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THE EFFECTS OF THE THERMAL ANOMALIES

OVER THE TIBETAN PLATEAU AND

ITS VICINITIES ON CLIMATE CHANGE IN CHINA

QIAN Yongfu, YAO Yonghong

ZHANG Yan, HUANG Yanyan and HUANG Ying

Department of Atmospheric Sciences, Nanjing University, Nanjing 210093, China ; qianzh2@netra.nju.edu.cn

ABSTRACT

The evident effects of the thermal anomalies over the Tibetan Plateau (TP) and its vicinities are summarized and discussed in this paper. By the SVD technique and numerical simulations of the effect of the snow depth anomaly over the TP it is depicted that the snow depth anomaly especially in winter is one of factors influencing precipitation in China and the winter snow anomaly is more important than the spring one to the regional precipitation in China. Results of numerical simulations also show that the snow anomaly over the TP has evident effects on China's summer monsoon climate. The relations between the sensible heat anomaly over the TP and the onset of the South China Sea (SCS) summer monsoon are studied, too. It is seen that there are two key areas of the sensible heat anomaly over the TP with opposite correlations to the SCS monsoon. The west one, west of 75°E, is positively correlated while the east one negatively correlated to the intensity of the SCS monsoon. The interannual variations of the key area sensible heat flux and the intensity of the SCS summer monsoon are compared with each other and the composite analysis is also done for both strong and weak sensible heating years. By use of the NCEP/NCAR monthly mean meteorological reanalysis data and the monthly precipitation amount data in 160 stations of China during 1958 to 1997 period the relationships between the South Asia High (SAH) and the precipitation in the years with typical droughts or floods in the mid to lower valleys of the Yangtze River and North China are investigated in some detail. It is found that in years with much stronger intensity of the SAH the rainfall amount in the mid to lower valleys of the Yangtze River is usually above normal while in North China lower than normal. Not only the intensity of the SAH over the TP, but also the 100 hPa level height at each grid point influence the precipitation over the two areas. The key regions of the 100 hPa level height field can be found in the tropical and subtropical belts between 20°S and 30°N with the maximal differences in the equatorial zone. Effects of the SAH on the onsets of the tropical Asian summer monsoon (TASM) including the SCS summer monsoon (SCSSM) and the tropical Indian summer monsoon (TISM) are studied as well in this paper. It is found that the onset time of both the SCSSM and the TISM can be determined by the position of the SAH center. When the center passes across 20°N the SCSSM onsets and when it passes through 25°N the TISM onsets. Such determined onset times of the SCSSM and the TISM are well coincident with that determined by the sign transition time of the temperature gradient between 25°N and 5°N averaged in the mid to high troposphere between 100 hPa and 500 hPa, the moist potential vorticity (MPV) and the abnormal zonal wind shear between the 850 and the 200 hPa levels.

Key words: effects of heating anomalies over the Tibetan Plateau, the South Asia High (SAH), the South China Sea monsoon, precipitation anomalies in China

I. INTRODUCTION

The Tibetan Plateau (TP) has its evident dynamic and thermodymanic effects on general circulation and climate, especially in the East Asia and China. Hahn and Manabe (1975) found that Asian summer monsoon could be well simulated when the Plateau topography was incorporated in their model. Wu et al. (1998) pointed out that the onset of Asian monsoon depends on the thermal effect of the Plateau to a large extent. Kuo and Qian (1982) found that if there were no topography of the Tibetan Plateau in their model, the simulated pattern of precipitation would be much different from the observations. Qian et al. (1988, 2001) discovered important influences of the Plateau on rainfall and onset date of monsoon. The thermal effects of the TP can be reflected in anomalies of snow, the surface sensible heat flux density and the circulation systems at lower and upper levels. The anomaly of the South Asia High (SAH) is one of representative circulation anomalies that are strongly controlled by the TP heating. Therefore in this paper some research achievements obtained by our group in Nanjing University are summarized and discussed.

 

II.  RESPONSES OF CHINA'S REGIONAL PRECIPITATION TO THE SNOW ANOMALY IN WINTER AND SPRING OVER THE TIBETAN PLATEAU

The anomaly of snow over the Tibetan Plateau can change its thermal forcing remarkably and influence the developing process of monsoon consequently, resulting in large area floods and droughts in China. The National Climate Center of China (1999) took the anomaly of the Plateau snow cover as one of important factors influencing the 1998 severe floods in the Yangtze River Basin and Northeast China.

1.  The SVD Analysis of the Relations between the Plateau Snow Anomaly and the Precipitation in China in Spring and Summer

Zheng and Qian (2000) studied the climatic effects of snow anomaly over the Tibetan Plateau on regional summer monsoon climate in China. At first, they adopted the SVD technique to diagnose the relationships between the Plateau snow anomalies and the regional precipitation in China. The data for SVD diagnosis are the monthly mean snow depth in 56 stations over the Tibetan Plateau and the monthly precipitation in 160 stations in China during 30 years from 1964 to 1993. Both data are standardized. Four pairs of snow and precipitation anomalies are analyzed. The first pair contains the pre-winter snow depth and the later spring precipitation. The second couples the pre-winter snow depth and the later summer precipitation. The third and the fourth are the same as the first and the second, but for spring snow depth. Figure1 gives the first mode heterocorrelation coefficients of precipitation for all the four pairs. Their square covariance is all about 20%, indicating that snow depth and the simultaneous or the later precipitations are well correlated to each other. In spring (Fig.1a), the positively correlative areas are located in east coastal South China, middle China, North China and Northeast China, the confidence level and the maximum values of coefficients in those areas exceed 0.10 (shaded in figure) and 0.6, respectively. The regions from the east coastal plain between 30°N and 33°N to Southwest China between 27°N and 30°N are the negatively correlative areas, but with a low confidence level. Therefore, when the winter snow depth over the TP is deeper than usual, the precipitation in spring in the above positively correlated areas is more than normal, while in the negatively correlated areas it is less. In summer (Fig.1b), when the winter snow depth is deeper, the rainfall over the Yangtze River basins especially over the lower and the upper basins is above the normal, while it is below the normal over South and Southwest China. So, the same winter snow depth anomaly may result in different patterns of precipitation anomaly in different seasons and different areas. The spring snow depth anomaly results in more precipitation in the same period in the areas, south of 33°N, and less precipitation in other places, north of 33°N (Fig.1c). It induces more rainfall in summer in East, South and Southwest China as well as in the south part of Northeast China, while less precipitation in middle China, the north part of Northeast China and a small area in the down Yangtze River Basin (Fig.1d). However, the heterocorrelation coefficients are small with the maximum value of only about 0.4, much less than that of the corresponding winter one.

Table 1. Correlation Coefficients between Precipitation and Snow Depth Anomaly

Preci  period

May

Summer (JJA)

Regions

SC     YH     ES     NC    NEC

SC    YH     ES    NC    NEC

Winter snow

Spring snow

-0.133  –0.218  –0.154  –0.126   0.176

0.126  –0.119  –0.121  –0.137  –0.122

-0.187  0.269   0.326   0.162  –0.226

0.134  0.146  –0.132   0.129  –0.125

Note: Abbreviations SC for South China, YH for the Yangtze and the Huaihe River Basins, ES for the east Sichuan Province, NC for North China and NEC for Northeast China.

The first mode of the SVD analysis only reflects the best coupling signal between two fields, but not the all. Therefore, in order to verify the above results the responses of precipitation in May and in summer over some typical regions in China to the winter and the spring snow anomalies are further studied. Their correlation coefficients are given in Table 1. The abbreviations in Table 1 represent different regions (see note below the table). Table 1 indicates that the anomalies of winter and spring snow depth are negatively correlated with precipitation in most areas in May except in Northeast China for winter snow and in South China for spring snow. The case is somewhat complicated for summer precipitation. The winter snow depth is positively correlated with precipitation in the Yangtze and the Huaihe River Basins, the East Sichuan Province and North China, while negatively correlated with precipitation in South China and Northeast China. The spring snow depth is positively correlated with precipitation in South China, North China and the Yangtze and the Huaihe River Basins, while negatively correlated with precipitation in the East Sichuan Province and Northeast China. Generally speaking, the coefficients between winter snow depth and precipitation anomalies are larger than that between spring snow depth and precipitation anomalies. However, no matter in May or in summer the absolute coefficients are all not large enough. Only the correlation coefficients between winter snow depth and precipitation in May in the Yangtze and the Huaihe River Basins and in summer in the above same area, the East Sichuan and Northeast China pass the confidence level of 0.10 (lightly shaded in Table 1). So, the snow depth anomaly especially in winter is one of factors influencing precipitation in China, however, it is perhaps not the unique one and even not the most important one. Nevertheless, it is proved that the winter snow anomaly over the Tibetan Plateau is more important than the spring one to the regional precipitation in China.

 

 

Fig.1. The heterocorrelation coefficients of precipitation of the first SVD mode. (a) for winter (DJF) snow and spring (MAM) precipitation, (b)
for winter snow and summer (JJA) precipitation, (d) for spring snow and spring precipitation and (d) for spring snow and summer precipitation.


2.  Numerical Simulations of the Snow Effect on Precipitation in China

In order to simulate the influences of the Tibetan Plateau snow anomalies on regional climate in China, fine mesh numerical models should be used. Therefore, the second version of the NCAR regional climate model (RegCM2) is selected. The turbulence kinetic energy (TKE) scheme and a new computational scheme of boundary layer tops with much better effectiveness of simulation is incorporated to replace the original ones in the model (Zheng et al., 1999).

Six experimental schemes are designed, that is control (CN), the winter snow depth deeper (DL), the winter snow cover larger (CL), the spring snow depth deeper (DL2), the winter snow depth shallower (DS) and the fixed boundary conditions in 1998 (BN). In order to save space, the detailed descriptions of the schemes are omitted and may be found in the paper of Zheng et al. (2000).

The simulated distributions of snow depth in Feb. and in May in the CN are shown in Figs.2a and 2b, respectively. It is clearly seen that the spatial distributions and time variations of snow depth are simulated quite well. In Feb. (Fig.2a), the areas with deeper snow depth concentrate over the main Tibetan Plateau and over the Tianshan Mountains. In between there is an area with shorter snow depth over the north slopes of the Plateau and the south Xinjiang Basin. Such a distribution is fairly coincident with observations and perhaps due to the influences of the special topographic properties. In May (Fig.2b), the snow mostly melts away due to the temperature rises except over the Tianshan Mountains and the southeast Plateau. It is also seen that the largest time variation of snow takes place in the east Plateau. The snow depth differences expressed in equivalent water amount (mm) in Feb. between the DL and the CN are shown in Fig.2c, showing the largest snow depth anomalies in the east Plateau and the assumed forcing of snow depth anomaly in that month.

The time variations of area mean snow depths in the CN and in the DL are plotted in Fig.2d. The peak value of snow depth in the CN appears in Feb. both in the west and the east parts of the Plateau. In the DL it appears in March with a delay of one more month than in the CN. From the beginning of Feb. the difference of snow depth between the DL and the CN becomes larger and larger, reaching a maximum at the end of the month. From early Mar. the difference gets smaller and smaller and disappears finally at the end of May. The above features of time variations are basically in agreement with the observed ones (Li, 1996). The simulated area mean snow depth in the CN is not very much different in both the west and the east of the Plateau. While in the DL the snow is much deeper in the east than in the west owing to the different percentage of incorporated snow forcing in the two areas (see Fig.2c). Therefore the forcing of snow depth anomaly not only influences the difference of snow depth between the two experiments, but also increases the difference of snow depth between the east and the west parts of the Plateau which may enhance the thermal contrast between the west and the east of the TP and therefore influence circulation patterns over the Plateau.

 

 

Fig.2. Simulated distributions of snow depth in Feb. (a) and May (b) in the CN, snow depth differences in Feb. between the DL and the CN (c) and time variations of the area mean snow depth (d). In Fig.2d crossed (+) curve for the West Plateau, west of 90°E, blank circled (o) for the East Plateau, east of 90°E, in the CN, dark circled (·) and blank squared (?) for the two same areas but in the DL. Unit: mm of equivalent Mater.

 

Figures 3a and 3b are the differences of precipitation (in mm/d.) between the DL and the CN in May (a) and in summer (b). It is seen that due to the increased snow depth over the Tibetan Plateau in Feb. the precipitation in May is remarkably reduced in the region south of the Yangtze River. The precipitation in summer is increased roughly between 30°N and 40°N while decreased both south and north of the area. So, the increase of winter snow depth reduces precipitation in the South China area both in May and in summer as well as in the north part of China in summer, while increases precipitation in the mid and the lower Yangtze River Basins in summer. Precipitation over the Bay of Bengal is even more severely influenced by the snow depth anomaly and largely reduced when the snow depth over the Plateau increases in winter.

 

 

Fig.3. Differences of precipitation rate (in mm/d) between the DL and the CN in May (a) and in summer (b), (c) and (d) the same but between the BN and the CN, (e) and (f) between the CL and the CN.

 

Figures 3c and 3d are the same as Figs.3a and 3b but for the BN. It can be found that the basic patterns of precipitation differences between the BN and the CN are similar to that between the DL and the CN but with much bigger values. The negative anomalies in May in the south of the Yangtze River and South China are more evident and the domain is much larger. The positive ones in summer occupy much larger area between 30°N and 40°N so that the whole region between the Yangtze and the Huaihe Rivers becomes an area with more precipitation. Therefore, the background circulation reflected in the boundary forcing conditions has in-phase effect with the deeper winter snow though, it may be more important to the summer floods in 1998.

 

Figures 3e and 3f show the precipitation differences between the CL and the CN. It is found that the spatial patterns of the differences in May and in summer are somewhat similar to that between the DL and the CN. However, precipitation anomalies are much smaller both in May and in summer except for the Bay of Bengal area in summer where the anomalies are as large as in Fig.3b and even larger than that in Fig.3d. Therefore, we may infer that the anomalies of snow depth and snow cover are equally important for the summer precipitation in the Bay of Bengal area and more important than that of the background conditions. However, the snow cover anomaly is relatively less important than that of snow depth for the floods over the Yangtze and the Huaihe River Basins in summer. Moreover, a comparison of Fig.3 with Fig.1b indicates the similarity of the anomaly patterns of summer precipitation in all the three experiments to that in the SVD analysis, though with some discrepancies in area and value.

 

 

 

III.  RESPONSES OF THE SOUTH CHINA SEA SUMMER MONSOON (SCSSM) TO THE HEAT ANOMALY OVER THE TIBETAN PLATEAU

 

The tropical Asian summer monsoon (TASM) begins earliest in the SCS, that is the SCS summer monsoon (SCSSM), and then it expends northward to the east continental areas of Asia inducing the onset of the subtropical East Asian summer monsoon (STEASM) and westward to the India Peninsula (IP) and the Arabian Sea (AS) resulting in the burst of the tropical Indian summer monsoon (TISM). The later or earlier onset and the weaker or stronger intensity of the SCSSM have close relations to the intensity of the Asian summer monsoon and the geographical distributions of the summer droughts and floods in Asia especially in China. Thus, the onset time and the intensity of the SCSSM is one of the focuses in the monsoon studies in recent years.

1.  The Key Area of the Surface Sensible Heat Flux Density over the Tibetan Plateau

The onset time and the intensity of the SCSSM both have large interannual and decadal or interdecadal variations. Zhang and Qian (2002) used the monthly mean surface sensible heat flux densities in 1949-2000, the wind and the temperature fields from 1958 to 1997 of the NCEP/NCAR reanalysis data with resolution of 2.5°´2.5° to analyze the causes of the SCSSM variations.

 

 

 

 

Fig.4. Spatial distribution of the correlation coefficient between the sensible heat in June and the SCS summer monsoon intensity index (significance level in the shaded area0.05).

 

The spatial distribution of the correlation coefficient between the sensible heat in June and the SCS summer (JJA) monsoon intensity index (refer to Yao and Qian, 2001) is given in Fig.4 with shaded areas representing the confidence level of 0.05. From Fig.4 the representative sensible heat region can be found, that is the large positive correlation area in the northwestern TP7075°E3540°Nwhich is defined as the key sensible area impacting the SCSSM and is also a large value area of variance of the sensible heat flux field in 40 years in spring and summer.

 

2.  The Interannual Variations of the June Sensible Heat Index and the SCSSM Index and Their Correlation

The June sensible heat index is defined as the area mean of the June sensible heat anomalies averaged in the key area. Figure 5 shows the time series of both the standardized sensible heat index (a, dark solid line) and the SCSSM intensity index (b, dashed line). It is found that there is an obvious positive correlation between the two indices and the correlation coefficient is 0.4667 passed the significance level of 0.001. It is also found from Fig.5 that the time series of the sensible heat has an obvious interdecadal change with the abrupt transition in the late 1970s. Before that period, the sensible heat fluxes are extremely strong; while after 1978, they are weak. This abruption can be also found in the index series of the SCSSM intensity. The reason may be explained as follows. When the June sensible heat over the TP is stronger in some year, the temperature is higher, the heat low over the Plateau becomes stronger, too, and results in stronger cyclonic circulation over the down stream areas of the SCS. The SCSSM intensity index is defined as the moist potential vorticity anomaly that is related to the moisture, the temperature and the vorticity, and consequently, the SCSSM intensity is stronger, and vice versa.

 

 

Fig.5.  The standardized time series of sensible heat flux of the TP key region (a, solid line) and the SCS summer monsoon intensity index (b, dashed line). 

3. The Composite Analysis of the Strong and the Weak Years of the Indices

Based on the standard deviations of the anomalies of both the sensible heat and the SCSSM intensity indexes, the strong year and the weak year of both indices can be defined according to the normalized anomalies of both fields greater than 0.5 and less than –0.5, respectively. During 40 years, there are six canonical strong years, i.e. 1959, 1961, 1962, 1963, 1965, 1966, and six canonical weak years, i.e. 1973, 1983, 1989, 1993, 1995, 1996.

 

Figure 6 presents the composite fields of the sensible heat flux in strong (a), weak (b) monsoon years and their difference (c). Comparing Fig.6a with Fig.6b, it is found that the surface sensible heating over the east and the west Plateau displays a significant difference. The surface sensible heating is stronger in the west Plateau and weaker in the east Plateau in the strong monsoon years, while in the weak monsoon years the case is reversed. The sensible heating difference distribution over the Plateau (Fig.6c) shows a structure of warmer west and cooler east. Besides, in the high-latitudes, north of the Plateau, there is a strong sensible heating center, corresponding to the higher tropospheric temperature. The above phenomena imply that the surface sensible heating anomaly over the Plateau will cause the temperature anomaly over there. And this change of thermodynamic field is bound to result in the change of stream patterns; consequently, the interannual variations of the surface sensible heating over the TP and the SCSSM intensity are positively correlated.

 

 

 

 

IV. EFFECTS OF THE SOUTH ASIA HIGH ON TYPICAL DROUGHTS AND FLOODS IN THE MID TO LOWER VALLEYS OF THE YANGTZE RIVER AND NORTH CHINA

 

By use of the NCEP/NCAR monthly mean meteorological reanalysis data and the monthly precipitation amount data in 160 stations of China during 1958 to 1997 periodHuang and Qian (2002a) analyzed the relationships between the South Asia High (SAH) and the precipitation in the years with typical droughts or floods in the mid to lower valleys of the Yangtze River and North China. They found that both the intensity and the center position of the SAH could have impacts on droughts and floods in the two areas. Anomalously intensifying of the SAH usually induces floods in the mid to lower valleys of the Yangtze River and droughts in North China; while anomalously weakening often gets the opposite precipitation anomalies. In addition, it is concluded that the anomalies of precipitation in the two areas are usually in opposite phase.

 

The intensity of the SAH can be expressed by the 100 hPa level height. When the 100 hPa level height is higher than normal, the intensity of the SAH is stronger than usual and vise versa (Zhang and Qian, 2000). Figure 7 shows the composite summer height difference distributions at the 100 hPa level between the flood and the drought years in the mid to lower valleys of the Yangtze River (a) and North China (b) with unit of gpm. It is clearly seen that in years with much stronger intensity of the SAH the rainfall amount in the mid to lower valleys of the Yangtze River is usually above normal while in North China lower than normal. Figure 7 also indicates that not only the intensity of the SAH over the TP, but also the 100 hPa level height at each grid point influence the precipitation over the two areas. The key regions of the 100 hPa level height field can be found in Fig.7, that is the tropical and subtropical belts between 20°S and 30°N. The maximal differences can be found in the equatorial zone.

 

 

 

 

Fig.7.  The composite summer 100 hPa geopotential height differences between the flood and the drought years in the mid to lower valleys of the Yangtze River (a) and North China (b)units: gpm.

Fig.8.  The composite anomalies of 100hPa circulation in previous spring of flood (a, c) and drought (b, d) years over the mid to lower valleys of the Yangtze River (a, b) and North China (c, d) (units: m s-1).

 

 


The composite circulation anomalies in the previous springtime (MAM) are also obvious and may be used as an indicator of the flood or the drought years. Figure 8 is the composite anomalies of 100 hPa circulation in previous spring of flood (a, c) and drought (b, d) years over the mid to lower valleys of the Yangtze River (a, b) and North China (c, d) with unit of m s-1 . It is seen that in the previous springtime, if the westerly anomalies over the tropical and subtropical belts exist and are stronger, then the coming summer precipitation in the Yangtze River Basins would be above normal, while over North China below normal, and vise versa.

 

 


Fig.9.  Interannual variations of the SAH parameters thin sold line and the precipitation in dark sohid line North China. (a) the anomalies of the SAH center longitude in June and the summer (JJA) rainfall in North China; (b) the anomalies of the SAH intensity in previous June and the summer rainfall in North China.

 

Huang and Qian (2002b) also carried out a special study on the relations between the SAH and precipitation in North China. Firstly, they analyzed the interannual variations of the SAH and the North China precipitation as shown in Fig.9. It is found that the interannual variations of the SAH and precipitation are closely correlated to each other, especially, correlation between the longitudes of the SAH in June and precipitation in summer (Fig.9a) that passes the confidence level of 0.05. The precipitation in North China in summer does not have good relation to the SAH intensities in June of the previous year. However, they are well related to each other after 1974 (Fig.9b). Figure10 shows the 100 hPa composed flow fields in June with (a) representing the years with more western SAH and higher precipitation in North China, (b) the years with more

Fig.10.  The 100 hPa composed flow fields in June. (a) the years with more western SAH and higher precipitation in North China, (b) the years with more eastern SAH and lower precipitation, and (c) the difference between a and b (unit: m/s).

eastern SAH and lower precipitation in North China, and (c) the difference between (a) and (b) (unit: m/s). It is seen that in higher precipitation years in North China the SAH center sifts more westward and northward and vice versa in lower precipitation years, the differential flow center between the two cases is located over 3540°N and 60°E. Much stronger easterly and northeasterly flow enters the east part of China.

 

 

 

V.  EFFECTS OF THE SOUTH ASIA HIGH ON THE ONSETS OF THE TROPICAL ASIAN SUMMER MONSOON (TASM) INCLUDING THE SCS SUMMER MONSOON (SCSSM) AND THE TROPICAL INDIAN SUMMER MONSOON (TISM)

 

 

Qian et al. (2002) have discussed the TASM onset process from the seasonal evolutions of the multi-yearly averaged pentad mean velocities at the low level and the TBB. They pointed out that due to the continuity of the earth fluid the seasonal evolution of general circulation should be reflected in the whole atmosphere. At the higher levels the general circulation is relatively simpler than that at the lower levels owing to the gradual weakening of the effect of topography and land-sea distribution. Meanwhile, at the high levels in summer the dominant circulation pattern is the SAH especially at the 100 hPa level. Therefore, in this section we are going to briefly discuss the relations between the onset of the TASM and the SAH seasonal evolution.


Figure11 shows the geographic distributions of the SAH centers in each pentad in April to July during 19801995 (a) and the multi-yearly averaged pentad mean in the same period (b). It is seen from Fig.11a that the SAH centers in pentads 19-24 scatter to high extent and most of the centers locate in south of 20°N. The centers begin to concentrate in two regions in pentads 2430, one is the north Indochina Peninsula (ICP) and the Bay of Bengal (BB) and the other the west Indian Peninsula (IP) and the east Arabian Sea (AS) with seldom centers over the western Pacific. In pentads 3136 the centers concentrate in three areas, that is, the east of the Tibetan Plateau (TP), the north TP and the north IP. In pentads 37-42 the centers are most located over a narrow and long belt north of 30°N. From the multi-yearly averages (Fig.11b) it is found that the centers are located over the middle ICP along 100°E with the mean position at 20°N in pentads 24-30. They locate over the TP along 90°E in pentads 31-36 with the mean position at 25°N. The onset time of the SCSSM is normally in pentads 24-30 and that of the TISM in pentads 31-36. Therefore, it is proper to suppose that the onset time of both the TASM and the TISM be determined by the position of the SAH center.

 

 

Fig.11.  The geographic distributions of the SAH centers in each pentad in April to July during 19801995 (a) and the multi-yearly averaged pentad mean in the same period (b). (Pentads 1923+2430о3136·3742´)


From Fig.11a it has been seen that there are big differences among the longitudes of the SAH centers in certain pentad in different years. Therefore, only the latitude of the center can be used as the indicator of the onset time of the TASM and the difference of the longitude should be omitted. Next, we determine the onset time by use of the latitude only, i.e. when the center passes across 20°N, the SCSSM onsets and when it passes across 25°N the TISM onsets. Tables 1 and 2 are the onset pentads of the SCSSM and the TISM, respectively, determined in the above way. The pentad when the temperature gradient between 25°N and 5°N averaged in the mid to high troposphere between 100 hPa and 500 hPa changes sign and the pentad when the moist potential vorticity (MPV) changes sign (see Yao and Qian, 2001) are also listed in Table 1. The pentad of sign transition of the anomalous zonal component shear (see Webster and Yang, 1992) between 850 hPa and 200 hPa in the IP area7085°E1020°Nis listed in Table 2 for comparisons. As is seen from Table 1 that the earliest onset time of the SCSSM determined by the SAH center is pentad 25; the latest is pentad 31; the mean one is 27.6. Years with earlier onset of monsoon (one or more pentads earlier than normal) are 1985,1986,1989,1990 and 1994, while years with later onset (one or more pentads later than normal) are 1982,1983,1987,1991 and 1993. The earliest, the latest and the mean onset time determined by the temperature gradient are pentads 25, 30 and 27.6, respectively, basically the same as the first method in the SCS area. The onset time determined with the third scheme has more interannual variation with the earliest onset in pentad 23, the latest in pentad 32 and the mean in 28.1. The above differences amongst the three schemes may be due to the different physical quantities used. When the low level physical quantities are used to determine the onset time of the TASM, the onset time is difficult to correctly determine because of their frequent alternation of active and break phases. While the SAH center positions and the temperature gradients are much stable in their seasonal evolutions avoiding the wrong determination of the onset time. From Table 2 the mean onset time in the IP area is pentad 31.3 determined with the center position of the SAH that is consistent with the normal one, while the mean onset time is pentad 29.5 and 28.8, respectively determined with the second and the third schemes. It is also found in Tables 1 and 2 that the onset time usually later than normal in the El Nino events (dark numbers in Tables 1 and 2) indicating certain connection between the El Nino and the TASM.

 

Table 1.  Onset Time (Pentad of the Year) of the TASM in the BB to SCS Regions, East of 90°E, in 1980-1994, Determined with Three Different Schemes: 1 SAH Center; 2 Temperature Gradient and 3 MPV

Ptd

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

Mean

SAH 20°N

27

27

30

29

28

25

26

29

28

26

26

29

28

31

25

27.6

T(25-5°N)

27

27

30

29

27

27

27

28

26

26

28

29

28

30

25

27.6

MPV

26

27

31

27

28

23

26

32

29

28

28

32

28

31

25

28.1

Table 2.  Onset Time (Pentad of the Year) of the TASM in the IP to AS Regions, West of 90°E, in 1980-1994, Determined with Three Different Schemes: 1 SAH Center; 2 Temperature Gradient and 3 Wind Shear between 850 and 200 hPa

Ptd

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

Mean

SAH 25°N

30

32

30

33

33

29

31

32

32

29

31

33

32

32

31

31.3

T(25-5°N)

28

28

30

30

29

29

31

31

28

28

27

31

32

31

30

29.5

Windshear

28

28

30

30

27

29

28

31

26

27

27

31

32

30

29

28.8

VI.  CONCLUSIONS AND REMARKS

 

The thermal state of the TP is represented with anomalies of the snow depth and cover, the surface sensible heat flux density and the circulation of the SAH. The climatic effects of the TP heating anomalies on the precipitation in various areas of China especially in the Yangtze River Basins and North China are diagnosed, numerically simulated, and proved significantly. Some new findings are displayed.

 

It is found that the snow depth anomaly especially in winter is one of factors influencing the precipitation in China. However, compared with the boundary circulation conditions in 1998, it is perhaps not the unique one and even not the most important one to the flood in that year. It is also proved that the winter snow anomaly over the Tibetan Plateau is more important than the spring one and the snow depth anomaly is more essential than the snow cover anomaly to the regional precipitation in China.

 

By defining the June sensible heating index over the TP, the relation of the index and the MPV SCSSM intensity index is discussed and a key heating area in the TP is found with which the SCSSM intensity is closely correlated with a positive coefficient of 0.4667. It is also found that the time series of the sensible heat has an obvious interdecadal change with the abrupt transition in the late 1970s. Before that period, the sensible heat fluxes are extremely strong; while after 1978, they are weak. This abruption can be also found in the index series of the SCSSM intensity.

 

By use of the NCEP/NCAR monthly mean meteorological reanalysis data and the monthly precipitation amount data in 160 stations of China during 1958 to 1997 periodthe relationships between the South Asia High (SAH) and the precipitation in the years with typical droughts or floods in the mid to lower valleys of the Yangtze River and North China are analyzed. It is found that both the intensity and the center position of the SAH could have impacts on droughts and floods in the two areas. Anomalously intensifying of the SAH usually induces floods in the mid to lower valleys of the Yangtze River and droughts in North China; while anomalously weakening often gets the opposite pattern of the precipitation anomalies. Not only the intensity of the SAH but also the 100 hPa level circulation anomaly in the previous springtime (MAM) are found important and may be taken as an indicator of the flood or the drought year. If stronger westerly anomalies in the previous springtime appear over the tropical and subtropical belts, the coming summer precipitation will be above normal in the Yangtze River Basins and below normal in North China, and vise versa.

 

Effects of the SAH on the onsets of the tropical Asian summer monsoon (TASM) including the SCS summer monsoon (SCSSM) and the tropical Indian summer monsoon (TISM) are studied as well in this paper. It is found that the onset time of both the SCSSM and the TISM can be determined by the latitude position of the SAH center. When the center passes across 20°N the SCSSM onsets and when it passes through 25°N the TISM onsets. Such determined onset times of the SCSSM and the TISM are well coincident with that determined by the sign transition time of the temperature gradient between 25°N and 5°N averaged in the mid to high troposphere between 100 hPa and 500 hPa, the moist potential vorticity (MPV) and the abnormal zonal wind shear between the 850 and the 200 hPa levels.

 

Acknowledgements: This study is jointly sponsored by the Chinese Academy of Sciences program: “Impacts of the ocean-land-atmosphere interactions in the Asian monsoon area on climate changes in China” (ZKCX2-SW-210) and the National Natural Science Foundation of China programs: “Studies on interaction between the South Asia High and the Asian monsoon and its mechanism” (No.40175021) and “Interannual and interdecadal variations of Meiyu in the Changjiang-Huaihe Basins and their mechanisms” (No. 40233037).

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