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Review

A Review of Impacts of the Tibetan Plateau Snow on Climate Variability over East Asia and North America

by
Zhibiao Wang
1,
Renguang Wu
2,* and
Xiaojing Jia
2
1
Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
2
Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province, School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(4), 618; https://doi.org/10.3390/atmos14040618
Submission received: 7 March 2023 / Revised: 19 March 2023 / Accepted: 21 March 2023 / Published: 24 March 2023
(This article belongs to the Special Issue Land–Atmosphere Coupling under Climate Change)
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Abstract

:
Snow anomalies over the Tibetan Plateau (TP) have been shown to contribute to the climate variability in the neighboring and remote regions. The present study provides a review of the research progress of studies on the impacts of the TP snow anomalies on the climate over East Asia and North America. This review covers long-term TP snow variations in different seasons and in different regions, interdecadal TP snow changes in different times and their contributions to the interdecadal rainfall changes over East Asia, impacts of TP snow anomalies in different parts and different seasons on East Asian and North America climate variability on interannual time scales, intraseasonal TP snow variations and their impacts on East Asian atmospheric circulation, and interdecadal changes in the relationship of the East Asian rainfall and North American air temperature to the TP snow. The review also includes the atmospheric circulation patterns that link the TP snow to East Asian and North American climate. Discussions are provided for relevant issues of the TP snow impacts.

1. Introduction

With its high terrain and large spatial coverage, the Tibetan Plateau (TP) serves as an elevated heat source and sink in the middle and upper troposphere. In boreal summer, the high air temperature over the TP and the neighboring regions (Figure 1a) leads to the formation of the South Asian high (Figure 1b), an important circulation system over Asia. The anomalous TP thermal state modulates the climate over Asia [1,2]. The TP also serves as an “Asian water tower’’, with a pool of water vapor maximum (Figure 1c), which provides water supply for several rivers in Asia [3].
Snow is an effective modulator of the thermal state of the land surface due to its albedo and hydrological effects [4,5]. The albedo effect is prominent near the periphery of the snow-covered regions, and the hydrological effect operates when the snow melts [5,6]. Through modulating the thermal condition of surface and lower troposphere, the TP snow anomalies cause anomalous heating or cooling in the atmosphere and, consequently, influence weather and climate in the neighboring and remote regions [7,8].
There is a large body of studies about the impacts of the TP snow on the South and East Asian climate variability [8,9,10,11]. Studies have identified long-term snow changes over the TP in different parts that vary with the season. Several interdecadal changes have been detected in the TP snow variations that may have contributed to interdecadal change in Asian rainfall. Numerous studies have shown the impacts of the TP snow anomalies in different parts on East Asian rainfall in different seasons through different pathways. A few studies have revealed the impacts of the TP snow anomalies on North American air temperature through atmospheric circulation patterns. Interdecadal changes have been found in the relationship of East Asian and North American climate to the TP snow. Recent studies have shown intraseasonal variations in the TP snow that may affect downstream East Asia.
A review of previous relevant studies would provide readers useful information of the current status of understanding of the TP snow impacts and potential issues that may be pursued in future studies. To limit the length, this review focuses on the impacts of the TP snow on downstream East Asian and North American climate and the associated processes. The impacts of the TP snow on the South Asian climate are not included in this review. The TP snow displays temporal variations on multiple time scales. This review covers the impacts of the TP snow variations on climate variability on decadal, interannual, and intraseasonal time scales.

2. Long-Term and Decadal Variations

The TP snow has decadal and long-term variations [8,10,13]. An interdecadal change occurred in the late 1970s for the winter and spring snow depth [14,15]. A decrease in the spring snow depth was identified around 2002 [16]. The snow depth and number of snow cover days displayed trends depending upon time periods [10,17,18,19,20,21]. A switch from the increasing to decreasing trend occurred in the early to mid-1990s [17,18,21].
Long-term changes in the TP snow cover display regional difference and seasonality [22]. The snow cover displays a decreasing trend in summer and fall in the western TP, a decreasing trend in all the four seasons in the southern TP, and an increasing trend in fall, winter, and spring in the central-eastern TP after the mid 1980s (Figure 2a,b). The increasing trend in the central-eastern TP is most prominent in spring (Figure 2c). An elevation dependence was also detected for long-term snow cover variations in the southern TP [22] where the snow cover above 5 km displays an increasing trend in the 1990s, distinct from the snow cover at lower elevations (Figure 2d).
The interdecadal TP snow change is shown to induce interdecadal changes in climate over East Asia. The winter–spring snow depth increase in the late 1970s was accompanied by an increase in summer rainfall in the Yangtze River reaches [14,15,23]. Zhu et al. (2015) [16] indicated that the spring snow depth decrease caused an increase in summer rainfall in the Huaihe River region after 2002. Wu et al. (2010) [24] suggested that the winter–spring central-eastern TP snow cover increase contributed to the interdecadal increase in summer rainfall over southern China around the early 1990s. Zhu et al. (2007) [25] noted that the winter–spring TP snow depth increase in the late 1970s is conducive to the southern flood and northern drought pattern of summer rainfall change over eastern China. Wu et al. (2012) [26] detected a link of the decadal to interdecadal variations in the heatwave frequency over northern China to the western TP snow cover change.
The TP snow contributed to the interdecadal changes in the East Asian summer rainfall through a meridional shift in the western Pacific subtropical high (WPSH) [14,15,16]. The excessive snowmelt induced surface cooling over the TP and neighboring regions, which was accompanied by high surface pressure anomalies. This resulted in a northwestward extension of the WPSH in the following summer [15]. In addition, the excessive snowmelt induced an increase in surface moisture supply, which was favorable for the development of low-level vortices that migrated eastward from the eastern part of the TP [15]. The snow-induced atmospheric cooling and higher surface pressure caused anomalous lower-level northerly winds that contributed to anomalous lower-level convergence and rainfall increase over southern China around the early 1990s [24]. Zhu et al. (2015) [16] indicated that the interdecadal northward shift of the WPSH and interdecadal variations of the large-scale precipitation conditions accompanying the spring TP snow depth decrease was favorable for the increase in summer rainfall in the Huaihe River valley after, rather than before, 2002.

3. Interannual Variations over East Asia

Numerous studies have shown roles of the TP snow in the East Asian climate variability [14,28,29,30,31,32,33,34,35,36,37,38,39,40]. Those studies can be summarized into two groups. One group is about the influence of the central-eastern TP snow in cold season (autumn-winter-spring). The other group is about the influence of the western and southern TP snow in summer. The analysis of the previous studies is mostly based on snow cover and snow depth changes.
Analysis in the early years is mainly based on station observations in the central-eastern TP. Studies indicate that more snow accumulation during winter-spring over the central-eastern TP tends to be followed by summer rainfall increase in the middle and lower Yangtze River region and rainfall decrease in South China and North China, e.g., [31,33,41]. However, Zhao et al. (2007) [36] obtained that there is less summer rainfall in the middle and lower Yangtze River region and more summer rainfall in southeastern China when there are more spring snow cover days over the TP. Jia et al. (2021) [42] identified that more autumn TP snow cover induces above-normal spring rainfall in southern China.
Using the satellite retrieved snow cover data, recent studies have detected the influence of the summer western TP snow on East Asian summer rainfall [39,40,43]. Wang et al. (2018b) [43] showed that both western and southern TP snow cover anomalies affect East Asian summer rainfall. More than normal western and southern TP snow cover leads to more precipitation over the middle and lower Yangtze River region and subtropical western North Pacific and less precipitation over tropical western North Pacific (Figure 3a,b). The role of snow cover over the western TP and Himalayas in the summer precipitation between the Yangtze and Yellow River basins was validated by Xiao and Duan (2016) [40] through numerical model simulations.
The climate anomalies associated with the TP snow depend upon the snow anomaly pattern. Wu and Qian (2003) [31] identified three winter snow depth anomaly patterns that are accompanied by different distributions of summer rainfall anomalies over Asia. Wang et al. (2017) [44] found that summer rainfall anomalies over eastern China display a different distribution corresponding to winter–spring southern and northern TP snow cover anomalies. More snow cover over the southern TP is followed by more rainfall in the Yangtze River region and northeastern China and less rainfall in South China, whereas more snow cover over the northern TP is followed by more rainfall in southeastern China and North China and less rainfall in the Yangtze River region. Xiao and Duan (2016) [40] found a difference in the impacts of central-eastern and western TP snow cover on the East Asian summer monsoon. They indicated that the preceding central and eastern TP snow cover anomalies exert little influence, whereas the winter or spring snow cover anomalies over the western TP and Himalayas can influence the East Asian summer monsoon by modulating the transport of water vapor to eastern China and eastward-migrating synoptic disturbances generated over the TP. The delayed effect of preceding winter–spring TP snow is associated with the persistence of snow anomalies [40,42]. Xiao and Duan (2016) [40] indicated that the impacts of preceding autumn–winter TP snow on succeeding East Asian summer monsoon are due to the persistence of the preceding snow anomalies to the following summer. Jia et al. (2021) [42] stated that autumn TP snow cover anomalies persist to the succeeding spring through a local positive snow-air feedback. The spring snow increase induced atmospheric cooling then leads to an increase in spring rainfall over southern China.
Studies have been conducted to understand the processes for the impacts of the TP snow on the climate over East Asia. It is generally agreed that the TP snow anomalies modify the atmospheric thermal state by modulating surface shortwave radiation and sensible and latent heat fluxes. However, different explanations have been proposed for how the modified TP thermal state induces rainfall anomalies over East Asia. One interpretation is the modulation of the large-scale land-sea thermal contrast [25,31,33,37,45]. Some studies emphasized the role of the WPSH and the East Asian jet stream in linking anomalous TP snow to East Asian rainfall changes [25,33,42]. Several studies invoked the moisture transport and moisture convergence to explain the occurrence of rainfall anomalies [25,40,41,42]. Some studies attributed the remote connection from the TP to East Asia to the atmospheric circulation anomaly pattern induced by anomalous TP snow [38,44]. The modulation of the eastward moving synoptic disturbances from the TP was also suggested to play a role in the linkage of the TP moisture change and the summer rainfall anomalies over eastern China [40].
Liu et al. (2014) [39] proposed the role of anomalous vertical circulations over the Indo-western Pacific region in relaying the early-summer TP snow anomalies to summer rainfall anomalies in the Yangtze River region. Wang et al. (2018b) [43] suggested that the summer snow anomalies in western and southern TP affect the East Asian summer rainfall through distinct pathways. The influence of the western TP snow anomalies is via an upper-level atmospheric wave pattern along the mid-latitude Asia that extends to Northeast China (Figure 3c). An anomalous barotropic cyclone develops over Northeast China (Figure 3a,c). The anomalous lower-level southwesterlies to the south of the anomalous cyclone bring more moisture from the lower latitudes, conducive to a band of excessive rainfall extending from the middle-lower Yangtze River to Japan (Figure 3a). The influence of the southern TP snow anomalies is through the tropical Indo-western Pacific vertical circulation proposed by Liu et al. (2014) [39]. More snow cover over the southern TP causes anomalous cooling, which, in turn, induces more convection over the Indian Ocean through an anomalous meridional overturning circulation. Anomalous convection over the Indian Ocean causes an anomalous zonal overturning circulation with anomalous upper-level westerlies over the tropical Indian Ocean-western Pacific and anomalous upper-level convergence over the western North Pacific (Figure 3d). Consequently, the convection is suppressed over the western North Pacific. Anomalous cooling over the western North Pacific induces a meridional atmospheric circulation anomaly pattern with an anomalous lower-level cyclone over East Asia (Figure 3b). This results in more rainfall extending from the middle-lower Yangtze River to Japan (Figure 3b). The distribution of wind and rainfall anomalies over East Asia and western North Pacific appears similar, corresponding to more snow cover over the western and southern TP [43].

4. Interannual Variations over North America

The impacts of the TP snow anomalies can extend downstream to North America [7,48,49,50,51]. Lin and Wu (2011) [48] presented evidence for a connection of autumn TP snow cover to a meridional seesaw pattern of North American winter surface air temperature. Qian et al. (2019) [52] detected a link between autumn TP snow and winter North American surface air temperature variations. Wang et al. (2020) [53] found that more spring snow cover over the TP tends to be followed by higher surface air temperature over North America.
The connection between the TP snow and the North American climate is attributed to atmospheric circulation pattern generated by the TP snow anomalies. Lin and Wu (2011) [48] indicated that the TP snow cover anomalies persist from autumn to the following winter through a positive snow–atmosphere feedback. The positive snow cover anomalies induce a positive Pacific–North America (PNA)-like anomaly pattern. This pattern is conducive to a warm–north and cold–south temperature anomaly distribution over North America. Qian et al. (2019) [52] indicated that the TP cooling induced by more snow cover in autumn extends to the East Asian jet stream core region. The accompanying vorticity perturbation generates an atmospheric wave pattern that extends from East Asia through the North Pacific and reaches North America. The accompanying anomalous meridional transport of air leads to positive and negative surface air temperature anomalies over western and eastern North America, respectively, in winter. Wang et al. (2020) [53] showed that the spring TP snow anomalies induce an atmospheric wave train extending from the eastern TP to North America. The anomalous descending motion and anomalous lower-level winds generate surface air temperature anomalies through surface heat fluxes and horizontal advection.
The impacts of the TP snow anomalies on the North American climate have been confirmed by numerical studies [7,51,53]. Liu et al. (2017) [7] showed that the dipole snow cover anomaly pattern with persisting more snow over the TP and less snow over Mongolia from October to March induces strong TP surface cooling and warming in the surrounding China and Mongolia regions. The anomalous diabatic cooling and heating generates a positive PNA-like atmospheric response in winter through the eastward propagating stationary Rossby wave energy and a transient eddy feedback mechanism. Liu et al. (2020) [51] demonstrated the impacts of the spring TP snow anomalies on global atmospheric circulation based on the numerical model experiments. Wang et al. (2020) [53] confirmed the role of anomalous divergence/convergence over the TP in inducing a wave train extending from the TP to North America.

5. Intraseasonal Variations over East Asia

Using the high temporal resolution snow data, recent studies identified obvious intraseasonal variations in the TP snow cover. The intraseasonal variations were detected for snow cover in wintertime [54,55,56,57], as well as during autumn [58]. Song et al. (2019) [58] found that the intraseasonal snow variation over the western and eastern TP has different sources. The intraseasonal variation of snow over the western TP is related to a midlatitude wave train associated with the Arctic oscillation, and the moisture comes from the Caspian Sea, while the intraseasonal variation of snow over the eastern TP is related to a subtropical wave train triggered by the North Atlantic oscillation, and the moisture originates from the Bay of Bengal. Li et al. (2020) [55] showed that the intraseasonal variability is a dominant component of the snow cover variations over most of the central and eastern TP, and the intraseasonal snow cover variation is more active in the cold than warm season.
Studies have presented evidence that the sub-seasonal snow cover variation over the TP exerts influences on atmospheric circulation over downstream East Asia. Li et al. (2018) [54] showed that the sub-seasonal TP snow cover variability in winter may lead to perturbation over East Asia approximately three to eight days later. The processes include the TP snow cover-induced anomalous cooling/heating, the modification of the land surface thermal condition, anomalous low at the upper level, the downstream extension of height anomalies, and East Asian lower-level jet stream intensity change. Li et al. (2021) [56] detected a rapid response of the East Asian trough strength to sub-seasonal TP snow cover variations during boreal winter. The snow cover events over the TP generate geopotential height anomalies that move eastward to East Asia to modulate the intensity of the East Asian trough.

6. Interdecadal Change in the Interannual Relationship

Studies have identified interdecadal changes in the relationship of the East Asian summer rainfall to the winter-spring TP snow cover or snow depth [16,45,59,60]. Si and Ding (2013) [45] identified that the relation between TP winter snow and East Asian summer rainfall experienced a change in the late 1990s. The above-normal rainfall band corresponding to more winter TP snow was located along the Yangtze River valley and southern Japan during the period 1979–1999, whereas it was displaced northward to the Huaihe River valley and the Korean Peninsula during the period 2000–2011. This interdecadal change is partly attributed to the TP warming accompanying the winter–spring snow decrease, which enhances the land-sea thermal contrast and shifts the TP snow-related rainfall belt northward. Zhang et al. (2021) [61] revealed that the impact of the TP spring snow cover on the Mei-yu rainfall over the Yangtze River Valley experienced an increase after the 1990s. Zhu et al. (2015) [16] linked the shift of the spring TP snow-related summer rainfall increase to the Huaihe River valley around 2002 to the northward shift of the WPSH and the change in the large-scale precipitation conditions. Wang et al. (2021) [60] found a change in the impact of the western TP summer snow on the East Asian precipitation in the early 2000s. Before the early 2000s, above normal precipitation extends from the southeastern TP to the Yangtze River and Japan, and below normal precipitation is seen in southeastern China. After the early 2000s, more precipitation is seen in northeastern China, and less precipitation is located in northern China-Mongolia. The change appears to be related to the reduction of the standard deviation of interannual variations in the TP snow cover.
Interdecadal changes have also been detected in the relation of the North American air temperature to the TP snow. Qian et al. (2019) [52] detected an interdecadal weakening in the relationship of the autumn eastern TP snow cover to the winter North American surface air temperature around 1994/95. They attributed the interdecadal change to the weakened cooling effect of the snow anomalies and the associated weakened vorticity forcing near the East Asian jet core. Wang et al. (2020) [53] identified a weakened influence of the spring TP snow cover on the spring North American surface air temperature around the mid 2000s (Figure 4a). More spring TP snow induces higher surface air temperature before the mid 2000s (Figure 4b), but this effect is weak after the mid 2000s (Figure 4c). This interdecadal change is associated with the intensified impact of the tropical central Pacific sea surface temperature (SST) anomalies on the PNA-like atmospheric circulation pattern [53].

7. Summary and Discussions

Through modulating surface and lower tropospheric thermal state, the TP snow anomalies cause anomalous heating/cooling in the atmospheric column. Consequently, the large-scale land–sea thermal contrast is modified, and an atmospheric circulation anomaly pattern is induced in the surrounding regions. Thus, the TP snow anomalies contribute to climate variability in the neighboring and remote regions on various time scales. Due to the changes in the magnitude of snow anomalies and in the impacts of other factors, the relationship between the TP snow and regional climate has been subjected to interdecadal modulations in the past.
Previous studies have identified long-term variations of TP snow in different seasons and in different regions. Several interdecadal changes have been detected in TP snow variations, which have been proposed to contribute to interdecadal changes in East Asian rainfall. Numerous studies have indicated that the TP snow anomalies in different parts and different seasons can affect East Asian and North American climate variability on interannual time scales through different processes. Interdecadal changes have been revealed in the relationship of the TP snow to the East Asian rainfall and North American air temperature.
Compared to interannual and interdecadal variations, intraseasonal variations of the TP snow received attention only recently, when high temporal resolution snow data became available. Our knowledge of intraseasonal variations in the TP snow and their impacts is limited at the current stage. Much effort needs to be made to delineate the contributions of intraseasonal snow variations over the TP to climate variations in various regions.
The climate variability over East Asia and North America is influenced by various lower boundary conditions, and snow is just one of them. The present view covers only the impacts of TP snow anomalies on East Asian and North American climate variability. The relative roles of TP snow and other lower boundary conditions remain to be investigated in the future.
Previous studies are mostly concerned with the impacts of the TP snow anomalies on East Asian climate in spring and summer. A recent study by Chen et al. (2021) [62] identified that the eastern TP autumn–winter snow anomalies affect the East Asian winter monsoon. The influence is through modulating the Siberian High and the Aleutian Low. Chen et al. (2021) [62] also detected a weakened impact of the TP snow on the East Asian winter monsoon after the mid 1990s due to the reduced persistence of the snow anomalies from autumn to winter.
Under global warming, the mean snow coverage is reduced over the TP. The snow variability and anomalous snow generated atmospheric cooling is expected to experience change. This may reduce the impacts of the anomalous TP snow on atmospheric circulation over the TP and in the surrounding regions. Further studies are needed to investigate future changes in the influence of the TP snow anomalies on the climate variability in various regions on different time scales.

Author Contributions

Draft and modification: R.W. and Z.W.; Modification: X.J. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China Grants (41721004 and 42105028) and the China Postdoctoral Science Foundation (2020T130640).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Climatological mean July (a) air temperature (K) at 300 hPa, (b) geopotential height (10 m) at 200 hPa and (c) specific humidity (g/kg) at 400 hPa for the period 1979–2022. The thick-black contour denotes the elevation of 2000 m. The analysis is based on the NCEP-NCAR reanalysis data [12] (https://psl.noaa.gov/data/ (accessed on 24 January 2023)).
Figure 1. Climatological mean July (a) air temperature (K) at 300 hPa, (b) geopotential height (10 m) at 200 hPa and (c) specific humidity (g/kg) at 400 hPa for the period 1979–2022. The thick-black contour denotes the elevation of 2000 m. The analysis is based on the NCEP-NCAR reanalysis data [12] (https://psl.noaa.gov/data/ (accessed on 24 January 2023)).
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Figure 2. (a) Linear trends of annual mean snow cover (% decade−1) for the period 1979–2006. Dotted regions denote trends significant at the 95% confidence level. The three boxes denote the domains of the west region, the south region, and the east region in calculating area-mean values. (b) Area–mean annual mean snow cover (%) anomalies in different regions. (c) Area–mean snow cover anomalies (%) in the east region in different seasons. (d) Area–mean annual mean snow cover anomalies (%) in the south region averaged for grid points with different elevations. The area–mean values are calculated by averaging values at grid points with elevation above 2000 m. The anomalies are calculated based on climatology for the period 1979–2006. All lines are obtained by a nine-year Gaussian filter. The analysis is based on the NSIDC snow cover data [27] (https://nsidc.org/data/NSIDC-0046/versions/4 (accessed on 3 May 2022)). (Based on modification of [22]).
Figure 2. (a) Linear trends of annual mean snow cover (% decade−1) for the period 1979–2006. Dotted regions denote trends significant at the 95% confidence level. The three boxes denote the domains of the west region, the south region, and the east region in calculating area-mean values. (b) Area–mean annual mean snow cover (%) anomalies in different regions. (c) Area–mean snow cover anomalies (%) in the east region in different seasons. (d) Area–mean annual mean snow cover anomalies (%) in the south region averaged for grid points with different elevations. The area–mean values are calculated by averaging values at grid points with elevation above 2000 m. The anomalies are calculated based on climatology for the period 1979–2006. All lines are obtained by a nine-year Gaussian filter. The analysis is based on the NSIDC snow cover data [27] (https://nsidc.org/data/NSIDC-0046/versions/4 (accessed on 3 May 2022)). (Based on modification of [22]).
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Figure 3. Anomalies of June-July-August 850-hPa winds (m/s) and precipitation (mm/month) (a,b) and 150-hPa winds (m/s) (c,d) obtained by linear regression against the June–July–August interannual snow cover index in (a,c) the west TP region (32.5° N–40.5° N, 70° E–79° E) and (b,d) the south TP region (26.5° N–31.5° N, 80° E–99° E) for the period 1979–2020. Dotted regions denote precipitation anomalies significant at the 95% confidence level, and black vectors denote wind anomalies significant at the 95% confidence level. The scale for wind vectors are shown in the upper-left corner. Cyan curves in (c,d) denote the region with elevation above 2000 m. Black shading in (a,b) denotes the elevation below 2000 m. The analysis is based on the NSIDC snow cover data [27]; https://nsidc.org/data/NSIDC-0046/versions/4 (accessed on 3 May 2022)), the Japanese 55-year Reanalysis (JRA-55) wind data [46] (http://jra.kishou.go.jp/JRA-55/ (accessed on 30 August 2022)), and the Global Precipitation Climatology Project (GPCP) version 2.3 precipitation data [47] (https://www.esrl.noaa.gov/psd/ (accessed on 6 May 2022)). (updated based on [43]).
Figure 3. Anomalies of June-July-August 850-hPa winds (m/s) and precipitation (mm/month) (a,b) and 150-hPa winds (m/s) (c,d) obtained by linear regression against the June–July–August interannual snow cover index in (a,c) the west TP region (32.5° N–40.5° N, 70° E–79° E) and (b,d) the south TP region (26.5° N–31.5° N, 80° E–99° E) for the period 1979–2020. Dotted regions denote precipitation anomalies significant at the 95% confidence level, and black vectors denote wind anomalies significant at the 95% confidence level. The scale for wind vectors are shown in the upper-left corner. Cyan curves in (c,d) denote the region with elevation above 2000 m. Black shading in (a,b) denotes the elevation below 2000 m. The analysis is based on the NSIDC snow cover data [27]; https://nsidc.org/data/NSIDC-0046/versions/4 (accessed on 3 May 2022)), the Japanese 55-year Reanalysis (JRA-55) wind data [46] (http://jra.kishou.go.jp/JRA-55/ (accessed on 30 August 2022)), and the Global Precipitation Climatology Project (GPCP) version 2.3 precipitation data [47] (https://www.esrl.noaa.gov/psd/ (accessed on 6 May 2022)). (updated based on [43]).
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Figure 4. (a) Sliding correlation coefficients between the spring eastern TP snow cover (27.5°–37.5° N, 89°–103° E) and the spring northern of North America surface air temperature (SAT) with an 11-year (blue line), 15-year (orange line), and 19-year (green line) moving window for the period 1973–2017. The gray line denotes that the 15-year sliding correlation coefficient is significant at the 95% confidence level. Anomalies of SAT (°C) in spring obtained by linear regression against the spring interannual snow cover index in the eastern TP region for the period (b) 1979–2004 and (c) 2005–2017. The dotted regions in (b,c) denote anomalies significant at the 95% confidence level. The box covered areas in (b,c) denote the domain for the northern North American region. The analysis is based on the NSIDC snow cover data [27] (https://nsidc.org/data/NSIDC-0046/versions/4 (accessed on 24 January 2023)) and the CRU SAT data [61] (http://www.cru.uea.ac.uk/data/ (accessed on 24 January 2023)). (Based on modification of Wang et al., 2020 [53]).
Figure 4. (a) Sliding correlation coefficients between the spring eastern TP snow cover (27.5°–37.5° N, 89°–103° E) and the spring northern of North America surface air temperature (SAT) with an 11-year (blue line), 15-year (orange line), and 19-year (green line) moving window for the period 1973–2017. The gray line denotes that the 15-year sliding correlation coefficient is significant at the 95% confidence level. Anomalies of SAT (°C) in spring obtained by linear regression against the spring interannual snow cover index in the eastern TP region for the period (b) 1979–2004 and (c) 2005–2017. The dotted regions in (b,c) denote anomalies significant at the 95% confidence level. The box covered areas in (b,c) denote the domain for the northern North American region. The analysis is based on the NSIDC snow cover data [27] (https://nsidc.org/data/NSIDC-0046/versions/4 (accessed on 24 January 2023)) and the CRU SAT data [61] (http://www.cru.uea.ac.uk/data/ (accessed on 24 January 2023)). (Based on modification of Wang et al., 2020 [53]).
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Wang, Z.; Wu, R.; Jia, X. A Review of Impacts of the Tibetan Plateau Snow on Climate Variability over East Asia and North America. Atmosphere 2023, 14, 618. https://doi.org/10.3390/atmos14040618

AMA Style

Wang Z, Wu R, Jia X. A Review of Impacts of the Tibetan Plateau Snow on Climate Variability over East Asia and North America. Atmosphere. 2023; 14(4):618. https://doi.org/10.3390/atmos14040618

Chicago/Turabian Style

Wang, Zhibiao, Renguang Wu, and Xiaojing Jia. 2023. "A Review of Impacts of the Tibetan Plateau Snow on Climate Variability over East Asia and North America" Atmosphere 14, no. 4: 618. https://doi.org/10.3390/atmos14040618

APA Style

Wang, Z., Wu, R., & Jia, X. (2023). A Review of Impacts of the Tibetan Plateau Snow on Climate Variability over East Asia and North America. Atmosphere, 14(4), 618. https://doi.org/10.3390/atmos14040618

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