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Physical Mechanisms of Summer Precipitation Variations in the Tarim Basin in Northwestern China WEI HUANG MOE Key Laboratory of West China’s Environmental System, Lanzhou University, Lanzhou, China
SONG FENG Department of Geosciences, University of Arkansas, Fayetteville, Arkansas
JIANHUI CHEN AND FAHU CHEN MOE Key Laboratory of West China’s Environmental System, Lanzhou University, Lanzhou, China (Manuscript received 3 June 2014, in final form 21 January 2015) ABSTRACT The Tarim basin (TB) in northwestern China is one of the most arid regions in the middle latitudes, where water is scarce year-round. This study investigates the variations of summer precipitation in the TB and their association with water vapor fluxes and atmospheric circulation. The results suggest that the variations of summer precipitation in the TB are dominated by the water vapor fluxes from the south and east, although the long-term mean water vapor mostly comes from the west. The anomalous water vapor fluxes are closely associated with the meridional teleconnection pattern around 508–808E and the zonal teleconnection pattern along the Asian westerly jet in summer. The meridional teleconnection connects central Asia and the tropical Indian Ocean; the zonal teleconnection resembles the ‘‘Silk Road pattern.’’ The two teleconnections lead to negative height anomalies in central Asia and positive height anomalies in the Arabian Sea and India and in northern central China. The anomalous pressure gradient force, caused by these height anomalies, leads to anomalous ascending motion in the TB and brings low-level moisture along the eastern periphery of the Tibetan Plateau and water vapor from the Arabian Sea passing over the Tibetan Plateau to influence precipitation development in the study region.
1. Introduction The Tarim basin (TB) is located in the western part of northwestern China, far from the ocean, and lies in the shadow of the Tibetan Plateau and Tienshan Mountains (Fig. 1). It is the second largest desert in the world and one of the most arid regions in the midlatitudes (Feng and Fu 2013). This region lies at the margin of sustainability, where water is scarce year round. The region is also the major source of dust aerosols that are affecting the East Asian countries (Mao et al. 2011). Therefore, understanding the precipitation variations in this region and their physical processes is important not only for the
Corresponding author address: Wei Huang, MOE Key Laboratory of West China’s Environmental System, 222 South Tianshui Rd., Lanzhou University, Lanzhou 730000, China. E-mail:
[email protected];
[email protected] DOI: 10.1175/JCLI-D-14-00395.1 Ó 2015 American Meteorological Society
regional ecosystems, but also for the environmental management of the East Asian countries. Many efforts have already been made to understand the current climate and environmental changes in the TB and nearby central Asia. Total precipitation, soil moisture, extreme precipitation, and flood events in the TB and central Asia have been increasing during the past decades (Jiang et al. 2005; Feng et al. 2007; Su and Wang 2007; Chen et al. 2011). The areas of inland lakes are expanding and lakes that were dried up in the 1960s– 1970s have now refilled with water (Shi et al. 2007). All this evidence suggests that the moisture conditions in this arid region have been improving in recent decades. Chen and Huang (2012) analyzed the atmospheric circulations associated with the July precipitation in the eastern part of northwest China and northern Xinjing. Because the precipitation variations in the TB are quite different compared to those of the eastern part of
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FIG. 1. The climatological water vapor fluxes (arrows, unit is kg m21 s21). Color shadings indicate the elevation (in m) of terrain. The area enclosed by red rectangle is the TB.
northwest China (Huang et al. 2013), the mechanisms discussed in their article cannot be directly applied to understand the summer precipitation in the TB. Therefore, the physical mechanisms causing the variations of precipitation in the TB have not been fully investigated. Because of prevailing westerlies, the long-term mean water vapor fluxes influencing the TB and its adjacent regions mostly come from the west, especially in winter (Yatagai 2003; Huang et al. 2013). In summer, a few case studies (e.g., Lin and Wu 1990) have suggested that water vapor from the Arabian Sea may be transported to the TB and cause heavy precipitation. Yatagai and Yasunari (1998) analyzed the summer water vapor transport and flux divergence in the TB during 1980–84. They found that most of the water vapor affecting the TB was transported from the northwest, along the periphery of the Tienshan Mountains. They also found that the southerly water vapor flows are related to heavy precipitation over the TB. Although water vapor transported from the south appeared in less than 10% of the total cases, these cases tended to occur mostly in wet summers (1981 and 1984). However, previous studies on the relationship between water vapor transport and precipitation in the TB were either focused on climatological water vapor transport or based on short-term observations. No attempts have been made to understand the precipitation variations and water vapor transport on interannual and longer time scales. The annual precipitation in the TB is usually less than 200 mm, with the majority of the precipitation falling in summertime (June–August). Therefore, the focus of this
study is to analyze the variations of summer precipitation in the TB and their relationship with water vapor transport and large-scale atmospheric circulation. Specifically, we will try to understand the water vapor budgets and their roles with regard to recent changes in TB precipitation. Addressing these issues is important for understanding the interactions between the lowlatitude monsoonal circulation and the midlatitude westerlies and the water supply for both natural and managed ecosystems in this arid region.
2. Data and methods The monthly precipitation dataset used in this study was obtained from the Global Precipitation Climatology Centre (GPCC) (Schneider et al. 2011). This dataset covers the period from 1901 to 2010 with a horizontal resolution of 1.08 latitude by 1.08 longitude. Because very few observations were available in the study region before 1960 (Feng et al. 2004), this study only focused on the variations of summer precipitation after 1960. To evaluate the regionality of precipitation in the TB and adjacent regions (358–438N, 75–92.58E), empirical orthogonal function (EOF) analysis was applied to the gridded summer precipitation in the TB. Our results suggest that the precipitation in TB exhibits coherent interannual variations compared to arid and semiarid midlatitude Asia (not shown). The areal mean summer precipitation in the TB during 1960–2010 is also highly correlated (correlation coefficient 0.98) to the principal component associated with the first EOF mode of the TB precipitation. Therefore, the areal mean summer
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precipitation in the TB is analyzed in this study because it can well depict the precipitation variations in the study region. Additionally, the daily precipitation obtained from Asian Precipitation-Highly Resolved Observational Data Integration toward Evaluation of Water Resources (APHRODITE; Yatagai et al. 2012) was also used to analyze extreme precipitation events. This dataset covers the period from 1 January 1951 to 31 December 2007 with a horizontal resolution of 0.258 latitude by 0.258 longitude. The global monthly precipitation reconstruction (PREC) dataset (Chen et al. 2004) with a horizontal resolution of 2.58 latitude by 2.58 longitude was also used to investigate the relationship between TB precipitation and anomalous heating over the northern Indian Ocean. Unlike the GPCC and APHRODITE datasets, the PREC dataset covers both land and ocean. In addition to precipitation, daily and monthly geopotential height, winds, vertical velocity, and specific humidity from 1960 to 2010 at various pressure levels were obtained from the National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) reanalysis (Kalnay et al. 1996). These data were analyzed to investigate the relationship between TB precipitation and large-scale atmospheric circulations. It is worth noting that the new NCEP Climate Forecast System Reanalysis (CFSR) is superior in many respects to the NCEP–NCAR reanalysis (Saha et al. 2010). Our evaluation suggested that the atmospheric circulations associated with the variations of TB precipitation are similar in both reanalysis datasets (not shown), suggesting that our results and conclusions are stable, and not dependent on the reanalysis data used. This study used the NCEP–NCAR reanalysis merely because the NCEP–CFSR dataset is shorter (1979–2009) than our focused period of precipitation variations (1960–2010). To evaluate the impacts of water vapor transport on TB precipitation, the vertically integrated horizontal water vapor fluxes were calculated by 1 Q5 g
ðP
s
qV dp,
(1)
300hpa
where q, g, Ps, V, and Q represent specific humidity, gravity, surface pressure, horizontal velocity, and water vapor flux, respectively. The pressure levels below the surface pressure as a result of topography were omitted when computing the water vapor fluxes. To evaluate the relative role of low- and upper-level water vapor on the TB precipitation, water vapor fluxes at low (1000– 700 hPa) and upper levels (700–300 hPa) were also computed.
The moisture transport is a product of specific humidity and wind speed, which can be divided into four components: ð 1 Ps (V q 1 Vq0 1 V0 q 1 V0 q0 ) dp , (2) Q5 g 300hpa where V and q are the long-term mean wind speed and specific humidity, respectively; V0 and q0 are the anomalies with respect to the long-term mean. The temporal variations of Q are related to the variations of wind (V0 q), 0 specific humidity (Vq0 ), and transient eddies (V q0 ). After computing the water vapor fluxes, the water vapor budget in TB as well as the moisture transport across each boundary can further be computed. Additionally, the possible moisture sources for anomalous precipitation are estimated using the relevant balance equation, assuming a steady state, as follows: precipitation 2 evaporation ð 1 Ps (V $q 1 q$ V) dp , ’ rw g 300hpa
(3)
where the moisture budget can be estimated as the contributions of advection of humidity by the wind (first term in parentheses) and the product of moisture and convergence (second term in parentheses).
3. Results a. Changes of precipitation and water vapor fluxes Before analyzing the relationship between water vapor transport and the precipitation in the TB, we investigated the vertically integrated summer mean water vapor fluxes. The water vapor fluxes from the northwest prevail in central Asia and then turn eastward to affect the study region (Fig. 1). This structure is consistent with a weak ridge over the north of the Caspian and Aral Seas and a weak trough over the northwestern border of China (Fig. 1). Compared to the Asian monsoon region, the water vapor fluxes affecting the TB are small. The mean water vapor fluxes influencing the TB mostly come from the west, while the mean water vapor transported from the south is very small. This notion is further supported by computing the water vapor transport across the boundary of the TB (Table 1). Although there are small water vapor fluxes from the northern and southern borders, the majority of the water vapor transported to the study region comes from the west and then leaves the region from the eastern boundary. Similar results were found when different reanalysis data were used (Yatagai and Yasunari 1998; Yatagai 2003).
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TABLE 1. Water vapor budget in the TB and its relationship with the summer precipitation. The numbers in columns 2–5 show the summer climatological water vapor across the each boundary. The positive (negative) numbers indicate the inward (outward) water vapor flux. The numbers in column 6 show the net water budget. Positive (negative) numbers indicate the TB gain (loss) water vapor. The numbers in parentheses are the Spearman rank order correlations between the water vapor budget and TB precipitation during 1960– 2010. One (*) and two asterisks (**) indicate that the Spearman rank order correlations between TB precipitation and water budget are significant at 95% and 99% confidence levels, respectively.
Low-level (1000–700 hPa) water vapor (31012 kg day21) Upper-level (700–300 hPa) water vapor (31012 kg day21) All-level water vapor (31012 kg day21)
Western boundary
Eastern boundary
0.31 (20.33*)
20.70 (0.37*)
0.00 (0.0)
2.63 (20.07)
23.54 (0.17)
0.52 (0.56**)
20.34 (20.53**)
20.73 (0.37*)
2.94 (20.10)
24.24 (0.26)
0.52 (0.56**)
0.37 (20.39*)
20.41 (0.49**)
To evaluate the impacts of water vapor transport on the variations of summer precipitation, Fig. 2a shows the temporal variations of summer precipitation in the TB and the water vapor budget. The net water vapor budget in the TB has been changing from slightly below zero in the early years to slightly above zero in recent decades, suggesting that the TB has been changing from a weak water vapor source to water vapor sink during the past 50 years. This result is consistent with the slightly increasing precipitation in TB. The variations of water vapor budget are significantly correlated to the summer precipitation (Table 1), suggesting that the water vapor budget plays an important role in causing the variations of summer precipitation in TB. We also estimated the relative contributions of the advection of humidity by the wind, and the product of moisture and wind convergence. The TB precipitation is strongly related to the advection of humidity (Fig. 2b) but weakly related to the product of moisture and the atmospheric convergence (Fig. 2c). This is understandable because the humidity in this arid region is very small, which leads to small contribution of wind convergence to the moisture budget. We further analyzed the water vapor fluxes from different directions and their roles with regard to the summer precipitation in TB. The correlations between precipitation and the water vapor fluxes are shown in Table 1. At the upper levels, the water vapor fluxes from the south dominate the variations of TB precipitation. This notion is also true when both the low- and upperlevel water vapor fluxes are considered. However, at low levels, the water vapor fluxes from the west (east) are negatively (positively) and closely related to the variations of precipitation (Table 1), suggesting that anomalous water vapor transports from the eastern boundary when the TB is under wetter conditions. These results are consistent with previous case studies that water vapor fluxes influencing the heavy precipitation in this region come from the south and east (Yatagai and Yasunari 1998; Lin and Wu 1990).
Southern boundary
Northern boundary 0.71 (0.10)
Budget in the box 0.32 (0.46**)
Because a relatively few days of precipitation may contribute most of the summer precipitation in the TB (Yatagai and Yasunari 1998), heavy precipitation may dominate the summer precipitation variations in this arid region. Therefore, the composite water vapor fluxes and atmospheric circulation for the 50 highest daily rainfall events in summer were computed. We examined the temporal distribution of these extreme events and found that the summers with more extremes are usually wet, while the summers without a top-50 extreme event are usually dry. As shown in Fig. 3, there is a noticeable ridge north of the Caspian and Aral Seas during the extreme precipitation events. The trough along the northwestern border of China deepened and penetrated to northern India. A strong ridge also exists over north-central China, downstream of the deep trough. The ridge over northcentral China can bring the low-level moisture along the east of the Tibetan Plateau to bend westward to impact the TB along the northern periphery of the plateau. The trough may also bring some water vapor from the north to affect the TB (Fig. 3a). The two low-level moisture flux convergences in the TB fuel the precipitation development. On the other hand, the deep trough may also bring abundant moisture from the northern Arabian Sea to northern Pakistan and northwestern India. At upper levels, the southwest wind associated with the deep trough can transport the water vapor from northern Pakistan and northwestern India to cross over the Tibetan Plateau to affect the TB, causing moisture convergence there (Fig. 3b). Compared to Fig. 3a, it suggested that the water vapor from the northern Arabian Sea can be first transported to the foothills of the southern Tibetan Plateau by low-level wind and then transported to the TB by upperlevel wind. Combination of the low and upper levels shows noticeable water vapor transported from the southwest to affect the extreme rainfall in the TB (Fig. 3c). These results are consistent with Table 1, showing that the TB precipitation is affected by low-level water vapor fluxes from the east and the upper-level water vapor fluxes from
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FIG. 2. (a) Temporal variations of the summer precipitation (black solid line) and moisture budget (blue dashed line) in the TB. The Spearman rank order correlation coefficient between the two time series is shown in the upper left. (b) As in (a), but for the humidity advection (green dashed line). (c) As in (a), but for the product of humidity and wind convergence (red dashed line).
the south. Our results are also consistent with previous studies (Yatagai and Yasunari 1998; Tao et al. 2014) showing that the southerly water vapor fluxes may pass over the Tibetan Plateau, and along the eastern periphery of the plateau at low levels, to affect the summer precipitation in the TB. To further delineate the large-scale water vapor fluxes and their relationship with precipitation, Fig. 4a shows the water vapor fluxes regressed against the summer TB precipitation. The summer TB precipitation is closely related to anomalous anticyclonic water vapor fluxes over the Arabian Sea and India and northern central China, and anomalous cyclonic water vapor fluxes in central Asia. These anomalous water vapor fluxes are consistent with the height anomalies at the 300 hPa (Fig. 4a), suggesting that the water vapor transport is affected by large-scale atmospheric circulation. Interactions between the negative height anomalies in central Asia and positive height anomalies in Arabian Sea/India transport the water vapor from the Arabian
Sea to the western periphery of the Tibetan Plateau and then bend north to affect the TB. The positive height anomalies in northern central China suppress the water vapor flux leaving the east border of TB, and hence induce an anomalous water vapor flux from the east to the TB, leading to water vapor convergence. To evaluate the robustness of the above results, the five wettest summers (1981, 1993, 1996, 2005, and 2010) and five driest summers (1960, 1961, 1978, 1980, and 1984) were chosen based on the regional averaged precipitation in the TB (Fig. 2). The spatial distributions of anomalous water vapor fluxes and geopotential height between the wet and dry summers (Fig. 4b) are similar to Fig. 4a, suggesting a linear relationship between TB precipitation and the atmospheric circulation and water vapor fluxes. The different water vapor transports caused by changes in specific humidity and wind are further analyzed. As shown in Fig. 5a, the water vapor fluxes due to changes in wind are similar to the results shown in Fig. 4, suggesting that the water vapor transport is dominated
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FIG. 3. (a) The mean vertically integrated low-level (1000–700 hPa) water vapor fluxes (arrows), water vapor convergence (color), and 500-hPa geopotential height (contour) based on the top 50 daily precipitation events in the TB in summer during 1960–2010. (b) As in (a), but for the upper-level (700–300 hPa) water vapor fluxes. (c) As in (a), but for the all-level (1000– 300 hPa) water vapor fluxes.
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FIG. 4. (a) The vertically integrated summer water vapor fluxes (arrows) and 300-hPa geopotential height (contour) regressed against the summer precipitation in TB during 1960–2010. Gray shadings (blue arrows) indicate the correlations between the geopotential height (water vapor fluxes) and the TB precipitation are significant at the 95% confidence level. Color shadings indicate moisture convergence or divergence. (b) Composite of the vertically integrated summer water vapor fluxes (arrows) and 300-hPa geopotential height (contour) between wet and dry years. Gray shadings (blue arrows) indicate differences of geopotential height (water vapor fluxes) between wet and dry years are significant at the 95% confidence level. Color shadings indicate moisture convergence or divergence.
by the variations of winds. The contributions of humidity to the water vapor transport are overall small, except over the Arabian Sea (Fig. 5b), suggesting that the humidity in the Arabian Sea may play an important role in the TB precipitation. These humidity anomalies can be transported to northern Pakistan and northwestern India by low-level wind and then transported to our study region by the upper-level wind (Fig. 3). The contribution of transient eddy water vapor transport to the TB precipitation is very small (Fig. 5c).
b. Relationship with atmospheric circulation To understand the physical mechanisms affecting the water vapor transport and the variations of summer
precipitation, we examined the mass and wind fields that are associated with the summer precipitation in the TB. As shown in Fig. 4, the TB precipitation is closely related to a west–east teleconnection over 358–508N, with positive anomalies appearing over the Mediterranean/ Caspian Sea and northern central China, and negative anomalies over central Asia and northeast China. The strong anomalous pressure gradient between the negative height anomalies in central Asia and the positive anomalies in northern central China induces strong southerly winds that affect the TB (Fig. 6a). It is also worth noting that this anomalous southerly wind prevails over the entire atmosphere (Fig. 6b). Additionally, the strong positive correlation between the precipitation
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FIG. 5. Regression between the TB precipitation and (a) water vapor transport due to changes in wind, (b) specific humidity, and (c) eddies during 1960–2010. Blue arrows indicate that the correlations between the water vapor fluxes and the TB precipitation are significant at the 95% confidence level. Color shadings indicate water vapor convergence or divergence.
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FIG. 6. (a) Summer 200-hPa meridional wind (unit is m s21) regressed against the summer precipitation in the TB during 1960–2010. Color shadings indicate the correlation between the meridional wind and precipitation is significant at the 95% confidence level. (b) As in (a), but for the height–longitude cross section of meridional wind averaged between 358 and 438N. The gray shading indicates terrain.
in the TB and the southerly wind in the Arabian Sea and at the India and Pakistan border (Fig. 6a) is consistent with Figs. 3 and 4, showing that the water vapor influencing the TB may come from the Arabian Sea. The anomalous southerly wind associated with the TB precipitation depicts a quasi-zonal wave like pattern along the Asian jet stream (Figs. 4 and 6). The vertical structure of this pattern is barotropic, although mostly evident at 200 hPa (Fig. 6b). According to the theory of stationary external Rossby waves (Held et al. 1985), this wavelike pattern is the result of propagation of the stationary external Rossby waves. For a short wave system, there will be ascending (descending) motion ahead of the trough (ridge) according to the omega equation (Holton 2004). Therefore, the negative geopotential height anomalies in central Asia and the positive anomalies in northern central China (Fig. 4) should cause ascending motion in the TB. In light of this height– omega relationship, we analyzed the vertical velocity and its relationship with the TB precipitation. As shown in Fig. 7, the anomalous ascending motions are dominant at low levels in the vicinity of 758–1008E. Therefore,
the confluences of the moisture convergence, ascending motion in the TB, and water vapor fluxes from the south are favorable conditions for precipitation development in the TB, leading to more precipitation there. Besides the zonal teleconnection, there is also a prominent meridional wave pattern around 508–808E, with positive anomalies over the Arabian Sea and India and the high-latitude regions near 608N and 608E, and negative anomalies in central Asia, suggesting a strong connection between the tropics and the middle and high latitudes (Fig. 4). Such pattern is also evident in the middle and lower atmosphere. Figure 8 shows the height–latitude cross section of the geopotential height anomalies regressed against the TB precipitation. A barotropic teleconnection pattern appears with out-ofphase anomalies between the tropics and central Asia.
4. Discussion Our results suggest that the TB precipitation is closely related to the zonal teleconnection in the midlatitude along the Asian westerly jet in summer (Figs. 4 and 6).
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FIG. 7. As in Fig. 6b, but for the vertical velocity (unit is Pa s21) averaged between 358 and 438N. Positive (negative) values indicate descending (ascending) motion.
This wave pattern resembles the regional expression of the circumglobal teleconnection (CGT) pattern (Ding and Wang 2005; Chen and Huang 2012), also called the ‘‘Silk Road pattern’’ (Enomoto et al. 2003). The pattern correlation between the height anomalies in Fig. 4 and the CGT pattern described in Chen and Huang (2012) is 20.84 over 308–608N and 308–1308E, suggesting that the excessive precipitation in the TB is linked to negative phases of the Silk Road pattern. Chen and Huang (2012) suggest that the CGT pattern can be considered as the
interannual component of the Silk Road pattern. This pattern is closely related to the strength of the Asian jet in summer. Enomoto et al. (2003) suggest that enhancing Asian jet is favorable for the propagation of stationary Rossby waves, and the sources of the Silk Road pattern are the descending motions over the Mediterranean Sea and the Indian monsoon heating. Further studies have suggested that the anomalous heating associated with Indian monsoon is mostly responsible for this wave pattern (Ding and Wang 2005; Ding et al.
FIG. 8. As in Fig. 6b, but for the height–latitude cross section of geopotential height (unit is gpm) averaged between 608 and 708E.
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FIG. 9. Correlation between the summer PREC precipitation and (a) the summer CGT index (Ding and Wang 2005) and (b) summer precipitation in TB during 1960–2010. Shadings indicate the correlations are significant at the 95% confidence level.
2011). Chen and Huang (2012) investigated the excitation mechanisms for the CGT and suggested that this wave pattern is the extratropical response to the anomalous tropical heating. The tropical heating excites divergent flow at the upper troposphere, which induces advections of vorticity and acts as effective Rossby wave sources. They further suggested that the anomalous heating in the northern Indian Ocean is responsible for the Silk Road pattern.
To further examine the relationship between TB precipitation and the Silk Road pattern and their mechanisms, we calculated the relationships between CGT, TB precipitation, and the PREC precipitation. The CGT index (Ding and Wang 2005) is significantly but negatively correlated to summer precipitation in our study region (Fig. 9a), consistent with our results that the excess summer precipitation in the TB is associated with the negative phase of the Silk Road pattern (Fig. 4).
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Additionally, the CGT is significantly and positively correlated to precipitation over the northern Indian Ocean and Indian subcontinent. These results confirm previous studies that the CGT is strongly linked to the Indian summer monsoon and associated heat anomalies (Ding and Wang 2005; Ding et al. 2011; Chen and Huang 2012). According to Chen and Huang (2012), anomalous heating (precipitation) in northern Indian Ocean may excite the CGT through the meridional teleconnection around 508–808E (Figs. 4 and 8). Therefore, stronger (weaker) heating in the northern Indian Ocean and Indian subcontinent may lead to positive (negative) CGT, which in turn may lead to drier (wetter) conditions in the TB. This notion is also supported by Fig. 9b, which shows that the correlations between the TB and the PREC precipitation are similar, but with opposite sign, to that between the CGT index and PREC precipitation. The Silk Road pattern associated with the TB precipitation also depicts opposite height anomalies between northern central and northeastern China (Figs. 4 and 9). The opposite height anomalies in the two regions lead to descending motion (Fig. 7) and less water vapor flux transport to northern China (358–508N, 1058–1208E) (Figs. 4 and 5); together they inhibit precipitation development there (Fig. 9). Therefore, our results can also explain the opposite precipitation variations between the TB and northern China (e.g., Feng et al. 2007, 2013; Chen et al. 2010, 2011; Huang et al. 2011, 2013).
5. Conclusions This study analyzed summer precipitation variations in the Tarim Basin (TB) in northwestern China, and their association with water vapor fluxes and atmospheric circulation. Our results suggest that although the mean water vapor influencing this region comes from the west, the upper-level water vapor fluxes from the south and low-level water vapor fluxes from the east play important roles in causing the variations of summer precipitation. The summer precipitation variations in the TB are associated with two teleconnection patterns. The meridional teleconnection around 508–808E depicts negative height anomalies in central Asia, and positive height anomalies in the tropics and sub-Arctic regions. This teleconnection pattern connects central Asia and the tropical Indian Ocean. The zonal teleconnection in the middle latitudes resembles the ‘‘Silk Road pattern.’’ The large pressure gradient force between the negative height anomalies in central Asia and the positive height anomalies in northern central China leads to ascending motion in the TB, and brings more water vapor from the Arabian Sea passing over the Tibetan Plateau and anomalous low-level water vapor from the east to influence the
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precipitation development in the study region. Additionally, the two teleconnection patterns can well explain the so-called out-of-phase relationships between precipitation in the TB and the East Asian summer monsoon. Acknowledgments. We thank the editor, Dr. Kerry H. Cook, and two anonymous reviewers for their constructive comments, which have led to improvement of this manuscript. We also thank Mr. Xiaojian Zhang for discussion and suggestions. This work was jointly supported by the National Basic Research Program of China (2012CB955301), National Natural Science Foundation of China (NSFC) (Grant 41130102, 41471162), and Program of Introducing Talents of Discipline to Universities (Grant B06026). Feng is also partly supported by NSF Grant AGS-1103316.
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