole continuing into spring. As the sea ice of the Barents–Kara Sea (BKS) decreases, a negative-phase Arctic oscillation (AO) is triggered over the Northern Hemisphere in winter, with warm and humid water vapor transported via zonal water vapor flux over the North Atlantic to southwest Eurasia, encouraging the accumulation of SWE in the southwest. With decreases in BKS sea ice, zonal water vapor transport in northern Eurasia is weakened, with meridional water vapor flux in northern Eurasia obstructing water vapor transport from the North Atlantic, discouraging the accumulation of SWE in northern Eurasia in winter while helping preserve the cold climate of the north. The distribution characteristics of Eurasian spring SWE are determined primarily by the memory effect of winter SWE. Whether analyzed through linear regression or support vector machine (SVM) methods, BKS sea ice is a good predictor of Eurasian winter SWE.
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spelling doaj.art-883ca3a98fe84d00af71bfefd9df91972023-11-23T15:14:24ZengMDPI AGRemote Sensing2072-42922022-01-0114224310.3390/rs14020243Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea IceJiajun Feng0Yuanzhi Zhang1Jin Yeu Tsou2Kapo Wong3School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaCenter for Housing Innovations, Faculty of Social Science, Chinese University of Hong Kong, Hong Kong 999777, ChinaSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong 999666, ChinaBecause Eurasian snow water equivalent (SWE) is a key factor affecting the climate in the Northern Hemisphere, understanding the distribution characteristics of Eurasian SWE is important. Through empirical orthogonal function (EOF) analysis, we found that the first and second modes of Eurasian winter SWE present the distribution characteristics of an east–west dipole and north–south dipole, respectively. Moreover, the distribution of the second mode is caused by autumn Arctic sea ice, with the distribution of the north–south dipole continuing into spring. As the sea ice of the Barents–Kara Sea (BKS) decreases, a negative-phase Arctic oscillation (AO) is triggered over the Northern Hemisphere in winter, with warm and humid water vapor transported via zonal water vapor flux over the North Atlantic to southwest Eurasia, encouraging the accumulation of SWE in the southwest. With decreases in BKS sea ice, zonal water vapor transport in northern Eurasia is weakened, with meridional water vapor flux in northern Eurasia obstructing water vapor transport from the North Atlantic, discouraging the accumulation of SWE in northern Eurasia in winter while helping preserve the cold climate of the north. The distribution characteristics of Eurasian spring SWE are determined primarily by the memory effect of winter SWE. Whether analyzed through linear regression or support vector machine (SVM) methods, BKS sea ice is a good predictor of Eurasian winter SWE.https://www.mdpi.com/2072-4292/14/2/243Eurasian SWEArctic sea iceArctic oscillationwater vapor flux
spellingShingle Jiajun Feng
Yuanzhi Zhang
Jin Yeu Tsou
Kapo Wong
Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea Ice
Remote Sensing
Eurasian SWE
Arctic sea ice
Arctic oscillation
water vapor flux
title Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea Ice
title_full Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea Ice
title_fullStr Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea Ice
title_full_unstemmed Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea Ice
title_short Analyzing Variations in the Association of Eurasian Winter–Spring Snow Water Equivalent and Autumn Arctic Sea Ice
title_sort analyzing variations in the association of eurasian winter spring snow water equivalent and autumn arctic sea ice
topic Eurasian SWE
Arctic sea ice
Arctic oscillation
water vapor flux
url https://www.mdpi.com/2072-4292/14/2/243
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AT yuanzhizhang analyzingvariationsintheassociationofeurasianwinterspringsnowwaterequivalentandautumnarcticseaice
AT jinyeutsou analyzingvariationsintheassociationofeurasianwinterspringsnowwaterequivalentandautumnarcticseaice
AT kapowong analyzingvariationsintheassociationofeurasianwinterspringsnowwaterequivalentandautumnarcticseaice