Contribution of PDO to Decadal Variations of Glaze Dipole Pattern in China

Yong Liu aDepartment of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan, China
bCentre for Severe Weather and Climate and Hydro-Geological Hazards, Wuhan, China

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Shui Yu cNansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Huopo Chen cNansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Abstract

Based on the in situ observations, reanalysis, and model simulation, the variations in glaze dipole pattern in China and its underlying physical mechanism have been explored. The glaze dipole pattern features an out-of-phase relationship between winter glaze in the south of the Yangtze River valley (YRV) and northern China, accompanied by pronounced interdecadal variation around the late 1970s. The results from synoptic analyses suggest that cold air brought by the northerly winds and warm moist air by the southwesterly winds, as well as the occurrence of inversion layer are vital to the glaze weather in the south of YRV. Further analyses indicate that the interdecadal shift of the Pacific decadal oscillation (PDO) contributes largely to variations in glaze dipole pattern. Specifically, the warm PDO provides a beneficial environment for the occurrence of glaze dipole pattern by stimulating the tropical–extratropical circulation configuration with the deepened East Asian trough, strengthened East Asian westerly jet, anomalous anticyclone over the tropical western Pacific Ocean, and cyclone over the southern Tibetan Plateau at the decadal time scale. Consequently, the enhanced moisture transport brought by southwesterly and cold air intrusion induced by the deepened East Asian trough benefit the glaze weather in the south of YRV, while the decreased precipitation and a much lower temperature in northern China depress the generation of glaze. Moreover, the results from the CAM4 model simulation indicate the atmospheric circulation anomalies forced by PDO-like SST can roughly reproduce the extratropical configuration related to the glaze, but it has difficulties in capturing the tropical circulation anomalies.

Significance Statement

The purpose of this study is to better understand how the glaze dipole pattern in China responds to climate anomalies, which focuses on the spatial–temporal evolution of glaze days and its underlying physical mechanism. This study highlights the important role of Pacific Ocean sea surface temperature anomalies in the interdecadal variations in glaze dipole pattern, and it gives a clear clarification to demonstrate the impacts of Pacific decadal oscillation on the climatological background for the occurrence of glaze. Our results provide a guide on what drives the interdecadal variation in the glaze dipole pattern and help to understand the climate dynamic mechanism of variations in freezing events in China.

© 2023 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: Chen Huopo, chenhuopo@mail.iap.ac.cn

Abstract

Based on the in situ observations, reanalysis, and model simulation, the variations in glaze dipole pattern in China and its underlying physical mechanism have been explored. The glaze dipole pattern features an out-of-phase relationship between winter glaze in the south of the Yangtze River valley (YRV) and northern China, accompanied by pronounced interdecadal variation around the late 1970s. The results from synoptic analyses suggest that cold air brought by the northerly winds and warm moist air by the southwesterly winds, as well as the occurrence of inversion layer are vital to the glaze weather in the south of YRV. Further analyses indicate that the interdecadal shift of the Pacific decadal oscillation (PDO) contributes largely to variations in glaze dipole pattern. Specifically, the warm PDO provides a beneficial environment for the occurrence of glaze dipole pattern by stimulating the tropical–extratropical circulation configuration with the deepened East Asian trough, strengthened East Asian westerly jet, anomalous anticyclone over the tropical western Pacific Ocean, and cyclone over the southern Tibetan Plateau at the decadal time scale. Consequently, the enhanced moisture transport brought by southwesterly and cold air intrusion induced by the deepened East Asian trough benefit the glaze weather in the south of YRV, while the decreased precipitation and a much lower temperature in northern China depress the generation of glaze. Moreover, the results from the CAM4 model simulation indicate the atmospheric circulation anomalies forced by PDO-like SST can roughly reproduce the extratropical configuration related to the glaze, but it has difficulties in capturing the tropical circulation anomalies.

Significance Statement

The purpose of this study is to better understand how the glaze dipole pattern in China responds to climate anomalies, which focuses on the spatial–temporal evolution of glaze days and its underlying physical mechanism. This study highlights the important role of Pacific Ocean sea surface temperature anomalies in the interdecadal variations in glaze dipole pattern, and it gives a clear clarification to demonstrate the impacts of Pacific decadal oscillation on the climatological background for the occurrence of glaze. Our results provide a guide on what drives the interdecadal variation in the glaze dipole pattern and help to understand the climate dynamic mechanism of variations in freezing events in China.

© 2023 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: Chen Huopo, chenhuopo@mail.iap.ac.cn

1. Introduction

Glaze is a special case of precipitation in the winter half year that is a transparent and homogeneous icelike attachment formed by freezing rain hitting objects on the ground (Stewart 1992). Previous studies have documented that the key structure for the occurrence of glaze is the presence of an inversion layer (temperature > 0°C) in the vertical atmosphere, in which the ice crystals or snowflakes melt into liquid water droplets and then pass through a layer below 0°C to become supercooled raindrops (Cortinas et al. 2004; Bernstein 2000; Rauber et al. 2001; Matsushita and Nishio 2008). When this kind of supercooled raindrops falls from the air and collides with any object on the ground (whether or not the object reaches below 0°C), it will soon freeze. The amount of glaze weather is not high in the cold season, but severe glaze is a major hazard to the national economy and national defense construction. For example, the damage to the power infrastructure caused by glaze and freezing rain severely restricts the normal operation of power transmission, communication, and transportation (Peng et al. 2015; Zhao et al. 2008). Thus, the simulation and prediction of glaze have attracted lots of attention. However, it remains unclear how the spatial–temporal evolution of glaze responds to climate warming.

The distribution of glaze in China is characterized by an obvious geographical difference (e.g., W. Wang et al. 2020). The traditional glaze belt occurs in southwestern China, south of the Yangtze River valley (YRV), and the region between the Yellow River and the YRV, while there are few glaze events in other regions of China (Zhao et al. 2010; Wang et al. 2014). Recent studies have documented that the frequency of freezing weather in China decreased, but the intensity increased, and the area of glaze has shrunk except for Guizhou and Hunan Provinces in past decades (W. Wang et al. 2020; Zhao et al. 2010). The decrease in total freezing days in China can be attributed to the weakened Asian polar vortex, strengthened Ural and Baykal blocking high, and the westward and weakened western Pacific subtropical high (WPSH) (Wang 2011). In addition to this, some studies have suggested that glaze days of traditional glaze belts in China are characterized by obvious interdecadal variation, and glaze days before the 1990s are significantly more than that in recent years (Wang 2011; W. Wang et al. 2020).

The formation and maintenance of glaze are closely related to the regional atmospheric circulation. For example, accompanied by a cold tongue extending from north to south below 850 hPa and a warm tongue stretching from south to north above 850 hPa, the advection inversion formed by the warm and humid air sliding and climbing on the low-altitude cold air pad is vital to the occurrence of glaze in the YRV (Wang and Bei 1992). Thus, the continuous southward cold air guided by the mid–high-latitude circulation and northward warm and humid moisture brought by southwesterly are necessary for the formation of freezing rain and glaze in southern China (Li et al. 2008; Shi et al. 2010; Sun and Zhao 2008; Zhou et al. 2009). Moreover, preceding circulation signals of atmospheric teleconnection and sea surface temperature (SST) variations can also be indicated as a meaningful proxy for the occurrence of glaze (Wang et al. 2017). For example, the abnormal active Arctic Oscillation (AO) and enhanced Middle East westerly jet partly contributed to the freezing and icing event in southern China in early 2008 (Wen et al. 2009). The La Niña and negative SST anomalies from the tropical Indian Ocean to the tropical western Pacific can also exert great impacts on glaze weather by strengthening the East Asian winter monsoon (Ding et al. 2008; Wang et al. 2014).

Considerable progress has been made in understanding the possible impacts of weather systems and climate anomalies on the occurrence and maintenance of glaze (Ding et al. 2008; Sun and Zhao 2008; Wang et al. 2014). But rare studies focus on the spatial–temporal evolution of glaze and its underlying physical mechanism. Especially, a recent study has reported that there is an inverse tendency of glaze days in southern and northern China, which features a decreasing trend in the North China Plain and a slight increasing trend in some sites of the Yangtze River basin (Zhang et al. 2015). However, it remains unclear what contributes to the interdecadal variations in glaze days of traditional glaze belts in China. Hence, we will explore the possible causes for the decadal variations in glaze dominate mode. This paper is arranged as follows. Section 2 will briefly introduce the data and method used in this paper. Section 3 will present the main results based on comprehensive data analysis and model simulation. The discussion and conclusions are presented in section 4.

2. Data and methods

The daily in situ glaze dataset of 756 meteorological stations in China from 1951 to 2010 is provided by the National Meteorological Information Center, China Meteorological Administration. The monthly gridded precipitation and temperature datasets with a horizontal resolution of 0.25° × 0.25° are retrieved from the interpolation from over 2400 meteorological stations in China (CN05.1) (Wu and Gao 2013). The heat flux data are provided by the National Centers for Environmental Prediction–National Center for the Atmospheric Research (NCEP–NCAR), with a horizontal resolution of 2.5° × 2.5° (Kalnay et al. 1996). The daily and monthly atmospheric reanalysis are obtained from the Japanese 55-year Reanalysis (JRA-55; Ebita et al. 2011), with a horizontal resolution of 1.25° × 1.25°, which was demonstrated that it has good applicability in northern East Asia when compared with NCEP reanalysis (Yang et al. 2002; Wu et al. 2005). The monthly SST dataset is acquired from the National Oceanic and Atmosphere Administration Extended Reconstructed SST V5 dataset with a horizontal resolution of 2.0° × 2.0° (Huang et al. 2017). Moreover, the monthly standardized Pacific decadal oscillation (PDO) index is from the National Oceanic and Atmospheric Administration (NOAA) (https://www.esrl.noaa.gov/psd/data/climateindices).

The empirical orthogonal function (EOF) is employed to identify the dominant mode of glaze variations in China. The moving t test and Lepage method (Lepage 1971) are utilized to determine the interdecadal transition period. The Lanczos 9-yr low-pass filtering is used to reserve the interdecadal signal. All variables are detrended before conducting the regression and correlation analysis so as to remove the possible impacts of climate warming. The confidence level of the linear regression is evaluated using the two-tailed Student’s t test, and the effective degree of freedom Neff is evaluated following Metz (1991). The Neff for the correlations of time series X and Y is evaluated as
NeffN1+2τ=110NτNrX(τ)rY(τ).
Here, N denotes the data length and rX(τ) and rY(τ) are autocorrelation of time series X and Y, respectively, with a lag of τ years.
The vertically integrated water vapor flux Q is employed to investigate the changes in moisture transport in eastern China:
Q=1gpspqVdp.
In addition, the wave activity flux is also calculated to diagnose the anomalous Rossby wave propagation related to the atmospheric teleconnection mode based on the method proposed by Takaya and Nakamura (2001):
W=P2|U|{u¯(ψx2ψψxx)+υ¯(ψxψyψψxy)u¯(ψxψyψψxy)+υ¯(ψy2ψψyy)f2N2[u¯(ψxψzψψxz)+υ¯(ψyψzψψyz)]}.
Here, U indicates the horizontal wind velocity, ψ represents the streamfunction, f is the Coriolis parameter, and N2 means the frequency of buoyancy squared. The overbars and primes denote the winter mean and monthly disturbances, respectively.

A previous study has documented that there was a rapid increase in the number of meteorological stations in China before 1960, and then the total stations tended to be stable (W. Wang et al. 2020). In this study, because of the limited access to glaze data, the period from 1960 to 2010 is selected as the analysis period. When the meteorological station observes the occurrence of glaze, it is counted as a glazing day. Significantly, if there are more than 10 consecutive missing glaze records in the cold season (from September to the following May), the station in this year will not be counted. If the number of missing glaze records reaches 10 years, the station in the whole analysis period will not be counted. Considering the glaze weather mainly occurred in December, January, February, and March (DJFM), hence, the boreal winter in this paper is defined as the months of DJFM. When conducting the statistical analyses of climatological glaze occurrence, the selected analysis period is the whole cold season, including 276 stations where glaze weather was observed. Moreover, to eliminate the impact of extreme values on the spatial pattern of glaze, the high-altitude stations (annual average glaze days are greater than 20) and less frequent glaze stations (annual glaze days are less than 0.1) are not considered in this paper when conducting EOF analysis. An extreme glaze day is defined as a day in which the number of total observed-glaze stations in a single day is greater than the daily 99th percentile. The threshold of the 99th percentile is estimated from all glaze days in winter during the past five decades from 1960 to 2010.

The Community Atmosphere Model (CAM4), which is the atmospheric component of the CESM, version 1.2.2, is employed to investigate the possible impact of PDO-like SST pattern on glaze dominant mode. Previous studies have indicated the acceptable capacity of the CAM4 in simulating the East Asian climate (e.g., He et al. 2017; H. Gong et al. 2014; Zhu et al. 2015; Zhang and Sun 2018). The component set of “F_2000,” one official selection in the CESM model, is used. The suffix of “2000” depicts that the atmospheric composition is fixed at the constant level in 2000, with the CO2 concentration of 367.0 ppm. In this study, the simulation adopted a 1.9° × 2.5° finite volume grid with 26 hybrid sigma pressure levels and a 30-min integration time step (Gent et al. 2011). Two experiments are designed as follows: The first one is driven by the warm Pacific SST (120°E–80°W, 20°–60°N; defined as the EXP_wPDO) in winter, which is scaled by 2σ (σ is the standard deviation of the PDO SST) and superimposes onto the climatological Pacific SST; another is driven by the cold Pacific SST (defined as the EXP_cPDO), which is scaled by 2σ and superimposes onto the climatological Pacific SST. The enhanced intensity of SST forcing is due to the small signal–noise ratio in the extratropic (Li 2004). The experiments run for 45 years, in which the first 10 years are used for the experiment spinup and the last 35 years are used for analysis. Such a process is equivalent to conducting ensemble simulations driven by the specific SST forcing with different initial atmospheric and land surface conditions (Wang et al. 2004; Zhao et al. 2012).

3. Results

a. Synoptic circulation configuration for extreme glaze occurrence

Figure 1a shows the spatial distribution of annual average glaze days. The glaze mainly occurs over the eastern part of China with the strong regionality. Specifically, the area with high frequency of glaze happens in the south of the YRV (25°–30°N, 102°–117°E; defined as region A), the eastern region of Hubei–Henan (30°–35°N, 112°–116°E; defined as region C), and the junction of Shanxi, Gansu, and Ningxia Province (33°–38°N, 102°–109°E; defined as region B), while there are few glaze days in the other regions of China. In addition to the varied climate between the south and north of China, previous study has also documented the occurrence of glaze is closely related to the special terrain topography (W. Wang et al. 2020). For instance, Hunan and Guizhou Provinces are surrounded by mountains on three sides and flat terrain to the north, and their terrain is conducive to the occurrence of glaze. The mountain to the south can compel the intruded cold air to gather and generate a cold wedge, which lifts the northward warm and humid moisture and thus is beneficial to the occurrence of inversion layer. Moreover, the glaze occurring date is also characterized by obvious regional differences. Figure 1b presents the spatial distribution of the median average glaze date. In general, the glaze in region A and C mainly occur in January and February, while the glaze date in other regions varies with geographical position and feature obvious spatial heterogeneity. One possible cause for the great discrepancies in median glaze date in Xinjiang and northeast China might be owing to the small sample size of glaze occurrence, which leads to the large discrete variance of statistics.

Fig. 1.
Fig. 1.

(a) The spatial distribution of annual average glaze days in China in the cold season. Region A indicates the south of the Yangtze River valley (25°–30°N, 102°–117°E), region B indicates the junction of Shanxi, Gansu, and Ningxia Province (33°–38°N, 102°–109°E), and region C indicates the eastern region of Hubei–Henan (30°–35°N, 112°–116°E). (b) The spatial distribution of annual median glaze dates.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Figure 2 shows the synoptic-scale circulation configuration of extreme glaze weather occurrence. In the upper troposphere (Fig. 2a), the subtropical westerly jet was significantly strengthened, especially on the southern Tibetan Plateau (TP) and East Asia. The enhanced subtropical jet over the south TP favors the development of cyclonic circulation (Fig. 2b), which facilitates the moisture transporting from the Bay of Bengal to southern China (Fig. 2d). Moreover, the strengthened East Asian jet at the entrance can trigger ascending motion in the south of YRV through the secondary circulation. In the middle troposphere, the establishment of the Ural blocking high and East Asian trough is conducive to the cold air intruding into the south of China. The anomalous Philippine anticyclone can facilitate the continued propagation of warm moist to southern China. Correspondingly, in the lower troposphere, the enhanced northerly dominates eastern China, while the wet and warm southerly prevails over the south of middle and lower YRV (Fig. 2c). Consequently, the cold air is stuck under the warm moist air like a wedge, while the warm moist air slides and climbs on the low-altitude cold air pad, which collectively results in the inversion layer over the south of middle and lower YRV (Fig. 3). It is worth noting that the topography of Guizhou Province (the western portion of region A) is high in the west and low in the east, with an average altitude of about 1100 m. The significant temperature inversion over the eastern portion of region A can only be found on the layer of 800 to 850 hPa and 750 to 800 hPa due to the high topography. While over the south of middle and lower YRV, the strong temperature inversion dominates the lower troposphere.

Fig. 2.
Fig. 2.

The composite daily mean (a) zonal winds (shading) at 200 hPa, (b) geopotential heights (shading) and winds (vectors) at 500 hPa, (c) geopotential heights (shading) and winds (vectors) at 850 hPa, and (d) vertically integrated water vapor flux (vectors) from the surface to 300 hPa between 57 extreme glaze events and winter climatological average during 1960–2010. The purple contours in (a) indicate the climatological mean winds. Only the vectors that pass the Student’s t test at 0.05 significance level are shown in (b) and (c). The purple stippling in (b) and (c) and green shading in (d) indicate that the regression is significant at 95% confidence level with Student’s t test.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Fig. 3.
Fig. 3.

The composite daily mean air temperature difference between (a) 850 and 900 hPa, (b) between 800 and 850 hPa, and (c) between 750 and 800 hPa during 57 extreme events. The purple-outlined box indicates the region where temperature inversions occur in region A.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

b. The decadal variation in glaze dipole pattern and its corresponding circulation anomalies

Figure 4 shows the first two leading EOF patterns of glaze days. The most striking feature of glaze dominant mode is that there is an obvious dipole pattern in eastern China, which is characterized by more glaze days in the south of middle and lower YRV (region A), while few glaze days happening in northern China (including region B and region C). Simultaneously, the second EOF pattern presents a roughly reduced mode, which contributes to 14.5% of explained variance. The glaze dominant pattern resembles the spatial distribution of climatological glaze, and its corresponding time coefficient (defined as glaze PC1 index) is characterized by obvious interdecadal variation. The results of running t test and Lepage test demonstrate that the interdecadal transition of glaze days in China occurs in 1979 (Fig. 5), which indicates more glaze in southern China and less glaze in northern China in the late 1970s.

Fig. 4.
Fig. 4.

(left) Spatial distribution of the (a) first and (b) second EOF pattern of glaze days in China in winter based on 135 meteorological stations from 1960 to 2010, as well as (right) their corresponding time series.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Fig. 5.
Fig. 5.

The decadal test of the glaze PC1 index is based on the methods of the (a) running t test and (b) Lepage test. The dashed lines in (a) indicate the critical value at the 0.05 significance level. The two dashed lines in (b) represent the critical value at the 0.05 and 0.01 significance level, respectively.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

It has been documented that the variations in Asia polar vortex, WPSH, and Ural blocking high exert great impacts on freezing days in China (Ding et al. 2009; Z. Wang et al. 2014, 2017, 2020). The preceding signal from atmospheric and oceanic conditions, such as the Arctic Oscillation, SST anomalies in Pacific and Indian Oceans, can also play an important role in persistent icing events (Wang et al. 2017). Still, the underlying cause of glaze dipole pattern response to climate anomalies remains further understood, especially on the decadal time scale. Figure 6 shows the regression pattern of atmospheric circulation with regard to the glaze PC1 index. The subtropical westerly jet in the upper troposphere is significantly strengthened, accompanied by the eastward displacement of the East Asian westerly jet (EAWJ) center (Fig. 6a). In the middle troposphere, the enhanced Ural blocking high and East Asian trough dominate the mid–high latitudes of Eurasia, whereas the anomalous anticyclonic circulation prevails over the South China Sea (Fig. 6b). The configuration of extratropical circulation in eastern Eurasia is conducive to the intensified northerly in eastern China, which can bring the cold air from high latitudes to intrude southward. Simultaneously, the strengthened cyclonic circulation over the southern TP and anticyclonic circulation over South China Sea prompts the warm moist air to transport to the south of China (Figs. 6c, 7c). Consequently, the low-temperature anomalies and more precipitation occur in the south of middle and lower YRV (Figs. 7a,b), which benefits the generation of glaze. While in northern China, due to the lack of moisture support and a much lower temperature, the climate conditions are not in favor of the occurrence of glaze. The configuration of extratropical circulation and moisture transport illustrate the physical cause of glaze dipole mode, but it remains unclear what contributes to the decadal variation in glaze dipole mode.

Fig. 6.
Fig. 6.

The regression modes of winter average (a) zonal winds (shading) at 200 hPa, (b) geopotential heights (shading) and winds (vectors) at 500 hPa, and (c) geopotential heights (shading) and winds (vectors) at 850 hPa with regard to glaze PC1 index. The black contours in (a) indicate the climatological mean winds. Only the vectors that pass the Student’s t test at 0.05 significance level are shown in (b) and (c). The stippling in (a)–(c) indicates that the regression is significant at 95% confidence level with Student’s t test. All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Fig. 7.
Fig. 7.

The regression modes of winter average (a) surface air temperature, (b) precipitation, and (c) vertically integrated water vapor flux from the surface to 300 hPa with regard to glaze PC1 index. The stippling in (a) and (b) and the green shading in (c) indicate that the regression is significant at 95% confidence level with Student’s t test. All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

c. The possible impact of PDO on glaze dipole pattern

Mounting evidence has suggested that SST anomalies in the Pacific and Atlantic Oceans contribute largely to the decadal variations in the East Asian climate (Liu et al. 2021a; Xu et al. 2015; Zhou et al. 2007; Zhu et al. 2015). The atmospheric teleconnection mode stimulated by PDO or AMO exerts great impacts on regional climate throughout wave–mean flow interaction (Liu et al. 2021b; Sung et al. 2019; Xu et al. 2015). Considering the important role of SST anomalies in modulating the decadal variation in regional climate (Shabbar and Skinner 2004; Steinman et al. 2015), Fig. 8 shows the regression pattern of global SST anomalies related to the glaze PC1 index. The spatial distribution of SST anomalies related to the PC1 index in the North Pacific resembles largely the PDO-like oscillation, which illustrates the cool anomalies in the interior North Pacific and warm anomalies along the Pacific coast (e.g., Newman et al. 2016). Furthermore, the statistical result also indicates that there is a positive correlation between the glaze PC1 index and PDO index after removing the interannual variability and warming trend, which has a correlation coefficient of 0.81, significant at the 99% confidence level.

Fig. 8.
Fig. 8.

(a) The regression mode of the SST with regard to the glaze EOF1 index. The stippling in (a) indicates that the regression is significant at 95% confidence level with Student’s t test. (b) The time series of glaze EOF1 index (blue curve) and Pacific decadal oscillation index (red curve). All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Figure 9 shows the regression pattern of atmospheric circulation anomalies related to the PDO. During the positive phase of PDO, the enhanced Rossby wave activity flux propagation dominates the middle–high latitudes of Eurasia, which results in the negative quasigeostrophic streamfunction anomalies in western Europe and East Asia, and positive quasigeostrophic streamfunction anomalies over the Urals (Fig. 9a). Simultaneously, the saddle-shaped SST anomalies in the North Pacific during the warm PDO greatly impact the tropospheric circulation anomalies throughout air–sea interaction. The positive SST anomalies of the northwest Pacific in winter favor the generation of upward heat flux (the sum of sensible heat flux and latent heat flux), and then give rise to the lift of geopotential height. While the cold SST anomalies in the central North Pacific lead to the enhancement of the East Asian trough (Fig. 9b). Correspondingly, the subtropical westerly jet over East Asia and North Pacific strengthened significantly (Fig. 9c). Previous study has also suggested that the eastward displacement of EAWJ corresponds with the strengthened Aleutian low and East Asian trough (Wu and Sun 2017). The increased meridional temperature gradient in the south of 40°N during the positive phase of the North Pacific Oscillation favors the eastward shift of EAWJ by accelerating the zonal winds (Wu and Sun 2017). In addition, the enhanced anomalous anticyclone related to the PDO over the tropical western Pacific, along with the anomalous cyclone over the southern TP, prompts the warm moisture to southern China by continuous southwesterly (figure not shown). The tropical–extratropical circulation configuration related to the PDO provides a beneficial environment for the glaze occurrence in southern China at the interdecadal time scale. Consequently, the convergence of cold air and warm moisture (precipitation and low temperature) in southern China would increase the probability of glaze weather occurrence, while the decreased precipitation and a much lower temperature in northern China cannot give rise to glaze weather (Figs. 10a,b).

Fig. 9.
Fig. 9.

The regression modes of winter average (a) quasigeostrophic streamfunction (shading) and wave activity flux (vectors) at 300 hPa, (b) geopotential heights (shading) at 200 hPa and sum of net sensible heat flux and latent heat flux (shading), and (c) zonal winds (vectors) at 200 hPa with regard to PDO index. The black contours in (c) indicate the climatological mean winds. Only the shading that passes the Student’s t test at 0.05 significance level is shown in (b). The purple stippling in (a) and (c) indicates that the regression is significant at 95% confidence level with Student’s t test. All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Fig. 10.
Fig. 10.

As in Fig. 7, except they are the regression models with regard to the PDO index.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

d. Cause-and-effect validation for the PDO impacting regional circulation related to glaze dipole pattern

To validate the possible role of PDO in modulating the atmospheric circulation configuration for glaze occurrence, the Pacific SST-forcing sensitivity experiments performed by CAM4 are employed. The prescribed SST forcing in the EXP_wPDO is shown in Fig. 11, and the sign reversed result in Fig. 11 is the SST forcing in EXP_cPDO. The prescribed SST forcing pattern resembles the SST anomaly pattern related to the dominant glaze mode, with a high pattern correlation of 0.98 over the North Pacific sector.

Fig. 11.
Fig. 11.

Distribution of the prescribed SST forcing in the EXP_wPDO.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Figure 12 shows the composite results between EXP_wPDO and EXP_cPDO experiments. The simulated results reproduced the intensification and eastward displacement of EAWJ, as well as the deepened East Asian trough. The strengthened East Asian trough and eastward jet stream favor the southward intrusion of cold air by intensifying the winter monsoon, and then gives rise to lowering the surface air temperature in eastern China, which provides a beneficial condition for the occurrence of glaze in southern China (Fig. 13). Moreover, the enhanced Rossby wave propagation dominates the mid–high latitudes of Eurasia, subsequently altering the downstream circulation system through wave–flow interaction. Consequently, there are strengthened cyclonic circulation anomalies over western Europe and East Asia, while the anomalous anticyclonic circulation occupies the high latitudes of Eurasia. However, the simulated patterns of anticyclonic circulation are more northward than the observation. Moreover, the simulations cannot reproduce the tropical circulation anomalies related to the PDO in the observations, which causes discrepancies between the observation and model simulation. Therefore, the process of PDO influence on Eurasian atmospheric circulation needs more validation through multimodel evaluation and large-ensemble simulation in the future.

Fig. 12.
Fig. 12.

The composite maps of winter average (a) wave activity flux (vectors) and quasigeostrophic streamfunction (shading) at 300 hPa, (b) geopotential heights at 200 hPa, and (c) zonal winds at 200 hPa between EXP_wPDO and EXP_cPDO experiment. The black contours in (c) represent the climatological mean winds. The purple stippling indicates that the composite is significant at 90% confidence level with Student’s t test.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

Fig. 13.
Fig. 13.

The composite maps of winter average surface air temperature between the EXP_wPDO and EXP_cPDO experiments. The stippling indicates that the composite is significant at 90% confidence level with Student’s t test.

Citation: Journal of Climate 36, 10; 10.1175/JCLI-D-21-0932.1

4. Conclusions and discussion

In this study, we have investigated the spatial–temporal variation of glaze in winter. From the in situ observations, reanalysis data, and model simulation, results identify that the glaze dipole pattern in China is characterized by obvious interdecadal variation, which is attributed to the phase shift of PDO. Specifically, the enhanced moisture transport brought by the southwesterly and southward intrusion of cold air induced by deepened East Asian trough are dominant contributors to glaze in the south of the middle and lower YRV at decadal time scale, whereas the decreased precipitation and a much lower temperature in northern China depress the generation of glaze. Further analyses suggest there is an intimate correlation between PDO and glaze dipole pattern. The warm PDO contributes largely to the deepened East Asian trough and strengthened EAWJ, which benefits the cold air intrusion from the high latitudes to southern China and gives rise to the decrease in temperature. Moreover, the anomalous anticyclone over the tropical western Pacific and anomalous cyclone over the southern TP could prompt warm moisture to the south of YRV by southwesterly. Therefore, the tropical–extratropical circulation configuration related to the PDO provides a beneficial environment for the occurrence of glaze dipole pattern in China. In addition to this, the results based on the CAM4 model simulation illustrate the important role of PDO in modulating the atmospheric circulation configuration related to the glaze weather. The atmospheric circulation anomalies forced by PDO-like SST can reproduce the enhanced East Asian trough, strengthened EAWJ, and the corresponding low-temperature anomalies in China. However, the model still has difficulties in simulating tropical circulation anomalies related to the PDO.

This study presents mounting evidence to illustrate the interdecadal variation in glaze dipole pattern and its underlying physical mechanism. But limited access to glaze dataset hinders the ability to perform extensive research. The vertical structure with inversion layer above 850 hPa and the supercooled layer below 850 hPa is crucial to the occurrence of glaze (Cortinas et al. 2004; Bernstein 2000; Rauber et al. 2001; Matsushita and Nishio 2008), which is also related to the warm advection and intruded cold air in the lower troposphere in southern China. Thus, the important role of the southwesterly in the development and maintenance of the melting layer should be highlighted, which provides continuous heat flux to ensure the stability of inversion layer (Rauber et al. 2001). While the warm and moist advection induced by the India–Burma trough or northwestern Pacific subtropical high plays a different role in cold events and extreme winter precipitation in southern China (Li et al. 2020; Qin and Li 2020). Especially, in some extreme cold events, the enhanced WPSH has exerted great impacts on promoting and maintaining the continuous freezing events in southern China by strengthening moisture transport (Li et al. 2008; Qin and Li 2020). Simultaneously, the strengthened polar vortex and winter monsoon favors the occurrence of glaze, but the different configuration of the mid–high-latitude circulation system has varying impacts on intensity and extent of icing freezing events (Z. Wang et al. 2020; Zheng et al. 2022). Hence, more studies should be devoted to investigating the combined effects of the interaction of tropical and extratropical systems on the intensity and location of icing freezing events.

Acknowledgments.

This research was jointly supported by the National Natural Science Foundation of China (Grants 42221004 and 42088101).

Data availability statement.

Because of confidentiality agreements, the glaze dataset can only be made available to bona fide researchers subject to a nondisclosure agreement. Details of the data and how to access them are available from the National Meteorological Information Center, China Meteorological Administration (http://data.cma.cn/). The gridded precipitation and temperature obtained from CN05.1 are included in Wu and Gao (2013). The JRA-55 reanalysis is openly available (https://climatedataguide.ucar.edu/climate-data/jra-55). The NCEP–NCAR reanalysis is openly available (https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html). The sea surface temperature data are openly available from NOAA (https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html) as cited in Huang et al. (2017). The monthly standardized NAO index and PDO index are available online (https://www.esrl.noaa.gov/psd/data/climateindices). The outputs from CAM4 experiments are available upon request from the corresponding author.

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    • Search Google Scholar
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    • Search Google Scholar
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Save
  • Bernstein, B. C., 2000: Regional and local influences on freezing drizzle, freezing rain, and ice pellet events. Wea. Forecasting, 15, 485508, https://doi.org/10.1175/1520-0434(2000)015<0485:RALIOF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Cortinas, J. V., Jr., B. C. Bernstein, C. C. Robbins, and J. W. Strapp, 2004: An analysis of freezing rain, freezing drizzle, and ice pellets across the United States and Canada. Wea. Forecasting, 19, 377390, https://doi.org/10.1175/1520-0434(2004)019<0377:AAOFRF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ding, Y., and Coauthors, 2008: Causes of the unprecedented freezing disaster in January 2008 and its possible association with the global warming (in Chinese). Acta Meteor. Sin., 66, 808825, https://doi.org/10.11676/qxxb2008.074.

    • Search Google Scholar
    • Export Citation
  • Ding, Y., X. Jia, Z. Wang, X. Chen, and L. Chen, 2009: A contrasting study of freezing disasters in January 2008 and in winter of 1954/1955 in China. Front. Earth Sci. China, 3, 129145, https://doi.org/10.1007/s11707-009-0028-2.

    • Search Google Scholar
    • Export Citation
  • Ebita, A., and Coauthors, 2011: The Japanese 55-year reanalysis “JRA-55”: An interim report. SOLA, 7, 149152, https://doi.org/10.2151/sola.2011-038.

    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and Coauthors, 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991, https://doi.org/10.1175/2011JCLI4083.1.

    • Search Google Scholar
    • Export Citation
  • Gong, H., L. Wang, W. Chen, R. Wu, K. Wei, and X. Cui, 2014: The climatology and interannual variability of the East Asian winter monsoon in CMIP5 models. J. Climate, 27, 16591678, https://doi.org/10.1175/JCLI-D-13-00039.1.

    • Search Google Scholar
    • Export Citation
  • He, C., A. Lin, D. Gu, C. Li, B. Zheng, and T. Zhou, 2017: Interannual variability of eastern China summer rainfall: The origins of the meridional triple and dipole modes. Climate Dyn., 48, 683696, https://doi.org/10.1007/s00382-016-3103-x.

    • Search Google Scholar
    • Export Citation
  • Huang, B., and Coauthors, 2017: Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 81798205, https://doi.org/10.1175/JCLI-D-16-0836.1.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lepage, Y., 1971: A combination of Wilcoxon’s and Ansari-Bradley’s statistics. Biometrika, 58, 213217, https://doi.org/10.1093/biomet/58.1.213.

    • Search Google Scholar
    • Export Citation
  • Li, C. Y., H. Yang, and W. Gu, 2008: Cause of severe weather with cold air, freezing rain and snow cover over South China in January 2008 (in Chinese). Climatic Environ. Res., 13, 113122.

    • Search Google Scholar
    • Export Citation
  • Li, S., 2004: Impact of northwest Atlantic SST anomalies on the circulation over the Ural Mountains during early winter. J. Meteor. Soc. Japan, 82, 971988, https://doi.org/10.2151/jmsj.2004.971.

    • Search Google Scholar
    • Export Citation
  • Li, X., Z. Wen, and W.-R. Huang, 2020: Modulation of South Asian jet wave train on the extreme winter precipitation over southeast China: Comparison between 2015/16 and 2018/19. J. Climate, 33, 40654081, https://doi.org/10.1175/JCLI-D-19-0678.1.

    • Search Google Scholar
    • Export Citation
  • Liu, Y., H. Chen, H. Li, G. Zhang, and H. Wang, 2021a: What induces the interdecadal shift of the dipole patterns of summer precipitation trends over the Tibetan Plateau? Int. J. Climatol., 41, 51595177, https://doi.org/10.1002/joc.7122.

    • Search Google Scholar
    • Export Citation
  • Liu, Y., H. Chen, and X. Hu, 2021b: The unstable relationship between the precipitation dipole pattern in the Tibetan Plateau and summer NAO. Geophys. Res. Lett., 48, e2020GL091941, https://doi.org/10.1029/2020GL091941.

    • Search Google Scholar
    • Export Citation
  • Matsushita, H., and F. Nishio, 2008: A simple method of discriminating between occurrences of freezing rain and ice pellets in the Kanto Plain, Japan. J. Meteor. Soc. Japan, 86, 633648, https://doi.org/10.2151/jmsj.86.633.

    • Search Google Scholar
    • Export Citation
  • Metz, W., 1991: Optimal relationship of large-scale flow patterns and the barotropic feedback due to high-frequency eddies. J. Atmos. Sci., 48, 11411159, https://doi.org/10.1175/1520-0469(1991)048<1141:OROLSF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Newman, M., and Coauthors, 2016: The Pacific decadal oscillation, revisited. J. Climate, 29, 43994427, https://doi.org/10.1175/JCLI-D-15-0508.1.

    • Search Google Scholar
    • Export Citation
  • Peng, C., and Coauthors, 2015: Classification and distribution characteristics of ice coating on wires in Guizhou. South. Power Syst. Technol., 4, 8489.

    • Search Google Scholar
    • Export Citation
  • Qin, M., and S. Li, 2020: Comparison of persistent cold events in China during January-February of 2018 and 2008 (in Chinese). Climatic Environ. Res., 25, 601615, https://doi.org/10.3878/j.issn.1006-9585.2020.19154.

    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., L. S. Olthoff, M. K. Ramamurthy, D. Miller, and K. E. Kunkel, 2001: A synoptic weather pattern and sounding-based climatology of freezing precipitation in the United States east of the Rocky Mountains. J. Appl. Meteor., 40, 17241747, https://doi.org/10.1175/1520-0450(2001)040<1724:ASWPAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Shabbar, A., and W. Skinner, 2004: Summer drought patterns in Canada and the relationship to global sea surface temperatures. J. Climate, 17, 28662880, https://doi.org/10.1175/1520-0442(2004)017<2866:SDPICA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Shi, X., X. Xu, and C. Lu, 2010: The dynamic and thermodynamic structures associated with a series of heavy precipitation events over China during January 2008. Wea. Forecasting, 25, 11241141, https://doi.org/10.1175/2010WAF2222335.1.

    • Search Google Scholar
    • Export Citation
  • Steinman, B. A., M. E. Mann, and S. K. Miller, 2015: Atlantic and Pacific multidecadal oscillation and Northern Hemisphere temperatures. Science, 347, 988991, https://doi.org/10.1126/science.1257856.

    • Search Google Scholar
    • Export Citation
  • Stewart, R. E., 1992: Precipitation types in the transition region of winter storms. Bull. Amer. Meteor. Soc., 73, 287296, https://doi.org/10.1175/1520-0477(1992)073<0287:PTITTR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sun, J., and S. Zhao, 2008: Quasi-stationary front and stratification structure of the freezing rain and snow storm over southern China in January 2008 (in Chinese). Climatic Environ. Res., 13, 962978.

    • Search Google Scholar
    • Export Citation
  • Sung, M.-K., H.-Y. Jang, B.-M. Kim, S.-W. Yeh, Y.-S. Choi, and C. Yoo, 2019: Tropical influence on the North Pacific Oscillation drives winter extremes in North America. Nat. Climate Change, 9, 413418, https://doi.org/10.1038/s41558-019-0461-5.

    • Search Google Scholar
    • Export Citation
  • Takaya, K., and H. Nakamura, 2001: A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. J. Atmos. Sci., 58, 608627, https://doi.org/10.1175/1520-0469(2001)058<0608:AFOAPI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, B., I. S. Kang, and J.-Y. Lee, 2004: Ensemble simulations of Asian–Australian monsoon variability by 11 AGCMs. J. Climate, 17, 803818, https://doi.org/10.1175/1520-0442(2004)017<0803:ESOAMV>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
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  • Fig. 1.

    (a) The spatial distribution of annual average glaze days in China in the cold season. Region A indicates the south of the Yangtze River valley (25°–30°N, 102°–117°E), region B indicates the junction of Shanxi, Gansu, and Ningxia Province (33°–38°N, 102°–109°E), and region C indicates the eastern region of Hubei–Henan (30°–35°N, 112°–116°E). (b) The spatial distribution of annual median glaze dates.

  • Fig. 2.

    The composite daily mean (a) zonal winds (shading) at 200 hPa, (b) geopotential heights (shading) and winds (vectors) at 500 hPa, (c) geopotential heights (shading) and winds (vectors) at 850 hPa, and (d) vertically integrated water vapor flux (vectors) from the surface to 300 hPa between 57 extreme glaze events and winter climatological average during 1960–2010. The purple contours in (a) indicate the climatological mean winds. Only the vectors that pass the Student’s t test at 0.05 significance level are shown in (b) and (c). The purple stippling in (b) and (c) and green shading in (d) indicate that the regression is significant at 95% confidence level with Student’s t test.

  • Fig. 3.

    The composite daily mean air temperature difference between (a) 850 and 900 hPa, (b) between 800 and 850 hPa, and (c) between 750 and 800 hPa during 57 extreme events. The purple-outlined box indicates the region where temperature inversions occur in region A.

  • Fig. 4.

    (left) Spatial distribution of the (a) first and (b) second EOF pattern of glaze days in China in winter based on 135 meteorological stations from 1960 to 2010, as well as (right) their corresponding time series.

  • Fig. 5.

    The decadal test of the glaze PC1 index is based on the methods of the (a) running t test and (b) Lepage test. The dashed lines in (a) indicate the critical value at the 0.05 significance level. The two dashed lines in (b) represent the critical value at the 0.05 and 0.01 significance level, respectively.

  • Fig. 6.

    The regression modes of winter average (a) zonal winds (shading) at 200 hPa, (b) geopotential heights (shading) and winds (vectors) at 500 hPa, and (c) geopotential heights (shading) and winds (vectors) at 850 hPa with regard to glaze PC1 index. The black contours in (a) indicate the climatological mean winds. Only the vectors that pass the Student’s t test at 0.05 significance level are shown in (b) and (c). The stippling in (a)–(c) indicates that the regression is significant at 95% confidence level with Student’s t test. All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

  • Fig. 7.

    The regression modes of winter average (a) surface air temperature, (b) precipitation, and (c) vertically integrated water vapor flux from the surface to 300 hPa with regard to glaze PC1 index. The stippling in (a) and (b) and the green shading in (c) indicate that the regression is significant at 95% confidence level with Student’s t test. All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

  • Fig. 8.

    (a) The regression mode of the SST with regard to the glaze EOF1 index. The stippling in (a) indicates that the regression is significant at 95% confidence level with Student’s t test. (b) The time series of glaze EOF1 index (blue curve) and Pacific decadal oscillation index (red curve). All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

  • Fig. 9.

    The regression modes of winter average (a) quasigeostrophic streamfunction (shading) and wave activity flux (vectors) at 300 hPa, (b) geopotential heights (shading) at 200 hPa and sum of net sensible heat flux and latent heat flux (shading), and (c) zonal winds (vectors) at 200 hPa with regard to PDO index. The black contours in (c) indicate the climatological mean winds. Only the shading that passes the Student’s t test at 0.05 significance level is shown in (b). The purple stippling in (a) and (c) indicates that the regression is significant at 95% confidence level with Student’s t test. All variables had been detrended and processed with Lanczos 9-yr low-pass filtering before analyses.

  • Fig. 10.

    As in Fig. 7, except they are the regression models with regard to the PDO index.

  • Fig. 11.

    Distribution of the prescribed SST forcing in the EXP_wPDO.

  • Fig. 12.

    The composite maps of winter average (a) wave activity flux (vectors) and quasigeostrophic streamfunction (shading) at 300 hPa, (b) geopotential heights at 200 hPa, and (c) zonal winds at 200 hPa between EXP_wPDO and EXP_cPDO experiment. The black contours in (c) represent the climatological mean winds. The purple stippling indicates that the composite is significant at 90% confidence level with Student’s t test.

  • Fig. 13.

    The composite maps of winter average surface air temperature between the EXP_wPDO and EXP_cPDO experiments. The stippling indicates that the composite is significant at 90% confidence level with Student’s t test.

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