15 NOVEMBER 2017
SONG AND WU
9247
Processes for Occurrence of Strong Cold Events over Eastern China LEI SONG AND RENGUANG WU Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China (Manuscript received 30 November 2016, in final form 13 August 2017) ABSTRACT A strong cold event hit eastern China around 24 January 2016 with surface air temperature reaching more than 108C below the climatological mean in most regions of eastern China south of 408N. A total of 37 strong cold events similar to the January 2016 event with temperature anomalies over eastern China exceeding 258C have been identified during the winters from 1979/80 to 2015/16. A comparative analysis of events with surface temperature anomalies of the same intensity but limited to north of 408N indicates that the southward invasion of cold air to eastern China south of 408N is related to two factors. One is the latitudinal location of the upper-level wave train, the surface Siberian high, and the midtropospheric East Asian trough over the mid- to high-latitude Eurasian continent. The other is a subtropical upper-level wave train emanating from the midlatitude North Atlantic. The emergence of the subtropical wave train is related to the positive phase of the North Atlantic Oscillation (NAO). When the mid- to high-latitude wave train is located too far northward and the subtropical wave train induces an anomalous midtropospheric high over southern China, the East Asian trough does not extend southwestward and the Siberian high does not expand southeastward. In such a case, the cold air mainly affects northeastern China and northern Japan.
1. Introduction During the boreal winter, East Asia is often subjected to the impacts of cold events. The cold events feature a steep rise of surface pressure, a strengthening of northerly surface winds, and a sharp drop in surface temperature (Zhang et al. 1997; Chen et al. 2002). These cold events exert tremendous societal and economic influences over East Asia (Kunkel et al. 1999; Lu et al. 2010; Park et al. 2011a; Ou et al. 2015). A strong cold event struck a large part of East Asia from 20 to 25 January 2016. The temperature in some southern provinces of mainland China was more than 108C lower than the average historical level. The sudden temperature drop caused the death of at least 85 people in Taiwan and the lowest temperature broke the record in Vietnam (http://edition.cnn.com/2016/01/25/asia/asiacold-weather-travel-disruption/index.html). The people in Hong Kong experienced the coldest days in nearly three decades according to the Hong Kong Observatory (http://www.hko.gov.hk/press/SP/pre20160124.htm), with the minimum temperature reaching 3.38C on 24 January 2016, the ninth lowest temperature on record and the lowest since 1957. Corresponding author: Renguang Wu,
[email protected]
From time series of surface air temperature anomalies averaged over the north region (408–608N, 908–1308E) and the south region (208–408N, 1008–1208E) in the winter of 2015/16, we can easily identify the strong cold event in late January (Fig. 1a). The above two regions encompass the cold anomaly centers of this event. The average temperature anomalies in the north and south regions reached their lowest points on 20 and 24 January 2016, respectively. In particular, the regional average temperature in the south region is more than 108C below the climatological mean. As shown in the Hovmöller diagram along 1008–1208E (Fig. 1b), the cold temperature anomaly moved southward starting from 558N around 20 January. This cold event was preceded by a weaker cold event during 15 to 20 January that, however, did not reach southern China. Near the end of January, another cold event appeared. During the southward movement, the cold event first intensified and then weakened. The cold anomaly also reached southern China, but had only about half the intensity of the event around 24 January. Over the mid- to high-latitude Eurasian continent, the temperature has a large meridional gradient and the atmospheric circulation often displays wave patterns with large meridional winds. As such, cold events are quite common over the mid- to high-latitude Eurasian
DOI: 10.1175/JCLI-D-16-0857.1 Ó 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
9248
JOURNAL OF CLIMATE
VOLUME 30
FIG. 1. (a) Time evolution of surface air temperature anomalies (8C) over the north and south regions and (b) Hovmöller diagram of surface air temperature anomalies (8C) along 1008– 1208E during the 2015/16 winter.
continent accompanying the changes in the wave phase and the associated cold and warm advection. However, not all of these cold events extend to eastern China south of 408N with large intensity. What determines the extent of the southward movement of large cold temperature anomalies? Understanding the conditions that enable large cold anomalies to reach lower latitudes is relevant to the improvement in the prediction of strong cold events.
The occurrence of cold events is associated with different circulation systems. Previous studies have indicated the roles of the Siberian high (Ding and Krishnamurti 1987; Ding 1990; Zhang et al. 1997; Jeong and Ho 2005; Bueh et al. 2011; Shoji et al. 2014), the Arctic Oscillation (AO) (Thompson and Wallace 1998, 2000; Jeong and Ho 2005; Park et al. 2011a; Park et al. 2014), the East Asian trough (Zhang et al. 1997; Jeong and Ho 2005; Bueh et al. 2011; Song et al. 2016), and the
15 NOVEMBER 2017
SONG AND WU
wave trains propagating along the polar front jet and the subtropical jet in the upper troposphere (Watanabe 2004; Takaya and Nakamura 2005a,b; Wen et al. 2009; Bueh et al. 2011; Song et al. 2016). These systems may work together in inducing strong cold events. While previous studies have revealed that the occurrence of cold events is associated with these circulation systems, it is still unclear in what circumstances these circulation systems may bring strong cold events to eastern China. The Siberian high has the highest sea level pressure center in the Northern Hemisphere during the boreal winter (Ding 1990; Kim et al. 2014). A strong Siberian high is an essential background for the occurrence of cold events (Ding 1990; Zhang et al. 1997; Gong and Ho 2004; Wu and Wang 2002; Takaya and Nakamura 2005a; Jeong et al. 2006). The formation, sudden intensification, and southeastward expansion of the Siberian high toward East Asia often cause cold air outbreaks (Ding and Krishnamurti 1987; Ding 1990). The AO is the leading mode of extratropical circulation in the Northern Hemisphere during the boreal winter (Thompson and Wallace 1998, 2000). The AO may influence the winter climate over East Asia by modulating the mid- and high-latitude atmospheric circulation such as the Siberian high, the upper-level trough, and the polar front jet (Gong et al. 2001; Wu and Wang 2002; Jeong and Ho 2005; Park et al. 2010; Park et al. 2011a). Gong et al. (2001) found that the negative phase of the AO is accompanied by a stronger East Asian trough that, in turn, results in a cold temperature anomaly over East Asia. Jeong and Ho (2005) stated that the chances of an intense Siberian high increase during the negative phase of the AO. The cold events during the negative AO phase may be modulated by the southward expansions of the Siberian high (Park et al. 2010). The cold events during the negative AO phase tend to be stronger than those during the positive AO phase because the positive AO is related to a weaker Siberian high (Park et al. 2011a). The development of the Siberian high is closely related to the wave train propagating along the upperlevel polar front waveguide. Takaya and Nakamura (2005b) found that the upper-level wave train may interact with the surface cold anomaly through the modification of the stratification, and thus enhance the Siberian high and the East Asian trough (Song et al. 2016). A wave train may also propagate along the subtropical Asian jet (Hoskins and Ambrizzi 1993) and influence the East Asian winter climate. The snowstorm that affected China in January 2008 was closely associated with an intensified subtropical Asian jet, which led to a strong trough over the southern Tibetan Plateau, and hence the water vapor was transported from the Bay
9249
of Bengal to China (Wen et al. 2009), which caused condensation and subsequent rain or snow (Zhou et al. 2009). The impacts of cold events depend upon the affected region. Lower-latitude regions are more vulnerable to cold events than mid- to high-latitude regions. Most of the previous studies have been conducted on cold events that influence the broad East Asian region (e.g., Zhang et al. 1997; Chen et al. 2004; Jeong and Ho 2005; Park et al. 2011a,b; Shoji et al. 2014). Several previous studies have documented single cold events (Chu and Park 1984; Chen et al. 2002; Park et al. 2008; Wen et al. 2009; Zhou et al. 2009; Bueh et al. 2011). Few studies have investigated what determines the latitudinal extent of the influence of cold events. The present study focuses on strong cold events that reach eastern China south of 408N. In this paper, eastern China refers to the region of 208–408N, 1008–1208E. The question to be addressed is under what type of large-scale setting the cold air may reach the region of eastern China south of 408N with large intensity. To address this question, cases from more than a 30-yr period are examined to identify the common features. A comparative analysis between the cold events reaching south of 408N and those limited to north of 408N is conducted to unravel the conditions required for cold air intrusion to lower latitudes. The rest of the text is organized as follows. In section 2, the dataset and methodology are described. In section 3, a composite analysis is conducted to reveal the common features of cold events reaching south of 408N. The events that are limited to north of 408N are analyzed in section 4. A summary of the main results is presented in section 5 along with some discussion.
2. Data and methodology This study uses the daily data from the National Centers for Environmental Prediction (NCEP)–Department of Energy (DOE) Reanalysis 2 product provided by the NOAA/OAR/ESRL PSD (Kanamitsu et al. 2002). The variables include surface air temperature, surface wind, sea level pressure, geopotential height, and meridional and zonal wind at different levels. The horizontal resolution of the pressure level data is 2.58 3 2.58 with 17 vertical layers extending from 1000 to 10 hPa. The daily surface air temperature and wind data are on the T62 Gaussian grid. We use the National Oceanic and Atmospheric Administration (NOAA) 1/48 daily Optimum Interpolation Sea Surface Temperature (OISST) data version 2, which is available from late 1981 to the present (Banzon et al. 2016). The mean winter sea surface temperature (SST) anomalies in individual years have been removed from the daily
9250
JOURNAL OF CLIMATE
TABLE 1. The years and lag 0 days of the strong south cold events. See the text for the definition of the events.
VOLUME 30
TABLE 2. The years and lag 0 days of the strong north cold events. See the text for the definition of the events.
Year
Lag 0 day
Year
Lag 0 day
Year
Lag 0 day
Year
Lag 0 day
1979/80 1980/81 1982/83 1983/84 1984/85 1985/86 1987/88 1989/90 1991/92 1993/94 1995/96 1997/98 1998/99
30 Jan; 4 Feb 27 Jan 8 Jan 21 Jan; 6 Feb 23 Dec; 7 Jan; 12 Jan 4 Jan 23 Jan 31 Jan 28 Dec 16 Dec; 18 Jan 20 Feb 18 Jan 11 Jan
2000/01 2001/02 2002/03 2003/04 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13 2013/14 2015/16
14 Jan 18 Dec 3 Jan 20 Jan 15 Jan 22 Dec; 23 Jan 19 Dec; 12 Jan; 12 Feb 15 Dec; 25 Dec; 3 Jan 22 Jan 22 Dec; 3 Jan 10 Feb 24 Jan; 1 Feb
1982/83 1986/87 1987/88 1989/90 1993/94 1994/95
10 Feb 25 Dec; 11 Feb 28 Dec 20 Jan 3 Jan 13 Dec
1998/99 2000/01 2005/06 2008/09 2009/10 2011/12
26 Jan 2 Feb 1 Feb 13 Feb 31 Jan 27 Jan
SST anomalies in the corresponding winter to exclude the effect of a linear trend. The AO index is obtained from the NOAA Climate Prediction Center (CPC) website (http://www.cpc. ncep.noaa.gov/products/precip/CWlink/daily_ao_index/ ao.shtml). The AO index is defined by projecting the daily 1000-hPa height anomalies poleward of 208N onto the leading spatial pattern of the AO (Thompson and Wallace 1998). The North Atlantic Oscillation (NAO) index is calculated using the method based on the rotated principal component analysis (Barnston and Livezey 1987), and it is also obtained from the CPC website (http://www.cpc.ncep.noaa.gov/products/precip/ CWlink/pna/nao.shtml). The Siberian high index is defined as the mean sea level pressure over the region of 408–658N, 808–1208E (Panagiotopoulos et al. 2005). A composite analysis is employed in the present study to obtain the common features of the strong cold events during the 1979/80 to 2015/16 winters. The cold event in late January 2016 features large regional mean surface air temperature anomalies in both the north and south regions with the temperature drop in the south region lagging that in the north region by a few days. To find similar events, we define a strong cold event when the surface air temperature anomalies in both the south region (208–408N, 1008–1208E) and the north region (408–608N, 908–1308E) exceed 258C and when the peak day of the temperature anomalies in the south region is 1 to 5 days later than that in the north region. For brevity, this kind of event is called a south cold event. Here, 408N is selected as the separation between the two regions based on the consideration that the cold air intrusions south of 408N may bring larger impacts compared to those limited to north of 408N. The standard deviation of the winter daily surface air temperature is mostly below 48C south of 408N and it can reach 68C north of 408N (not shown). The threshold of 58C is approximately 1.5
standard deviations of the area-mean daily temperature in the south region. We identified 37 strong south cold events during the study period (1979–2016) (Table 1). The day when the negative temperature anomalies in the south region reach the maximum is used as the reference (lag 0 day) in the composite analysis. For comparison, we define a strong cold event when the regional average negative temperature anomalies in the north region exceed 258C and the regional average negative temperature anomalies in the south region remain above 258C within a 1–5-day lag of the peak temperature anomalies in the north region. This kind of event is called a north cold event. We obtained 13 strong north cold events during the study period (1979–2016) (Table 2). During the north cold events, the lag 0 day is defined as the day when the negative temperature anomalies in the north region reach the maximum. The significance of the composite anomalies is using the Student’s t test. Our definition of cold events differs from previous studies in that we are concerned with events that display a regional mean temperature drop with a large magnitude. To examine the probability of the occurrence of strong south and north cold events, we define general south and north cold events based on the regional average temperature anomalies in individual regions using the same criterion of 258C. We obtain 52 general south cold events and 65 general north cold events. Among these events, there are 15 general south cold events that are accompanied by temperature anomalies of smaller than 258C in the north region and there are 15 general north cold events that are accompanied by temperature anomalies in the south region exceeding 258C outside the 1–5-day time lag. This indicates that the number of strong north cold events is relatively small (about 20%) compared to the total general north cold events. Nevertheless, the analysis of the strong north cold events is valuable for understanding the conditions for the occurrence of strong cold events over eastern China. The propagation of Rossby wave trains is illustrated by wave activity flux which is independent of the wave phase and parallel to the local group velocity on a
15 NOVEMBER 2017
SONG AND WU
zonally varying basic flow (Plumb 1985; Takaya and Nakamura 2001). The wave activity flux can be written as follows: 9 8 0 0 0 0 02 0 0 > > u(y 2 c y ) 1 y(2u y 1 c u ) > > x x > > > > > > > > 0 0 0 0 = < 0 0 02 p0 u(2u y 1 c ux ) 1 y(u 1 c uy ) . W5 > 2jVj > > > > > f R > > 0 0 0 0 0 0 0 0 0 > > > ; :N 2 H [u(y T 2 c Tx ) 1 y(2u T 2 c Ty )] > 0
Here V 5 (u, y) is the winter mean horizontal wind velocity averaged over the 1979–2010 period, V 0 5 (u0 , y 0 ) is the perturbation horizontal geostrophic wind velocity, c0 is the perturbation geostrophic streamfunction, f0 is the Coriolis parameter at 458N, R is the gas constant of dry air, N 2 is the square of the buoyancy frequency, p0 is the pressure divided by 1000 hPa, T 0 is perturbation air temperature, and H0 is the scale height. Subscripts x and y denote partial derivatives in the zonal and meridional directions, respectively. Primes denote the value with the climatological mean removed. In this study, we diagnose the contributions of the different terms to the temperature change. The temperature tendency equation is written as follows: ›T 5 2V =T 2 ›t
p p0
CR
p
v
›u 1 Q. ›p
One variable (A) can be divided into two components: A 5 A 1 A0 . The overbar indicates the climatological mean, and the prime denotes the value with the climatological mean removed. Therefore, the advection term in the temperature tendency equation can be written as V =T 5 (V 1 V0 ) =(T 1 T 0 ) . After the climatological mean terms are dropped, we have V =T ; u
›T 0 ›T ›T 0 ›T 0 ›T ›T 0 1 u0 1 u0 1y 1 y0 1 y0 . ›x ›y ›x ›x ›y ›y
We use a barotropic model to examine the effect of an anomalous divergence source. The model is based on a barotropic vorticity equation linearized at 300-hPa climatological flow (Watanabe 2004): ›t =2 c0 1 J(c, =2 c0 )1 J(c0 , =2 c 1 f )1 a=2 c0 1n=6 c0 5 S0 , where J is a Jacobian operator, c and c0 are the basic state and perturbation streamfunctions respectively, f is
9251
the Coriolis parameter, and S0 is an anomalous vorticity source induced by the divergent part of the circulations. Also, n denotes the damping coefficient that acts to damp the smallest-scale eddy in a 3-day period, and a is the damping coefficient with a value of (14.7 days)21.
3. Strong south cold events In this section, we document the common features of the strong south cold events over eastern China. These features will be compared with those of the strong north cold events in the next section to reveal the important differences that are required for cold events to reach lower latitudes. The cold event of January 2016 will be briefly described after the presentation of the composite analysis. Previous studies have documented cold air outbreaks in East Asia (termed as cold surges in general). Here, we are focused on those strong cold air outbreaks over a large area of eastern China. Although the mid- to high-latitude circulation features of the strong cold events revealed in this section are mostly similar to those of previous studies about cold surges (e.g., Zhang et al. 1997; Jeong and Ho 2005; Park et al. 2011a), it is essential to display these features for comparison with the strong north cold events. This comparison is presented in the next section to demonstrate the conditions required for cold air invasion to lower latitudes. During strong south cold events, large negative surface air temperature anomalies are mainly confined to north of 408N three days before with the center located north of Lake Baikal (Figs. 2a–c). The negative temperature anomalies start to move southward on lag 22 day (Fig. 2d) and approach 208N on lag 21 day (Fig. 2e). On lag 0 day, the negative anomalies cover a large part of eastern China and the magnitude of anomalies reaches 268C or more (Fig. 2f). At this time, the anomalies in the midlatitude regions have largely weakened. The cold air outbreak over East Asia usually follows the development of the Siberian high, the deepening of the East Asian trough, and strong northerly winds (Ding and Krishnamurti 1987; Zhang et al. 1997; Jeong and Ho 2005; Song et al. 2016). The temperature anomalies are closely related to surface wind anomalies. A strong anomalous anticyclone or high is present over Siberia on lag 25 and 23 days (Figs. 3a,b,e,f). Anomalous northeasterly winds along the southeastern part of the anomalous high lead to the accumulation of cold air and contribute to large negative temperature anomalies around Lake Baikal (Figs. 2a–c). With the southeastward movement of the anomalous anticyclone and high, the Siberian high expands southeastward
9252
JOURNAL OF CLIMATE
VOLUME 30
FIG. 2. Composite surface air temperature anomalies (8C) on lag days of (a) 25, (b) 24, (c) 23, (d) 22, (e) 21, and (f) 0 of strong south cold events. The black dots indicate anomalies significant at the 95% confidence level.
and anomalous northerly winds blow over eastern China (Figs. 3c,d,g,h). This leads to the southward intrusion of cold air into eastern China south of 408N (Figs. 2d–f). The low-level circulation anomalies are consistent with those in the middle troposphere. A wave pattern of 500-hPa height anomalies develops over the mid- to high-latitude Eurasian continent from lag 27 to 24 day (Figs. 4a–d). This leads to the intensification and northeastward extension of an anomalous ridge over western Siberia. The enhanced northwesterly flow in front of the ridge favors the development of a low-level anomalous high, leading to the intensification of the Siberian high (Figs. 3a,b,e,f). With the additional eastward movement of the ridge, the East Asian trough deepens and extends southwestward (Figs. 4e–g). This is followed by the southeastward expansion of the Siberian
high (Figs. 3g,h) and the formation of anomalous northerly winds over eastern China (Figs. 3c,d). The wave train over the mid- to high-latitude Eurasian continent is also observed in the upper level, which is associated with Rossby wave activity. On lag 27 day, Rossby wave activity fluxes emerge over western Siberia (Fig. 5a). The distribution of the wave activity fluxes indicates that the source lies in the high latitudes. The presence of positive height anomalies over the polar region reflects the negative AO signal during its decay phase. The region around Lake Baikal is a sink of wave activity fluxes where the wave energy contributes to the intensification of the Siberian high. On the following days, the wave train intensifies and moves eastward (Figs. 5b–f). Correspondingly, the geopotential height anomalies enhance along the wave train. A southeastward movement of the sink region is observed
15 NOVEMBER 2017
SONG AND WU
9253
FIG. 3. Composite surface wind anomalies (scale on bottom right of the first panel) on lag days (a) 25, (b) 23, (c) 21, and (d) 0 of strong south cold events. (e)–(h) As in (a)–(d), but for sea level pressure (hPa; contour) and sea level pressure anomalies (hPa; shading). The black dots in (a)–(d) and the gray dots in (e)–(h) indicate anomalies significant at the 95% confidence level. The contour interval in (e)–(h) is 5 hPa.
after lag 23 day (Figs. 5f–h), which is followed by the southeastward expansion of the Siberian high (Figs. 3f–h). The dipole pattern of height anomalies over Asia contributes to the wave train type strengthening of the Siberian high (Takaya and Nakamura 2005b) and the deepening of the East Asian trough (Song et al. 2016).
During this process, the preexisting surface cold anomaly in the region of the Siberian high acts as an anticyclonic potential vorticity anomaly and interacts with the upper-level wave train by modifying the stratification. When the incoming Rossby wave train reaches above the preexisting cold anomalies, the downward influence
9254
JOURNAL OF CLIMATE
VOLUME 30
FIG. 4. Composite geopotential height (gpm; contour) and geopotential height anomalies (gpm; shading) at 500 hPa on lag days of (a) 27, (b) 26, (c) 25, (d) 24, (e) 23, (f) 22, (g) 21, and (h) 0 of strong south cold events. The gray dots in the figures indicate anomalies significant the 95% confidence level. The contour level is 100 gpm.
of the upper-level potential vorticity anomaly leads to the development of shallow cold anticyclonic anomalies at the surface (i.e., the Siberian high) (Takaya and Nakamura 2005b; Song et al. 2016). We analyzed the circulation changes corresponding to the cold event of January 2016 and obtained similar features. The cold event was preceded by the
development and northeastward extension of an upstream ridge, followed by the deepening and southwestward extension of the East Asian trough in the midtroposphere. At the surface, the Siberian high was first enhanced around Lake Baikal and then expanded southeastward, accompanied by anomalous northerly winds over East Asia. A Rossby wave train and its
15 NOVEMBER 2017
SONG AND WU
9255
FIG. 5. As in Fig. 4, but for the geopotential height anomalies at 300-hPa (gpm; shading) and wave activity flux (unit m2 s22; scale on bottom right of the fourth panel; vector). The black dots in the figures indicate anomalies significant at the 95% confidence level.
associated wave activity flux were also observed in the upper levels along the polar front jet. The temporal relationships among the surface temperature changes in the north and south regions, the Siberian high, and the AO are illustrated in Fig. 6. The surface temperature in the north region starts to drop from lag 29 day and reaches its lowest value on
lag 23 day. This temperature decline is preceded by changes in the AO, which reaches the peak of its negative phase on lag 28 day. This suggests that the strong south cold events tend to occur during the decaying stage of the negative AO phase. Among the 37 strong cold events, 24 events are observed during the decay of the negative AO phase. The Siberian high begins to
9256
JOURNAL OF CLIMATE
VOLUME 30
FIG. 6. Time evolution of surface air temperature anomalies (8C) in the north and south regions, the Siberian high index (hPa), and the AO index during lag 213 to lag 5 days of strong south cold events.
strongly intensify around lag 23 day when the temperature anomalies in the north region reach their maximum. The Siberian high attains its maximum intensity two days later than the peak cold anomaly in the north region. This time lag indicates a thermodynamic effect of the cold air on the Siberian high. The temperature in the south region appears to follow the Siberian high index with 1 day lag. This may be explained by the effect of the Siberian high on the southward advection of cold air (Ding and Krishnamurti 1987; Panagiotopoulos et al. 2005; Takaya and Nakamura 2013). The surface cold temperature anomaly may interact with the upper-level wave train by modifying the stratification, which could lead to the strengthening of the Siberian high (Takaya and Nakamura 2005b; Song et al. 2016). As shown in Fig. 6, the AO index reaches its lowest value on lag 28 day and the strong south cold events develop during the decay of the negative AO phase. Previous studies have indicated that the occurrence of cold events over East Asia is closely related to the negative AO by its modification of the Siberian high and the East Asian trough (Jeong and Ho 2005). The geopotential height anomalies during the south cold events are characterized by an anticyclone–cyclone couplet over mid- to high-latitude Asia (Figs. 4 and 5), which leads to strong northeasterly flow within the couplet (Figs. 3b–d) and causes strong cold anomalies over Asia. The feature is similar to the cold event cases during
negative AO phases identified by Park et al. (2011a). During the development of the strong south cold events, the positive height anomalies move southeastward from the Arctic region toward northern Asia (Figs. 4a–g and 5a–g). The Siberian high is strengthened in this process (Park et al. 2010). Therefore, the negative AO may contribute to the development of the strong south cold events through its influence on the Siberian high and the East Asian trough. The above analysis suggests the effect of anomalous northerly winds in the southward intrusion of cold air into eastern China south of 408N. To confirm the role of anomalous northerly winds, we diagnose the contributions of different terms to the temperature change. Figure 7 shows the evolutions of the temperature tendency and the advection terms in the south region during the strong south cold events. The temperature tendency drops largely from lag 22 day, indicating the influence of the cold event over this region. The temperature tendency turns positive after lag 0 day, meaning that the temperature recovers from the cold event. The term (2y 0 ›T/›y) evolves in a consistent manner with the temperature tendency before lag 1 day and its amplitude is larger than the temperature tendency. This result indicates that the cold anomaly over the south region is mainly contributed by the advection of mean temperature by anomalous meridional wind. In addition, anomalous meridional advection (2y 0 ›T 0 /›y) and
15 NOVEMBER 2017
SONG AND WU
9257
FIG. 7. Time evolution of the tendency of surface air temperature anomalies in the south region and the different terms of the temperature tendency equation during lag 212 to lag 5 days of strong south cold events.
anomalous zonal wind advection (2u0 ›T 0 /›x) by the transients also contribute to the temperature tendency from lag 24 to lag 1 day. The recovery of temperature is mainly attributed to the surface heat flux (figures not shown) as the advection terms are small (Fig. 7).
4. Strong north cold events The previous section revealed the common features of the strong south cold events reaching south of 408N over eastern China. In this section, we analyze the cold events that are limited to north of 408N. The comparison between these two types of events helps to understand the conditions necessary for strong cold events to invade eastern China south of 408N. During the developing stage of the strong north cold events, the cold anomalies originate in the northern Siberian region (Fig. 8a). In the following days, these cold anomalies intensify and extend southward (Figs. 8b–d). On lag 0 day, large anomalies approach 408N with the center located northwest of Lake Baikal (Fig. 8e). Two days later, cold anomalies extend southeastward to northern Japan (Fig. 8f). Compared to the strong south cold events, the temperature anomalies develop at higher latitudes in the strong north cold events. The surface wind and pressure anomalies feature an obvious contrast with the anticyclone or high over western Russia and the cyclone or low around Lake Baikal (Fig. 9a). The anomalous northerly winds between the anticyclone and the cyclone explain the
development and intensification of the large cold anomalies over Siberia (Fig. 8). In the following days, with the eastward movement of the anticyclone/high, the cyclone/low moves southward to occupy eastern China (Figs. 9b,c). The presence of an anomalous cyclone/low over eastern China and anomalous southerly winds along the east coast restricts the anomalous northerly winds to the north of 408N (Figs. 9a–c). As such, the cold air cannot intrude over eastern China south of 408N (Fig. 8). In the midtroposphere, a wave train is observed over the Eurasian continent, but it is located at higher latitudes compared to the strong south cold events (Figs. 9e–g). Meanwhile, the intensification of the East Asian trough is confined to east of 1208E (Figs. 9f–h). This accounts for why the Siberian high has limited southward expansion over eastern China. The Rossby wave activity flux is also calculated for the strong north cold events. The source of the wave activity lies in the polar region (Fig. 10), similar to the strong south cold events (Fig. 5). However, the sink of wave activity is located at higher latitudes. The sink region moves eastward and intensifies along with the anomalous low (Figs. 10a–d). This movement is then followed by southeastward movement after lag 23 day (Figs. 10e–h). An obvious wave activity emanating from the North Atlantic is detected over the subtropics. A prominent wave source appears over the midlatitude North Atlantic on lag 27 day and intensifies quickly in the following days with eastward movement (Figs. 10b–d). The wave train propagates eastward along the subtropical
9258
JOURNAL OF CLIMATE
VOLUME 30
FIG. 8. As in Fig. 2, but for strong north cold events on lag (a) 24, (b) 23, (c) 22, (d) 21, (e) 0, and (f) 2 days.
jet, reaching the Arabian Peninsula on lag 25 day (Fig. 10c) and southern China on lag 22 day (Fig. 10f). This propagation is followed by the development of an anticyclonic anomaly that moves eastward with some intensification (Figs. 10e–h). The eastward propagation of the wave train is clear in the Hovmöller diagram along 258–358N (Fig. 11). The anomalous high over the North Atlantic appears over 308W on lag 28 day and intensifies over the following two days. Afterward, the wave pattern develops downstream. The anomalous high east of 708E intensifies and moves eastward after lag 25 day. It takes approximately 4 days for the wave train to affect southern China. The propagation of the wave train along the subtropics suggests the influence of the signal from the North Atlantic on East Asia. Distinct from the north cold events, neither an obvious wave train along the subtropics nor an anomalous divergence over the midlatitude North Atlantic is observed for the south cold events.
The temporal relationships among the AO, the NAO, the temperature anomaly, and the Siberian high during the north cold events are demonstrated in Fig. 12. Contrary to the south cold events, the negative temperature anomalies in the north are preceded by a positive Siberian high index, as proposed by Panagiotopoulos et al. (2005). This corresponds to the presence of an anomalous low (Figs. 9a–c). Therefore, the Siberian high does not amplify during the development of the north cold events. Consistent with the south cold events, however, the cold anomalies are followed by an upward trend of the Siberian high index, which is indicative of a contribution of the temperature change to the pressure change. Instead of serving as a precursory signal for the cold events, the AO index reaches the lowest value after the largest negative temperature anomalies during the north cold events. This suggests a tendency for the strong north cold events to occur during the development of the
15 NOVEMBER 2017
SONG AND WU
9259
FIG. 9. Composite surface wind (vector, scale at the right-bottom) and sea level pressure (shading) anomalies (hPa) on lag (a) 24, (b) 22, (c) 0, and (d) 2 days of strong north cold events. (e)–(h) As in (a)–(d), but for geopotential height (contour; gpm) and geopotential height anomalies (shading; gpm) of 500 hPa. The contour level is 100 gpm. The gray dots in (e)–(h) indicate anomalies significant at the 95% confidence level.
negative AO phase. Among the 13 strong cold events, we observe 10 events during the development of the negative AO phase. This feature differs from the strong south cold events that occur during the decay of the negative AO phase (Fig. 6). The NAO is in its positive phase when the north cold events develop,
and 9 of the 13 north cold events are related to the positive phase of the NAO. This differs from the strong south cold events during which the NAO index is small (within 60.1). The values of the AO and NAO indices show some differences during the north cold events.
9260
JOURNAL OF CLIMATE
VOLUME 30
FIG. 10. As in Fig. 5, but for strong north cold events.
The above subtropical wave train propagation is very similar to that obtained by Watanabe (2004) based on composites of the NAO index. Hu et al. (2017) detected a subtropical wave train using monthly mean data. Watanabe (2004) interpreted the wave train as quasi-stationary Rossby waves trapped in the Asian jet waveguide (Hoskins and Ambrizzi 1993) triggered by anomalous convergence over the Mediterranean Sea that is concurrent with the downstream extension of the NAO signal during its decay. The NAO is in the decaying stage when the wave source develops over the North Atlantic (Fig. 12). Indeed, the distribution of the sea level pressure anomaly over the North Atlantic features the NAO pattern before lag 27 day (figures not shown). Different from Watanabe (2004), the sea level pressure anomaly in the north pole of the NAO pattern
does not extend to the North Pole, which may explain the difference between the values of the NAO and AO indices (Fig. 12). Another difference is that the anomalous convergence over the Mediterranean Sea noted by Watanabe (2004) is weak in our case. So the subtropical wave train appears to be at lower latitudes compared to that in Watanabe (2004). To examine whether the anomalous divergence over the Mediterranean region is necessary for the subtropical wave train to reach southern China, we conducted model experiments using a barotropic model (Sardeshmukh and Hoskins 1988). An anomalous divergence is added to the model around 458N and 208W but without a Mediterranean source in the barotropic model. The amplitude of the anomalous divergence is set to 1.74 3 1026 s21, the same as that in the composite
15 NOVEMBER 2017
SONG AND WU
FIG. 11. Hovmöller diagram of geopotential height anomalies (gpm) at 300 hPa along 258–358N during strong north cold events. The black crosses indicate anomalies significant at the 95% confidence level.
north cold events on lag 26 day. A wave train along the subtropical jet appears in the model integration (Fig. 13), similar to the observations (Fig. 10). The wave train originates from the region between 608W to 158W on model day 4 and propagates eastward. After model day 14, the high pressure anomaly is located between 908 and 1208E. The horizontal patterns and wave-activity fluxes are presented in Fig. 14. As shown in the figure, the Rossby wave packets emit from the divergence source and propagate along the subtropics, as indicated by the wave-activity fluxes. The wave train pattern on the model day 7 is quite similar to that on lag 27 day of
9261
the composite north cold events (Figs. 13 and 10b–e). This similarity indicates that the anomalous divergence over the midlatitude North Atlantic related to the NAO is vital to the wave train in the strong north cold events, but the Mediterranean source is not necessary in this case. The wave train in the barotropic model propagates more slowly than in the observations (Figs. 10 and 11). This difference may be due to the effects of other wave sources along the wave train in the north cold events. Negative SST anomalies are identified in the midlatitude and eastern tropical North Atlantic Ocean about one week before the north cold events (Fig. 15). The lower-level wind anomalies over the North Atlantic feature the positive NAO at lag 29 and 27 days with an anomalous anticyclone over the subtropical North Atlantic (Figs. 15a,b). The anomalous northeasterly winds southeast of the anomalous anticyclone strengthen the trade winds and enhance surface latent heat flux (not shown), contributing to the development of negative SST anomalies in the eastern tropical North Atlantic. The anomalous westerly winds over the midlatitudes strengthen the surface winds, increase surface evaporation, and induce cold advection by anomalous southward Ekman currents, all of which contribute to the SST decrease in the midlatitude North Atlantic. In comparison, the wind anomalies display a relatively fast change compared to the SST anomalies. According to previous studies, there may be interactions between the NAO and the North Atlantic SST anomalies (Marshall et al. 2001; Chen et al. 2015). The anomalous anticyclone over the eastern subtropical North Atlantic (Figs. 15b–d) appears to be a Rossby wave–type response to negative
FIG. 12. Time evolution of surface air temperature anomalies (8C) in the north region, the Siberian high index (hPa), the AO index, and the NAO index during the lag 213 to lag 5 days of strong north cold events.
9262
JOURNAL OF CLIMATE
FIG. 13. Hovmöller diagram of geopotential height anomalies (gpm) along 258–358N from the barotropic model run with an anomalous divergence of 21.74 3 1026 s21 at 458N, 208W.
SST anomalies. However, the anomalous downward motion is limited to the coastal region (figure not shown). This indicates that the atmospheric forcing may play a dominant role in the ocean–atmosphere interaction. In response to the above changes, an upperlevel divergence anomaly is induced (Fig. 10), which triggers a subtropical Rossby wave train that propagates to eastern China. This suggests that the north cold events may be related to the NAO and the associated SST variations in the North Atlantic Ocean on the intraseasonal time scales.
5. Summary and discussion The present study attempts to understand the conditions required for cold air intrusion to eastern China south of 408N by contrasting atmospheric circulation changes corresponding to two different types of strong cold events. In one type (denoted as south cold events), strong cold events with regional average temperature anomalies exceeding 258C affect both north and south of 408N. In the other type (denoted as north cold events), strong cold events are restricted to north of 408N. We
VOLUME 30
FIG. 14. Geopotential height anomalies (contour interval: 20 gpm) and wave activity flux (vector; scale on the right-bottom of the third panel; unit: m2 s22 ) on days (a) 7, (b) 11, and (c) 15 of model integration with an anomalous divergence of 21.74 3 1026 s 21 at 458N, 208W.
identified 37 strong south cold events and 13 strong north cold events during the period 1979–2016. Several important differences have been identified in atmospheric circulation changes corresponding to the two types of cold events. One prominent difference is detected in the location of circulation anomalies. The mid- to high-latitude Eurasian wave train in the upper levels is located at higher latitudes in the north cold events (Fig. 16b) than in the south cold events (Fig. 16a). The midtropospheric East Asian trough extends southwestward in the south cold events (Fig. 16a). This feature is not observed in the north cold events (Fig. 16b). The surface Siberian high expands more southward in the south cold events (Fig. 16a) than in the north cold events (Fig. 16b). In association, anomalous northerly winds in lower levels invade lower latitudes, and bring cold air to south of 408N during the south cold events (Fig. 16a). In contrast, the southward extension of northerly winds is restricted to the areas north of 408N so that the cold air cannot
15 NOVEMBER 2017
SONG AND WU
9263
FIG. 15. SST anomaly (8C) (shading) and surface wind anomaly (vector) on (a) lag 29, (b) lag 27, (c) lag 25, and 9d) lag 23 day of the north cold events. The black vectors and dots indicate the anomalies significant at the 95% confidence level.
invade the region of eastern China south of 408N during the north cold events (Fig. 16b). Another prominent difference is a subtropical wave train in the upper-level emanating from the North Atlantic. This wave train is observed in the north cold events (Fig. 16b) but not in the south cold events (Fig. 16a). This wave train propagates from the North Atlantic to East Asia and induces an anomalous high over southern China. This high obstructs the southwestward deepening of the East Asian trough and the southward expansion of the Siberian high. Because of the above unfavorable conditions, the cold air cannot intrude eastern China south of 408N during the north cold events. The two types of events tend to be associated with different AO behavior. The south cold events occur
during the decay of the negative AO phase, which is a proper condition for cold air outbreaks induced by a Rossby wave train over the mid- to high-latitude Eurasian continent (Jeong and Ho 2005; Park et al. 2011a). Different from the south cold events, the north cold events occur during the development of the negative AO phase. Previous studies have classified the cold events over East Asia based on the phase of the AO (Jeong and Ho 2005; Park et al. 2011a; Park and Ahn 2016). These studies found that the cold events tend to be more frequent during the negative than during the positive AO phase. The present study indicates that the extent and region affected by the cold events may depend upon whether the AO is in the decaying or developing stage of the negative phase. This result suggests that more detailed analysis is needed to
9264
JOURNAL OF CLIMATE
VOLUME 30
Wang and Chen 2010; Woo et al. 2015; Lehtonen and Karpechko 2016). How the stratospheric processes contribute to the strong cold events is a topic worthy of further investigation. Previous studies have noted the influence of the Madden–Julian oscillation (MJO) on the occurrence of the cold events over eastern China (e.g., Jeong et al. 2005; Park et al. 2010; He et al. 2011). The dynamics of the influence of the MJO on the intraseasonal variations over East Asia is an interesting topic. The interannual variability of the frequency and intensity of East Asian cold events and the factors is also a topic for future studies.
FIG. 16. Schematic diagrams showing the main features of the (a) south and (b) north cold events. The red contour denotes the region of the Siberian high anomaly, the blue contour denotes the region of the cold anomaly, the black contour refers to the 500-hPa geopotential height contour at 5300 gpm, the light blue and red shadings denote the negative and positive geopotential height anomalies at 500 hPa, the gray contours denote the geopotential height anomalies at 300 hPa with the bold-gray arrows indicating the subtropical wave train, the blue shading over North Atlantic denotes the cold SST anomaly, and the blue arrows denote anomalous lower-level winds.
document the relationship of the cold events to the AO phase. The subtropical wave train identified in the north cold events is generated by the NAO-related anomalous divergence over the North Atlantic. During the south cold events, the NAO index is small and there is no obvious subtropical wave train. However, the NAO is not the only factor driving the subtropical wave train. There may be other factors that contribute to the anomalous divergence over the North Atlantic (e.g., eastern Pacific SST anomalies; Hu et al. 2017) and other sources along the wave train (e.g., the Mediterranean region; Watanabe 2004). The subtropical wave train may be sensitive to the intensity and location of the anomalous divergence over the North Atlantic according to the sensitivity experiments using the barotropic model. Thus, the subtropical wave train may not always accompany the NAO fluctuations. The present study focuses on the tropospheric circulation changes leading to strong cold events over East Asia. Previous studies have indicated that the signals from the stratosphere could impact the occurrence of cold events over East Asia (e.g., Kolstad et al. 2010;
Acknowledgments. We appreciate the comments from five anonymous reviewers that have helped the improvement of this manuscript. This study is supported by a National Key Basic Research Program of China grant (2014CB953902), a National Key Research and Development Program of China grant (2016YFA0600603), and National Natural Science Foundation of China grants (41530425, 41475081, 41705063, and 41275081). The NCEP reanalysis 2 data were obtained from ftp://ftp. cdc.noaa.gov/, and the NOAA-OISST data were obtained from ftp://eclipse.ncdc.noaa.gov. REFERENCES Banzon, V., T. M. Smith, T. M. Chin, C. Liu, and W. Hankins, 2016: A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies. Earth Syst. Sci. Data, 8, 165–176, doi:10.5194/ essd-8-165-2016. Barnston, A. G., and R. E. Livezey, 1987: Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon. Wea. Rev., 115, 1083–1126, doi:10.1175/ 1520-0493(1987)115,1083:CSAPOL.2.0.CO;2. Bueh, C., N. Shi, and Z. Xie, 2011: Large-scale circulation anomalies associated with persistent low temperature over southern China in January 2008. Atmos. Sci. Lett., 12, 273–280, doi:10.1002/asl.333. Chen, S., R. Wu, and W. Chen, 2015: The changing relationship between interannual variations of the North Atlantic Oscillation and northern tropical Atlantic SST. J. Climate, 28, 485– 504, doi:10.1175/JCLI-D-14-00422.1. Chen, T.-C., M.-C. Yen, W.-R. Huang, and W. A. Gallus, 2002: An East Asian cold surge: Case study. Mon. Wea. Rev., 130, 2271–2290, doi:10.1175/1520-0493(2002)130,2271: AEACSC.2.0.CO;2. ——, W.-R. Huang, and J.-H. Yoon, 2004: Interannual variation of the East Asian cold surge activity. J. Climate, 17, 401–413, doi:10.1175/1520-0442(2004)017,0401:IVOTEA.2.0.CO;2. Chu, P.-S., and S.-U. Park, 1984: Regional circulation characteristics associated with a cold surge event over East Asia during winter MONEX. Mon. Wea. Rev., 112, 955–965, doi:10.1175/ 1520-0493(1984)112,0955:RCCAWA.2.0.CO;2. Ding, Y., 1990: Build-up, air mass transformation and propagation of Siberian high and its relation to cold surge in East Asia. Meteor. Atmos. Phys., 44, 281–292, doi:10.1007/BF01026822.
15 NOVEMBER 2017
SONG AND WU
——, and T. N. Krishnamurti, 1987: Heat budget of the Siberian high and the winter monsoon. Mon. Wea. Rev., 115, 2428–2449, doi:10.1175/1520-0493(1987)115,2428: HBOTSH.2.0.CO;2. Gong, D.-Y., and C.-H. Ho, 2004: Intra-seasonal variability of wintertime temperature over East Asia. Int. J. Climatol., 24, 131–144, doi:10.1002/joc.1006. ——, S.-W. Wang, and J.-H. Zhu, 2001: East Asian winter monsoon and Arctic Oscillation. Geophys. Res. Lett., 28, 2073–2076, doi:10.1029/2000GL012311. He, J., H. Lin, and Z. Wu, 2011: Another look at influences of the Madden-Julian oscillation on the wintertime East Asian weather. J. Geophys. Res., 116, D03109, doi:10.1029/ 2010JD014787. Hoskins, B. J., and T. Ambrizzi, 1993: Rossby wave propagation on a realistic longitudinally varying flow. J. Atmos. Sci., 50, 1661–1671, doi:10.1175/1520-0469(1993)050,1661: RWPOAR.2.0.CO;2. Hu, K.-M., G. Huang, R. Wu, and L. Wang, 2017: Structure and dynamics of a wave train along the wintertime Asian jet and its impact on East Asian climate. Climate Dyn., doi:10.1007/ s00382-017-3674-1, in press. Jeong, J.-H., and C.-H. Ho, 2005: Changes in occurrence of cold surges over East Asia in association with Arctic Oscillation. Geophys. Res. Lett., 32, L14704, doi:10.1029/ 2005GL023024. ——, ——, B.-M. Kim, and W.-T. Kwon, 2005: Influence of the Madden-Julian oscillation on wintertime surface air temperature and cold surges in East Asia. J. Geophys. Res., 110, D11104, doi:10.1029/2004JD005408. ——, B.-M. Kim, C.-H. Ho, D. Chen, and G.-H. Lim, 2006: Stratospheric origin of cold surge occurrence in East Asia. Geophys. Res. Lett., 33, L14710, doi:10.1029/2006GL026607. Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 1631–1643, doi:10.1175/BAMS-83-11-1631. Kim, J.-W., S.-W. Yeh, and E.-C. Chang, 2014: Combined effect of El Niño–Southern Oscillation and Pacific decadal oscillation on the East Asian winter monsoon. Climate Dyn., 42, 957–971, doi:10.1007/s00382-013-1730-z. Kolstad, E. W., T. Breiteig, and A. A. Scaife, 2010: The association between stratospheric weak polar vortex events and cold air outbreaks in the Northern Hemisphere. Quart. J. Roy. Meteor. Soc., 136, 886–893, doi:10.1002/qj.620. Kunkel, K. E., R. A. Pielke Jr., and S. A. Changnon, 1999: Temporal fluctuations in weather and climate extremes that cause economic and human health impacts: A review. Bull. Amer. Meteor. Soc., 80, 1077–1098, doi:10.1175/1520-0477(1999)080,1077: TFIWAC.2.0.CO;2. Lehtonen, I., and A. Y. Karpechko, 2016: Observed and modeled tropospheric cold anomalies associated with sudden stratospheric warmings. J. Geophys. Res. Atmos., 121, 1591–1610, doi:10.1002/2015JD023860. Lu, Q. F., W. J. Zhang, P. Zhang, X. B. Wu, F. Y. Zhang, Z. Q. Liu, and M. B. Dale, 2010: Monitoring the 2008 cold surge and frozen disasters snowstorm in south China based on regional ATOVS data assimilation. Sci. China Earth Sci., 53, 1216– 1228, doi:10.1007/s11430-010-3040-1. Marshall, J., H. Johnson, and J. Goodman, 2001: A study of the interaction of the North Atlantic Oscillation with ocean circulation. J. Climate, 14, 1399–1421, doi:10.1175/ 1520-0442(2001)014,1399:ASOTIO.2.0.CO;2.
9265
Ou, T., D. Chen, J.-H. Jeong, H. W. Linderholm, and T. Zhou, 2015: Changes in winter cold surges over southeast China: 1961 to 2012. Asia-Pac. J. Atmos. Sci., 51, 29–37, doi:10.1007/ s13143-014-0057-y. Panagiotopoulos, F., M. Shahgedanova, A. Hannachi, and D. B. Stephenson, 2005: Observed trends and teleconnections of the Siberian high: A recently declining center of action. J. Climate, 18, 1411–1422, doi:10.1175/JCLI3352.1. Park, H.-J., and J.-B. Ahn, 2016: Combined effect of the Arctic Oscillation and the western Pacific pattern on East Asia winter temperature. Climate Dyn., 46, 3205–3221, doi:10.1007/ s00382-015-2763-2. Park, T.-W., J.-H. Jeong, C.-H. Ho, and S.-J. Kim, 2008: Characteristics of atmospheric circulation associated with cold surge occurrences in East Asia: A case study during 2005/06 winter. Adv. Atmos. Sci., 25, 791–804, doi:10.1007/s00376-008-0791-0. ——, C.-H. Ho, S. Yang, and J.-H. Jeong, 2010: Influences of Arctic Oscillation and Madden-Julian Oscillation on cold surges and heavy snowfalls over Korea: A case study for the winter of 2009–2010. J. Geophys. Res., 115, D23122, doi:10.1029/ 2010JD014794. ——, ——, and ——, 2011a: Relationship between the Arctic Oscillation and cold surges over East Asia. J. Climate, 24, 68–83, doi:10.1175/2010JCLI3529.1. ——, ——, S.-J. Jeong, Y.-S. Choi, S. K. Park, and C.-K. Song, 2011b: Different characteristics of cold day and cold surge frequency over East Asia in a global warming situation. J. Geophys. Res., 116, D12118, doi:10.1029/2010JD015369. ——, ——, and Y. Deng, 2014: A synoptic and dynamical characterization of wave-train and blocking cold surge over East Asia. Climate Dyn., 43, 753–770, doi:10.1007/ s00382-013-1817-6. Plumb, R. A., 1985: On the three-dimensional propagation of stationary waves. J. Atmos. Sci., 42, 217–229, doi:10.1175/ 1520-0469(1985)042,0217:OTTDPO.2.0.CO;2. Sardeshmukh, P. D., and B. J. Hoskins, 1988: The generation of global rotational flow by steady idealized tropical divergence. J. Atmos. Sci., 45, 1228–1251, doi:10.1175/ 1520-0469(1988)045,1228:TGOGRF.2.0.CO;2. Shoji, T., Y. Kanno, T. Iwasaki, and K. Takaya, 2014: An isentropic analysis of the temporal evolution of East Asian cold air outbreaks. J. Climate, 27, 9337–9348, doi:10.1175/ JCLI-D-14-00307.1. Song, L., L. Wang, W. Chen, and Y. Zhang, 2016: Intraseasonal variation of the strength of the East Asian trough and its climatic impacts in boreal winter. J. Climate, 29, 2557–2577, doi:10.1175/JCLI-D-14-00834.1. Takaya, K., and H. Nakamura, 2001: A formulation of a phaseindependent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. J. Atmos. Sci., 58, 608–627, doi:10.1175/1520-0469(2001)058,0608: AFOAPI.2.0.CO;2. ——, and ——, 2005a: Geographical dependence of upper-level blocking formation associated with intraseasonal amplification of the Siberian high. J. Atmos. Sci., 62, 4441–4449, doi:10.1175/JAS3628.1. ——, and ——, 2005b: Mechanisms of intraseasonal amplification of the cold Siberian high. J. Atmos. Sci., 62, 4423–4440, doi:10.1175/JAS3629.1. ——, and ——, 2013: Interannual variability of the East Asian winter monsoon and related modulations of the planetary waves. J. Climate, 26, 9445–9461, doi:10.1175/ JCLI-D-12-00842.1.
9266
JOURNAL OF CLIMATE
Thompson, D. W. J., and J. M. Wallace, 1998: The Arctic Oscillation signature in the wintertime geopotential height and temperature fields. Geophys. Res. Lett., 25, 1297–1300, doi:10.1029/98GL00950. ——, and ——, 2000: Annular modes in the extratropical circulation. Part I: Month-to-month variability. J. Climate, 13, 1000–1016, doi:10.1175/1520-0442(2000)013,1000: AMITEC.2.0.CO;2. Wang, L., and W. Chen, 2010: Downward Arctic Oscillation signal associated with moderate weak stratospheric polar vortex and the cold December 2009. Geophys. Res. Lett., 37, L09707, doi:10.1029/2010GL042659. Watanabe, M., 2004: Asian jet waveguide and a downstream extension of the North Atlantic Oscillation. J. Climate, 17, 4674– 4691, doi:10.1175/JCLI-3228.1. Wen, M., S. Yang, A. Kumar, and P. Zhang, 2009: An analysis of the large-scale climate anomalies associated with the snowstorms affecting China in January
VOLUME 30
2008. Mon. Wea. Rev., 137, 1111–1131, doi:10.1175/ 2008MWR2638.1. Woo, S.-H., B.-M. Kim, and J.-S. Kug, 2015: Temperature variation over East Asia during the life cycle of weak stratospheric polar vortex. J. Climate, 28, 5857–5872, doi:10.1175/ JCLI-D-14-00790.1. Wu, B., and J. Wang, 2002: Winter Arctic Oscillation, Siberian high and East Asian winter monsoon. Geophys. Res. Lett., 29, 1897, doi:10.1029/2002GL015373. Zhang, Y., K. R. Sperber, and J. S. Boyle, 1997: Climatology and interannual variation of the East Asian winter monsoon: Results from the 1979–95 NCEP/NCAR reanalysis. Mon. Wea. Rev., 125, 2605–2619, doi:10.1175/1520-0493(1997)125,2605: CAIVOT.2.0.CO;2. Zhou, W., J. C. L. Chan, W. Chen, J. Ling, J. G. Pinto, and Y. Shao, 2009: Synoptic-scale controls of persistent low temperature and icy weather over southern China in January 2008. Mon. Wea. Rev., 137, 3978–3991, doi:10.1175/2009MWR2952.1.
