Vol.11 No.1 JOURNAL OF TROPICAL METEOROLOGY June 2005 Article ID: 1006-8775(2005) 01-0023-08 ON THE KEY REGIONS OF 500 hpa GEOPOTENTIAL HEIGHTS OVER NORTHERN HEMISPHERE IN WINTER YAN Hua-sheng ( 严华生 ) 1, WAN Yun-xia ( 万云霞 ) 1, 2, CHENG Jian-gang ( 程建刚 ) 2 (1. Department of Atmospheric Sciences, Yunnan University, Kunming 650091 China; 2. Yunnan Meteorology Bureau, Kunming 650034 China) ABSTRACT: Variance analysis, correlation analysis and regression analysis methods are applied to analyze the variation of circulation at 500 hpa. In winter, there are three regions (180 E 150 W, 45 N 60 N, 70 W 100 W,45 N 75 N, 60 E 100 E, 65 N 80 N) whose variations are strong. Those regions are the key regions in which atmospheric circulation can change. Those regions are correlated to some teleconnections and can present a part of variations of 500 hpa to some degree. The linear contemporary correlation between those regions and the height at 500 hpa is significant. Those regions can account for 88 % of variations of concurrent height at 500 hpa. Those regions can present and forecast some variations to some degree in March and April. The longer the time interval, the worse the forecast effect will be. The interannual variations of Q1, Q2 and the SST are weak in the western Pacific. Key words: winter; Northern Hemisphere; geopotential height field; key regions CLC number: P424.4.2 Document code: A 1 INTRODUCTION Global climate change has caused widespread concerns among scientists. As the general circulation is closely related with the changes in weather and climate, local anomalies will inevitably result in global ones to cause anomalies in weather and climate. It can then be seen to be of great significance to the study of temporal and spatial variation of the general circulation. There are quite a number of people who have worked on its variation and the effect on climate change. In their study on the variation of geopotential height field in the Northern Hemisphere (N.H.), Wallace et al [1]. suggested five patterns of teleconnection; Yang [2]. made an observational study on them for summertime; Wang et al [3]. analyzed the geographic distribution and seasonal variation of monthly mean geopotential height field at 50 hpa; Yang [4] worked on the teleconnection and circulation characteristics of the 500-hPa mean geopotential height field in the summer of the N.H.; Shi [5] discussed the long-term variation of the teleconnection of the general circulation in the winter of the N.H.; Zhu et al [6]. studied the long-term variation of centers of atmospheric activity in the same season and location and its relationship with the climate change in China. In the previous research [1-9], while the effects of the 500-hPa geopotential height field and associated anomalies of the general circulation on weather and climate are well studied and many conclusions drawn, few attempts have been documented in addressing the temporal and spatial distribution of interannual variation of the 500-hPa geopotential height field. Then, what is the temporal and spatial distribution of interannual variation of the field? What kind of implication does the distribution hold for the change of the whole general circulation? Is there Received date: 2003-11-03; revised date: 2005-01-20 Foundation item: Key foundation project of Yunnan province (2003D00142); Natural Science Foundation of China (40065001) Biography: YAN Hua-sheng (1956 ), male, native from Yunnan Province, professor, mainly undertaking the study of climate change, forecasting of droughts and floods and non-linear dynamic statistics.
24 JOURNAL OF TROPICAL METEOROLOGY Vol.11 any key region that brings about the variation of the general variation? With these questions, we analyzed the 500-hPa geopotential height field for the understanding of the temporal and spatial distribution of its interannual variation, recognizing of the key area in which there is the maximum variation of the general circulation and revealing of the relationship between the key area and simultaneous geopotential field, in an attempt to have a better picture of the variation of the general circulation. 2 DATA The current dataset used in the work is that of mesh grids of the monthly mean geopotential height field at the level of 500 hpa in the N.H. provided by the China Meteorological Center, which covers a domain of 10 N 85 N, 10 E 180 and a grid interval of 5 10. The index of the atmospheric oscillation comes from references [10 12] and characteristic circulation quantities issued by the National Climate Center. The index of teleconnection connection for the troposphere comes from references [6, 13]. The above datasets all cover a period from 1951 to 2001. 3 EVOLUTION OF VARIANCE ANALYSIS OF THE 500-hPa GEOPOTENTIAL FIELD On the monthly 500-hPa geopotential height field, there are mainly three large systems of circulation, the subtropical high in the low latitude, the ultra-longwave in the westerly zone of the middle latitude and the polar vortex in the high latitude. They are active differently in phases of season. For instance, the ultra-longwave is displayed as three deep and strong troughs in winter but four shallow and weak ones in summer; in winter, the polar vortex is strong and expands southward while the subtropical high is weak and retreats southward; in summer the subtropical high expands northward while the polar vortex is weak and retreats northward. The anomalies of the three systems will result in the anomalies of the general circulation. As shown empirically, the general circulation does not vary always in the same season and location but differs with them. The anomalous variation of the general circulation often take place within specific regions, which can be called key regions. Are they just the regions where the general circulation has the maximum variation and how do they vary with time? With these questions, we applied the method of variance analysis to the 500-hPa geopotential height field for every month from January to December to seek monthly values of variance for 576 gridpoints. As we know, the magnitude of variance represents that of the variation of the geopotential height field the greater the former, the greater the general circulation will vary. Tab.1 lists the mean, maximum, minimum variance values and their differences for the 576 gridpoints from January to December. From Tab.1 and a figure of monthly spatial distribution (not shown), it is known that the mean of the variance for the 576 gridpoints is the maximum in winter but minimum in summer and so are the variation of variance maximum and maximum difference. It shows that the winter is a season when the general circulation varies the most. Therefore, February, the month with the maximum variance in winter, is analyzed, for the variation of the general circulation is representative to some degree. Tab.1 The monthly mean, high and low variances and their differences (unit: gpm) Month 1 2 3 4 5 6 7 8 9 10 11 12 Mean 35.06 35.12 28.49 19.43 15.31 12.21 10.68 11.81 14.28 18.05 24.58 30.05 Max. 103.8 114.4 104.6 65.2 48.8 34.3 33.9 38.4 45.5 58.4 89.0 92.1 Min. 0.99 1.1 0.6 0.6 0.6 0.6 0.5 0.4 0.5 0.4 0.5 0.9 Dif. 102.8 113.3 104 64.6 48.2 33.7 33.4 38 45 58 88.5 91.2
No.1 YAN Hua-sheng ( 严华生 ), WAN Yun-xia ( 万云霞 ) and CHENG Jian-gang ( 程建刚 ) 25 Fig.1, which is the distribution of variance at the 576 gridpoints, shows that with the decrease of latitude, variance changes from high to low variance is high in high latitudes but low in low latitudes. There are three centers of high variance values respectively over the northern Pacific (180 150 W, 45 N 60 N), northern Atlantic (70 W 10 W, 45 N 75 N) and a region around the Novaya Zemlya Island (60 W 100 E, 65 N 80 N). As we know, the greater the variance value, the more dramatically the represented 500-hPa geopotential height varies. In the current work, the centers of the above three high variance values are called the key regions where the general circulation varies. Comparing the three key regions with the distribution patterns of mid-troposphere in winter, we can see that the key regions are not over the place where there are three main troughs for wintertime. 0 90E 90W 180 Fig.1 The variances for February. 4 RELATIONSHIP BETWEEN THREE KEY REGIONS AND SIMULTANEOUS AND SUCCESSIVE GEOPOTENTIAL HEIGHT FIELD 4.1 Distribution of the correlation coefficients between the key regions and simultaneous 500-hPa geopotential height field Addressing the above questions, links between the key regions and simultaneous 500-hPa geopotential height are studied for correlation. The mean height of Index 1 (60 E 100 E, 65 N 68 N), Index 2 (180 160 W, 45 N 60 N) and Index 3 (60 W 20 W, 50 N 70 N) are used to represent the temporal variation of the height field. Then, correlation between these series and the 576 gridpoints are sought. Figs.2, 3 and 4 are the distribution of the correlation in the first, second and third key regions. For the first key region, the best (positively) correlated region is around Novaya Zemlya Island while negative correlation is found in Siberia, Alaska and south Pacific. Let s look at the area from 50 E to 160 E specifically. It also shows north-south swings with large correlation coefficients mainly inside the area; positive correlation is seen north of 50 N and negative one south of it. The negative correlation coefficient can be as large as over 0.6, showing significant
26 JOURNAL OF TROPICAL METEOROLOGY Vol.11 correlation (Fig.2). It is known from Fig.3 that the areas with the most significant (positive) correlation are the Aleutian Islands or north Pacific and Mexico while significant negative correlation is found in the south Pacific and Canada. Areas with large coefficients are mainly over the Pacific Ocean, where the distribution shows well-defined north-south swings, with positive correlation north of 30 N and negative one south of it. The negative coefficient can be as large as more than 0.7, showing very close links between them. 0 0 90E 90W 90E 90W 180 180 Fig.2 The coefficient distribution of the correlation between mean geopotential height series of the first key region and simultaneous 500-hPa geopotential height. The shaded areas are with coefficients passing the 99% significance level, same below. Fig.3 Same as Fig.2 but for the second key region. The most significantly correlated areas in the third key region are Greenland and continental Eurasia (positive) and southern part of north Atlantic and Vladimir (negative), with large coefficients mostly over the north Atlantic. The coefficients are also of north-south swings in variation. Positive correlation is seen north of 45 N and negative one south of it, with negative correlation coefficient as high as more than 0.6. It shows very close linkage between them (Fig.4). In other words, the correlation between the key regions and the 500-hPa geopotential height field is very close over the Novaya Zemlya Island, Siberia, Pacific Ocean and north Atlantic and in north-south swings. In addition, such swing variation is similar to the teleconnection pattern described in [14]. Then, do they relate to the four great oscillations in low levels? How do they link with patterns of atmospheric teleconnection on the same levels? The time series of the key regions and indexes of teleconnection patterns on both high and low levels are studied for correlation (Tab.2). It is seen that the first key region is correlated only PNA in the upper troposphere, the second key region is well correlated with NPO and SO in low levels and PNA and EP for the troposphere, and the third key region is well correlated with NAO and AO in low levels and EU and WA for the troposphere. In other words, the variation of geopotential height in
No.1 YAN Hua-sheng ( 严华生 ), WAN Yun-xia ( 万云霞 ) and CHENG Jian-gang ( 程建刚 ) 27 the three key regions differs in its correlation with individual patterns of teleconnection, but reflects to some degree part of the characteristics of general circulation variation. 0 90E 90W 180 Fig.4 Same as Fig.2 but for the third key region. Tab.2 The series of mean geopotential height for the three key regions and their correlation with individual patterns of teleconnection Corr. Coeff. First key region Second key region Third key region NPO 0.13 0.59-0.18 NAO -0.08 0.05-0.54 AO -0.07 0.13-0.50 SO 0.06 0.32-0.20 WP -0.12-0.24-0.04 PNA -0.32-0.45-0.03 EP 0.24-0.28 0.08 EA -0.07-0.09-0.22 EU -0.20-0.21-0.29 WA 0.16-0.19 0.61 Note: The bold figures are those that pass the 95% confidence test. 4.2 Regression analysis of the key regions and the simultaneous 500-hPa geopotential height field The above analysis shows that the geopotential variation of the key regions reflect to some extent the variation of the general circulation. But can it represent the whole situation of the circulation field? For the purpose, the series of the mean geopotential height for the key regions are used as independent variables and the 576 gridpoints for the simultaneous 500-hPa geopotential height field as dependent variables in analyses using the ternary regression technique. Through the computation, complex correlation coefficients for 508 out of 576
28 JOURNAL OF TROPICAL METEOROLOGY Vol.11 gridpoints have passed the 95% significance test, taking up the total by 88%. Fig.5 gives distribution of the complex correlation coefficients. Comparing Fig.5 and Figs.1 4, we know that (1) most of the geopotential height field can basically be fitted with the height of the key regions; (2) complex correlation coefficients in regions with large (small) variance are also relatively large (small); (3) in regions where the key regions are well correlated with the field the complex correlation coefficients are relatively high and have relatively good fitting and otherwise are true. In addition, an analysis of the distribution of residual variance (figure omitted) shows that the residual variance is basically the opposite to the complex correlation in distribution. In regions where there are large (small), the values of the residual variance are relatively small (large). Generally speaking, it is relatively satisfactory for the fitting between the geopotential height in the key regions and simultaneous 500-hPa circulation field. The geopotential height of the key regions are so closely correlated with the simultaneous 50-hPa geopotential height field that its variation can represent about 88% of the field. 0 90E 90W 180 Fig.5 The coefficient distribution of the complex correlation between the three key regions and simultaneous 500-hPa geopotential height in the Northern Hemisphere. The shaded areas are with coefficients passing the 99% significance level. Same below. 4.3 Regression analysis of the key regions and the simultaneous 500-hPa geopotential height field The three key regions represent about 88% of the variation of the simultaneous 500-hPa circulation field. Likewise, do they represent the variation in coming periods? Again the ternary regression method is used to study the relationships between the geopotential height series of the key regions and the geopotential field for March November. The number of gridpoints that pass the 95% significance test for the complex correlation coefficients in March November are listed in Tab.3. It shows that the number is generally decreasing for the gridpoints that pass the test for March July, with March being the month with the largest number (315 gridpoints), taking up
No.1 YAN Hua-sheng ( 严华生 ), WAN Yun-xia ( 万云霞 ) and CHENG Jian-gang ( 程建刚 ) 29 54.69% of the total, and July the month with the smallest number (166 gridpoints), taking up only 28.82%. Tab.3 Gridpoints that pass the significance test in February November Month Feb. Mar. Apr. May Jun. Number of gridpoints passing the significance test 508/576 315/576 256/576 174/576 186/576 Month Jul. Aug. Sept. Oct. Nov. Number of gridpoints passing the significance test 166/576 233/576 175/576 155/576 170/576 Next, let s look at the fitting of the key regions with the 500-hPa circulation field in March. Figs.6 and 7 present the distribution of complex correlation coefficients and residual variance. It can be seen that the fitting is less satisfactory than in February and the complex correlation coefficients passing the significance test are mainly over the Atlantic and Pacific areas where there are also relatively small residual variances. It shows that the geopotential height of the key regions can represent part of the variation of the general circulation in coming periods, with better fitting results for the areas of the Atlantic and Pacific. The fitting is similar in April to March, though with poorer results (figure omitted). Summarizing what has been described above, we conclude that the three key regions in February can in some degree account for the variation of the general circulation at 500 hpa in the coming March and April. To some extent, it forecasts the evolution, though the predictability lowers with larger intervals of time. 0 0 90E 90W 90E 90W 180 180 Fig.6 The coefficient distribution of complex correlation between the mean geopotential series of the key regions and the 500-hPa geopotential height field in coming March. Fig.7 Same as Fig.6 but for the coefficient distribution of residual variance. 5 CONCLUDING REMARKS a. The three regions of large variance values (180 150 W, 45 N 60 N; 70 W 10 W,
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