Isentropic Analysis of Regional Cold Events over Northern China

Qingyi LIU, Qian LIU, and Guixing CHEN

School of Atmospheric Sciences, and Guangdong Province Key Laboratory for Climate Change and Natural Disaster

Studies, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China

ABSTRACT From the perspective of cold air mass (CAM) analysis, we examine the characteristics and mechanisms of regional cold events (RCEs) over northwestern and northeastern China in the past 58 years (1958/59?2015/16). The RCEs in northwestern (northeastern) China are shown to have an average duration of 6.8 (4.7) days with a moderate (sharp)temperature drop. We quantitatively estimate the RCE-related CAM, for the first time, using an isentropic analysis method.Before an RCE in northwestern China, CAM is accumulated in western Siberia with convergent CAM flux under a blocking pattern in the Urals region. During RCE outbreak, CAM penetrates the valleys of the Tianshan?Altay Mountains to the Tarim Basin and Hexi Corridor. The CAM moves slowly because of the blocking pattern and orographic effect,which explains the relatively long duration of RCEs. Comparatively, during RCEs in northeastern China, the CAM depth anomaly originates more to the east and quickly passes the Mongolian Plateau guided by an eastward-moving trough.Diagnostic analyses further show that adiabatic processes play a crucial role in regulating the local change of CAM depth during the two kinds of RCEs. The advection term of adiabatic processes mainly increases the CAM depth during RCE outbreak, while the convergence term increases (reduces) CAM depth before (after) RCE outbreak. Both terms are relatively strong during RCEs in northeastern China, resulting in the rate of change in CAM depth being ～50% larger than for those in northwestern China. Therefore, the variations of RCEs in duration and intensity can be well explained by the different evolution of CAM depth and flux.

Key words: cold events, northern China, cold air mass, isentropic analysis, regional difference

1. Introduction

In the winter season, cold-air outbreaks are one of the major meteorological disasters in East Asia (Wen et al.,2009; Zhou et al., 2009; Lu et al., 2010; Wang et al., 2014,2017b). In particular, strong cold events with prolonged anomalous low temperature have severe influence on society and economy (Anderson and Bell, 2009; Zhang and Qian, 2011;Wang et al., 2012a). Previous studies show that more than half of such cold events occur in several parts of China, suggesting strong regionality (Bueh et al., 2011a; Peng and Bueh, 2011; Feng et al., 2015). These so-called regional cold events (RCEs) are frequently observed in northern China (Wang and Ding, 2006), but their occurrence, duration and intensity may vary in the subregions of northern China. RCEs occur more frequently in northeastern China than in other parts of northern China (Gao et al., 2019).Many RCEs in northeastern China have a relatively short duration, while those in northwestern China usually persist for several days (Wang et al., 2017a). RCEs in northeastern China are also characterized by a sharper temperature drop than those in other areas (Qian and Zhang, 2007). To clarify the possible causes of the abovementioned differences,there is a need for detailed analyses of RCEs in the subregions of northern China.

Previous studies have recognized that the formation and evolution of cold events are closely associated with dynamic and thermodynamic processes from the surface to the troposphere. The precondition and outbreak of cold events are characterized by the intensification and southward movement of the Siberian high in the near-surface layer (Ding, 1990; Zhang et al., 1997; Bueh et al., 2011b;Park et al., 2011; Peng and Bueh, 2012), indicating the accumulation and movement of cold air mass (CAM). The outbreak of cold events is also usually characterized by strong cold advection in the middle and lower troposphere (Kim et al., 2014; Cheung et al., 2015; Wang and Chen, 2014;Zhuang et al., 2018), which manifests as an equatorward transportation of CAM. The cold advection is guided by amplified westerly disturbances, such as the blocking pattern over the Urals region in the middle and upper troposphere (Wang et al., 2010; Cheung et al., 2013; Xie and Bueh, 2017; Lin et al., 2018). The pathway and southward extension of the cold advection are also regulated by the tilting of the axis and the strength of the East Asian trough (Wang et al.,2009; Feng et al., 2015; Song et al., 2016; Song and Wu,2017). These studies from many aspects indicate that cold events are associated with the evolution of vertically extending CAM under various atmospheric processes. Therefore,estimating the vertically integrated properties of CAM may provide new insights into the characteristics and regional differences of RCEs.

To describe CAM quantitatively, Iwasaki et al. (2014)proposed an isentropic analysis method that defines the air below a designated threshold of potential temperature as CAM. The thickness, coldness, flux and generation/loss of CAM can be measured in an explicit manner. The method has been applied to describe streams of cold-air outbreaks(Shoji et al., 2014; Kanno et al., 2017; Liu et al., 2019), the relationship between cold-air outbreaks and tropical signals(Abdillah et al., 2017), and global-scale air mass exchange(Kanno et al., 2015a, b). It is also suitable for case studies of cold events. For instance, Yamaguchi et al. (2019) analyzed the accumulation and movement of CAM to explain in detail the processes of a record-breaking cold event over East Asia in January 2016. The isentropic analysis method may help us to clarify the evident differences of the RCE climatology over northern China from the perspective of quantified CAM.

In this study, we apply the isentropic framework of Iwasaki et al. (2014) to depict CAM variations during RCEs in northern China. The aim is to clarify how the evolution of CAM regulates the different features of RCEs. The rest of the paper is organized as follows: Section 2 introduces the data and methods used in this study. Section 3 examines the statistics of RCEs in the past 58 years, as well as the related large-scale circulations. Section 4 describes the close relationships between the properties of CAM and the duration/intensity of RCEs, considering the differences in atmospheric conditions and the orographic effect between the two subregions.In section 5, diagnostic analysis results are used to explain the physical processes that govern the CAM variations associated with the precondition/outbreak of RCEs. A summary of the major results is presented in section 6, along with some further discussion.

2. Data and methods

2.1. Data source

The analyses are based on data in boreal winter (December to February) over a 58-yr period (1958/59?2015/16). Specifically, we utilize the six-hourly Japanese 55-yr Reanalysis (JRA-55) with a spatial resolution of 1.25° latitude ×1.25° longitude (Kobayashi et al., 2015). JRA-55 is one of the more recent reanalyses with advanced data assimilation and model physical schemes, and it outperforms its predecessor in almost all aspects (Harada et al., 2016). The pressure-level product of JRA-55 has a high vertical resolution of 37 pressure levels with an interval of 25 hPa below 750 hPa, which thus depicts well the variables in the lower troposphere. An evaluation of four mainstream reanalysis datasets, including JRA-55, over East Asia showed that JRA-55 represents well the temperature and winds from the surface to the upper troposphere (Chen et al., 2014). Regarding the representation of CAM, JRA-55 has a good consistency with other reanalysis datasets (Kanno et al., 2016). It has also been applied to depict the fine structures and temporal evolutions of CAM during a specific cold-air outbreak(Yamaguchi et al., 2019).

2.2. Definition of RCEs

To examine the detailed differences among RCEs in this study, we divide northern China into northwestern China (35°?50°N, 70°?100°E) and northeastern China(35°?50°N, 100°?130°E), as shown in Fig. 1a. The anomaly of surface air temperature averaged over these two subregions is estimated using JRA-55 and the climate-mean diurnal variation is removed. An RCE is identified when the regional-mean temperature anomaly exceeds ?4°C and lasts for at least one day, which is similar to the method used in Song and Wu (2017). This relative threshold of ?4°C exceeds one standard deviation of the regional-mean surface air temperature in both regions, so that highly anomalous events can be identified. As exemplified in Fig. 1b, the duration of an RCE is defined by the period with a temperature anomaly lower than ?4°C, while the intensity of an RCE is given as the anomaly of minimum temperature. For brevity, day 0 denotes the onset day of an RCE, and day ?1 (+1)denotes the first day before (after) the onset of an RCE, and so on.

2.3. Isentropic analysis of CAM

Isentropic coordinates are convenient for tracing the air mass trajectory because potential temperature is conserved under adiabatic processes. To analyze the CAM activity during RCEs, we diagnose the CAM in an isentropic coordinate (Iwasaki et al., 2014). The CAM thickness is measured by the depth of pressure (DP), i.e., the difference between the surface pressure (ps) and the pressure at an isentropic surface of threshold potential temperatureThe threshold isentropic surface is set as 280 K, which has been shown to be suitable for defining the wintertime CAM (Iwasaki et al., 2014; Kanno et al., 2015a).The horizontal flux of CAM is calculated by the vertical integration of horizontal wind (v) from the ground to the level of the threshold potential temperatureThe tendency of CAM depthcan be written as the sum of the flux convergence and the genesis/loss rate of CAM[G(θT)]:

Following Yamaguchi et al. (2019), the mean wind of CAM is defined as the CAM flux divided by the depth:

The tendency of CAM depth can be rewritten as below:

The convergence of CAM flux in Eq. (1) is thus divided into the first two terms on the right-hand side of Eq. (3), by which we can estimate the contributions of advection and convergence by the mean wind of CAM to the local change of CAM depth, respectively. The diabatic term of CAM [G(θT)] in Eq. (1) is estimated as a residual of the conservation relation. Overall, the isentropic analysis gives a quantitative diagnosis tool for CAM streams, which estimates the genesis/loss of CAM based on its conservation.This tool has been used to estimate the CAM depth and fluxes during cold surges, as well as their relationship to surface temperature (Shoji et al., 2014; Abdillah et al., 2018;Yamaguchi et al., 2019).

3. Characteristics of RCEs in northern China

3.1. RCE statistics

In this section, we describe the characteristics of RCEs in the western and eastern parts of northern China, from the aspects of occurrence frequency, duration and intensity.Figure 2a shows that 83 RCEs can be identified as having occurred in northwestern China during 1958?2015, with a frequency of 1.4 times per year. Among them, 47 events are in January, which account for 56.6% of the total events in winter. The second highest frequency of occurrence (22 events) appears in December, and the rest (14 events)appear in February. Comparatively, there are 153 RCEs in northeastern China, which is almost twice that in northwestern China. This indicates RCEs are relatively frequent in the eastern region, which is consistent with other studies (e.g.,Gao et al., 2019). The occurrence frequency of RCEs in northeastern China is highest (57.5%) in January and lowest(14.3%) in February. The subseasonal variations of RCEs are thus similar in the two subregions, despite the difference in occurrence frequency. Such a temporal distribution of RCEs is consistent with the monthly variation in the intensity of winter monsoon in terms of surface temperature and sea level pressure (SLP), which maximize in January(Zhang et al., 1997; Zhuang et al., 2018).

The durations of RCEs in the two sub-regions are shown in Fig. 2b. In northwestern China, the average duration of RCEs is 6.8 days (black cross), while the median duration is 4.5 days (red bar), suggesting a distribution skewed to a long-duration range. Half of the RCEs can last for 2.5 to 8.0 days (blue box). Some RCEs exceeding the 90th percentile can last for more than 15 days (red cross marks). As for the RCEs in northeastern China, the average duration is 4.7 days, which is obviously shorter than that of the RCEs in northwestern China, with a 99% confidence level. Meanwhile, the difference between the average and median duration (1.5 days) is somewhat smaller than that of 2.3 days in northwestern China. Half of the RCEs in northeastern China last 2.0 to 5.5 days, suggesting that they are closely associated with short-period synoptic disturbances. The 90th-percentile RCEs last for about 10.5 days, which is shorter than in northwestern China (～15 days). It is thus concluded that most RCEs in northeastern China have a relatively short duration, while those in northwestern China last longer and vary across a relatively large range of duration.

Figure 2c shows the intensity of the RCEs, i.e., the anomaly of minimum surface temperature during the events. The RCEs in northwestern China have an average intensity of?6.8°C (black cross) and a median intensity of ?6.5°C (red bar). Half of the RCEs have an intensity ranging from?5.7°C to ?7.7°C (blue box). The extremely strong RCEs(90th percentile) have an anomaly of minimum temperature below ?8.6°C (red crosses at the bottom). In northeastern China, the average (median) intensity of RCEs is ?7.0°C(?6.7°C), which is similar to those in northwestern China.Half of the RCEs range from ?5.6°C to ?8.0°C (blue box).The extremely strong RCEs have an anomaly of minimum temperature below ?9.4°C. Therefore, RCEs seem to induce anomalies of minimum temperature at a comparable magnitude in the two regions, although they have large differences in occurrence and duration.

3.2. Temporal evolution of RCEs and associated largescale circulation

In this section, we first examine the temporal variations of composite RCEs. Figure 3a shows the variations of the regional mean surface temperature during the RCEs in northwestern China. The temperature begins to decrease at day ?4.5 and then drops to the minimum of ?5.7°C at day+1.25. The largest rate of change in temperature is estimated as ?1.9°C d?1near the onset of RCEs. The regional mean temperature anomaly below ?4.0°C lasts till day+4.25. Comparatively, the RCEs in northeastern China are characterized by a decrease in surface temperature that begins at day ?2.5 (Fig. 3b), with a delay of two days compared to those in northwestern China. The minimum temperature anomaly (?5.6°C) occurs at day +1. Therefore, the decreasing temperature lasts for 3.5 days, which is much shorter than that of 5.75 days in northwestern China. The largest rate of change in temperature is as large as ?2.4°C d?1.The regional mean temperature anomaly below ?4.0°C lasts for 2.75 days, which is shorter than that in northwestern China. Therefore, we can see that RCEs in northwestern China are characterized by relatively long periods of temperature drop and cold anomalies, while those in northeastern China undergo a sharper drop of temperature and a shorter duration of cold anomalies. These results are analogous to those reported in previous studies (Qian and Zhang, 2007;Wang et al., 2017a).Figure 4 further shows the progress of the extent of temperature anomalies exceeding ?4°C. At day ?4 of the RCEs in northwestern China, the temperature anomaly originates in the Siberian region adjacent to northwestern China(Fig. 4a). From day ?4 to ?1, its boundary gradually extends to the north side of the Tianshan Mountains. The boundary of low temperature crosses the Tianshan?Altay area and reaches the north side of the Qinghai?Tibetan Plateau at day 0. The boundary then extends mainly southeastward to the Hexi Corridor and partly southwestward to the Tarim Basin. At day +2, low temperature influences almost the entire region of northwestern China, and its effects even extend to northeastern China. Here, we further show the center of the temperature anomaly (colored dots) and its pathway. From day ?4 to 0, the center moves southward to northwestern China. Then, it passes the valleys between the Tianshan and Altay mountains from day +1 to +2, and reaches the Hexi Corridor at day +4. The movement speed of the center is estimated and shown in Fig. 4c. The movement speed is 200?300 km d?1from day ?4 to +1, and increases to 400?550 km d?1after day +2. Such an acceleration of movement speed coincides with the passage of the Tianshan?Altay Mountains, as discussed in section 4.

Fig. 3. Time series of the regional-mean temperature anomaly (black line) and its rate of change (red line) during RCEs in(a) northwestern and (b) northeastern China. (c, d) As in (a, b) but for the anomaly of CAM depth and its rate of change.

Figure 4b shows that the temperature anomaly associated with the RCEs in northeastern China originally occurs in the Siberian region at day ?4, which has a similar location to those events in northwestern China. From day ?4 to?2, its boundary extends to Lake Baikal and the Tianshan Mountains. Different from the western boundary blocked by the Tianshan Mountains, the eastern boundary crosses the Mongolian Plateau and reaches northeastern China at day?1. The low temperature anomaly dominates almost the whole of northeastern China at day 0, and its boundary can further influence central and southern China. From day ?4 to 0, the center of the temperature anomaly moves southeastward and reaches Lake Baikal, which indicates a pathway more to the east than that in northwestern China, despite the similar location of origin. After day 0, the center moves southward to the North China Plain at day +2. The movement speed of the low-temperature center is relatively slow

(200?300 km d?1) at days ?4 and ?3 (Fig. 4d). However,the movement accelerates dramatically to a speed above 400 km d?1after day ?2 and reaches its maximum (628 km d?1)at day +1. Therefore, the movement of the center of low temperature is much faster than that in northwestern China from day ?3 to +2 (Figs. 4c and d). This difference may be due to the effect of different orography along the pathways of the cold air. Overall, RCEs in northwestern China are characterized by relatively slow movement, while those in northeastern China have higher movement speeds.

Figure 5 shows the evolution of large-scale atmospheric conditions associated with RCEs. At day ?4 of the RCEs in northwestern China, a ridge at the 500-hPa geopotential height appears upstream of the Urals region around(60°N, 60°E) (Fig. 5a). The ridge is collocated with an anomaly of SLP, which is located to the west of the temperature anomaly. At day ?2, the 500-hPa ridge and SLP anomaly amplify with a slow eastward movement to the Urals region and a northeastward tilt to Siberia (Fig. 5b), indicating the development of a blocking pattern (e.g., Cheung et al.,2015). At the east of the ridge, the northwesterly wind is enhanced in the lower troposphere, which may lead to cold advection downstream to northwestern China. At the onset day of RCEs, the 500-hPa ridge and SLP anomaly reach their maxima near northwestern China (Fig. 5c). The southeastern boundary of the SLP anomaly coincides with that of the temperature anomaly. At day +2, the 500-hPa ridge weakens along with slow eastward movement. The boundaries of SLP and temperature anomalies arrive at the northern periphery of the Qinghai?Tibetan Plateau and move into the Hexi corridor (40°N, 115°E) (Fig. 5d). The boundaries thus seem to take around 5 days (from day ?2 to +2) passing northwestern China.

Fig. 4. Temporal evolutions of the low-temperature zone (temperature anomaly lower than ?4°C) for RCEs in (a) northwestern and (b) northeastern China. Colored shading in (a) and (b) stands for the day when the temperature anomaly becomes lower than ?4°C for the first time. Colored dots denote the daily mean center of the low-temperature zone. Grey dashed contours mark the elevations of 2000 and 4000 m. Black dashed rectangles in (a) and (b) denote northwestern and northeastern China, respectively. (c, d) The movement speed of the low-temperature center in (c) northwestern and (d) northeastern China.

As for the RCEs in northeastern China, the 500-hPa ridge and SLP anomaly move rapidly from the Urals region to Lake Baikal from day ?4 to 0 (Figs. 5e?g). At the onset day, the East Asian trough deepens obviously with a strengthened northwesterly wind over northeastern China(Fig. 5g). The boundaries of SLP and temperature anomalies pass rapidly through northeastern China. They further extend to southern China but weaken at day +2 (Fig. 5h). In contrast to the events in northwestern China, the 500-hPa ridge and SLP anomaly during RCEs in northeastern China show a much faster eastward movement. Given the strong connection between mid—lower tropospheric conditions and surface temperature, there is a need to analyze RCEs through estimating the dynamic/thermodynamic properties of cold-air activities in the troposphere.

4. CAM associated with RCEs

4.1. Spatiotemporal variations of CAM during RCEs

In this section, we describe the dynamic and thermodynamic properties of cold air quantitively using the isentropic analysis method as introduced in section 2. The coldair activities are measured in terms of the depth and flux of CAM to explain the evolution of RCEs. Figure 3c shows the temporal variations of the CAM depth anomaly averaged in northwestern China. The CAM depth anomaly begins to increase from day ?5 and reaches a maximum of 65.8 hPa at day +0.5. The rate of increase in CAM depth has a maximum of 26.1 hPa d?1at day ?0.75. The maxima of both CAM depth and its rate of change have a lead of ～0.5 d to those of the surface temperature anomaly. This phase shift is because the anomaly of potential temperature is tilted southeast with height (figure not shown). As for the RCEs in northeastern China (Fig. 3d), the CAM depth anomaly appears from day ?3 and its maximum (92.0 hPa) appears at day+0.5. The maximum rate of increase in CAM depth is estimated as 46.0 hPa d?1. The CAM depth in northeastern China thus seems to increase much faster than that in northwestern China (c.f., Figs. 3c and d). This difference in the rate of change in CAM depth corresponds well to the faster decrease in surface temperature in northeastern China than in northwestern China (c.f., Figs. 3a and b). Also of note is that the period with increasing CAM depth is about 3 d in northeastern China and 5.25 d in northwestern China, which also coincides with the different length of cooling period in the two sub-regions.

Fig. 5. Composite large-scale atmospheric conditions during RCEs in (a?d) northwestern and (e?h) northeastern China at days ?4, ?2, 0 and +2. Black contours denote the geopotential height at 500 hPa with intervals of 100 gpm,colored shading denotes the SLP anomaly, and the vectors stand for the wind at 850 hPa. Blue contours denote the surface temperature anomaly of ?4°C in the corresponding days. Black dashed rectangles in (a?d) and (e?h) denote northwestern and northeastern China, respectively. Black bold contours denote the elevations of 2000 and 4000 m.

Figure 6 further shows the spatial patterns of CAM depth and flux during the RCEs. At day ?4 of the RCEs in northwestern China, the anomaly of CAM depth appears in western Siberia (Fig. 6a). The CAM flux shows an anomalous cyclone (marked “C”) in western Siberia where CAM depth is accumulated. At day ?2, an anticyclonic anomaly of CAM flux (marked “A”) is established in the Urals region and forms a dipole pattern with the cyclone in western Siberia (Fig. 6b), which may relate to the development of the blocking pattern at 500 hPa (Fig. 5b). This dipole pattern induces the anomalous northeasterly flux of CAM at high latitudes (50°?70°N). The anomalous flux turns northwesterly and guides the CAM to northwestern China. Thus,the anomaly of CAM depth intensifies in strength and enlarges in area, which coincides with the extended area of the temperature anomaly. At day 0, the anomaly of CAM depth dominates the Tianshan?Altay region, with its boundary reaching the northern periphery of the Qinghai?Tibetan Plateau (Fig. 6c). Both the anomalies of CAM depth and flux have a local maximum in the valleys between the Tianshan and Altay mountain ranges, implying a channel for CAM movement. In the following days, one part of the CAM moves westward into the Tarim Basin, while the major part moves to the Hexi Corridor and Mongolian Plateau with an enhanced southeastward flux at the head of the CAM depth anomaly (Fig. 6d). The anomaly of CAM depth extends to its largest range and corresponds to the mature stage of RCEs.

Fig. 6. Spatiotemporal evolution of the CAM anomaly for RCEs in (a?d) northwestern and (e?h) northeastern China.Colored shading denotes the anomaly of CAM depth. Vectors denote the anomaly of CAM flux. Red lines (dots)indicate the trajectories (centers) of the CAM depth anomaly. Black dashed rectangles in (a?d) and (e?h) denote northwestern and northeastern China, respectively. Black contours mark the elevations of 2000 and 4000 m. Red contours denote the surface temperature anomaly of ?4°C in the corresponding days. Red rectangles in (d) and (h)mark the propagation route of CAM and low temperature for making Fig. 8. The “A” and “C” in the figures denote the centers of the anticyclonic and cyclonic CAM flux, respectively.

Also of note is that there is a spatial shift between the CAM depth anomaly (Figs. 6a?d) and the SLP anomaly(Figs. 5a?d). The anomalous center of CAM depth is generally located to the east of the SLP anomaly, where the northerly winds and resultant cold advection prevail. A similar shift between SLP and surface temperature has also been reported in previous studies (Peng and Bueh, 2012; Cheung et al., 2015; Song and Wu, 2017). Further, we can see that the anomalous center of CAM depth is displaced southeast of the surface temperature anomaly during the RCEs (Figs.6a?d). Such a spatial shift actually shows that the anomaly of potential temperature is tilted southeast with height (figure not shown). This shift also explains the maximum CAM depth having a lead time of 0.5 d before the lowest surface temperature (Figs. 3a and c).

During the RCEs in northeastern China, the anomaly of CAM depth originates north of the Altay Mountains at day?4 (Fig. 6e). The anomalous CAM flux shows the dipole pattern with an anticyclone and a cyclone over western Siberia.The centers of the CAM depth anomaly and the dipole of CAM flux are located ～20° east of those in Fig. 6a. At day?2, the CAM depth anomaly dominates the Mongolian Plateau, centered at Lake Baikal. The dipole of CAM flux also moves rapidly eastward, which leads to the strong northwesterly flux near the center of CAM depth over the Mongolian Plateau (Fig. 6f). At day 0, the anomaly of CAM depth and strong northwesterly flux of CAM dominate northeastern China, which correspond to the onset of the temperature anomaly (Fig. 6g). In the following days, the anomalies of CAM depth and flux reach southern China, the East China Sea and the Sea of Japan, where they begin to dissipate(Fig. 6h). The track of the CAM depth anomaly can be defined by the centers of the highest 1% of CAM depth within (20°?70°N, 40°?160°E) (dots in Fig. 6h). This track shows the anomaly of CAM depth moves from the north of the Altay Mountains to Lake Baikal, and finally reaches the North China Plain, which coincides well with the movement of the temperature anomaly in Fig. 4b. The southeastward movement of CAM depth seems to be guided by the anomalous northerly CAM flux between the dipole pattern,which agrees with the case study of Yamaguchi et al. (2019)carried out for a record-breaking RCE in East Asia.Comparing the RCEs in northwestern and northeastern China (Fig. 6), one important feature is the difference in the location and movement of the CAM depth anomaly. Figure 7 further shows the movement speed of the CAM depth anomaly, estimated by its moving centers (red dots in Figs. 6d and h). During the events of northwestern China, the movement speed of the center is relatively slow before day +1,with a range of 280?600 km d?1. It increases dramatically to about 900 km d?1at days +2 and +3, when the center passes the Tianshan?Altay Mountain regions (Fig. 6d). A longitude?time diagram of CAM and temperature, which is calculated by the zonal-mean variables in the red parallelogram in Figs. 6d and h, also confirms the change in the movement speed of the CAM depth anomaly after passing the Tianshan?Altay Mountains (Fig. 8a). This feature of CAM movement corresponds well to that of the temperature anomaly(Fig. 8b). These results suggest that the orographic effect plays an important role in regulating the movement of CAM, thereby affecting the evolution of the temperature anomaly during RCEs in northwestern China.As for the RCEs in northeastern China, the center of the CAM depth anomaly remains at a movement speed of 500?700 km d?1from day ?3 to +1, which is much faster than that in the northwestern China events (Fig. 7). From day +2, the movement speed of the center for the RCEs in northeastern China begins to decrease because of the dissipation of CAM over the ocean surface (Fig. 6h). Figure 8c also shows that the CAM depth anomaly tends to move at a steady speed of ～700 km d?1from day ?2 to +2 as it moves across the Mongolian Plateau, which corresponds to that of the temperature anomaly in Fig. 8d. It seems that the orographic effect on CAM is not so evident for RCEs in northeastern China, compared to that in northwestern China. Therefore, the fast movement of CAM in northeastern China likely explains the rapid drop in temperature. Comparatively, the relatively slow movement of CAM in northwestern China owing to orographic effects may account for the moderate drop in temperature but relatively long-lasting temperature anomaly.

4.2. CAM anomalies associated with the intensity and duration of RCEs

Fig. 7. Movement speed of the center of the CAM depth anomaly derived from the red dots in Fig. 6. The blue and red lines denote the values during the RCEs in northwestern and northeastern China, respectively.

The intensity and duration of low temperature vary largely among the RCEs, as shown in Figs. 2b and c, which may be closely associated with the variations in CAM. To clarify this linkage, we estimate the regression patterns of CAM depth/flux onto the intensity of RCEs (Fig. 9). The patterns present the departure of CAM depth/flux from the events’ average in Fig. 6 with respect to the enhancement of RCE intensity by 1°C. Figures 9a and b show that, at days?4 and ?2, there are positive departures of CAM depth and northeasterly flux over Siberia (50°?70°N, 60°?110°E).The increased accumulation of CAM depth thus favors the subsequent intensification of the RCEs in northwestern China. At day 0, the enhancement of CAM depth occurs in the Tianshan?Altay region (Fig. 9c), which overlaps with the anomaly of CAM depth shown in Fig. 6c. Over there, an additional increase in CAM depth by ～40 hPa, which is comparable to 30% of the composite anomaly in Fig. 6c, corresponds to a decrease in minimum temperature by 1°C. The departure of CAM flux also suggests a strengthened anticyclonic pattern over Siberia in Fig. 6c. At day +2, when the anomaly of CAM depth has moved southeastward to the downstream region (Fig. 6d), the departure of CAM depth in northwestern China caused by its stagnation usually corresponds to the strong RCEs (Fig. 9d). The maintenance of CAM depth in northwestern China, particularly after the onset of RCEs, also regulates the duration of low temperature (figures not shown). It is concluded that the enhanced accumulation of CAM depth near northwestern China and the strengthened anticyclonic CAM flux over Siberia are favorable for the occurrence of strong and long-lasting RCEs.

As for the RCEs in northeastern China, the departure of CAM depth over Siberia at day ?4 has a weak relationship with the intensity of RCEs (Fig. 9e). At day ?2, a positive departure of CAM depth of ～20 hPa appears over Siberia(Fig. 9f). It then moves to Lake Baikal and increases to ～30 hPa at day 0 (Fig. 9g). In the following days, the enhanced CAM depth in northeastern China corresponds to the anomalously low minimum temperature (Fig. 9h). The departure of CAM depth in Figs. 9f?h is usually located to the northwest of the CAM center, shown in Figs. 6f?h, and a similar pattern of CAM depth departure is also observed in prolonged RCEs (figures not shown). This distribution of CAM depth departure indicates that the stronger and longer-duration RCEs tend to have a larger spatial extent of the CAM depth anomaly and a greater supply of CAM in upstream areas.We also note the departure of CAM depth in the Sea of Okhotsk at days ?4 and ?2 (Figs. 9e?f). It seems that some parts of the CAM affecting northeastern China may originate from there during strong RCEs, as also noted in the case study of Yamaguchi et al. (2019). Overall, the CAM depth and flux are closely associated with the evolution of RCEs(section 4.1), and their variations among RCEs also regulate the intensity and duration of low temperature (section 4.2).

5. Physical processes governing the evolution of CAM

Because the variation in CAM depth is closely related to RCEs, in this section, we diagnose the contributions of various physical processes to the local change in CAM depth using Eq. (3), as introduced in section 2. Figure 10 shows the spatial patterns of the local change in CAM depth and the rate of change by various processes during RCEs in northwestern China. From day ?4 to ?2, the positive tendency of CAM depth is located over Siberia (Fig. 10a), which corresponds to the accumulation of CAM depth (Figs. 6a and b).At day 0, there is an increasing CAM depth to the north of the Qinghai?Tibetan Plateau where the cold air breaks out.By day +2, an increasing CAM depth and northerly flux appear in most areas of eastern China, while a decreasing CAM depth occurs in northwestern China. The spatiotemporal variations of CAM tendency thus represent well the accumulation and outbreaks of cold air. Figure 10b shows that the local change in the CAM depth anomaly by diabatic heating/cooling is small at mid—high latitudes during the RCEs. The local change in CAM depth by adiabatic processes (Fig. 10c), however, is highly analogous to the total tendency in Fig. 10a in terms of pattern and magnitude.This suggests that the local change in CAM depth is mainly attributable to adiabatic processes rather than diabatic heating/cooling during RCEs, which is consistent with the findings from the case study by Yamaguchi et al. (2019).

To further clarify the influence of adiabatic processes,we decompose them into the advection and convergence terms by the mean wind of the CAM. Figure 10d shows the increase in CAM depth due to the advection term mainly appears at the southeast boundary of the CAM depth anomaly (Fig. 6), i.e., in northwestern China at day ?2, north of the Qinghai?Tibetan Plateau at day 0, and in eastern China at day +2. Its magnitude is comparable to that in Figs. 10a and c. Figure 10e shows that the CAM tendency due to the convergence term is positive from day ?4 to ?2 in Siberia.The convergence term is evident on the north side of the Tianshan?Altay Mountains, indicating the influence of the orographic barrier. The convergence process thus contributes partly to the accumulation of CAM over there. After day 0,the divergence of CAM depth begins to dominate northwestern China and leads to the decrease in CAM depth. The precondition process of RCEs is thus characterized by the convergence of CAM over Siberia, while the outbreak of RCEs is accompanied by the advection of CAM from Siberia to East Asia.

As for the RCEs in northeastern China, the local change in CAM depth (Fig. 11a) is also mostly attributable to the adiabatic processes (Fig. 11c), while the diabatic processes make little contribution (Fig. 11b). The rate of change in CAM depth due to adiabatic processes is estimated as 70?80 hPa d?1over northeastern China after day ?2(Fig. 11c). Figure 11d shows that the advection term contributes the most to the CAM tendency after day ?2, as indicated by the pattern and magnitude that are highly similar to those in Fig. 11c. It seems that the strong advection of CAM depth explains the rapid change in CAM depth during RCEs in northeastern China, which is ～50% faster than in northwestern China, as also shown in Figs. 3c and d. Figure 11e shows that the convergence term contributes a part of the positive CAM tendency at the northern periphery of northeastern China at day ?2, when the leading edge of anomalous CAM arrives. It then turns negative after day 0, resulting in the decrease in CAM depth in northeastern China.

We further examine the temporal variation of CAM tendency and associated physical processes at its center, through estimating the budget of CAM depth in the moving boxes as shown in Figs. 10a and 11a. Figure 12 shows that the CAM tendency is mainly attributable to the adiabatic processes during the two kinds of RCEs. Figure 12a shows that the convergence term contributes an increase in CAM depth (～10 hPa d?1) before the onset of RCEs in northwestern China,which is comparable to the advection term (10?20 hPa d?1).The advection term becomes the dominant part of adiabatic processes after day 0, while the convergence term is near zero. Figure 12b shows that the convergence term of CAM depth is quite strong (～20 hPa d?1) before the onset of RCEs in northeastern China. This enhanced convergence is due to the anomalous cyclone of CAM flux to the north of northeastern China (Figs. 6f and g), in association with the deepening trough over northeastern Asia (Figs. 5f and g). The convergence term is also thought to intensify the horizontal gradient of CAM depth, thereby leading to an increase in the advection term. At the onset day of RCEs, the advection term reaches a maximum of 85 hPa d?1in northeastern China,which is nearly twice that in northwestern China. Therefore,the rapid change in CAM depth due to a strong advection term at the center of CAM explains the dramatic temperature drop in northeastern China during RCEs. The tendency decreases rapidly after day +1 because the CAM depth center moves to the ocean, where it begins to dissipate.

6. Summary and discussion

In this study, we examine the climatology of RCEs in northern China, for the first time, from the perspective of quantitative CAM analysis. We have clarified the characteristics and evolution of RCEs that are evidently different in northwestern and northeastern China. The major findings can be summarized as follows:

Based on the regional-mean surface temperature anomaly, we identify the occurrence of RCEs in the winter. In the past 58 years (1958/59?2015/16), 83 (153) RCEs are found to have occurred in northwestern (northeastern) China, most of which were in January. On average, RCEs last for 6.8 days in northwestern China and 4.7 days in northeastern China, indicating a large regional difference in duration.The temperature drops at a rate of ?2.4°C d?1before the onset of RCEs in northeastern China, which is much faster than in northwestern China (?1.9°C d?1), although the anomaly of minimum temperature is comparable in both subregions. These differences suggest that the cold air moves relatively fast during events in northeastern China. The associated atmospheric conditions also differ in terms of the movement of westerly disturbances, suggesting that RCEs are strongly tied to the dynamic and thermodynamic processes in the mid—lower troposphere.

We further estimate the depth and flux of CAM in a quantitative manner and connect them with the evolution of RCEs. Before the occurrence of RCEs in northwestern China, the CAM anomaly builds up over Siberia, where a dipole of anticyclonic and cyclonic anomalies of CAM flux is established under the blocking pattern over the Urals region. The CAM moves southeastward to the Tianshan?Altay Mountains at the onset day of RCEs. It penetrates the valleys between the mountains and flows to the Tarim Basin and Hexi Corridor in the following days. The movement speed of CAM and the low-temperature zone increases considerably after passing the Tianshan?Altay Mountains, suggesting the importance of the orographic effect. Comparatively,during RCEs in northeastern China, the CAM anomaly occurs more to the east and its trajectory is displaced to the Mongolian Plateau near Lake Baikal. It moves southeastward to northeastern China at a relatively fast and steady speed in the absence of an obvious orographic barrier, as compared to in northwestern China. Regression analyses further suggest that a larger anomaly of CAM depth contributes to stronger RCEs with lower minimum temperature. When the CAM has a northwest displacement with a delayed CAM inflow, it leads to relatively long-duration RCEs. Therefore,the CAM depth and flux not only result in the different features of RCEs in the two subregions, but their variations in strength and transport also explain the diverse intensity and duration of individual RCEs.

To clarify the mechanisms governing CAM variations,we further investigate the local change in CAM depth due to different physical processes. It is shown that adiabatic processes play a crucial role in regulating the change in CAM depth during RCEs in both subregions, while the effect of diabatic cooling is much smaller. The rate of change in CAM due to adiabatic processes during RCEs in northeastern China is ～50% larger than in northwestern China. Within the adiabatic processes, the advection term mainly explains the increase in CAM depth at the leading edge of cold air,while the convergence term leads to the accumulation (reduction) of CAM depth before (after) the onset of RCEs. The convergence term of CAM depth is observed at the windward sides of the mountains in northwestern China because of the orographic barrier, while the convergence term is much stronger in northeastern China in association with the deepened trough. This also enhances the gradient of CAM depth, which helps to produce the relatively strong advection of CAM depth. Such strong advection then leads to the rapid increase in CAM depth, thereby resulting in a sharper drop in temperature in northeastern China.

Fig. 12. (a) Time series of the tendency of CAM depth (black, bold) and that caused by diabatic generation/loss (red), adiabatic processes (blue), advection (brown, dashed) and convergence (green, dashed)by the mean wind of CAM. These time series are calculated by the areal mean tendencies in a moving box shown in Fig. 11a. The box has a width of about 1110 km. The climate mean is removed from the time series. (b) As in (a) but for the RCEs in northeastern China.

Previous studies have noted the topographic influence on cold-air activities (Nong and Lv, 1994; Zehnder and Bannon, 2010; Kanno et al., 2015a). In this study, we also notice that the CAM variation is strongly regulated by topography, with large regional differences. The Qinghai?Tibetan Plateau and large mountains act like a barrier to CAM, while the valleys between the Tianshan and Altay mountains form channels for the movement of CAM. Using isentropic analysis, we could further quantify such orographic effects on the cold air with different CAM properties. On the other hand, we notice that RCE occurrences exhibit evident interannual variations and interdecadal declines over northern China (figure not shown), suggesting a reduction in RCEs (Hu et al., 2009; Zhang and Qian,2011; Heo et al., 2018). A long-term decrease in cold days has also been observed in other regions of East Asia in a warming climate (Qian and Lin, 2004; Park et al., 2011; Lee et al., 2011; Wang et al., 2012b; Xu et al., 2018). Recent studies using isentropic analysis suggest that variations of CAM can be strongly associated with long-term change of the winter climate (Kanno et al., 2015b, 2017; Abdillah et al.,2017, 2018). Given the strong connection between CAM and RCEs, further analysis of the long-term variations of CAM may provide us with greater insight into the nature of extreme cold weather and its change under global warming.

Acknowledgements.The authors are thankful to the JMA for providing the JRA-55 data and Prof. Toshiki IWASAKI of Tohoku University for providing the source code of the isentropic analysis. They also thank the two anonymous reviewers for their helpful comments. This study was supported by the National Key Research and Development Program of China (Grant No. 2016 YFA0600704) and the National Natural Science Foundation of China (Grant No. 41805122).