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  • View in gallery

    Distribution of (a) mean snow cover (SC; shaded; %) and interannual standard deviation of snow cover (contours; interval: 3%) and (b) mean total heating in the atmospheric column Q1 (shaded; W m−2) and interannual standard deviation of heating (contours; interval: 7 W m−2) in spring for the period 1979–2017. The boxes denote the domain of the eastern Tibetan Plateau region. Gray curves denote 3000-m elevation (same in other figures).

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    Anomalies of (a) snow cover (SC; %) and (b) total heating in the atmospheric column Q1 (W m−2) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2017. (c) Normalized time series of area-mean interannual snow-cover anomalies (%; bars) and interannual total heating in the atmospheric column Q1 (W m−2; green line) in the eastern Tibetan Plateau region, and area-mean interannual surface air temperature (SAT; °C; orange line) in the northern North America region in spring for the period 1979–2017. In (a) and (b) the boxes denote the domain of the eastern Tibetan Plateau region, and the stippled regions denote anomalies significant at the 95% confidence level.

  • View in gallery

    Anomalies of surface air temperature (SAT; °C) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period (a) 1979–2017, (c) 1979–2004, and (d) 2005–17 based on the CRU data. (b) Sliding correlation coefficients between the spring eastern Tibetan Plateau snow cover and the spring northern North America SAT with an 11-yr (blue line), 15-yr (orange line), and 19-yr (green line) moving window for the period 1973–2017. In (a), (c), and (d) the boxes denote the domain for the northern North America region, and the stippled regions denote anomalies significant at the 95% confidence level. The gray line in (b) denotes that the 15-yr sliding correlation coefficient significant at the 95% confidence level.

  • View in gallery

    Anomalies of air temperature (air tmp; °C) at (a) 850, (b) 400, and (c) 200 hPa in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The boxes denote the domain used to calculate the area-mean SAT anomalies. The stippled regions denote anomalies significant at the 95% confidence level.

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    Area-mean northern North Amerca (a) air temperature (air tmp; °C) and (b) geopotential height (hgt; gpm) anomalies in spring at the pressure levels from 1000 to 100 hPa obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The domains are denoted by boxes in Fig. 4. The red dots denote area-mean anomalies significant at the 95% confidence level.

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    Anomalies of (a) geopotential height (hgt; gpm) and corresponding wave activity flux (WAF; m2 s−2) at 200 hPa and (b) geopotential height (hgt; contours; interval: 3 gpm) and air temperature (air tmp; °C; shading) at 850 hPa in spring obtained by linear regression against spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The scale for the wave activity flux vector is shown at the bottom-right corner of (a). Cyan curves denote the 3000-m elevation. Gray shading in (b) indicates topography below 3000 m. The purple contours in (a) denote geopotential height anomalies significant at the 95% confidence level. The stippled regions in (b) denote air temperature anomalies significant at the 95% confidence level.

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    Difference of barotropic model geopotential height (gpm) and corresponding wave activity flux (WAF; m2 s−2) (only shown for regions north of 30°N) averaged over days (a) 11–15, (b) 21–25, and (c) 31–35 and difference of imposed idealized convergence and divergence anomaly (red contours) that is added to climatological mean divergence in spring. The scale for the wave activity flux vector is shown at the bottom-right corner of (c). Cyan curves denote the 3000-m elevation.

  • View in gallery

    Anomalies of (a) surface air temperature (SAT; °C), (b) vertical velocity (omega; Pa h−1) at 400 hPa, (c) total cloud cover (TCC; %), (d) snow cover (SC; %), (e) net shortwave radiation (SWR; W m−2), (f) sensible heat flux (SHF; W m−2), (g) net longwave radiation (LWR; W m−2), and (h) wind at 10 m (m s−1) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004 based on the NCEP–DOE reanalysis-2 data. The red contour in (h) is seasonal mean surface air temperature (SAT; °C) in spring for the period 1979–2004 based on the NCEP–DOE Reanalysis-2 data. The boxes denote the domain of the northwestern and central North America region. The scale for wind vectors is shown at the bottom-right corner of (h). The stippled regions in (a)–(g) denote anomalies significant at the 95% confidence level. The black vectors in (h) denote 10-m wind anomalies significant at the 95% confidence level.

  • View in gallery

    Anomalies of advective terms (a) υT¯/y (−VaTm; W m−2), and (b) u¯T/x (−UmTa; W m−2) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The unit of horizontal advection is converted to W m−2, assuming a mixed-layer depth of 100 m. The boxes denote the domain of the northwestern and central North America region. The stippled regions denote anomalies significant at the 95% confidence level.

  • View in gallery

    Anomalies of (a) CRU surface air temperature (SAT CRU; °C), NCEP–DOE Reanalysis-2 surface air temperature (SAT NCEP2; °C), and JRA-55 surface air temperature (SAT JRA55; °C) and (b) net shortwave radiation (SWR; W m−2), net longwave radiation (LWR; W m−2), sensible heat flux (SHF; W m−2), latent heat flux (LHF; W m−2), and advective terms υT¯/y (−VaTm); W m−2) and u¯T/x (−UmTa; W m−2) averaged over the northwestern (orange bars) and central (blue bars) North America in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The asterisks denote anomalies significant at the 95% confidence level.

  • View in gallery

    Anomalies of snow cover (%) in spring obtained by linear regression against the spring interannual eastern Tibetan Plateau snow-cover index for the period (a) 1979–2004 and (b) 2005–17. (c),(d) As in (a) and (b), but for Q1 (W m−2). The boxes denote the domain of the eastern Tibetan Plateau region. The stippled regions denote anomalies significant at the 95% confidence level.

  • View in gallery

    Anomalies of winter sea surface temperature (SST; °C) obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period (a) 1979–2004 and (b) 2005–17. The box in (a) denotes the Niño-3 region and the box in (b) denotes the Niño-3.4 region. The stippled regions denote anomalies significant at the 95% confidence level.

  • View in gallery

    Anomalies of spring surface air temperature (SAT; °C) obtained by linear regression against winter Niño-3.4 SST for the period (a) 1979–2004 and (b) 2005–17. The box denotes the domain of the northern North American region. The stippled regions denote anomalies significant at the 95% confidence level.

  • View in gallery

    (top) Anomalies of spring geopotential height (hgt; gpm) at 200 hPa obtained by linear regression against (a) the winter interannual Niño-3 SST for the period 1979–2004 and (b) the winter interannual Niño-3.4 SST for the period 2005–17. (bottom) Anomalies of spring geopotential height (hgt; gpm) at 850 hPa obtained by linear regression against (c) the winter interannual Niño-3 SST for the period 1979–2004 and (d) the neagtive interannual Niño-3.4 SST for the period 2005–17. The purple contours denote geopotential height anomalies significant at the 95% confidence level.

  • View in gallery

    Anomalies of spring surface air temperature (SAT; °C) obtained by partial regression (top) against the spring interannual eastern Tibetan Plateau snow-cover index after removing (a) the winter Niño-3 SST signal for the period 1979–2004 and (b) the winter Niño-3.4 SST signal for the period 2005–17 and (bottom) against (c) the winter Niño-3 SST for the period 1979–2004 and (d) the winter Niño-3.4 SST for the period 2005–17 after removing the spring interannual eastern Tibetan Plateau snow-cover signal. The boxes denote the domain of the northern North American region. The stippled regions denote anomalies significant at the 95% confidence level.

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Influence of Eastern Tibetan Plateau Spring Snow Cover on North American Air Temperature and Its Interdecadal Change

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  • 1 Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • | 2 School of Earth Sciences, Zhejiang University, Hangzhou, and Center for Monsoon System Research, and State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • | 3 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • | 4 Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
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Abstract

Previous studies revealed the influence of the autumn–winter Tibetan Plateau snow cover on atmospheric circulation and climate in the North American region. The present study documents the relationship between the eastern Tibetan Plateau snow cover and the North American air temperature in spring and the associated physical processes using satellite-based snow cover, reanalysis atmospheric and surface variables, observation-based surface air temperature (SAT), and sea surface temperature (SST). A stable relationship is identified between the eastern Tibetan Plateau snow cover and the North American SAT in spring before the mid-2000s. Positive snow-cover anomalies over the eastern Tibetan Plateau induce cooling in the local atmospheric column. The atmospheric cooling stimulates a large-scale atmospheric wave pattern at the upper level that extends northeastward from the eastern Tibetan Plateau via northeast Asia and the North Pacific to North America. An anomalous high forms over North America, accompanied by anomalous descent. In the northwestern part, the horizontal advection by anomalous southerly winds along the west flank of anomalous anticyclone induces SAT increase. In the central part, the enhanced surface sensible heat flux following anomalous descent-induced downward shortwave radiation increase leads to SAT increase. The relationship between the eastern Tibetan Plateau snow cover and the North American SAT is weakened after the mid-2000s. The weakened relationship is attributed to an intensified impact of tropical central Pacific SST anomalies on the North American SAT variations through a Pacific–North America-like atmospheric circulation pattern, which overcomes the influence of the Tibetan Plateau snow-cover anomalies.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Renguang Wu, renguang@zju.edu.cn

Abstract

Previous studies revealed the influence of the autumn–winter Tibetan Plateau snow cover on atmospheric circulation and climate in the North American region. The present study documents the relationship between the eastern Tibetan Plateau snow cover and the North American air temperature in spring and the associated physical processes using satellite-based snow cover, reanalysis atmospheric and surface variables, observation-based surface air temperature (SAT), and sea surface temperature (SST). A stable relationship is identified between the eastern Tibetan Plateau snow cover and the North American SAT in spring before the mid-2000s. Positive snow-cover anomalies over the eastern Tibetan Plateau induce cooling in the local atmospheric column. The atmospheric cooling stimulates a large-scale atmospheric wave pattern at the upper level that extends northeastward from the eastern Tibetan Plateau via northeast Asia and the North Pacific to North America. An anomalous high forms over North America, accompanied by anomalous descent. In the northwestern part, the horizontal advection by anomalous southerly winds along the west flank of anomalous anticyclone induces SAT increase. In the central part, the enhanced surface sensible heat flux following anomalous descent-induced downward shortwave radiation increase leads to SAT increase. The relationship between the eastern Tibetan Plateau snow cover and the North American SAT is weakened after the mid-2000s. The weakened relationship is attributed to an intensified impact of tropical central Pacific SST anomalies on the North American SAT variations through a Pacific–North America-like atmospheric circulation pattern, which overcomes the influence of the Tibetan Plateau snow-cover anomalies.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Renguang Wu, renguang@zju.edu.cn

1. Introduction

Snow affects the surface energy budget and hydrological cycle and modulates weather and climate (Barnett et al. 1989; Cohen and Rind 1991; Yasunari et al. 1991). The large-scale snow cover over Eurasia and North America has an important effect on local and global climate through modulating surface and atmospheric column heating and atmospheric circulation (Barnett et al. 1988; Wu et al. 2014; Orsolini et al. 2016; Wu and Chen 2016; Henderson et al. 2018; Luo and Wang 2019). The Tibetan Plateau has an average elevation over 4000 m and is covered by a large area of snow. With the rapid warming in the past few decades (Wang et al. 2008; Duan and Xiao 2015), the snow cover over the Tibetan Plateau has experienced low-frequency variations, with an annual mean decrease in the whole area but an increase in the eastern part in spring (Wang et al. 2018; Xu et al. 2017).

The influence of snow cover over the Tibetan Plateau on climate variability in the surrounding areas, especially the Asian monsoon region, has been investigated by many studies (Dey and Bhanu Kumar 1982; Liu and Yanai 2002; Zhang et al. 2004; Wu and Kirtman 2007; Zhao et al. 2007; Wu et al. 2010, 2012; Zhu et al. 2015; Senan et al. 2016; Xiao and Duan 2016; Wang et al. 2017; Yuan et al. 2019). Wang et al. (2019) showed that the snow-cover anomalies over the central-eastern Tibetan Plateau form mainly in autumn and persist to the succeeding spring, but the effect of snow-cover anomalies on local atmospheric thermal state increases from autumn to spring. However, few analyses have been conducted on the impact of the Tibetan Plateau snow-cover anomalies on climate in remote regions. Lin and Wu (2011) indicated that autumn snow-cover anomalies over the Tibetan Plateau can induce the North American surface air temperature variation through atmospheric circulation changes. Liu et al. (2017) revealed that autumn-winter snow anomalies over the Tibetan Plateau induce a Pacific–North America-like atmospheric circulation response. Qian et al. (2019) detected that the impact of autumn Tibetan Plateau snow-cover anomalies on winter North American temperature variation experienced a weakening in the mid-1990s. The present study presents evidence for the influence of spring snow-cover anomalies over the Tibetan Plateau on the North American air temperature variation and its interdecadal change. We investigate the associated processes of the above influence and the plausible reason of the interdecadal change in the influence.

The rest of the paper is organized as follows. The data and methods are described in section 2. The relationship between the Tibetan Plateau snow cover and North American air temperature variations is presented in section 3. In section 4, we show the atmospheric circulation pattern that links the Tibetan Plateau snow cover and the North American climate. The processes for the North American air temperature variations are analyzed in section 5. In section 6, we present the role of the tropical central Pacific sea surface temperature (SST) anomalies in the weakening of the connection between the Tibetan Plateau snow cover and North American surface air temperature variation after the mid-2000s. The summary and discussions are presented in section 7.

2. Data and methods

We used the weekly Northern Hemisphere snow-cover, version 4, data (Brodzik and Armstrong 2013). The data were obtained from the National Snow and Ice Data Center (NSIDC) (https://nsidc.org/data/NSIDC-0046/versions/4). The original Equal-Area Scalable Earth Grid (EASE-Grid) snow-cover fraction data has a 25-km spatial resolution and is available from October 1966 to December 2017. We converted weekly snow cover to monthly mean on regular 1° × 1° grids.

The present study utilized monthly output of the National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis-2 (Kanamitsu et al. 2002) from 1979 to 2017. The variables include surface air temperature (SAT) at 2 m, winds at 10 m, latent heat flux, sensible heat flux, upward and downward shortwave radiation, upward and downward longwave radiation, total cloud cover, precipitation rate, air temperature and winds at pressure levels, and geopotential heights and vertical velocity at pressure levels. The convention for latent and sensible heat fluxes is positive for upward flux. We also used the JRA-55 (Kobayashi et al. 2015) and ERA-Interim (Dee et al. 2011) surface and pressure level variables from 1979 to 2017 to verify the results obtained from the NCEP–DOE Reanalysis-2. Monthly CRU v4.02 (Harris et al. 2014) SAT was also utilized in the present study. Monthly centennial in situ observation-based estimates of the variability of sea surface temperature (COBE-SST) (Ishii et al. 2005) were used in this study.

This study focused on the interannual relationship between snow cover over the Tibetan Plateau and atmospheric variables in spring [March–May (MAM)]. The interannual variations were obtained by a 9-yr high-pass Gaussian filter. Linear regression analysis, correlation analysis, and sliding correlation analysis were used in the present study to depict the relationships of interannual variations between the Tibetan Plateau snow cover and other variables in spring. The statistical significance of correlation and regression was estimated based on the Student’s t test.

3. Relationship between the Tibetan Plateau snow cover and North American air temperature

In this section, we present evidence for the relationship between the Tibetan Plateau snow cover and North American SAT variations in spring. Before that, we first identify the key region of the Tibetan Plateau spring snow-cover variations. Then, we analyze the influence of the Tibetan Plateau snow-cover anomalies on local atmospheric heat source. These provide a basis for understanding the impacts of the Tibetan Plateau snow-cover anomalies on climate in remote regions.

The climatological mean spring snow cover over the Tibetan Plateau has two large value regions. One is located in the western Plateau and the other lies in the southeastern part of the Plateau (Fig. 1a, shading). The mean values exceed 80% and 50%, respectively, in the above two regions. The mean snow coverage is much larger in the western part than in the eastern part. However, the standard deviation of snow cover is somewhat larger in the eastern part (Fig. 1a, contour). The standard deviation reaches over 15% in a large area of the eastern part, consistent with the large loading region of the leading mode of spring interannual snow-cover variations (Wang et al. 2019). In the western part, the standard deviation is large in the northeastern side of large mean snow-cover region, but relatively small in the large mean snow-cover region. The above regional discrepancy is due to that snowfall or snowmelt has little impact on snow cover in thick snow-covered region (Wu and Chen 2016).

Fig. 1.
Fig. 1.

Distribution of (a) mean snow cover (SC; shaded; %) and interannual standard deviation of snow cover (contours; interval: 3%) and (b) mean total heating in the atmospheric column Q1 (shaded; W m−2) and interannual standard deviation of heating (contours; interval: 7 W m−2) in spring for the period 1979–2017. The boxes denote the domain of the eastern Tibetan Plateau region. Gray curves denote 3000-m elevation (same in other figures).

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

Snow can affect local thermal state through modulating the surface energy budget. To illustrate the influence of snow cover on atmospheric thermal condition, we calculated total atmospheric column heat source Q1 following Zhao and Chen’s (2001) method based on the NCEP–DOE Reanalysis-2 data. We also verified Q1 using the JRA-55 data. The distributions of obtained seasonal mean Q1 are similar to the results of Yanai et al. (1992). The seasonal mean Q1 is positive in most of the Plateau except for the edge along the western and southwestern part (Fig. 1b, shading). The cooling or weak heating regions coincide with large snow-cover regions. This implies an effect of snow cover on seasonal mean thermal state over the Plateau. The standard deviation of interannual variation of Q1 has large values in western, southern, and southeastern part of the Plateau (Fig. 1b, contour). The largest standard deviation of Q1 is located in the southeastern part with the value above 60 W m−2.

From the above analyses, the eastern part of the Tibetan Plateau is a key region for impact of snow cover on local atmosphere and also likely on climate in remote regions. So, we use area-mean snow-cover anomalies over the eastern Plateau (the domain denoted by the box in Fig. 1) as an index to analyze the influence of spring snow-cover anomalies over the eastern Plateau on local atmospheric state and climate variability in remote regions. The area-mean anomalies are normalized by dividing the anomalies with the standard deviation. The normalized time series of interannual variation of area-mean snow cover in the above region is presented in Fig. 2c (bars).

Fig. 2.
Fig. 2.

Anomalies of (a) snow cover (SC; %) and (b) total heating in the atmospheric column Q1 (W m−2) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2017. (c) Normalized time series of area-mean interannual snow-cover anomalies (%; bars) and interannual total heating in the atmospheric column Q1 (W m−2; green line) in the eastern Tibetan Plateau region, and area-mean interannual surface air temperature (SAT; °C; orange line) in the northern North America region in spring for the period 1979–2017. In (a) and (b) the boxes denote the domain of the eastern Tibetan Plateau region, and the stippled regions denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

To validate the representativeness of the snow-cover index for the eastern Tibetan Plateau snow-cover variations and the impact of eastern Plateau snow-cover anomalies on Q1 changes, we regressed the grid snow cover and Q1 anomalies against the snow-cover index. Corresponding to a positive snow-cover index, positive snow-cover anomalies are distributed in the eastern Plateau (Fig. 2a). The distribution is similar to that of mean and standard deviation in the Plateau (Fig. 1a). There are large negative Q1 anomalies over the eastern Plateau (Fig. 2b). Further, we calculated area-mean Q1 in the eastern Plateau based on average in the same domain as the snow-cover index. The time series of area-mean Q1 (Fig. 2c, green line) and snow-cover anomalies are opposite in most of the years during 1979–2017. The correlation coefficient between them is about −0.63 for the above period, significant at the 99% confidence level. This confirms the cooling effect of spring snow-cover anomalies on local atmospheric column in the eastern Plateau.

Now, we analyze the relationship between the eastern Plateau snow cover and the North American SAT variations in spring. Corresponding to more snow cover in the eastern Plateau, positive SAT anomalies are observed in most areas and weak negative anomalies in the southwestern part of North America (Fig. 3a). More obvious SAT anomalies are located in northwest and central parts. This pattern is very similar to the first leading mode of spring interannual SAT variations over North America that accounts for a percentage variance of about 39.9% (figure not shown). To quantify the relationship, we calculated area-mean SAT anomalies in the domain denoted by the box in Fig. 3a as an index. The correlation coefficient between the eastern Plateau snow-cover index and the North America SAT index is about 0.32 for the period 1979–2017, significant at the 95% confidence level. Further analysis reveals that the relationship between the Plateau snow cover and North America SAT variations is not stationary. This is illustrated by a sliding correlation analysis between the two indices (Fig. 3b). Here, we extended the data period backward from 1979 to 1973. For the three moving windows, the correlation coefficient remained large positive in most years before the early 2000s, but it weakened dramatically around early 2000s and even dropped to negative after the end of 2000s (Fig. 3b, orange and blue lines). The weakening of correlation is also detected using original anomalies though slightly less obvious. The above analyses imply that the positive relationship between the Plateau snow cover and North American SAT variations is only up to early 2000s. Thus, we focused on the time period 1979–2004 to investigate the connection between the Plateau snow cover and North American SAT variations in the following analysis.

Fig. 3.
Fig. 3.

Anomalies of surface air temperature (SAT; °C) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period (a) 1979–2017, (c) 1979–2004, and (d) 2005–17 based on the CRU data. (b) Sliding correlation coefficients between the spring eastern Tibetan Plateau snow cover and the spring northern North America SAT with an 11-yr (blue line), 15-yr (orange line), and 19-yr (green line) moving window for the period 1973–2017. In (a), (c), and (d) the boxes denote the domain for the northern North America region, and the stippled regions denote anomalies significant at the 95% confidence level. The gray line in (b) denotes that the 15-yr sliding correlation coefficient significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

For the period 1979–2004, the correlation coefficient between the two indices reaches about 0.55, which is significant at the 99% confidence level. Corresponding to more snow cover in the eastern Plateau, the distribution of SAT anomalies over North America is similar to that from 1979 to 2017 (Figs. 3a,c). In comparison, the SAT anomalies are larger and more significant. The SAT anomalies in the northwestern and eastern parts of North America are significant at the 95% confidence level, and are higher than 1°C in part of the northwestern region (Fig. 3c).

The above analysis shows that more snow cover in the eastern Tibetan Plateau is accompanied by higher SAT over North America. What about air temperature variations in the atmospheric column there? To answer this question, we regressed the North America air temperature at 850, 400, and 200 hPa against the snow-cover index. The above levels represent the lower, middle, and upper troposphere, respectively. Corresponding to more snow cover in the eastern Tibetan Plateau, positive air temperature anomalies are observed over the northern part of North America at 850 hPa (Fig. 4a) with the spatial distribution similar to that of the SAT anomalies (Figs. 4a, 3b). At 400 hPa, air temperature anomalies become smaller in the eastern North America (Fig. 4b). At 200 hPa, temperature anomalies are nearly opposite to those at the lower levels with larger negative anomalies north of 40°N (Fig. 4c).

Fig. 4.
Fig. 4.

Anomalies of air temperature (air tmp; °C) at (a) 850, (b) 400, and (c) 200 hPa in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The boxes denote the domain used to calculate the area-mean SAT anomalies. The stippled regions denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

To show more clearly the vertical change of air temperature anomalies over North America, we calculated area-mean air temperature anomalies at the pressure levels from 1000 to 100 hPa based on the average over the domain denoted by the box in Fig. 4 where large anomalies are detected. Significant positive air temperature anomalies extend from the surface to 400 hPa (Fig. 5a). The area-mean anomalies are above 0.6°C below 700 hPa, significant at the 95% confidence level. The temperature anomalies change from positive to negative around 300 hPa and achieve the largest negative value at 200 hPa.

Fig. 5.
Fig. 5.

Area-mean northern North Amerca (a) air temperature (air tmp; °C) and (b) geopotential height (hgt; gpm) anomalies in spring at the pressure levels from 1000 to 100 hPa obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The domains are denoted by boxes in Fig. 4. The red dots denote area-mean anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

4. The role of atmospheric circulation pattern during 1979–2004

The previous section shows a good relationship between the eastern Tibetan Plateau snow cover and North American air temperature variations in spring during 1979–2004. In this section, we analyze atmospheric circulation anomalies associated with the eastern Tibetan Plateau snow-cover anomalies and illustrate their role in connecting the Tibetan Plateau snow cover and North American air temperature variations. We conduct numerical experiments to verify the effect of the Tibetan Plateau snow in generating the atmospheric circulation pattern.

Corresponding to more snow cover in the eastern Tibetan Plateau, geopotential height anomalies display a large-scale wave pattern over the eastern Tibetan Plateau through East Asia and the northern North Pacific to North America at 200 hPa (Fig. 6a). The geopotential height anomalies are significant over the North Pacific and North America though insignificant over East Asia. We calculated the wave activity fluxes (Plumb 1985) based on regressed geopotential height anomalies at 200 hPa. The wave activity fluxes extend northeastward from the Tibetan Plateau to East Asia. After that, two branches can be observed. One branch continues to go northeastward to northern North Pacific and northwestern North America. The other branch goes southeastward to subtropical western North Pacific, turns eastward to eastern North Pacific, and then goes northward to western North America. The northern wave train is more relevant to the northern North American SAT variations. The wave activity fluxes display divergence over the southeastern Tibetan Plateau and weaken after reaching the northern part of North America. This indicates that the above regions are the source and sink of wave activity, respectively. It implies that the atmospheric wave pattern is stimulated by anomalous atmospheric cooling induced by more snow cover over the eastern Tibetan Plateau.

Fig. 6.
Fig. 6.

Anomalies of (a) geopotential height (hgt; gpm) and corresponding wave activity flux (WAF; m2 s−2) at 200 hPa and (b) geopotential height (hgt; contours; interval: 3 gpm) and air temperature (air tmp; °C; shading) at 850 hPa in spring obtained by linear regression against spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The scale for the wave activity flux vector is shown at the bottom-right corner of (a). Cyan curves denote the 3000-m elevation. Gray shading in (b) indicates topography below 3000 m. The purple contours in (a) denote geopotential height anomalies significant at the 95% confidence level. The stippled regions in (b) denote air temperature anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

At 850 hPa, corresponding to more snow cover in the eastern Tibetan Plateau, positive and negative geopotential height anomalies are observed over northern North America and the northern North Pacific, respectively (Fig. 6b, blue contour). This suggests a quasi-barotropic vertical structure of atmospheric circulation change in the above regions. To confirm this, we calculated area-mean geopotential height anomalies at the pressure levels from 1000 to 100 hPa in the domain denoted by the box in Fig. 6a. The result shows that positive geopotential height anomalies increase upward from 850 hPa and reach the maximum at 300 hPa (Fig. 5b). Most significant anomalies extend from 600 to 200 hPa. The area-mean geopotential height anomalies are negative below 900 hPa (Fig. 5b). Comparing Figs. 5a and 5b, the vertical changes of geopotential height and air temperature anomalies follow the hydrostatic equilibrium relationship. The air temperature anomalies at 850 hPa display an alternative negative, positive, negative, and positive distribution from the Tibetan Plateau to North America (Fig. 6b, shading), consistent with the geopotential height anomalies at the upper troposphere (Fig. 6a).

To verify the generation of the above wave pattern by an anomalous atmospheric thermal state associated with the snow-cover anomalies over the eastern Tibetan Plateau, we performed numerical experiments with a barotropic model (Sardeshmukh and Hoskins 1988). Two experiments have been conducted. In experiment 1, the model is driven by climatological mean spring divergence plus a convergence anomaly added in the southeastern Tibetan Plateau. In experiment 2, the model is forced by climatological mean spring divergence plus a divergence anomaly with the same magnitude and distribution. The maximum intensity of prescribed convergence anomaly is 7 × 10−6 s−1 with a center at 32°N, 90°E (Fig. 6c). We have chosen the location of the divergence anomaly based on the snow-cover and Q1 anomalies (Figs. 2a,b). In the two experiments, the model is integrated for 40 days. We show the difference of geopotential heights between the two experiments averaged over the three 5-day time slots: 11–15, 21–25, and 31–35 days (Fig. 7). The height response extends northeastward to the Russian Far East (Fig. 7a) and then southeastward to North America (Figs. 7b,c). The model response in days 31–35 features an obvious wave train with alternative negative and positive geopotential heights anomalies from the Tibetan Plateau through Lake Baikal in Far East Russia to northwestern North America (Fig. 7c). Compared to the observations, the height anomalies in the middle part of the wave train are located northwestward (Figs. 6a, 7c). The discrepancy may be due to the effect of other forcing that may exist in various regions. The above model results provide a support for the impact of the Tibetan Plateau forcing on the observed atmospheric wave pattern.

Fig. 7.
Fig. 7.

Difference of barotropic model geopotential height (gpm) and corresponding wave activity flux (WAF; m2 s−2) (only shown for regions north of 30°N) averaged over days (a) 11–15, (b) 21–25, and (c) 31–35 and difference of imposed idealized convergence and divergence anomaly (red contours) that is added to climatological mean divergence in spring. The scale for the wave activity flux vector is shown at the bottom-right corner of (c). Cyan curves denote the 3000-m elevation.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

5. Formation of North American air temperature anomalies

The large-scale atmospheric circulation pattern discussed in the previous section serves as a connection from the Tibetan Plateau snow cover to atmospheric circulation anomalies over North America. In turn, the latter may lead to changes in air temperature variations over North America. In this section, we investigate the specific processes to cause SAT anomalies over North America in spring.

For comparison, we show the NCEP–DOE Reanalysis-2 SAT anomalies. Corresponding to more snow cover over the eastern Tibetan Plateau in spring, obvious positive SAT anomalies are observed in northwestern and central North America (the blue boxes in Fig. 8a). The distribution is very similar to that of the SAT anomalies obtained from the CRU data (Fig. 3b). This confirms the influence of the eastern Tibetan Plateau snow-cover anomalies on the North American air temperature variation.

Fig. 8.
Fig. 8.

Anomalies of (a) surface air temperature (SAT; °C), (b) vertical velocity (omega; Pa h−1) at 400 hPa, (c) total cloud cover (TCC; %), (d) snow cover (SC; %), (e) net shortwave radiation (SWR; W m−2), (f) sensible heat flux (SHF; W m−2), (g) net longwave radiation (LWR; W m−2), and (h) wind at 10 m (m s−1) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004 based on the NCEP–DOE reanalysis-2 data. The red contour in (h) is seasonal mean surface air temperature (SAT; °C) in spring for the period 1979–2004 based on the NCEP–DOE Reanalysis-2 data. The boxes denote the domain of the northwestern and central North America region. The scale for wind vectors is shown at the bottom-right corner of (h). The stippled regions in (a)–(g) denote anomalies significant at the 95% confidence level. The black vectors in (h) denote 10-m wind anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

To understand the formation of SAT anomalies, we examined relevant quantities, including vertical motion, cloud, snow cover, surface shortwave radiation, surface longwave radiation, sensible and latent heat fluxes, and wind at 10 m over North America in spring obtained by regression against the Tibetan Plateau snow-cover index. Here, we note that latent heat flux anomalies are relatively small compared to sensible heat flux anomalies. Surface shortwave radiation serves to alter the land surface temperature that in turn affects the SAT by modulating sensible heat flux. The vertical motion may affect cloud amount that modulates downward shortwave and longwave radiation. The snow-cover anomalies may affect the absorption of shortwave radiation by the land surface. In addition, anomalous atmospheric advection may affect SAT variations.

Anomalous descent is observed in major regions of SAT increase over North America (Figs. 8a,b). Correspondingly, cloud amount is reduced in central and northwestern North America (Fig. 8c). The downward shortwave radiation anomalies are positive over central North America (figure not shown) due to cloud decrease. The upward shortwave radiation anomalies are negative over central and northwestern North America (figure not shown), which is associated with a decrease of surface albedo due to reduced snow cover (Fig. 8d). The correlation coefficients between snow cover and upward shortwave radiation in the northwestern and central North America are about −0.49 and −0.89, respectively, for the period 1979–2004, both significant at the 99% confidence level. The larger correlation in the central part than in the northwestern part is related to the difference in snow albedo effect. The mean snow is thick in the northwestern part, leading to smaller snow-cover anomalies and thus less snow albedo effect. Consequently, surface net shortwave radiation has larger positive anomalies in the central part than in the northwestern part (Fig. 8e). Surface net longwave radiation anomalies are negative with their magnitude smaller than surface net shortwave radiation anomalies, in particular in the central part (Figs. 8e,g). Increased shortwave radiation warms up the land surface that in turn enhances upward sensible heat flux in the central part (Fig. 8f), which contributes to the SAT increase there (Fig. 8a).

The decreased snow cover over central North America may be caused by surface warming. This suggests a positive feedback involved in surface heat flux, surface temperature and snow-cover variations over central North America. Specifically, increased downward shortwave radiation warms up the land surface. The warmer surface decreases the snow cover, leading to a decrease in surface albedo. In turn, upward shortwave radiation decreases. The surface absorbs more shortwave radiation and warms up the land and surface air.

In the northwestern part, surface net shortwave radiation anomalies are relatively small (Fig. 8e) and surface sensible heat flux anomalies are negative (Fig. 8f). Surface net longwave radiations anomalies are negative as well (Fig. 8g). Thus, positive SAT anomalies cannot be explained by surface heat flux changes in this region. How do we explain the SAT increase in this region? We note that there are large anomalous southerly winds in this region (Fig. 8h). As the mean temperature decreases northward in the lower troposphere, anomalous southerly winds can transport warmer air from lower latitudes and thus contribute to the SAT increase.

To confirm the contribution of horizontal advection to the SAT variation over North America, we calculated the four terms of horizontal advection −V ⋅ ∇T as uT¯/xυT¯/yu¯T/xυ¯T/y, where V is the surface wind, ∇T is the horizontal gradient of SAT, u¯ and υ¯ are the mean zonal and meridional wind, T¯ is the mean SAT, u′ and υ′ are the zonal and meridional wind anomalies, and T′ is the SAT anomaly. The terms υT¯/y and u¯T/x have positive values in the northwestern part of North America (Fig. 9). The other two terms are small. The result indicates that the advection of the mean temperature gradient by anomalous meridional wind and the advection of the anomalous temperature gradient by mean zonal wind have positive contributions to the SAT increase in this region. In contrast, the contribution of horizontal advection terms is small in central North America.

Fig. 9.
Fig. 9.

Anomalies of advective terms (a) υT¯/y (−VaTm; W m−2), and (b) u¯T/x (−UmTa; W m−2) in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The unit of horizontal advection is converted to W m−2, assuming a mixed-layer depth of 100 m. The boxes denote the domain of the northwestern and central North America region. The stippled regions denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

To quantify the contribution of surface heat fluxes and horizontal advection to the SAT anomalies in the northwestern and central North America (the domains denoted by the boxes in Fig. 8), we calculated area-mean SAT anomalies based on CRU, NCEP–DOE Reanalysis-2, and JRA-55, and anomalies of surface net shortwave and longwave radiations, sensible and latent heat fluxes and the four terms of horizontal advection anomalies in northwestern and central regions. Corresponding to more snow cover over the eastern Tibetan Plateau, positive SAT anomalies are 0.71° and 0.43°C, respectively, in the northwestern and central parts based on the CRU data (Fig. 10a). The SAT anomalies are somewhat smaller based on the NCEP–DOE Reanalysis-2 and larger based on JRA-55 compared to those based on the CRU data. Surface net shortwave radiation anomalies are about 0.47 W m−2 in the northwestern part and about 2.63 W m−2 in the central part (Fig. 10b). Sensible heat flux anomalies are about −1.89 and 2.32 W m−2, respectively, in the northwestern and central regions. Surface net longwave radiation anomalies are weak positive in the northwestern part and negative in the central part (about −0.78 W m−2). Latent heat flux anomalies are small negative in both regions. The horizontal advection terms of υT¯/y and u¯T/x are positive in the northwestern region (0.68 and 1.06 W m−2), but small in the central region (Fig. 10b). Thus, it appears that horizontal advection terms contribute to SAT increase and sensible heat flux has a damping effect in the northwestern part.

Fig. 10.
Fig. 10.

Anomalies of (a) CRU surface air temperature (SAT CRU; °C), NCEP–DOE Reanalysis-2 surface air temperature (SAT NCEP2; °C), and JRA-55 surface air temperature (SAT JRA55; °C) and (b) net shortwave radiation (SWR; W m−2), net longwave radiation (LWR; W m−2), sensible heat flux (SHF; W m−2), latent heat flux (LHF; W m−2), and advective terms υT¯/y (−VaTm); W m−2) and u¯T/x (−UmTa; W m−2) averaged over the northwestern (orange bars) and central (blue bars) North America in spring obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period 1979–2004. The asterisks denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

Large negative air temperature anomalies are present at 200 hPa over northwest North America, which is opposite to the patterns in the lower and middle troposphere (Figs. 4 and 5). This difference is due to the reversal of climatological meridional temperature gradient from the lower–middle troposphere to the upper troposphere. The climatological temperature decreases northward at the lower–middle troposphere, whereas the climatological temperature at 200-hPa increases from the mid- to higher latitudes over the North Pacific through North America (figure not shown). As such, anomalous southerly winds over northwest North America bring lower temperatures from lower latitudes, leading to a temperature decrease in the northwest North American region at 200 hPa.

6. The role of tropical central Pacific SST during 2005–17

The relationship between the eastern Tibetan Plateau snow cover and North American SAT variations experienced a pronounced change around 2004 (Fig. 3). Corresponding to more snow cover over the eastern Tibetan Plateau, there are weak negative SAT anomalies in the northwestern part and positive SAT anomalies in the southeastern part of North America during 2005–17 (Fig. 3d). In this section, we investigate the plausible reasons for the change in the above relationship.

Is the weakened influence of the Tibetan Plateau snow-cover anomalies on the North American SAT variation related to a change in the mean state or interannual variability of snow cover over the eastern Plateau after the mid-2000s in spring? To answer this question, we compared the seasonal mean and the interannual standard deviation of the eastern Tibetan Plateau snow cover in the periods 1979–2004 and 2005–17. The results show that the mean snow cover in spring has no obvious decrease during the period 2005–17 and the difference of the interannual standard deviation between the two time periods is small (figures not shown). This implies that the mean and variance of the eastern Tibetan Plateau snow cover are not the factors that caused the observed change in the relationship between the eastern Tibetan Plateau snow cover and North American SAT variations.

We further compare the snow cover and atmospheric column heating anomalies obtained by regression against the snow-cover index between 1979–2004 and 2005–17. The snow-cover anomalies over eastern Tibetan Plateau do not show obvious differences between the two periods (Figs. 11a,b), nor do the Q1 anomalies (Figs. 11c,d). The area-mean snow-cover anomalies over the eastern Plateau (the boxed region in Fig. 11) are 6.73% and 6.54%, respectively, during 1979–2004 and 2005–17. The area-mean Q1 anomalies are 22.55 and 22.11 W m−2, respectively, during the two periods.

Fig. 11.
Fig. 11.

Anomalies of snow cover (%) in spring obtained by linear regression against the spring interannual eastern Tibetan Plateau snow-cover index for the period (a) 1979–2004 and (b) 2005–17. (c),(d) As in (a) and (b), but for Q1 (W m−2). The boxes denote the domain of the eastern Tibetan Plateau region. The stippled regions denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

Previous studies have shown the impact of tropical Pacific SST anomalies on climate over North America (Trenberth et al. 1998). Does the tropical Pacific SST play a role in the change in the Tibetan Plateau snow cover–North American SAT relationship around the mid-2000s? To examine this possibility, we regressed winter [December–February (DJF)] SST anomalies against the snow-cover index for the period 1979–2004 and 2005–17 separately. Here, we use DJF SST anomalies because tropical Pacific SST variations are dominated by El Niño–Southern Oscillation (ENSO) that reaches the mature phase in boreal winter. The spring SST anomalies display similar features but with smaller magnitudes (not shown). During 1979–2004, positive SST anomalies are identified in the tropical eastern Pacific (Fig. 12a). During 2005–17, obvious negative SST anomalies are observed in the tropical central Pacific (Fig. 12b). In comparison, the area and magnitude of the SST anomalies are larger during the period 2005–17 than during the period 1979–2004 in addition to the opposite sign. This suggests a change in the connection between the eastern Tibetan Plateau snow cover and the tropical Pacific SST variations around the mid-2000s. This implies a role of the tropical Pacific SST anomalies in the change in the relationship between the Tibetan Plateau snow cover and North American SAT variations.

Fig. 12.
Fig. 12.

Anomalies of winter sea surface temperature (SST; °C) obtained by linear regression against the spring interannual snow-cover index in the eastern Tibetan Plateau region for the period (a) 1979–2004 and (b) 2005–17. The box in (a) denotes the Niño-3 region and the box in (b) denotes the Niño-3.4 region. The stippled regions denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

We use area-mean Niño-3.4 (5°S–5°N, 170°–120°W) SST anomalies as an index to examine the tropical Pacific SST influence on the North American SAT variation. Corresponding to positive Niño-3.4 SST anomalies, weak positive SAT anomalies appear in the northwestern part and negative anomalies in the southern part of North America during the period 1979–2004 (Fig. 13a). In contrast, large positive SAT anomalies are observed in the northern North America during the period 2005–17 (Fig. 13b). This SAT anomaly pattern is similar to the distribution of SAT anomalies corresponding to more snow cover in the eastern Tibetan Plateau during the period 1979–2004 (Fig. 3c). We also examined the SST anomalies corresponding to area-mean northern North American SAT anomalies in spring. Large and significant positive SST anomalies are detected in the equatorial central Pacific region for the period 2005–17. These analyses illustrate that the North American SAT variation is largely influenced by the tropical central Pacific SST anomalies after the mid-2000s. This tropical central Pacific SST impact overcomes the impact of the eastern Tibetan Plateau snow-cover anomalies, leading to a weakened relationship between the Tibetan Plateau snow cover and North American SAT variations after the mid-2000s.

Fig. 13.
Fig. 13.

Anomalies of spring surface air temperature (SAT; °C) obtained by linear regression against winter Niño-3.4 SST for the period (a) 1979–2004 and (b) 2005–17. The box denotes the domain of the northern North American region. The stippled regions denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

The tropical Pacific SST influence on the North American climate is through atmospheric circulation change over the North Pacific through North America (Horel and Wallace 1981; Trenberth et al. 1998). For verification, we regressed the geopotential height anomalies against the Niño-3.4 SST index for the period 2005–17. Corresponding to the positive Niño-3.4 SST index, an obvious geopotential height anomaly pattern is observed over the tropical Pacific through North America at 200 hPa, with positive anomalies over the tropical North Pacific, negative anomalies over the northern Pacific, and positive anomalies over North America (Fig. 14b). Weak positive anomalies over North America are also observed at 850 hPa (Fig. 14d), indicative of a barotropic vertical structure. A very similar distribution of geopotential height anomalies over the North Pacific through North America is obtained in the regression against area-mean northern North American SAT anomalies in spring (not shown). The pattern is also very similar to the Pacific–North America pattern (Horel and Wallace 1981; Trenberth et al. 1998). The associated anomalous descent over northern North America favors the SAT increase by allowing more shortwave radiation reaching the surface and anomalous southerly winds over northwestern North America contribute to the SAT increase by advection of warmer air from lower latitudes.

Fig. 14.
Fig. 14.

(top) Anomalies of spring geopotential height (hgt; gpm) at 200 hPa obtained by linear regression against (a) the winter interannual Niño-3 SST for the period 1979–2004 and (b) the winter interannual Niño-3.4 SST for the period 2005–17. (bottom) Anomalies of spring geopotential height (hgt; gpm) at 850 hPa obtained by linear regression against (c) the winter interannual Niño-3 SST for the period 1979–2004 and (d) the neagtive interannual Niño-3.4 SST for the period 2005–17. The purple contours denote geopotential height anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

The distribution of 200-hPa geopotential height anomalies associated with tropical Pacific SST anomalies during 2005–17 (Fig. 14b) appears similar to that associated with the Tibetan Plateau snow-cover anomalies during 1979–2004 (Fig. 6a). This appears to suggest a possibility that both the Tibetan Plateau snow cover and North American SAT anomalies are induced by tropical Pacific SST anomalies. To examine whether the Tibetan Plateau snow-cover anomalies can influence the North American SAT variations after the mid-2000s, we conduct a partial regression analysis. After removing the Niño-3.4 SST signal, there is a positive relationship between the eastern Tibetan Plateau snow cover and northern North American SAT variations (Fig. 15b). After removing the Tibetan Plateau snow-cover signal, a positive correlation exists between Niño-3.4 SST and North American SAT anomalies (Fig. 15d), which is larger than that of Tibetan Plateau snow cover (Fig. 15b). These results indicate that the eastern Tibetan Plateau snow-cover anomalies have an independent influence on the North American SAT variations though their impact is smaller than those of the tropical Pacific SST anomalies during 2005–17.

Fig. 15.
Fig. 15.

Anomalies of spring surface air temperature (SAT; °C) obtained by partial regression (top) against the spring interannual eastern Tibetan Plateau snow-cover index after removing (a) the winter Niño-3 SST signal for the period 1979–2004 and (b) the winter Niño-3.4 SST signal for the period 2005–17 and (bottom) against (c) the winter Niño-3 SST for the period 1979–2004 and (d) the winter Niño-3.4 SST for the period 2005–17 after removing the spring interannual eastern Tibetan Plateau snow-cover signal. The boxes denote the domain of the northern North American region. The stippled regions denote anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 12; 10.1175/JCLI-D-19-0455.1

As noted above, the spring eastern Tibetan Plateau has a positive correlation with SST in the tropical eastern Pacific during 1979–2004 (Fig. 12a). This suggests an influence of the tropical Pacific SST on the relationship between the Tibetan Plateau snow cover and North American SAT variations before the mid-2000s. Here, we use the area-mean Niño-3 (5°S–5°N, 150°–90°W) SST anomalies as an index to analyze whether this is the case. Corresponding to the Niño-3 SST index, spring geopotential height anomalies over North America are much weaker at both 200 and 850 hPa (Figs. 14a,c) compared to those during 2005–17 (Figs. 14b,d). The spring SAT anomalies associated with the winter Niño-3 SST index are small over North America after removing the spring Tibetan Plateau snow signal (Fig. 15c). In contrast, the spring SAT anomalies associated with the spring Tibetan Plateau snow cover remains large positive after removing the winter Niño-3 SST signal (Fig. 15a). We also performed a partial regression analysis of geopotential height with the winter Niño-3 SST index. The wave pattern does not show obvious change after the Niño-3 SST signal is excluded (figure not shown). This indicates that the influence of the eastern Tibetan Plateau snow-cover anomalies on the North American SAT variations is mostly independent of the eastern equatorial Pacific SST anomalies during 1979–2004.

7. Summary and discussion

The impact of spring Tibetan Plateau snow-cover anomalies on eastern and southern Asia climate has been investigated in many previous studies. However, few studies were focused on the influence of spring Tibetan Plateau snow on climate in remote regions. In this study, we revealed an obvious relationship between spring eastern Tibetan Plateau snow cover and North American surface air temperature variations. We investigated the physical processes of the connection from the Tibetan Plateau snow cover to surface air temperature over North America.

The snow cover and Q1 have large interannual standard deviations over the eastern Plateau in spring. The snow-cover anomalies over the eastern Tibetan Plateau in spring have a significant cooling effect on local atmospheric column. The anomalous atmospheric cooling induces an atmospheric circulation pattern at the upper level with alternating negative and positive height anomalies extending from the eastern Tibetan Plateau to North America. The atmospheric wave pattern serves as a linkage between the Tibetan Plateau snow cover and North American temperature variations. The role of the Tibetan Plateau snow-cover anomalies in exciting the atmospheric wave pattern was confirmed by numerical experiments with a barotropic model.

The atmospheric circulation pattern induces an anomalous high and anomalous descent over North America, which corresponds to more snow cover over the eastern Tibetan Plateau. This is accompanied by warming over North America in the atmospheric column under 300 hPa. The formation of SAT anomalies in northwestern and central North America is attributed to different processes. In central North America, the SAT increase is mainly due to surface heat fluxes. Anomalous descent reduces the cloud cover and allows more shortwave radiation to reach the surface. This warms up the land surface and enhances sensible heat flux, contributing to the SAT increase. In northwestern North America, the SAT increase is mainly due to horizontal advection. The anomalous high induces anomalous southerly winds to the west that transport warmer air from lower latitudes, leading to the SAT increase. Surface sensible heat flux acts as a damping effect in this region.

The connection between the Tibetan Plateau snow cover and North American SAT variations was robust during the period 1979–2004, but weakened largely around the mid-2000s. The change in this connection is related to the impact of tropical Pacific SST anomalies. Before the mid-2000s, the impact of tropical Pacific SST anomalies on atmospheric circulation and North American SAT variations appears relatively weak. As such, the Tibetan Plateau snow-cover anomalies exert an independent influence on the North American SAT variations. After the mid-2000s, the eastern Tibetan Plateau snow cover tends to vary out of phase with the tropical central Pacific SST. As the impact of tropical central Pacific SST anomalies on the North American SAT is opposite to that of eastern Tibetan Plateau snow-cover anomalies, the connection between the eastern Tibetan Plateau snow cover and North American SAT variations is largely weakened during the recent period.

The present study reveals that the weakened relationship between the Tibetan Plateau snow cover and North American SAT variations after the mid-2000s is related to the enhanced impact of tropical Pacific SST anomalies on North American SAT variations. An issue is why the influence of the tropical Pacific SST anomalies on the North American SAT variations is enhanced after the mid-2000s. Possible reasons include the shift of location of large equatorial Pacific SST anomalies, change in the tropical Pacific mean SST that modulates anomalous heating induced by tropical Pacific SST anomalies, effects of SST anomalies in other regions that may interfere constructively or destructively the impacts of tropical Pacific SST anomalies, and change in the mean atmospheric winds that affect the response of atmosphere to tropical Pacific SST anomalies. The standard deviation of spring SST anomalies is large in the equatorial central-eastern Pacific during 1979–2004, but only in the equatorial central Pacific during 2005–17 (figure not shown). The spring mean SST change from 1979–2004 to 2005–17 is small in the equatorial Pacific region (figure not shown). The SAT anomalies in North America do not show a large difference with respect to Niño-3 and Niño-4 (5°S–5°N, 160°E–150°W) SST anomalies (figure not shown). According to these results, the shift in the location of equatorial Pacific SST anomalies and tropical Pacific mean SST change do not appear to provide an explanation of the enhanced impacts of tropical Pacific SST anomalies on the North American SAT variations. It remains to be investigated what the specific reasons are for enhanced impacts of the tropical Pacific SST anomalies on the North American SAT variations after the mid-2000s.

An issue remains as to why the relationship between the Tibetan Plateau snow cover and the tropical Pacific SST variations changed in the mid-2000s. One plausible reason is change in anomalous circulation patterns over the tropics. He and Wu (2018) detected a change in the summer rainfall and circulation anomaly pattern over the tropical western Pacific in the mid-2000s, which, in turn, is related to a change in the coherence of tropical Indo-Pacific SST influence. There exists the possibility that changes in the SST anomaly pattern and the associated circulation anomalies may affect the relationship between tropical Pacific SST and Tibetan Plateau snow-cover variations. In the present study, however, we focus on examining the role of the tropical Pacific SST anomalies in the interdecadal change of the TP snow cover–North America SAT relationship. The reason for change in the relationship between the TP snow cover and tropical Pacific SST is beyond the scope of this study. Our preliminary analysis indicates that this issue may include evolution and impact of preceding tropical Indo-Pacific SST anomalies in addition to the change in the tropical Pacific SST anomaly pattern. We are working on this issue and will present the results in the near future.

Another issue is whether the connection between the Tibetan Plateau snow cover and North American air temperature variations will remain weak in the coming years. It is also worth investigating whether the western Tibetan Plateau snow-cover anomalies can affect the North American climate and whether the impact, if it exists, is subject to interdecadal changes. These issues need to be investigated in the future.

Acknowledgments

The comments of three anomalous reviewers have helped improve the paper. This study is supported by the National Key Research and Development Program of China Grant (2016YFA0600603), the National Natural Science Foundation of China Grants (41530425, 41775080, 41475081, and 41721004), and the China Postdoctoral Science Foundation Grant (2019M660762). The snow-cover data, NCEP–DOE Reanalysis-2 data, JRA-55 data, ERA-Interim data, CRU surface air temperature data, and COBE-SST data were obtained from http://nsidc.org/data/, https://www.esrl.noaa.gov/psd/, http://jra.kishou.go.jp/JRA-55/, http://www.ecmwf.int/en/research/climate-reanalysis, http://www.cru.uea.ac.uk/data/, https://www.esrl.noaa.gov/psd/, respectively.

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