Unusual Late-Season Cold Surges during the 2005 Asian Winter Monsoon: Roles of Atlantic Blocking and the Central Asian Anticyclone

Mong-Ming Lu Central Weather Bureau, Taipei, Taiwan

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Chih-Pei Chang Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan, and Department of Meteorology, Naval Postgraduate School, Monterey, California

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Abstract

The highest frequency of late-winter cold-air outbreaks in East and Southeast Asia over 50 years was recorded in 2005, when three strong successive cold surges occurred in the South China Sea within a span of 30 days from mid-February to mid-March. These events also coincided with the first break of 18 consecutive warm winters over China. The strong pulsation of the surface Siberian Mongolia high (SMH) that triggered these events was found to result from the confluence of several events. To the east, a strong Pacific blocking with three pulses of westward extension intensified the stationary East Asian major trough to create a favorable condition for cold-air outbreaks. To the west, the dominance of the Atlantic blocking and an anomalous deepened trough in the Scandinavian/Barents Sea region provided the source of a succession of Rossby wave activity fluxes for the downstream development. An upper-level central Asian anticyclone that is often associated with a stronger SMH was anomalously strong and provided additional forcing. In terms of the persistence and strength, this central Asian anticyclone was correlated with the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) only when SMH is weak (warm winters). During strong SMH seasons (cold winters) the correlation vanishes. However, during late winter 2005 the central Asian anticyclone was strengthened by the Atlantic blocking through both the downstream wave activities and a circulation change that affected the Atlantic and west Asian jets. As a result, the period from mid-February to mid-March of 2005 stands out as a record-breaking period in the Asian winter monsoon.

Corresponding author address: Dr. Mong-Ming Lu, No. 64, Gongyuan Rd., Central Weather Bureau, Taipei City 100, Taiwan. Email: lu@rdc.cwb.gov.tw

Abstract

The highest frequency of late-winter cold-air outbreaks in East and Southeast Asia over 50 years was recorded in 2005, when three strong successive cold surges occurred in the South China Sea within a span of 30 days from mid-February to mid-March. These events also coincided with the first break of 18 consecutive warm winters over China. The strong pulsation of the surface Siberian Mongolia high (SMH) that triggered these events was found to result from the confluence of several events. To the east, a strong Pacific blocking with three pulses of westward extension intensified the stationary East Asian major trough to create a favorable condition for cold-air outbreaks. To the west, the dominance of the Atlantic blocking and an anomalous deepened trough in the Scandinavian/Barents Sea region provided the source of a succession of Rossby wave activity fluxes for the downstream development. An upper-level central Asian anticyclone that is often associated with a stronger SMH was anomalously strong and provided additional forcing. In terms of the persistence and strength, this central Asian anticyclone was correlated with the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) only when SMH is weak (warm winters). During strong SMH seasons (cold winters) the correlation vanishes. However, during late winter 2005 the central Asian anticyclone was strengthened by the Atlantic blocking through both the downstream wave activities and a circulation change that affected the Atlantic and west Asian jets. As a result, the period from mid-February to mid-March of 2005 stands out as a record-breaking period in the Asian winter monsoon.

Corresponding author address: Dr. Mong-Ming Lu, No. 64, Gongyuan Rd., Central Weather Bureau, Taipei City 100, Taiwan. Email: lu@rdc.cwb.gov.tw

1. Introduction

Southeast Asian cold surges are manifested by rapid decrease in surface temperature and an increase in surface pressure over the northern South China Sea that occurs following the intensification and southeastward migration of the surface Siberian Mongolia high (SMH; e.g., Chang and Lau 1980; Boyle and Chen 1987; Chang et al. 2006). Both 2004 and 2005 are among the warmest years in a century (information online at http://www.ncdc.noaa.gov/oa/climate/research/2007/perspectives.html), and the 2004/05 boreal winter coincided with a weak El Niño. Under such conditions, the East Asian winter monsoon (EAWM) would normally be expected to be weaker and occurrences of cold surges less frequent (Zhang et al. 1996; Zhang et al. 1997; Wang et al. 2000; Chan and Li 2004). However, from mid-February to mid-March 2005, three successive strong cold-surge events passed through the South China Sea, which was an exceptional period that was unprecedented in recent history. The 2004/05 winter also saw surface temperatures dropping to below normal over a broad area in the East Asian continent, with China experiencing its first cold winter after 18 consecutive warm winters (Ma et al. 2008). This was opposite to the forecast of a warm winter by all major operational meteorological services in East Asia1 and caused widespread economic impacts over the region.

The interannual variation of the EAWM is influenced by several leading modes of the large-scale atmospheric variability, including El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO; Chang et al. 2006, and the references therein). The EAWM can be influenced by ENSO through the anomalous circulation over the Philippine Sea induced by the equatorial eastern Pacific SST anomalies (Wang et al. 2000). The EAWM tends to be weaker during El Niño years but stronger during La Niña years. The NAO and AO, which are highly correlated with each other, are found to correlate with the variation of EAWM, in particular in the decadal time scale (Wu and Wang 2002; Gong and Ho 2004). The correlations can result from the changes of surface temperature and snow cover over the Eurasian continent that affects thermal advection, and thus the intensity of EAWM (Wang et al. 2005), or the upper-level Rossby wave train excited by the divergent wind field originated over the Mediterranean Sea (Watanabe 2004). The NAO/AO can also be driven by the stratospheric variability (Ambaum and Hoskins 2002; Baldwin et al. 2003). Jeong et al. (2006) proposed that prior to the occurrence of a cold-surge event in East Asia, a precursory signal can be found in the stratosphere.

Correlation between the EAWM and the East Asian jet stream associated with a deeper Aleutian low and East Asian major trough has been reported by Yang et al. (2002). They pointed out that the East Asian jet stream has a more direct impact on the EAWM than ENSO because it is associated with the extratropical western North Pacific SST. The influence of the SST in the western North Pacific on the EAWM, particularly in the decadal time scale, was also discussed by Chan and Li (2004). The jet stream serves as a waveguide for planetary- to synoptic-scale waves that can cause downstream influences over a large distance. In addition to the external large-scale forcing, it is found that the prolonged extreme weather events are often associated with intraseasonal large-scale flow patterns. One of the most prominent patterns is the atmospheric blocking or the persistent anticyclonic flow anomaly that can modulate the climatic leading modes (Croci-Maspoli et al. 2007) and upper-level jet streams.

In this paper we will investigate the possible causes for these unusual late-winter strong cold surges. Ding and Ma (2007) and Ma et al. (2008) focused their studies on the synoptic developments associated with two major cold-air outbreaks (“cold waves”) over mainland China—one in late December 2004 and the other in mid-February 2005. Hong et al. (2008a) studied all four cold surges in Taiwan between December 2004 and February 2005 and found that the surges were due to anomalously active wave activity propagating along the enhanced subtropical jet that lies between west and East Asia. The last case of all of these studies was associated with the first of the three unusual late-winter strong surges studied here. Our investigation looks for broader-scale developments that provided the conditions that are conducive to the synoptic events and the reasons that these conditions are rare.

2. Data and method

The daily data of the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (Kalnay et al. 1996) are used to analyze the global-scale circulation during February–March 2005. The cold-surge cases are identified from the daily surface temperature data at Kaohsiung (22.6°N, 120.3°E), which is a station located near the southern tip of Taiwan and the northeastern corner of the South China Sea. The winter surface temperature fluctuations at Kaohsiung and Hong Kong (22.3°N, 114.2°E), a station that has been used in many studies to measure the strength of surges, are very similar, although the air temperature at Hong Kong is usually lower because of less influence from the warm ocean surface. The cold-surge definition is adapted from the operational requirements set by Taiwan’s Central Weather Bureau. A cold episode at day 0 is identified if the following two conditions are satisfied: 1) the daily mean temperature decreases by more than 4° in 48 h, that is, T(day 0) − T(day 2) > 4°C, and 2) the lowest daily temperature on day1 or day 2 falls to 14°C or lower. If two episodes appear in two consecutive days, they are counted as one event. The “late winter” in this paper means the period between mid-February and mid-March. The indices of AO and NAO are obtained from the public ftp site of the National Oceanic and Atmospheric Administration/Climate Prediction Center (NOAA/CPC; at ftp://ftp.cpc.ncep.noaa.gov/cwlinks/).

Blockings are frequently observed during late winter. Two parameters GHGS and GHGN are adapted from the operational practice of NOAA’s CPC (http://www.cpc.noaa.gov/products/precip/CWlink/blocking/blocking.html), and are used to quantify the occurrence and duration of the blockings. The parameters are calculated for each longitude based on the daily 5-day running average 500-hPa geopotential height (ϕ) as
i1520-0442-22-19-5205-e1
i1520-0442-22-19-5205-e2
where
i1520-0442-22-19-5205-eq1

A given longitude is determined as blocked at a given time if the following conditions are satisfied for at least one value of δ:

  1. GHGS > 0,

  2. GHGN < −5 gpm per degree latitude.

The blocking index is an adapted version of Tibaldi and Molteni (1990). The index was designed to identify the blocking patterns of the anomalous mass difference between high and middle latitudes associated with anomalous easterly winds. A blocking event can be identified when the zonal index represented by the 500-hPa geopotential height difference between 60° and 40°N [500-hPa geopotential height gradient south (GHGS)] is positive. A substantial negative difference between 80° and 60°N [500-hPa geopotential height gradient north (GHGN)] is required for excluding possible cutoff lows that can satisfy the positive GHGS condition. Tibaldi and Molteni (1990) required at least three consecutive 2.5° interval longitudes to appear as blocked for at least 5 days to identify a blocking event.

3. Results

a. Cold surges and SMH in 2005

The time series of the daily mean surface air temperatures from 1 December 2004 to 31 March 2005 at three stations, Tanshui (in northern Taiwan), Kaohsiung, and Hong Kong are shown in Fig. 1. At all three stations a sharp temperature decrease accompanied by a sharp surface pressure rise started on 16 February 2005, and the lowest temperatures occurred on 20 February 2005. At Hong Kong, the temperature decreased by 15.5°C in 4 days from 16 to 20 February. In the subsequent 20 days, large fluctuations occurred with temperature maxima on 24 February (16.9°C) and 11 March (23.5°C), and temperature minima on 4 March (12.3°C) and 13 March (10.3°C). After 15 March these cold conditions ceased to occur, although significant temperature fluctuations continued. The out-of-phase relationship between the temperature and surface pressure depicted in Fig. 1 confirms that the temperature drops corresponded to the southward movement of the cold air mass from the East Asian continent.

The temperature fluctuations in Taiwan and Hong Kong are strongly influenced by the fluctuations of the SMH. This influence has been well documented in the literature (e.g., Chan and Li 2004, and the references therein). The fluctuations associated with the late December 2004 and mid-February 2005 surge cases studied by Ma et al. (2008) and Ding and Ma (2007) were attributed by these authors to be due to 10–20-day oscillations. However, the strong surges between mid-February and mid-March occur at a higher frequency, and the condition that is favorable for the cold surges to repeatedly occur within the time span of 1 month is an interesting question that will be analyzed here.

Figure 2 shows that the SMH intensity, defined by the sea level pressure (SLP) averaged over the region of 33°–50°N, 80°–110°E (Chan and Li 2004), fluctuates with a period of about 5–10 days from late January to the end of March. It can be seen by comparing Figs. 1b and 2a that, in general, the coldest daily mean temperature at Hong Kong lags the SMH peak by 1 day. The early February cold episodes marked by letters A and B in Fig. 1b, are weaker than the episodes of C, D, and E. The temperature fluctuations associated with F, G, and H are even weaker as the SMH weakens after mid-March. It is evident that the cold surges and the fluctuations of the SMH are well correlated. The Hong Kong station data are replotted in Fig. 2b for comparison with the SMH fluctuation. The reference lines between mid-February and mid-March in Fig. 2b indicate the dates at which the SMH reaches peak values. We can see that the maximum surface pressure and minimum temperature at Hong Kong lag the SMH peak by 1 day.

b. Large-scale features during late winter 2005

A most conspicuous large-scale feature in late winter 2005 (16 February–17 March) was the pronounced and persistent Atlantic blocking. Garcia-Herrera et al. (2007) pointed out that the blocking frequency during winter (January–March) 2005 surpassed the 95th percentile of the record from 1958 to 2005. The number of blocking days in March 2005 was record breaking for March since 1958. The unusual blocking was one of the major culprits that caused the severe drought condition in the Iberian Peninsula in the 2004/05 hydrological year (October 2004–September 2005).

This blocking is evident in the total and anomalous 500-hPa height fields depicted in Figs. 3a,b, respectively. These figures can be compared with Fig. 3c, which is the 30-yr mean field averaged over the same late-winter period of 1971–2000 [the World Meteorological Organization (WMO)-recommended climatology base period]. The corresponding 500-hPa winds are presented as vectors and the jet streams are indicated by the contours of u. Figure 3b shows several other circulation features. South of the Atlantic blocking is an east–west-elongated low pressure anomaly extending across the entire Atlantic from eastern North America to western Europe. A separate blocking high appears over Alaska. The Alaska blocking is associated with a wave train pattern extending from East Asia to North America, with three low centers and two high centers. The lows are over the East Asian coast, the midlatitude eastern North Pacific, and eastern North America. The highs are over the western North Pacific and Alaska.

Another conspicuous feature is the distribution of three major subtropical jet cores over the Atlantic, North Africa, and the western Pacific, respectively. These jets are depicted by the 500-hPa zonal wind in 2005 in both Figs. 3a,b and the 1971–2000 climatology in Fig. 3c. In general, the extent of the Pacific jet streak is about twice that of the other jet streaks. Figure 3b shows that the wave train over the Pacific is embedded in this jet, and the waves over the eastern Pacific and Alaska appear to emanate from this jet. Near the entrance region of the Pacific jet streak a meridional wave structure with a cyclonic circulation over the Arabian Sea and an anticyclonic circulation over central Asia around Kazakhstan formed upstream of the Tibetan Plateau. It turns out that this central Asian anticyclone played a crucial role in the development of the SMH and cold surges, which will be discussed in subsequent sections.

Comparing the 2005 late-winter wind field with the 1971–2000 climatology (Fig. 3c) shows significant southward displacement of the jet cores by the Atlantic and Pacific blockings. Anomalous westerly winds are found over the eastern Pacific and Atlantic along 20°N. The displacement of the jet cores aligns the Atlantic jet with the Pacific and African jets, which enhances the terrain-blocking effects of the Zagros Mountains in Iran and the Tibetan Plateau. The terrain effects are reflected in the amplified flow splitting to the east of the Arabian Peninsula and the Caspian Sea, which are manifested by the anomalous central Asian anticyclone (centered near 45°N, 70°E) and the Arabian Sea cyclone (15°N, 65°E). During the period of study the major tropical convection center represented by the outgoing longwave radiation (OLR) anomaly (not shown) is situated far away over the Pacific near the date line, with the convection over the Indian Ocean clearly suppressed. This suggests that the appearance of this cyclone–anticyclone pair and the weakening of the climatological west Asia–Middle East jet (Chang and Lau 1980; Yang et al. 2004) are unlikely a result of forcing by tropical convection.

c. Upper-level waves and SMH

After checking the 55-yr data for 1951–2005 (not shown), it was found that the large fluctuation of the SMH in the 2005 boreal winter depicted in Fig. 2 was rare. Previous studies have reported that the fluctuation of SMH is linked to the upper-level (500 hPa) eastward-moving short waves that disturb the polar jet streak west of Lake Balkhash (Chu 1978; Boyle and Chen 1987; Wu and Chan 1997; Ding 1994). To find the areas where the upper-level short waves are most influential for the SMH, correlations between the daily SMH intensity and 500-hPa geopotential height for 45 late winters (16 February–17 March 1961–2005) are computed and shown in Fig. 4. Here the SMH intensity is that of the SLP averaged over the area of 33°–50°N, 80°–110°E (marked by the square in Fig. 4), with positive correlations significant at the 5% level highlighted. The southwest–northeast orientation of this correlation pattern suggests that the SMH intensity is particularly sensitive to the perturbations passing through an axis extending from Iran to the central Siberian Plateau.

Downstream from this pattern, weaker indications of correlations are also found to the east of the SMH over the Yellow Sea and northern Indochina, although the values are below significance. Upper-level circulations in these two areas are known to be related to the Southeast Asian cold surges because the cold air mass from Mongolia is often steered by the upper-level Yellow Sea trough to the south and the northerly surge is often associated with the Indochina anticyclone (Murakami 1981).

The 500-hPa central Asian anticyclone anomaly shown in Fig. 3b is located in the southwestern part of the southwest–northeast correlation pattern in Fig. 4. We therefore divide the central part of this pattern into two rectangular boxes—one centered over central Asia (CAS; 40°–50°N, 60°–80°E) and the other centered over the West Siberian Plain (WSP; 50°–60°N, 75°–95°E). The area-averaged geopotential heights within the two boxes, the central Asian anticyclone index (CAI) and WSP, respectively, are then used as the base points to compute the point correlations over the entire domain, which are shown in Fig. 5. The correlation with the base point CAI (Fig. 5a) shows a wave train pattern with two negative centers near the Baltic Sea and the Yellow Sea, although these negative correlations do not reach the 5% significant level. A similar wave train pattern shows up with the WSP base point (Fig. 5b). Here, a significant negative correlation area is found near the Baltic Sea.

The lag correlation maps using the two base points with lags up to 10 days earlier (lag = −10 day) are computed to trace the development of the correlation patterns. Although the simultaneous correlation patterns are similar with either CAI or WSP as the base point, their lag correlation patterns are distinctly different. Figure 6 shows that the central Asia height is positively correlated with the 500-hPa geopotential height over southern Greenland for as long as −9 days. At −5 days, negative coefficients appear at the downstream of Greenland over the Scandinavian Peninsula in association with the positive correlation over northwest Iran and Iraq. It is particularly interesting to note the gradual northwest extension of the positive correlation from Iran to central Asia from day −5 to day 0. The simultaneous negative coefficient over the Yellow Sea shown in Fig. 5a may be traced back to day −8, but the 5% significance level was not reached until day 0. This seems to suggest the possibility that the deepening of the Yellow Sea trough is related to the development of the 500-hPa ridge over central Asia. We also calculated lag correlations in 30-day segments (overlapped every 15 days) from November to March, and found significant long lead correlation between the Greenland geopotential height and CAI only in late winter.

The lag correlation with the west Siberia base point (Fig. 7) shows a different wave train pattern compared to that in Fig. 6. Significant negative correlation does not appear until −5 days over the Barents Sea, and positive correlation appears between Lake Balkhash and Lake Baikal at day −4. The coefficients of this correlation dipole steadily increase from day −4 to day 0.

The lag correlation results suggest that fluctuation of the SMH may be triggered by perturbations originated from the Scandinavian Peninsula and the Barents Sea. In this sequence of events low pressure perturbations over the Scandinavian Peninsula excite an anticyclonic anomaly near the Caspian Sea, which tends to move northeastward through central Asia to Mongolia. On the other hand, low pressure perturbations over the Barents Sea can directly excite an anomalous anticyclone downstream over Mongolia.

d. Origin of SMH fluctuations in 2005

The correlation results from the previous section suggest an examination of the 500-hPa height over the Scandinavian Peninsula and the Barents Sea region in relation to the SMH region. In particular, they suggest the possibility that the large fluctuations of SMH during late winter 2005 were the result of downstream development of the fluctuations of the negative height anomaly over the Scandinavian Peninsula that is associated with the strong Atlantic blocking. Figure 8a is a latitude–time cross section of the 500-hPa height averaged over 10°–30°E that depicts the meridional structure of the upper-level fluctuations over the Scandinavian Peninsula (55°–80°N). The letters plotted along the reference line at 45°N marks the peaks of the SMH intensity marked in Fig. 2a. Deepening of the polar low occurs ahead of all peaks except event H at the end of March. Similar features also appear in the latitude–time cross section for 30°–50°E (Fig. 8b), which is the longitudinal range of the Barents Sea (70°–75°N). Here an oscillation with a time scale of about 5–10 days and the repeated outbreaks of the polar low from late February to late March can be observed. The oscillation begins on 10 February, and the main polar low outbreak begins on 21 February. In the first 10 days of February, a large area to the south of the Barents Sea and northern Europe and from eastern Europe to northern Iran and Iraq (35°–60°N) is occupied by a persistent high pressure system with a ridge near 55°N in central Russia. The persistent high disappears on 10 February with the intrusion of the polar low. After this intrusion, the height field at 40°–55°N continued to oscillate until late March.

The anomalous Atlantic blocking discussed earlier (Fig. 3) can be identified in the latitude–time cross section of the 500-hPa height averaged over the longitudes of Greenland (30°–60°W) shown in Fig. 8c. A strong pressure gradient during 1–10 February at 60°N is generated by the polar low in the north and a persistent subtropical high in the south. The polar low weakens rapidly after mid-February and a blocking high emerges on 20 February. The blocking high experienced a break on 5 March, revived after 6 March, and remained strong until 15 March.

There is also evidence that the SMH was influenced by events over the Pacific. Figure 9 shows the longitude–time section of the blocking index GHGS, which measures the equatorward pressure gradient from the blocking ridge at the blocked longitudes. The figure depicts both the evolution of the Atlantic blocking and that of a more intermittent but nevertheless conspicuous blocking over the Pacific. The dates of the six SMH peaks shown in Fig. 2 are marked in the center of the diagram near the longitudes of the SMH. An extrapolation of the slow eastward movement of the pulses of the Atlantic blocking appears to project influences to the development of the SMH peaks. Meanwhile, the Pacific blocking, though much weaker compared with its Atlantic counterpart, had four distinct pulses with clear westward movements that appeared to converge with the influence of the Atlantic blocking. The first three occurred around the time frame of the three major SMH peaks (C, D, and E) in Fig. 2a, and the last one occurred in late March when an extended event of Atlantic blocking was also moving toward the east. This convergence increases the chance of deepening the East Asian major trough near Japan (figure not shown), which contributes to the cold surges.

The patterns appear to resemble those proposed by Takaya and Nakamura’s (2005a,b) model that showed that the formation mechanisms of the blocking ridges to the east and west of the upper-level East Asian major trough are different. To the west, the quasi-stationary Rossby wave train propagating across the Eurasian continent reinforced by the modest feedback forcing of transient eddies can force the west Siberia anticyclone, while to the east a westward development of anticyclonic anomalies from the North Pacific reinforced by strong feedback forcing from the Pacific storm track can provide forcing from the east.

4. Distinction of late winter 2005

Our results indicate the roles played by a strong Atlantic blocking and the central Asian anticyclone in the development of strong SMH and cold surges in late winter 2005. In Fig. 10 we use a scatter diagram to delineate the possible relationship between the SMH and the Atlantic blocking and the central Asian anticyclone in a 55-yr dataset (1951–2005). Here the SMH is represented by a category index that represents both its persistence and strength during the period of the late winter defined in this study. The “persistent strength” is measured by the sum of the positive standardized daily anomaly over the period of 16 February–17 March. Recall that SMH is defined in section 3 as the average SLP over 33°–50°N, 80°–110°E. The mean and standard deviation used for computation of the standardized daily anomaly are the mean and standard deviation of the SMH of 55 winters (November–March) from 1951 to 2005. The 55 persistent strength data are further categorized into three categories according to their standard deviation (σ). A year is ranked as category 3 if the persistent strength is larger than 0.5σ. It is ranked as category 1 if the persistent strength is smaller than −0.5σ. The rest of the years are ranked as category 2. Therefore, category 3 indicates strong late-winter SMH in terms of its persistent strength, while category 1 indicates weak late-winter SMH.

In Fig. 10 the vertical axis is the persistent strength of Atlantic blocking, or the Atlantic blocking index (ABI). This index is based on the sum of the standardized anomalies of the GHGS within each late season that satisfies the blocking criteria described in section 2. Note that only the normalized GHGS anomalies larger than 1 are included so that insignificant or ambiguous blocking signals are ruled out. Again, the standard anomalies are computed using the data of 55 winters, but only the late-winter (16 February–17 March) anomalies are summed for each year. The ABI is then defined as the standardized anomaly of the 55 sums. The horizontal axis is the persistent strength of the central Asian anticyclone, or the CAI, which is similarly defined as the standardized anomaly of the sum of the standardized anomalies of the average 500-hPa geopotential height over the region of 40°–50°N, 60°–80°E. Here only the positive anomalies of the geopotential height are included when computing the sum because the focus is on the strength of the anticyclonic circulation only.

Figure 10 shows that in general ABI has only a very weak relationship with SMH while CAI has a stronger and positive relationship with SMH, as is implied in Fig. 4. When the two parameters are combined the relationship is enhanced. The figure may be divided into four quadrants by the zero horizontal and vertical lines. In the upper-right quadrant in which both ABI and CAI are positive, 50% of the SMH is strong (category 3), which is nearly 5 times the percentage in the opposite (lower left) quadrant in which both ABI and CAI are negative. In this negative ABI–negative CAI quadrant 61% of the SMH is weak (category 1), which is more than that in any other quadrant. The 2005 point (circled in the figure) stands out distinctively in the upper-right quadrant with the strongest Atlantic blocking and central Asian indexes.

Many investigators have noticed a strong anticorrelation between blocking occurrence and the phase of the NAO (e.g., Shabbar et al. 2001; Luo 2005; Scherrer et al. 2006; Croci-Maspoli et al. 2007). Woollings et al. (2008) proposed that the low-frequency variability of NAO arises as a result of variations in the occurrence of upper-level Rossby wave–breaking events over the North Atlantic; thus, the positive and negative phases of NAO are simply a description of periods of infrequent and frequent blockings, respectively. The NAO is highly correlated with the AO (Thompson and Wallace 2001), and the out-of-phase relationship between NAO/AO and SMH has also been reported by many authors (e.g., Gong and Ho 2004; Jeong and Ho 2005; Gong and Drange 2005; Hong et al. 2008b). In particular, the decadal-scale relationship is most noticeable in which the weakening of the East Asian winter monsoon since the late 1980s coincides with a positive phase of NAO (e.g., Jhun and Lee 2004; Chang et al. 2006; Wu et al. 2006). This relationship is apparently due to the advection of warm air from eastern Europe causing milder-than-normal SMH (Panagiotopoulos et al. 2005). On the other hand, Wu and Wang (2002), Jhun and Lee (2004), and Wu et al. (2006) found little evidence of an NAO/AO relationship with the East Asian winter monsoon on an interannual time scale. Figures 11 and 12 are similar to Fig. 10 except that the vertical coordinate is the normalized indexes of NAO and the Northern Hemisphere annular mode (NAM; representing the AO), respectively. Based on the results of previous investigators, one would expect more category-1 SMH and less category-3 SMH in the upper half of the figure (NAO/NAM positive) compared to the lower half of the figure (NAO/NAM negative). However, in both figures this relationship is valid only for weak CAI (second and third quadrants). When the central Asian anticyclone is strong (first and fourth quadrants), the relationship becomes murkier as the situation for weak SMH (category 1) is reversed. We also notice that for both NAO and NAM the 2005 case is not an outlier as is the case in Fig. 10.

The fact that the central Asian anticyclone plays an independent role from the favorable background circulation (NAO/AO/NAM) for a strong late-winter monsoon can also be seen from the correlations between CAI and three indexes: ABI, NAM, and NAO. Table 1 shows these correlations for the three categories of the SMH index as well as for all of the cases. Significant correlations (1% level) between CAI and NAM and NAO exist only for the weak SMH category, or when the winter monsoon is weak. The correlations are not significant at the 5% level for medium and strong SMH, or when the winter monsoon is normal or strong. The results remain practically the same if decadal-scale variations, which are known to contain negative correlation between NAO and the various East Asian monsoon indexes (Chang et al. 2006), are removed through a fourth-order polynomial filter (not shown). Thus, the correlation between the NAM (AO)/NAO and the central Asian anticyclone during a weak (warm) monsoon is robust on the interannual time scale. In other words, the atmosphere tends to see a weak central Asian anticyclone associated with positive NAM/AO and NAO during warm late winters. The Atlantic blocking is not correlated with the central Asian anticyclone for any of the three SMH categories. The only reason that there is a slight correlation (5% significance level) for the all 55-yr data is apparently due to the uniquely strong event of 2005.

5. Summary and discussion

The late-winter successive cold surges that occurred in 2005 are associated with strong oscillations in SMH on a time scale of 7–8 days. The large-scale circulation during the cold-surge period is characterized by the extremely persistent Atlantic blocking and the central Asian anticyclone. The central Asian anticyclone is an important upper-level winter circulation feature that has been noticed previously in regional climate studies in the eastern Mediterranean basin and the Middle East, covering a region that spans Greece, Turkey, Israel, and Iran (Kutiel et al. 2002; Ghasemi and Khalili 2008). Its daily variations are highly correlated with both the SMH and upstream wave activities that propagate from near the North Atlantic region more than 1 week earlier. In late winter 2005 it was enhanced by the unusually strong and persistent Atlantic blocking through a realignment and strengthening of the subtropical jet that interacts with terrain, and the upper-level wave trains that propagate downstream from the blocking region (Joung and Hitchman 1982; Takaya and Nakamura 2005a,b). To the east the Pacific blocking was also strong (an event that occurs concurrently with Atlantic blocking about 22% of the time in the 55-yr data period for either blocking), leading to periodic westward movement of the anticyclonic anomalies from the North Pacific that contributes to the reinforcement of a strong SMH and deepening of the East Asian major trough near Korea and Japan. Because blocking is one of the most difficult forecast problems and its frequency is usually underestimated in medium-range and seasonal forecast models (Pelly and Hoskins 2003; Palmer et al. 2008), the dominance of the blockings in late winter 2005 may have contributed to the operational forecast failures of this unusual season.

Atlantic and Pacific blockings occur simultaneously on about 22% of the days of either blocking in the 55-yr dataset, but successive cold surges occurring within the time span of 1 month in late winter were rare. An examination of cold-surge events in the 1951–2005 data revealed only 13 late-winter cold-surge events, and only 2 of the 55 yr, 1986 and 2005, produced more than one surge event in the late season. The late winter of 1986 had two episodes, and late winter 2005 was the only one with three episodes.

In the winter 1986, when the ENSO condition was neutral, persistent blocking in both the Atlantic and the Pacific were also present, albeit less strong. Hsu et al. (1990) reported that cold surges in China were mainly triggered by eastward-propagating tropical convection originated in the Indian Ocean and organized by a subtropical Rossby wave train. The 2005 winter had a weak El Niño condition, and tropical convection was clearly suppressed during the late season and unlikely to trigger the cold surges. Nevertheless, ENSO may still have an effect on the SMH, and therefore the cold surges, through its influence on the polar vortex. Garfinkel and Hartmann (2008) pointed out that a warm ENSO can weaken the polar vortex through the forced Pacific–North America (PNA) pattern that deepens the Aleutian low, particularly during the westerly phase of the quasi-biennial oscillation (QBO), in which the extratropical planetary-scale wavenumber one is enhanced by being in phase with the climatological wavenumber one and can propagate upward and break in the stratosphere, thus weakens the polar vortex. This wave breaking effect is more pronounced from late winter to early spring. During the period of this study, a PNA-like structure can be identified in Fig. 3a. The Aleutian low had been significantly deep in late January (figure not shown) and the QBO was westerly (online at http://www.cpc.noaa.gov/data/indices/qbo.u50.index). Therefore, the large-scale condition in the higher latitudes appeared to be favorable for ENSO to cause wave breaking and a weakening of the polar vortex.

Gong and Ho (2004) and Jeong and Ho (2005) found that the recent decade of the positive NAO/AO phase had unfavorable conditions for strong Southeast Asian cold surges. On the other hand, a relationship between NAO/AO and the East Asian winter monsoon on interannual time scales was not found (Wu et al. 2006; Jhun and Lee 2004). Our results suggest that the subseasonal fluctuations of the East Asian winter monsoon are also correlated with NAO/AO, but only when the persistent strength of the central Asian anticyclone is weak. In this case, the SMH tends to be weak so that the correlation does not exist in strong winter monsoon seasons. Therefore, despite the correlation between the NAO and Atlantic blocking, the main cause of the strong SMH during late winter 2005 is the unusually strong Atlantic blocking and its influence on the central Asian anticyclone, rather than the negative NAO phase during that season. The Pacific blocking provided additional forcing.

Finally, most of the Asian winter monsoon research studied the entire boreal winter season or the period when the climate mean SMH stays high (from December to mid-February, see Fig. 2), but less attention has been paid to the late season. The lag correlation between Greenland and central Asia reported in this study (Fig. 6) is significant only during the late-winter period from mid-February to mid-March, when the SMH is weakening. Therefore, the concurrent relationship between the positive NAO/AO, weak central Asian anticyclone, and weak SMH suggests a possible process in a warm climate that can result in the shortening of the winter monsoon season over East Asia when NAO/AO is positive. Further studies are needed to verify and understand this process and its possible effects.

Acknowledgments

We wish to thank Professor R. L. Haney of the Naval Postgraduate School for reading the manuscript. This study was supported in part by the Central Weather Bureau under the Climate Variation and Severe Weather Monitoring and Forecasting System Development Project and the National Science Council of the Republic of China under Grants NSC97-2625-M-052-008 to CWB and NSC97-2111-M-002-017-MY3 to National Taiwan University.

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Fig. 1.
Fig. 1.

(a) Map of Tanshui, Kaohsiung, and Hong Kong stations. (b) The temperature and surface pressure at these three stations for the period of 1 Dec 2004–20 Mar 2005. Ten cold episodes are indicated by full circles, each marking the minimum temperature within a 5-day period. The letters A–H mark the peaks of SMH as in Fig. 2a.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 2.
Fig. 2.

(a) Time series of the SMH intensity (area mean sea level pressure over 33°–50°N, 80°–110°E). The line with filled circles represents the 1971–2000 climatic mean, with large circles indicating the late-winter period (16 Feb–17 Mar) defined in this paper. The line with open circles represents the values in 2004/05 winter. The eight peaks after January 2005 are labeled with letters A–H, which can be compared with the eight cold episodes in Fig. 1. (b) The temperature and surface pressure at Hong Kong as in Fig. 1 is presented for the convenience of comparing with the SMH. The dark bars represent temperature and the light bars represent mean sea level pressure.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 3.
Fig. 3.

The (a) total field and (b) anomaly in 2005, and (c) the 1971–2000 climatology of the 500-hPa geopotential height (contour) and winds (vector) averaged over the period of 16 Feb–17 Mar. The 500-hPa u (shading) in (a) and (b) are the total zonal wind component over 16 Feb–17 Mar 2005, and in (c) it is the climatology averaged over the same period of the late-winter season. The two boxes representing CAS and WSP are explained in Fig. 4.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 4.
Fig. 4.

The late-winter correlation of SMH and 500-hPa geopotential height during the period of 16 Feb–17 Mar computed from 45 yr of data from 1961 to 2005. The contours of positive correlations are dashed lines and the negative correlations are solid lines. The correlations significant at the level of 0.05 are shaded, with darker shading for the level of 0.01. Two boxes arranged from southwest to northeast marked by CAS and WSP along the axis of the maximum correlation are selected to test the sensitivity of the 500-hPa height to the perturbations in other regions. The big square to the right of the two boxes marks the area of SMH.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 5.
Fig. 5.

The late winter 500-hPa geopotential height correlation during the period of 16 Feb–17 Mar, with the reference point at (a) central Asia at 40°–50°N, 60°–80°E, and (b) west Siberia at 50°–60°N, 75°–95°E. The contours of positive correlations are dashed lines and the negative correlations are solid lines. The correlations significant at the level of 0.05 are shaded.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 6.
Fig. 6.

Maps of 500-hPa geopotential height lag correlation with the base point at central Asia (40°–50°N, 60°–80°E) for the lags from (top left) −10 days to (bottom right) −1 day. Contour interval of the coefficient is 0.1. Shaded regions have correlations significant at the level of 0.05.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 7.
Fig. 7.

Same as Fig. 6, but with the base point at west Siberia (50°–60°N, 75°–95°E).

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 8.
Fig. 8.

Time–latitude cross section of 500-hPa height contours averaged over the longitudes of (a) 10°–30°E, (b) 30°–50°E, and (c) 60°–30°W. The heights lower than 5400 m are shaded, with those lower than 5200 m are dark shaded. The thick line marks the 5500-m height contour. The contour interval is 100 m. A reference line is indicated by the dashed line along 45°N. The letters of C–H correspond to the SMH major peaks shown in Fig. 2a.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 9.
Fig. 9.

Hovmoeller diagram of the blocking index parameter GHGS at the blocked longitudes. GHGS is the height gradient measured from the blocking ridge equatorward, as explained in the text. The marked dates are that of SMH major peaks shown in Fig. 2a. The thick lines that link the blocking and the dates of SMH peaks suggest the possible temporal relationship between these two systems.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 10.
Fig. 10.

The scatter diagram of the SMH categories (represented by the numbers 1, 2, and 3 in the figure) with respect to the persistent strength of the central Asian anticyclone (horizontal axis) and Atlantic blocking (vertical axis). The circle marks 2005.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 11.
Fig. 11.

Same as Fig. 10, but the vertical axis is the standardized anomalies of the NAO anomaly averaged over the period of 16 Feb–17 Mar.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Fig. 12.
Fig. 12.

Same as Fig. 10, but the vertical axis is the standardized anomalies of the NAM index anomaly averaged over the period of 16 Feb–17 Mar.

Citation: Journal of Climate 22, 19; 10.1175/2009JCLI2935.1

Table 1.

Correlations of CAI with ABI, NAM, and NAO indexes according to the strength of the Siberian–Mongolian High (SMHI) (confidence level: bold = 99%, italic = 95%). The numbers in the parenthesis are the number of years used in calculating the correlations.

Table 1.

1

Seasonal forecasts were made by the Korea Meteorological Administration, China Meteorological Administration, and Japan Meteorological Agency at the Fifth Joint Meeting for Seasonal Prediction of the East Asian Winter Monsoon, 13–14 November 2004, Busan, Korea.

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  • Ambaum, M. H. P., and B. J. Hoskins, 2002: The NAO troposphere–stratosphere connection. J. Climate, 15 , 19691978.

  • Baldwin, M. F., D. B. Stephenson, D. W. J. Thompson, T. J. Dunkerton, A. J. Charlton, and A. O’Neill, 2003: Stratospheric memory and extended-range weather forecasts. Science, 301 , 636640.

    • Search Google Scholar
    • Export Citation
  • Boyle, J. S., and T. J. Chen, 1987: Synoptic aspects of the wintertime East Asian monsoon. Monsoon Meteorology, C. P. Chang, and T. N. Krishnamurti, Eds., Oxford University Press, 125–160.

    • Search Google Scholar
    • Export Citation
  • Chan, J., and C. Li, 2004: The East Asia winter monsoon. East Asian Monsoon, C.-P. Chang, Ed., World Scientific Series on Meteorology of East Asia, Vol. 2, World Scientific, 54–106.

    • Search Google Scholar
    • Export Citation
  • Chang, C-P., and K. M. W. Lau, 1980: Northeasterly cold surges and near-equatorial disturbances over the winter MONEX area during December 1974. Part II: Planetary-scale aspects. Mon. Wea. Rev., 108 , 298312.

    • Search Google Scholar
    • Export Citation
  • Chang, C-P., Z. Wang, and H. Hendon, 2006: The Asian Winter Monsoon. The Asian Monsoon, B. Wang, Ed., Praxis, 89–127.

  • Chu, E. W. K., 1978: A method for forecasting the arrival of cold surges in Hong Kong. Hong Kong Observatory, Royal Observatory Tech. Note 43, 32 pp.

    • Search Google Scholar
    • Export Citation
  • Croci-Maspoli, M., C. Schwierz, and H. C. Davies, 2007: Atmospheric blocking: Space–time links to the NAO and PNA. Climate Dyn., 29 , 713725.

    • Search Google Scholar
    • Export Citation
  • Ding, Y. H., 1994: Monsoons over China. Kluwer Academic, 419 pp.

  • Ding, Y. H., and X. Ma, 2007: Analysis of isentropic potential vorticity for a strong cold wave in 2004/2005 winter (in Chinese). Acta Meteor. Sin., 65 , 695707.

    • Search Google Scholar
    • Export Citation
  • Garcia-Herrera, R., D. Paredes, R. M. Trigo, I. F. Trigo, E. Hernandez, D. Barriopedro, and M. A. Mendes, 2007: The outstanding 2004/05 drought in the Iberian Peninsula: Associated atmospheric circulation. J. Hydrometeor., 8 , 483498.

    • Search Google Scholar
    • Export Citation
  • Garfinkel, C. I., and D. L. Hartmann, 2008: Different ENSO teleconnections and their effects on the stratospheric polar vortex. J. Geophys. Res., 113 , D18114. doi:10.1029/2008JD009920.

    • Search Google Scholar
    • Export Citation
  • Ghasemi, A. R., and D. Khalili, 2008: The effect of the North Sea-Caspian Pattern (NCP) on winter temperature in Iran. Theor. Appl. Climatol., 92 , (1–2). 5974.

    • Search Google Scholar
    • Export Citation
  • Gong, D. Y., and C-H. Ho, 2004: Intra-seasonal variability of wintertime temperature over East Asia. Int. J. Climatol., 24 , 131144.

  • Gong, D. Y., and H. Drange, 2005: A preliminary study on the relationship between Arctic oscillation and daily SLP variance in the Northern Hemisphere during wintertime. Adv. Atmos. Sci., 22 , 313327.

    • Search Google Scholar
    • Export Citation
  • Hong, C-C., H-H. Hsu, and H-H. Chia, 2008a: Study of East Asian cold surges during the 2004/05 winter: Impact of East Asian jet stream and subtropical upper-level Rossby wave trains. Terr. Atmos. Oceanic Sci., 20 , 333343. doi:10.3319/TAO.2008.02.04.01(A).

    • Search Google Scholar
    • Export Citation
  • Hong, C-C., H-H. Hsu, H-H. Chia, and C-Y. Wu, 2008b: Decadal relationship between the North Atlantic Oscillation and cold surge frequency in Taiwan. Geophys. Res. Lett., 32 , L24707. doi:10.1029/2008GL034766.

    • Search Google Scholar
    • Export Citation
  • Hsu, H-H., B. J. Hoskins, and F-F. Jin, 1990: The intraseasonal oscillation and the role of the extratropics. J. Atmos. Sci., 47 , 823839.

    • Search Google Scholar
    • Export Citation
  • 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.

    • Search Google Scholar
    • Export Citation
  • Jeong, J-H., 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.

    • Search Google Scholar
    • Export Citation
  • Jhun, J-G., and E-J. Lee, 2004: A new East Asian winter monsoon index and associated characteristics of the winter monsoon. J. Climate, 17 , 711726.

    • Search Google Scholar
    • Export Citation
  • Joung, C. H., and M. H. Hitchman, 1982: On the role of successive downstream development in East Asian polar air outbreaks. Mon. Wea. Rev., 110 , 12241237.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437471.

  • Kutiel, H., P. Maheras, M. Turkes, and S. Paz, 2002: North Sea-Caspian pattern (NCP)—An upper level atmospheric teleconnection affecting the eastern Mediterranean: Implications on the regional climate. Theor. Appl. Climatol., 72 , 173192.

    • Search Google Scholar
    • Export Citation
  • Luo, D., 2005: Why is the North Atlantic block more frequent and long-lived during the negative NAO phase? Geophys. Res. Lett., 32 , L20804. doi:10.1029/2005GL022927.

    • Search Google Scholar
    • Export Citation
  • Ma, X., Y. H. Ding, H. Xu, and J. He, 2008: The relation between strong cold waves and low-frequency waves during the 2004/2005 winter (in Chinese). Chin. J. Atmos. Sci., 32 , 380394.

    • Search Google Scholar
    • Export Citation
  • Murakami, T., 1981: Orographic influence of the Tibetan Plateau on the Asiatic winter monsoon circulation. Part III. Short-period oscillation. J. Meteor. Soc. Japan, 59 , 173200.

    • Search Google Scholar
    • Export Citation
  • Palmer, T. N., F. J. Doblas-Reyes, A. Weisheimer, and M. J. Rodwell, 2008: Toward seamless prediction: Calibration of climate change projections using seasonal forecasts. Bull. Amer. Meteor. Soc., 89 , 459470.

    • Search Google Scholar
    • Export Citation
  • Panagiotopoulos, F., M. S. Anova, A. Hannachi, and D. B. Stephenson, 2005: Observed trends and teleconnections of the Siberian high: A recent declining center of action. J. Climate, 18 , 14111422.

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  • Fig. 1.

    (a) Map of Tanshui, Kaohsiung, and Hong Kong stations. (b) The temperature and surface pressure at these three stations for the period of 1 Dec 2004–20 Mar 2005. Ten cold episodes are indicated by full circles, each marking the minimum temperature within a 5-day period. The letters A–H mark the peaks of SMH as in Fig. 2a.

  • Fig. 2.

    (a) Time series of the SMH intensity (area mean sea level pressure over 33°–50°N, 80°–110°E). The line with filled circles represents the 1971–2000 climatic mean, with large circles indicating the late-winter period (16 Feb–17 Mar) defined in this paper. The line with open circles represents the values in 2004/05 winter. The eight peaks after January 2005 are labeled with letters A–H, which can be compared with the eight cold episodes in Fig. 1. (b) The temperature and surface pressure at Hong Kong as in Fig. 1 is presented for the convenience of comparing with the SMH. The dark bars represent temperature and the light bars represent mean sea level pressure.

  • Fig. 3.

    The (a) total field and (b) anomaly in 2005, and (c) the 1971–2000 climatology of the 500-hPa geopotential height (contour) and winds (vector) averaged over the period of 16 Feb–17 Mar. The 500-hPa u (shading) in (a) and (b) are the total zonal wind component over 16 Feb–17 Mar 2005, and in (c) it is the climatology averaged over the same period of the late-winter season. The two boxes representing CAS and WSP are explained in Fig. 4.

  • Fig. 4.

    The late-winter correlation of SMH and 500-hPa geopotential height during the period of 16 Feb–17 Mar computed from 45 yr of data from 1961 to 2005. The contours of positive correlations are dashed lines and the negative correlations are solid lines. The correlations significant at the level of 0.05 are shaded, with darker shading for the level of 0.01. Two boxes arranged from southwest to northeast marked by CAS and WSP along the axis of the maximum correlation are selected to test the sensitivity of the 500-hPa height to the perturbations in other regions. The big square to the right of the two boxes marks the area of SMH.

  • Fig. 5.

    The late winter 500-hPa geopotential height correlation during the period of 16 Feb–17 Mar, with the reference point at (a) central Asia at 40°–50°N, 60°–80°E, and (b) west Siberia at 50°–60°N, 75°–95°E. The contours of positive correlations are dashed lines and the negative correlations are solid lines. The correlations significant at the level of 0.05 are shaded.

  • Fig. 6.

    Maps of 500-hPa geopotential height lag correlation with the base point at central Asia (40°–50°N, 60°–80°E) for the lags from (top left) −10 days to (bottom right) −1 day. Contour interval of the coefficient is 0.1. Shaded regions have correlations significant at the level of 0.05.

  • Fig. 7.

    Same as Fig. 6, but with the base point at west Siberia (50°–60°N, 75°–95°E).

  • Fig. 8.

    Time–latitude cross section of 500-hPa height contours averaged over the longitudes of (a) 10°–30°E, (b) 30°–50°E, and (c) 60°–30°W. The heights lower than 5400 m are shaded, with those lower than 5200 m are dark shaded. The thick line marks the 5500-m height contour. The contour interval is 100 m. A reference line is indicated by the dashed line along 45°N. The letters of C–H correspond to the SMH major peaks shown in Fig. 2a.

  • Fig. 9.

    Hovmoeller diagram of the blocking index parameter GHGS at the blocked longitudes. GHGS is the height gradient measured from the blocking ridge equatorward, as explained in the text. The marked dates are that of SMH major peaks shown in Fig. 2a. The thick lines that link the blocking and the dates of SMH peaks suggest the possible temporal relationship between these two systems.

  • Fig. 10.

    The scatter diagram of the SMH categories (represented by the numbers 1, 2, and 3 in the figure) with respect to the persistent strength of the central Asian anticyclone (horizontal axis) and Atlantic blocking (vertical axis). The circle marks 2005.

  • Fig. 11.

    Same as Fig. 10, but the vertical axis is the standardized anomalies of the NAO anomaly averaged over the period of 16 Feb–17 Mar.

  • Fig. 12.

    Same as Fig. 10, but the vertical axis is the standardized anomalies of the NAM index anomaly averaged over the period of 16 Feb–17 Mar.

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