Interdecadal Variations of the Western Pacific Subtropical High and Surface Heat Flux over East

阿留申低压四种环流指数的分析和比较孙晓娟;王盘兴;智海;郭栋【摘要】分析和比较了20世纪90年代以来不同学者提出的阿留申低压(Aleutian Low,AL)四种强度指数(Ii,i=1,4)、两种中心位置指数(λi、ψi,i=3、4)的时频特征及其与同期北半球太平洋海面温度、气温、降水的相关联系.结果表明:1)强度指数Ij、i=2,4演变特征最相似;20世纪70年代中期之前AL偏弱,之后AL偏强;近年来又出现AL偏弱趋势.因I1为5个月平均场中AL的强度指数,故它与Ii、i=2,4差别较大.2)两种中心位置指数地理分布区域(λc3,ψc3)大于(λc4,ψc4),这与平均时段长短及中心位置指数定义差别有关.λc4由偏西转向偏东较λc3提早约5 a,它与Ii、i=2,4的一致性更好.3)在强El Ni(n)o事件中,AL加强、中心位置偏东,强La Ni(n)a 事件则相反.强度指数I2、I4和位置指数λc4反映上述关系较好.4)AL偏强、偏东年,中纬北太平洋区域低温、少雨,北太平洋东北部至北美西北部气温偏高、降水偏多,而北关南部气温偏低、降水偏少;反之亦然.【期刊名称】《大气科学学报》【年(卷),期】2011(034)001【总页数】11页(P74-84)【关键词】阿留申低压;环流指数比较;演变规律;太平洋海表温度异常;气候异常【作者】孙晓娟;王盘兴;智海;郭栋【作者单位】南京信息工程大学,大气科学学院,江苏,南京,210044;南京信息工程大学,大气科学学院,江苏,南京,210044;南京信息工程大学,大气科学学院,江苏,南京,210044;南京信息工程大学,大气科学学院,江苏,南京,210044【正文语种】中文【中图分类】P4340 引言阿留申低压(Aleutian Low,AL)是冬季中心位于北太平洋阿留申群岛附近的副极地气旋,是北半球主要的半永久性大气活动中心之一,其强度和位置异常对北半球的天气、气候异常有重要的影响(Latif and Bernett,1994;Trenberth andHurrell,1994;郭冬和孙照渤,2004)。

Tracking millennial-scale climate change by analysis of the modern summer precipitation in the marginal regions of the Asian monsoonYu Li ⇑,Nai’ang Wang,Hongbao Chen,Zhuolun Li,Xuehua Zhou,Chengqi ZhangCollege of Earth and Environmental Sciences,Center for Hydrologic Cycle and Water Resources in Arid Region,Lanzhou University,Lanzhou 730000,Chinaa r t i c l e i n f o Article history:Received 14September 2011Received in revised form 13June 2012Accepted 4July 2012Available online 17July 2012Keywords:Millennial-scale HoloceneInterannual-scaleSummer precipitation Asian monsoon Westerly windsa b s t r a c tThe Asian summer monsoon and the westerly winds interact in the mid-latitude regions of East Asia,so that climate change there is influenced by the combined effect of the two climate systems.The Holocene millennial-scale Asian summer monsoon change shows the out-of-phase relationship with the moisture evolution in arid Central Asia.Although much research has been devoted to the long-term climate change,little work has been done on the mechanism.Summer precipitation,in the marginal regions of the Asian monsoon,is strongly affected by the monsoon and the westerly winds.The purpose of this paper is to examine the mechanism of the millennial-scale out-of-phase relationship by modern summer precipitation analysis in the northwest margin of the Asian monsoon (95–110°E,35–45°N).First,the method of Empirical Orthogonal Function (EOF)analysis was carried out to the 1960–2008summer rain-fall data from 64stations in that region;then the water vapor transportation and geopotential height field data were studied,in order to explain and understand the factors that influence the summer precip-itation;lastly,the East Asian Summer Monsoon Index (EASMI),South Asian Summer Monsoon Index (SASMI),Summer Westerly Winds Index (SWI)were compared with the EOF time series.The results indi-cate the complicated interannual-scale interaction between the Asian summer monsoon and the westerly winds,which can result in the modern out-of-phase relationship in the study area.This study demon-strates that the interaction between the two climate systems can be considered as a factor for the millen-nial-scale out-of-phase relationship.Ó2012Elsevier Ltd.All rights reserved.1.IntroductionSince it is not possible to go back in time to see what climates were like,scientists use imprints created during past climate,known as proxies,to reconstruct paleoclimate (Ruddiman,2001).The processes of the modern climate system provide a scientific basis for understanding the evolution of paleoclimate (Cronin,2009).Past climate can be reconstructed using a combination of different types of proxy records.These records can then be inte-grated with observations of Earth’s modern climate and placed into a computer model to infer past as well as predict future climate.Study on the relationship between proxy indicators and modern climate is helpful to reconstruct the past climate conditions (Helle and Schleser,2004).Accordingly,several different methods have been developed for quantitative paleoclimatic reconstructions (Sheldon and Tabor,2009;Xu et al.,2010).Besides,understanding the processes governing modern climate variability and change provides significant understanding of the climate changes over a variety of different timescales.The Asian monsoon system reaching from the western Arabian Sea through East Asia and North Australia,which can be divided into the East Asian monsoon system and South Asian (or Indian)monsoon system,is a dynamic component of the modern climate system (Webster et al.,1998;Wang and Lin,2002).Wang et al.(2005b)provided an overview of past and current paleomonsoon research on tectonic to interan-nual timescales,and emphasized the importance of modern mon-soonal climate research for interpreting paleoclimate change.Much attention has been focused on the links of monsoon systems across timescales (Wang et al.,2003,2010).While many studies have been published concerning the millennial-scale relationship between the Asian monsoon and the westerly winds,little infor-mation is available on interannual to interdecadal timescales (Chen et al.,2008,2010).In East Asia,the Asian summer monsoon and the westerly winds interact in the mid-latitude regions (Zhang and Lin,1992;Wang et al.,2005a ,Fig.1).Mid-latitude climates are dominated by the interaction of air masses,specifically cold air masses origi-nating in high latitudes and warm air masses originating in the sub-tropical Highs;therefore,the climates are commonly charac-terized by vigorous circulation (Aguado and Burt,2004;Barry et al.,2004).The interaction between the Asian summer monsoon and the westerly winds plays a critical role in East Asia climate changes over several different time scales.Precisely dated speleo-1367-9120/$-see front matter Ó2012Elsevier Ltd.All rights reserved./10.1016/j.jseaes.2012.07.001Corresponding author.Tel.:+869318912709;fax:+869318912712.E-mail address:liyu@ (Y.Li).them records have provided a continuous history of Holocene East Asian summer monsoon intensity (Fleitmann et al.,2003;Wang et al.,2005c ).The Holocene Asian summer monsoon variability re-flected by d 18O from Qunf Cave (17°100N,after Fleitmann et al.(2003)),Dongge Cave (25°200N,after Wang et al.(2005c)and Dykoski et al.(2005)),Lianhua Cave (29°290N,after Cosford et al.(2008)),Heshang Cave (30°270N,after Hu et al.(2008)),Sanbao Cave (31°400N,after Dong et al.(2010))and Jiuxian Cave (33°340N,after Cai et al.(2010))shows a similar result (Figs.1and 2).Moreover,the evolution of the Holocene Asian summer monsoon reconstructed by lake records from the Qinghai-Tibet Plateau agrees with the result from the speleothem records (Gasse et al.,1991;Fleitmann et al.,2003;Shen et al.,2005;Wang et al.,2005c;Morrill et al.,2006;Liu et al.,2007).On the other hand,Chen et al.(2008)synthesized 11Holocene lake records from arid Central Asia to evaluate spatial and temporal patterns of moisture changes.Fig.3shows the synthesized moisture index and the Holocene lake records from Bosten Lake,Telmen Lake and Wulun-gu Lake (Fowell et al.,2003;Wünnemann et al.,2006;Chen et al.,2008;Liu et al.,2008).The Holocene moisture change in arid Cen-tral Asia is out-of-phase with the Asian summer monsoon evolu-tion (Fig.3).In addition,this out-of-phase relationship is also implied by the Holocene loess-paleosol records in East and Central Asia (Feng et al.,2011).Chen et al.(2008,2010)pointed out that the millennial-scale out-of-phase relationship can be related to the variability of the westerly winds.It is difficult to verify the hypothesis with lack of modern climate research.Summer precip-itation,in the northwest margin of the Asian summer monsoon (95–110°E,35–45°N,Figs.1and 4),is directly influenced by the monsoon and the westerly winds.The objective of the present pa-per is to study the interaction between the Asian summer monsoon and the westerly winds through the research on summer precipita-tion and its relationship with the two climate systems.In the pres-ent investigation,we examined the 1960–2008summer rainfalldata from 64stations (95–110°E,35–45°N,Fig.4)by using Empir-ical Orthogonal Function (EOF)analysis.And then,the geopotential height field and water vapor transportation data,East Asian Sum-mer Monsoon Index (EASMI),South Asian Summer Monsoon Index (SASMI),and Summer Westerly Winds Index (SWI)were used to study the interaction of the monsoon and the westerly winds and their impact on summer precipitation.2.Regional settingThe northwest margin of the Asian monsoon (95–110°E,35–45°N,Fig.4)is located in the transition zone of the Asian summer monsoon region,the arid region of Northwest China,and the Qing-hai-Tibet Plateau (Zhao,1983).The study area,varying in altitude from 1000m to 5000m above sea level,mainly comprises moun-tains,valleys,glaciers,deserts,oases,rivers,and lakes that reflect the characteristics of the transition zone.The Qilian Mountains,lo-cated in the middle of the study area,can reach an altitude of 5000m above sea level.The mean annual temperature in the mountain zone is 2–4°C and the annual precipitation is 200–700mm.To the north of the Qilian Mountains is the Tengger Des-ert;the annual mean temperature here is 6–8°C and the annual precipitation is 50–200mm.The annual potential evaporation ex-ceeds 2600mm in the desert (Chen and Qu,1992).The distribution of modern vegetation is strongly related to elevation:perennial snow and ice zone (>4500m);cushion-like vegetation zone (4500–3800m);meadow zone (3800–3500m);alpine shrub zone (3500–3100m);Picea and Sabina forest zone (3100–2500m);mountainous grassland zone (2500–2350m);desert grass zone (2350–2000m)and gobi-sand desert zone (<2000m)(Huang,1997).Rivers are mostly derived from the cold and humid moun-tain zone from 2000m to 5000m above sea level (Chen and Qu,1992).Water vapor,in the study area,is from the Asiansummer1.Map of East and Central Asia.The modern Asian summer monsoon limit is shown by a dashed line.Lines with arrows indicate the climate systems affecting East Central Asia,including East Asian summer monsoon,South Asia (or Indian)summer monsoon,Asian winter monsoon,and westerly winds.The black circles show caves mentioned in this research,including (a)Dongge Cave,(b)Lianhua Cave,(c)Heshang Cave,(d)Sanbao Cave,(e)Jiuxian Cave,(f)Qinghai Lake,(g)Bosten Lake,Wulungu Lake and (i)Telmen Lake.monsoon and the westerly winds (Wang et al.,2005a ).It is also confirmed by an atmospheric general circulation model (GCM),as well as column integrated moisture source analysis (Numaguti,1999;Yoshimura et al.,2004).Fig.5a shows the summer vertically integrated atmospheric water vapor flux that implies the interaction between the Asian summer monsoon and the westerly winds.A number of studies have been conducted on the summer precipitation in adjacent areas;however,little attention has been paid to the interaction between the Asian summer monsoon and the westerly winds and its effect on the summer precipitation (Wang et al.,2001;Feng and Hu,2004;Yatagai,2007).In this pa-per,we will attempt to show how the two climate systems affect the summer precipitation in the northwest margin of the Asian monsoon.3.Data and methods(1)Summer rainfall data were observed at 64weather stationsin the study area over the period 1960–2008(95–110°E,35–45°N,Figs.1and 4).The 2.5°Â2.5°resolution monthlymean water vapor and geopotential height field data are from the NCEP/NCAR reanalysis to describe the atmosphere characteristics (Kalnay et al.,1996).(2)The dominant summer rainfall patterns and variability wereidentified using Empirical Orthogonal Function (EOF)analy-sis.North’s significance test was used to determine the level of significant (North et al.,1982).(3)East Asian Summer Monsoon Index (EASMI)and South AsianSummer Monsoon Index (SASMI)(Zeng et al.,1994;Li and Zeng,2002)were given byd ¼k V 1*ÀV m ;n *kk V *kÀ2;where V 1*and V m ;n *are the January climatological and monthly wind vectors at a point,respectively,(n ,year;m ,month),V *is the mean of January and July climatological wind vectors at the same point.The indices were calculated in the two key monsoon sectors:East Asian (10–40°N,110–Holocene speleothem records and Holocene Qinghai Lake record including d 18O (‰)from Qunf Cave (17°100N,after (25°200N,after Wang et al.(2005c)),d 18O (‰)of D4from Dongge Cave (25°200N,after Dykoski et al.(2005)),(2008)),d 18O (‰)from Heshang Cave (30°270N,after Hu et al.(2008)),d 18O (‰)of SB43from Sanbao Cave (31°400N,(31°400N,after Dong et al.(2010)),d 18O (‰)of cc996-1from Jiuxian Cave (33°340N,after Cai et al.(2010)),d 18(2010)),pollen concentration (grains/g)from Qinghai Lake (36°500N,after Shen et al.(2005)),d 18O (‰)of ostracode (2007))and summer insolation at 30°N (after Berger and Loutre (1991)).140°E)at 850hPa and South Asian (2.5–20°N,70–110°E)at 850hPa.(4)Westerly Index (WI)(Rossby,1939;Li et al.,2008)was givenbyI ¼35 À55¼1n X n k ¼1H k ð35 ÞÀ1n X n k ¼1H k ð55 Þ¼1n X n k ¼1D H k ;where H k is the 500-hPa height geopotential at latitude k and longitude n ,and I is the Westerly Index (WI)between 35°N and 55°N.(5)Water vapor flux (Chen,1985;Simmonds et al.,1999)wasgiven byQ u ¼À1ZptpsqudpQ v ¼À1gZptpsq v dp ;where g is gravity acceleration,ps represents surface pres-sure,pt stands for top pressure,which is chosen as 300hPain this study,q is specific humidity,and Q u and Q v are water vapor fluxes in the zonal and meridional directions,respec-tively (unit:kg m À1s À1).4.Results4.1.Temporal and spatial trends in the summer precipitation Fig.5b shows the spatial distribution of summer rainfall.Thesummer rainfall peaks in the eastern part of the study area,reach-ing a maximum of 310.7mm,while rainfall,in the western part,is generally low with a minimum of 22.6mm.The summer rainfall can reach 284.5mm in the northeast of the Qinghai-Tibet Plateau (37–38.5°N,99.5–102°E).As shown in Fig.5c,a remarkable increasing trend in summer rainfall was observed in most partsFig.4.Map of topography and 64meteorological stations in the study area.moisture indices in arid Central Asia,including moisture evolution trend from arid Central Asia (after Chen et al.(2008)),moisture index from Bosten Lake (after Wünnemann et al.(2006)and Chen et al.(2008)),Chen et al.(2008))and lake-level change from Wulungu Lake (Liu et al.,2008).of the study area from 1960to 2008.However,the summer rainfall in the southeast of the study area,the upper reaches of the Yellow River,exhibits a downward trend.Generally,the summer rainfall is relatively low from 1960to 1975,and relatively high from 1976to 1998;there is an increasing trend in summer rainfall since 1999(see Fig.5d).Nine years,1961,1964,1976,1979,1981,1988,1992,1994and 1996,with abnormally high summer rainfall are shown by summer rainfall anomalies in Fig.5d,while nine years,1962,1963,1965,1969,1971,1972,1974,1982and 1991,with abnormally low summer rainfall are shown in Fig.5d.4.2.EOF analysis of the summer precipitation,water vapor transportation and geopotential height fieldKriging,an optimal method of spatial interpolation (Oliver and Webster,1990),was chosen to interpolate the normalized summer rainfall anomalies for establishing the summer rainfall field.Empirical Orthogonal Function (EOF)analysis was applied to the summer rainfall field,and the correlation matrix of the variables was used for computing the eigenvalues and eigenvectors of the EOFs.The first three EOFs that account for 47.73%of total variance can pass the North’s significance test.4.2.1.EOF1The first EOF mode (EOF1)that shows positive values in most areas accounts for 26.66%of the total variance (Fig.6a).The rela-tively low values mainly appear in the west of the Qilian Moun-tains and the desert area.The EOF1time series indicates that the summer rainfall is relatively high in 1961,1964,1979,1994and 1996,and relatively low in 1962,1963,1965,1982and 1991(Fig.6b).The result is consistent with the summer rainfall anoma-lies from 1960to 2008(Fig.5d).Differences of water vapor flux be-tween the 5years with the highest values of the EOF1time series and the 5years with the lowest values of the EOF1time series are significant in the southeast of the study area,as Fig.6d shows.Fig.6c shows anomaly correlation between the 500hPa geopoten-tial height field and the EOF1time series.There is a positive corre-lation between the intensity of the subtropical high and the EOF1time series.This means that EOF1of summer rainfall is strength-ened by the western Pacific subtropical high whose intensity is al-ways related to the strength of the Asian summer monsoon (Sun et al.,2005).This 500hPa geopotential height field between 50°N to 80°N and 40°E to 110°E is positively correlated with the EOF1time series that is negatively correlated with the 500hPa geopo-tential height field between 50°N to 80°N and 110°E to 180°E.The result suggests the strong westerly winds can strengthen EOF1summer rainfall.Therefore,EOF1summer rainfall is influ-enced by the combined effect of the western Pacific subtropical high and the westerly winds.Differences of water vapor flux,as shown in Fig.6d,indicate the Asian summer monsoon water vapor transportation play a more important role than the westerly winds.In the previous work it was proved that the water vapor from the westerly winds had little effect on summer precipitation in north-west China (Wang et al.,2005a;Li et al.,2008).Although EOF1summer rainfall is affected both by the westerly winds and the western Pacific subtropical high,there is little water vapor contri-bution from the westerly winds.4.2.2.EOF2The second EOF mode (EOF2),accounting for 12.07%of the total variance,indicates the opposite trends between the upper reaches of the Yellow River and other areas,as shown in Fig.7a.Itsuggestssummer vertically integrated water vapor fluxes (unit:kg m À1s À1,1960–2008)in the northwest margin of the Asian monsoon.Summer rainfall shown by Fig.5b,while the linear trend pattern (1960–2008)is represented by Fig.5c.An increasing trend is indicated in black,whereas a Fig.5d shows summer rainfall anomalies (1960–2008).that EOF2summer rainfall shows a negative correlation between the upper reaches of the Yellow River and other areas.The EOF2time series indicates that the summer rainfall is relatively high in 1979,1983,1993,1996and 2007,and relatively low in 1961,1962,1964,1978and 2001(Fig.7b).The 5years with the highest values of the EOF2time series and the 5years with the lowest val-ues of the EOF2time series are chosen to calculate differences of water vapor flux (Fig.7d).Fig.7c shows anomaly correlation be-tween the 500hPa geopotential height field and the EOF2time ser-ies.As can be seen in Fig.7c,positive values appear in mid-to-low latitudes and high values concentrating in India –the Bay of Bengal –South Peninsula –South China Sea,while the highest correlation coefficient is 0.55in India and the Bay of Bengal.The correlation coefficient also can reach 0.45in the northern Arabian Sea,which is significant at the 0.05level.The low pressure system in India,the Bay of Bengal and the northern Arabian Sea is highly correlated with the Asian summer monsoon.It is likely that while the 500hPa geopotential height field is low/high in those regions,the Asian summer monsoon is accompanied by high/low water vapor flux.At the same time,EOF2summer rainfall over the upper reaches of the Yellow river is relatively high/low due to negative EOF2val-ues in that area.On the other hand,the western Pacific subtropical high (between 30°N and 40°N)is positively correlated with EOF2summer rainfall over the upper reaches the Yellow River (see Fig.7c).It could be inferred that the western Pacific subtropicalhigh could promote water vapor transportation in the southeast of the study area.As illustrated by Fig.7d,differences in water va-por flux between the 5years with the highest and lowest values of the EOF2time series are mainly reflected in the southeast of the study area,the upper reaches of the Yellow River.It is conceivable that the negative correlation between the upper reaches of the Yel-low River and other areas in EOF2is related to the low pressure system and water vapor transportation in the low latitudes.4.2.3.EOF3The third EOF mode (EOF3),accounting for 9.00%of the total variance,shows the opposite trends between the southwest study area,where the high-altitude zones occupy most of the area,and other areas,as shown in Fig.8a.This indicates that EOF3summer rainfall shows a negative correlation between the two parts.Fig.8b shows the EOF3time series,and Fig.8c shows anomaly cor-relation between the 500hPa geopotential height field and the EOF3time series.The 5years with the highest values of the EOF3time series (1962,1966,1968,1969and 1979)and the 5years with the lowest values of the EOF3time series (1961,1967,1976,1989and 1998)are chosen to calculate differences of water vapor flux (Fig.8d).The 500hPa geopotential height field in the high-latitude regions,concentrated in the Arctic Ocean,shows a positive correla-tion with the EOF3time series,while a positive correlation be-tween the 500hPa geopotential height field and the EOF3time(a)shows the eigenvector spatial pattern of the first mode (EOF1).Shaded areas indicate regions with negative values.Fig.6b shows the EOF1time series (the while the dashed line represents the 9-year Gaussian-type filtered value.Fig.6c shows the correlation between the 500-hPa geopotential height anomalies and the series.Positive values are indicated by solid lines,and negative ones are dash lines.Shaded areas indicate regions with the correlation significant at the 0.05level.the difference in vertically integrated water vapor fluxes (unit:kg m À1s À1)between typical years.series appears in the mid-to-low latitudes.It is evident that EOF3summer rainfall in the southwest study area is positively related to the western Pacific subtropical high,while the intensity of the westerly winds strengthened by the high-latitude flows has a posi-tive correlation with EOF3summer rainfall in other areas.Differ-ences of water vapor flux between the 5years with the highest and lowest EOF3time series reveals a considerably higher amount of water vapor input from the high-latitude regions (Fig.8d).It is different from EOF1and EOF2and suggests that EOF3summer rainfall is more related to water vapor transportation from the high latitudes.4.3.East Asian Summer Monsoon Index (EASMI),South Asian Summer Monsoon Index (SASMI)and Summer Westerly Index (SWI)EASMI,SASMI,SWI and the EOF time series,from 1960to 2008,are given in Fig.9,and their correlation coefficients can be found in Table 1.It appears that the intensities of the East Asian summer monsoon,the South Asian summer monsoon and the summer wes-terly winds are correlated with each other,as shown in Table 1.However,they have different effects to the EOF time series.The EOF1time series is positively correlated with SWI,but negatively correlated with SASMI.On the contrary,the EOF2time series is negatively correlated with all three indices.Then,it seems that there is no obvious relationship between the EOF3time series and the three indices.As listed in Table 1,summer rainfall anom-alies are positively correlated with SWI,but negatively correlated with EASMI and SASMI;therefore,the summer monsoon system and the westerly winds have opposite effects to summer rainfall anomalies in the study area.5.DiscussionPrior work has documented the Holocene millennial-scale out-of-phase relationship between the Asian summer monsoon evolu-tion and the moisture change in arid Central Asia (Chen et al.,2008,2010;Feng et al.,2011).However,these studies focused on Holo-cene climate records in East and Central Asia which cannot provide physical mechanisms underpinning the out-of-phase relationship.In this study we tested the modern interaction between the Asian summer monsoon and the westerly winds using 1960–2008sum-mer rainfall data,East Asian Summer Monsoon Index (EASMI),South Asian Summer Monsoon Index (SASMI),and Summer Wes-terly Winds Index (SWI).Three types of interaction are recovered by EOF analysis in the northwest margin of the Asian summer monsoon.EOF1summer rainfall is influenced by the combined effect of the western Pacific subtropical high and the westerly winds,while the EOF1time ser-ies is positively correlated with SWI,but negatively correlated with SASMI.Therefore,the South Asian summer monsoon and the wes-terly winds may have opposite effect on EOF1summer rainfall.EOF2summer rainfall shows a negative correlation betweentheshows the eigenvector spatial pattern of the second mode (EOF2).Shaded areas indicate regions with negative values.Fig.7b shows the EOF2time series while the dashed line represents the 9-year Gaussian-type filtered value.Fig.7c shows the correlation between the 500-hPa geopotential height anomalies and series.Positive values are indicated by solid lines,and negative ones are dash lines.Shaded areas indicate regions with the correlation significant at the 0.05level.difference in vertically integrated water vapor fluxes (unit:kg m À1s À1)between typical years.(a)shows the eigenvector spatial pattern of the third mode(EOF3).Shaded areas indicate regions with negative values.Fig.8b shows the EOF3time series(the while the dashed line represents the9-year Gaussian-typefiltered value.Fig.8c shows the correlation between the500-hPa geopotential height anomalies and the series.Positive values are indicated by solid lines,and negative ones are dash lines.Shaded areas indicate regions with the correlation significant at the0.05level.the difference in vertically integrated water vaporfluxes(unit:kg mÀ1sÀ1)between typical years.shows EOF1time series(EOF1-T),EOF2time series(EOF2-T),EOF3time series(EOF3-T),East Asian Summer Monsoon Index(EASMI),South Asian Summer Monsoon Winds Index(SWI)and summer rainfall anomalies(P)versus time(1960–2008).upper reaches of the Yellow River and other areas that is related to the northward anomalous water vapor transportation originated from the Asian summer monsoon.The EOF2time series is nega-tively correlated with EASMI,SASMI and SWI.As a result,summer rainfall in the upper reaches of the Yellow River is strengthened by the Asian summer monsoon.On the contrary,the intensity of the westerly winds is positively related to the summer rainfall in other areas.EOF3summer rainfall shows a negative correlation between the high-altitude zones and other areas.Water vapor transporta-tion from the high latitudes plays an important role in EOF3.There is no obvious relationship between the EOF3time series,EASMI, SASMI and SWI.In addition,the summer rainfall in the southeast of the study area exhibits a downward trend,while other areas indicate a remarkable increasing trend.Furthermore,summer rain-fall anomalies,in the study area,are positively correlated with SWI, but negatively correlated with EASMI and SASMI.These relation-ships jointly show the modern interaction between the Asian sum-mer monsoon and the westerly winds,which can be expressed as the modern out-of-phase relationship in the northwest margin of the Asian summer monsoon.Chen et al.(2008,2010)proposed that North Atlantic sea-sur-face temperatures(SSTs)and high-latitude air temperatures,as well as topography of the Qinghai-Tibet Plateau,affect the Holocene millennial-scale out-of-phase relationship.Holocene long-term climate model further confirmed the impact from the westerly winds that can affect the millennial-scale out-of-phase relationship(Li and Morrill,2010;Jin et al.,2012).However, although the effect of westerly winds on the millennial-scale out-of-phase relationship was demonstrated,little attention has been paid to the interaction between the Asian summer monsoon and the westerly winds.Our results provide compelling evidence of the modern interaction between the two climate systems that also can trigger the modern out-of-phase relationship for summer rainfall in the marginal region of the Asian summer monsoon. However,some limitations are worth noting.Although the modern out-of-phase relationship was supported statistically,it is still un-clear whether the relationship appears in other regions and re-search,regarding the modern interaction between the Asian summer monsoon and the westerly winds,is needed.Future work should therefore include large-scale summer rainfall and climate model designed to evaluate the mechanism.6.ConclusionsIn summary,we have presented EOF analysis of the summer rainfall in the northwest margin of the Asian summer monsoon. Water vapor transportation,geopotential heightfield,EASMI,SAS-MI and SWI have been considered for explaining the interaction between the Asian summer monsoon and the westerly winds and its impact on summer rainfall.There are four aspects that can be expressed regarding the modern out-of-phase relationship in the northwest margin of the Asian summer monsoon.First, the summer rainfall in the southeast of the study area shows the out-of-phase relationship with others areas.Second,the Asian summer monsoon and the westerly winds have opposite effects to the summer rainfall anomalies in the study area.Third,the EOF1time series has a positive correlation with Summer Westerly Winds Index,but is negatively correlated with South Asian Sum-mer Monsoon Index.Finally,there are out-of-phase relationships in EOF2and EOF3summer rainfall which are related to the inter-action between the Asian summer monsoon and the westerly winds.The modern out-of-phase relationship on summer rainfall provides clues for understanding the long-term climate change. AcknowledgementsI would like to express my sincere gratitude to the editor,Pro. Qinghai Xu and another anonymous reviewer who have put con-siderable time and effect into their comments on this paper.Spe-cial thanks should go to my advisor,Dr.Carrie Morrill,who works at University of Colorado and NOAA.I am deeply grateful of her help in completion of this research.I am also deeply in-debted to all the other professors in Lanzhou University for their help in scientific English writing.This study was supported by the National Natural Science Foundation of China(No.41001116). ReferencesAguado,E.,Burt,J.E.,2004.Understanding Weather and Climate,third ed.Prentice Hall,Upper Saddle River,New Jersey.Barry,R.G.,Chorley,R.J.,Yokoi,N.J.,2004.Atmosphere,Weather,and Climate, eighth ed.Routledge,London.Berger,A.,Loutre,M.F.,1991.Insolation values for the climate of the last10,000,000 years.Quaternary Science Reviews10,297–317.Cai,Y.,Tan,L.,Cheng,H.,An,Z.,Edwards,R.L.,Kelly,M.J.,Kong,X.,Wang,X.,2010.The variation of summer monsoon precipitation in central China since the last deglaciation.Earth and Planetary Science Letters291,21–31.Chen,T.,1985.Global water vaporflux and maintenance during FGGE.Monthly Weather Review113,1801–1819.Chen,L.H.,Qu,Y.G.,1992.Water-Land Resources and Reasonable Development and Utilization in the Hexi Region.Science Press,Beijing(in Chinese).Chen,F.H.,Yu,Z.C.,Yang,M.L.,Ito,E.,Wang,S.M.,Madsen,D.B.,Huang,X.Z.,Zhao,Y., Sato,T.,Birks,H.J.B.,Boomer,I.,Chen,J.H.,An,C.B.,Wünnemann,B.,2008.Holocene moisture evolution in arid central Asia and its out-of-phase relationship with Asian monsoon history.Quaternary Science Reviews27, 351–364.Chen,F.H.,Chen,J.,Holmes,J.,Boomer,I.,Austin,P.,Gates,J.B.,Wang,N.,Brooks,S.J., Zhang,J.,2010.Moisture changes over the last millennium in arid central Asia:a review,synthesis and comparison with monsoon region.Quaternary ScienceReviews29,1055–1068.Cosford,J.,Qing,H.R.,Eglington,B.,Mattey,D.,Yuan,D.X.,Zhang,M.L.,Cheng,H., 2008.East Asian monsoon variability since the Mid-Holocene recorded in a high-resolution,absolute-dated aragonite speleothem from eastern China.Earth and Planetary Science Letters275,296–307.Cronin,T.M.,2009.Paleoclimates:Understanding Climate Change Past and Present.Columbia University Press,New York.Dong,J.,Wang,Y.,Cheng,H.,Hardt,B.,Edwards,R.L.,Kong,X.,Wu,J.,Chen,S.,Liu,D.,Jiang,X.,Zhao,K.,2010.A high-resolution stalagmite record of the HoloceneEast Asian monsoon from Mt Shennongjia,central China.The Holocene20,257–264.Table1Correlation coefficients(1960–2008)between EOF1time series(EOF1-T),EOF2time series(EOF2-T),EOF3time series(EOF3-T),East Asian Summer Monsoon Index(EASMI), South Asian Summer Monsoon Index(SASMI),Summer Westerly Winds Index(SWI)and summer rainfall anomalies(P).EASMI SASMI SWI P EOF1-T EOF2-T EOF3-TEASMI 1.000SASMI0.758** 1.000SWI0.407**0.396** 1.000PÀ0.158À0.1870.243 1.000EOF1-TÀ0.094À0.1110.315*0.982** 1.000EOF2-TÀ0.449**À0.549**À0.336*0.0790.002 1.000EOF3-TÀ0.0020.0760.038À0.1230.0000.009 1.000*Correlation is significant at the0.05level.**Correlation is significant at the0.01level.86Y.Li et al./Journal of Asian Earth Sciences58(2012)78–87。

利用Argo数据计算吕宋海峡以东海域水文特性参数和流场何建玲;蔡树群【摘要】利用2006年Argo浮标资料分析吕宋海峡以东海域水团季节特性和混合层的月平均变化规律;并分别利用Argo多年季节平均资料与2006年资料,以秋季为例,基于P矢量方法计算该区域流场;同时考虑风生流的影响,将所得结果分别与利用Levitus和高度计资料计算的流场进行比较。

结果表明,水团特性季节变化不明显,春冬季表层水团与夏秋季比较表现为低温高盐;次表层、中层和深层季节变化不大;混合层深度明显表现为冬季最深、夏季最浅的季节性变化。

利用2002—2009年Argo季节平均资料基于P矢量方法能得到地转流场的基本结构,与Levitus资料的计算结果相比较,除可以反映黑潮,还可以反映一些涡旋结构;利用2006年秋季Argo资料计算流场与高度计资料计算的地转流场比较,其流场结构位置吻合得比较好,但存在流速偏小等不足,这可能与Argo资料较少且分布不均以及插值误差等有关,但其可以获得流场的三维结构,而利用高度计资料计算只能得到表层流场结构。

【期刊名称】《热带海洋学报》【年(卷),期】2012(031)001【总页数】10页(P18-27)【关键词】Argo;水团分析;混合层深度;P矢量方法;吕宋海峡;流场【作者】何建玲;蔡树群【作者单位】【正文语种】中文【中图分类】P731国际Argo计划由美国、日本等国提出, 于2000年正式启动。

截止2010年1月, 全球共有29个国家和地区参与了 Argo浮标的布放, 共投放浮标6623个, 其中目前仍在海上正常工作的浮标 2941个, 获取了约 50余万条海洋剖面资料, 建立了全球、区域和国家的三级资料管理中心, 实现Argo资料的全球共享[1]。

Argo浮标设计的工作流程为: 浮标被投入海后先自动下潜至预先设定的漂流深度(约1000m), 漂流约8—10d后自动潜到2000m深度,然后自动上升至海面, 并进行温度、盐度的剖面测量, 这大约需要 10h, 到达海面后, 将数据通过Argos卫星系统传给用户, 完成一次观测。

东亚副热带西风急流的年代际变化对我国降水量分布的影响摘要利用1983-2011年全国各省市随机挑选出来的气象站点观测的全年日降水资料和同年NCEP/NCAR月平均再分析资料，对我国南北方全年降水与同期东亚副热带西风急流的位置的年代际变化进行了分析。

关键字：东亚副热带西风急流；中国降水；年代际变化；急流轴引言：东亚副热带西风急流，一直以来都是气象学家们所研究的重点，它不仅是大气环流形势的重要组成部分，更是影响我国乃至整个亚太地区的天气、气候异常的重要系统之一。

东亚副热带西风急流是一条独立环绕副热带地区的强锋带，终年在东亚上空活动，常常出现在西太平洋副热带高压的北部边缘，具有明显的季节变化特征。

东亚副热带西风急流的北跳和南退是东亚大气环流季节性突变的重要特征，影响着中国天气的变化。

陶诗言等[1]指出东亚梅雨的开始和结束与6月及7月份亚洲上空南支西风急流的两次北跳过程密切相关。

叶笃正等[2]很早就注意到亚洲地区气候的季节变化与6月及10月大气环流的突变紧密相连，并指出这种突变的重要表现之一是副热带西风急流的北跃或南落。

高由禧[3]及丁一汇等[4]的研究则表明高空急流带所引起的次级环流往往导致其南侧出现明显的降水中心。

Krishnamurti[5]分析了1955年冬季北半球200hPa风速场，得出副热带西风急流是围绕着地球的一个连续带，在这支西风急流中有三个波，但未提及其与天气分布的关系。

Liang 等[6]通过对资料观测和CCM3 模拟资料的对比分析研究了东亚季风降水与对流层急流的联系，认为北部的东亚副热带西风急流与南部的Hadley环流是影响东亚区域季风降水的显著系统。

东亚副热带西风急流与亚洲、西北太平洋地区的天气、气候变化关系如此密切，对于分析其变化特征和及其地面气象要素可以加深对东亚副热带西风急流的理解，对东亚区域气候变化在年代尺度上的认识。

尽管人们在东亚副热带西风急流的形成机制方面做了大量的研究，但是由于东亚地区地形复杂，海陆分布不均，特别是青藏高原的影响，许多问题仍待解决，尤其是对东亚副热带西风急流的时空变化特征等问题需要进一步的研究。

DOI: 10.16562/ki.0256-1492.2020101101西太平洋帕劳砗磲高分辨率氧同位素记录及其指示的气候环境变化文汉锋1,2，赵楠钰1,2，刘成程1,2，周鹏超1,3，王国桢1,2，晏宏11. 中国科学院地球环境研究所，黄土与第四纪地质国家重点实验室，西安 7100612. 中国科学院大学，北京 1000493. 北京师范大学地球科学前沿交叉研究中心，北京 100875摘要：砗磲是海洋中最大的双壳类贝壳，其碳酸盐壳体通常具有年纹层和天纹层，是一种理想的高分辨率古气候研究载体。

氧同位素是砗磲古气候研究中最常用的指标之一，但在将其应用于古气候重建之前，通常需要对其现代地球化学过程进行准确的校准。

帕劳群岛位于西太平洋暖池西北边缘，其珊瑚礁盘具有丰富的砗磲壳体资源，为开展古气候研究提供了丰富的材料。

在本次研究中，对采自帕劳群岛的现代活体库氏砗磲（Tridacna gigas ）PL-1的内层壳体进行了高分辨率氧同位素分析，同时利用该砗磲较为清晰的天生长纹层对氧同位素的年代学框架进行了标定。

结果表明，该砗磲壳体的氧同位素没有明显的变化趋势，说明砗磲个体的生命效应对氧同位素没有显著影响；砗磲壳体氧同位素没有清晰的年周期变化，常出现不规则的毛刺状峰值。

结合现代器测资料分析发现，帕劳砗磲内层壳体的氧同位素记录了热带太平洋ENSO 活动对该区域水文气候变化的影响。

该研究结果表明，帕劳砗磲内层壳体天生长纹层和氧同位素，具有用于开展高分辨率古气候研究的潜力。

关键词：砗磲；天生长纹层；氧同位素；ENSO 中图分类号：P532，P736.4 文献标识码：AHigh-resolution oxygen isotope records of Tridacna gigas from Palau, Western Pacific and its climatic and environmental implicationsWEN Hanfeng 1,2, ZHAO Nanyu 1,2, LIU Chengcheng 1,2, ZHOU Pengchao 1,3, WANG Guozhen 1,2, YAN Hong 11. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, China2. University of Chinese Academy of Sciences, Beijing 100049, China3. Interdisciplinary Research Center of Earth Science Frontier (IRCESF), Beijing Normal University, Beijing 100875, ChinaAbstract: Tridacna gigas is the largest marine bivalve, and its hard and dense aragonite shells usually have annual and daily growth lines, which have been demonstrated to be an ideal material for high-resolution paleoclimate research. The oxygen isotope has been widely used in Tridacna paleoclimate studies. However, the oxygen isotope of Tridacna shells must be accurately calibrated by modern geochemical process before paleoclimate reconstructions. Palau is located in the northwestern edge of the Western Pacific Warm Pool. Long-lived Tridacna spp. is a common species in the coral reefs of Palau Islands, which may provide abundant materials for paleoclimate reconstructions. In this study, we present a high-resolution oxygen isotope profile from the inner shell of a modern living T. gigas specimen PL-1 from Palau. The high-resolution chronology of the oxygen isotope profile is determined by the clear daily growth layers in the inner shell. The result suggests that the δ18O c profile of the T. gigas shell has no obvious trend, indicating that the vital effects have no significant influence on the oxygen isotope of bining with the instrumental data, we found that the ENSO activities in the tropical Pacific had impacts on the regional hydro-climate changes of Palau, and left some fingerprint in the oxygen isotope of Tridacna shell. This study indicates that the daily growth layer and the oxygen isotope in the inner shell of Tridacna from Palau have the potential for high-resolution paleoclimate research.Key words: Tridacna spp.; daily growth layers; oxygen isotope; ENSO资助项目：国家自然科学基金“利用砗磲重建南海北部小时分辨率气候变化初探”（41877399），“地质新时代的人类世：时限、特征与影响”（41991250）；中国科学院战略性先导科技专项B 类（XDB40000000）；中国科学院“西部之光”人才培养引进计划作者简介：文汉锋（1995―），男，硕士研究生，研究方向为砗磲地球化学，E-mail ：whfloess2019@ 通讯作者：晏宏（1986―），男，研究员，主要从事热带-亚热带气候环境变化研究，E-mail ：yanhong@ 收稿日期：2020-10-11；改回日期：2020-11-07. 蔡秋蓉编辑ISSN 0256-1492海 洋 地 质 与 第 四 纪 地 质第 41 卷 第 1 期CN 37-1117/PMARINE GEOLOGY & QUATERNARY GEOLOGYVol.41, No.1气候的季节和年际变化是地球气候系统中的重要组成部分，通常会对生态环境及人类生活造成巨大的影响[1–3]。

暴雨灾害TORRENTIAL RAIN AND DISASTERSVol.39No.6Dec.2020第39卷第6期2020年12月收稿日期：2020-10-31；定稿日期：2020-12-25资助项目：安徽省自然科学基金(1908085MD109);气象预报业务关键技术发展专项子项目(YBGJXM20206A-02);安徽省气象局科研项目KM201903)第一作者：田红，主要从事气候业务及服务。

E-mail:*****************通信作者：程智，主要从事短期气候预测。

E-mail:*******************田红,程智,谢五三,等.2020.2020年安徽梅雨异常特征及预测前兆信号分析[J].暴雨灾害,39(6):564-570TIAN Hong,CHENG Zhi,XIE Wusan,et al.2020.Analysis on the characteristics of Meiyu anomaly and prediction precursor signal in Anhui Province in 2020[J].Torrential Rain and Disasters,39(6):564-5702020年安徽梅雨异常特征及预测前兆信号分析田红，程智，谢五三，戴娟(安徽省气候中心，合肥230031)摘要：基于安徽省气象台站降水资料和NCEP 再分析数据，分析了2020年安徽梅雨气候异常特征及其成因，评估了汛期预测效果及其预测前兆信号的有效性。

结果表明：(1)2020年安徽6月2日入梅，8月1日出梅，梅雨期长度为60d，梅雨量沿江江南1057mm，江淮之间810mm，多地降水强度创历史极值。

综合来看，梅雨期之长、覆盖范围之广、累计雨量之大、梅雨强度之强，均为1961年以来第一位。

(2)梅雨异常偏多的主要原因是6—7月乌拉尔山、东西伯利亚-鄂霍茨克海附近阻塞高压活跃，东亚沿海500hPa 位势高度距平场上EAP 波列的形势明显，夏季风偏弱，西太平洋副热带高压(副高)异常偏强偏西偏南，有利于冷暖空气在安徽交汇，副高西侧向安徽省的水汽输送异常偏强，水汽辐合明显；梅雨期偏长的原因是副高脊线6月偏北、7月偏南，导致入梅偏早、出梅偏迟。

全球变暖背景下西北太平洋热带气旋活动的时空变化特征及潜在风险分析顾成林;康建成;闫国东;陈志伟【摘要】以美国联合台风中心的热带气旋资料为基础,探讨全球变暖背景下1951-2015年65年间西北太平洋热带气旋(TC)活动变化的时空特征,并对中国所受潜在风险进行分析.结论如下:①1951-2015年热带气旋频数、超强台风频数长期变化趋势并不明显.热带气旋频数在1950年左右发生突变,由1950年以前的偏少期向偏多期转变,但只有在1960年代初期到1970年代初期、1990年代末期至2000年代初期两个阶段增加趋势通过0.05的显著水平检验.②从1950年代初期至1950年代末期,西北太平洋热带气旋年均最大强度与年均强度呈现短期加强趋势,之后呈现长期减弱趋势.总体上看,西北太平洋热带气旋年均最大强度与年均强度总体上呈明显下降趋势.平均强度在1972年左右发生突变,说明在1972年以后平均强度减少的趋势显著.最大强度在1968年左右发生突变,说明在1968年以后最大强度减少的趋势显著.③从热带气旋最大强度(成熟)阶段,路径频数,观测强度线性变化趋势的空间分布来看,线性变化呈上升趋势的位置均向东亚大陆靠近,这也就意味着西北太平洋热带气旋活动强度在一定程度上呈减弱趋势,但是登陆的频次、强度极有可能加强.也就是在整个东亚大陆受西北太平洋热带气旋潜在威胁会进一步加剧.④产生这样结果极有可能是由于全球变暖导致的西太平洋与中东太平洋纬向温度梯度加大,从而导致walker环流的加强,正在加强的walker环流能够加强热带西北太平洋风垂直切变与相对涡度的变化,从而影响西北太平洋TC活动的时空变化.【期刊名称】《灾害学》【年(卷),期】2019(034)002【总页数】8页(P89-96)【关键词】全球变暖;西北太平洋;热带气旋;时空变化特征;大尺度背景场【作者】顾成林;康建成;闫国东;陈志伟【作者单位】上海师范大学环境与地理科学学院,上海200234;佳木斯大学理学院环境科学系,黑龙江佳木斯154007;上海师范大学环境与地理科学学院,上海200234;上海工程技术大学,上海200234;上海师范大学环境与地理科学学院,上海200234【正文语种】中文【中图分类】X43;X915.5;P444;P461在过去几十年，揭示热带气旋的生成、发展以及影响因素一直是气象学所面临的挑战。

808太平洋年代际海洋变率的信号通道王东晓刘征宇中国科学院南海海洋研究所热带海洋环境动力学开放实验室, 广州510301Deptartment of Atmospheric and OceanicSciences, University of Wisconsin-Madison, Madison, WI 53706, USA. Email: dxwang@)摘要 运用复经验正交函数展开(CEOF)和合成分析方法, 研究了太平洋上层海洋抛弃式温深计(XBT)温度观测资料所揭示的北太平洋年代际海洋变率的若干个例及其时空演变特征. 研究表明,中纬度海气相互作用的信息可以沿温跃层所在的等密面传到副热带海域. 观测分析的另一个发现是Ｎ，　热带西太平洋的年代际海洋信号主要来自于南太平洋热带区域. 这类信号沿着太平洋经向型通道传播, 具有温跃层环流的特征.关键词 年代际海洋变率 太平洋 潜沉 信号通道大量的观测分析表明, 太平洋海洋大气组成的气候系统在1976年前后经历了一次明显的年代际调整[1ÕûÀíºÍʹÓÃ, 一个有魅力的假设已经在观测分析和理论分析的基础上形成, 即副热带和中纬度海洋热异常信号可以沿着温跃层潜沉, 历经数年后传播到低纬度海域[7,8]. 许多研究在不同程度上支持了这个假设[9±±Ì«Æ½Ñóº£ÑóÓ°ÏìÈÈ´øº£Ñó(特别是热带西太平洋)年代际变化的信号通道. 本文试图回答两个问题(2) 如果这类传播中断,热带西太平洋年代际海洋信号的源地在何处(1) 19502°上层海洋(01 000 m 共19层, 为气候平均逐月资料(共12个月).本文采用复经验正交函数分析(complex empirical orthogonal function, CEOF)[14]和合成分析等方法1).1) 采用CEOF 分析出于以下的考虑: 一是借助这种方法将ENSO 时间尺度的信号和年代际信号较彻底地分离开来,这是以往研究中使用简单合成方法所难以较好实现的[8]; 二是CEOF 分析得到的复数主成分, 其时间系数传统EOF 或扩展EOF [15,16]分析难以提取的重要信息.8092 太平洋年代际海洋变率的水平特征由于SST 的低频变化会受到海面海气相互作用过程的强烈调制, 其变化特征不能准确地反映上层海洋真正的年代际演变, 所以我们采用XBT 资料01993年上层海洋热含量观测资料的CEOF 分析表明, 太平洋400 m 上层海洋热含量年代际模态具有的空间型为在热带太平洋,年代际海洋变化呈东西向的(图略). 这个空间型与1950ůÐźÅÊÇ·ñ´«µ½ÈÈ´øÎ÷̫ƽÑó½ü³àµÀµØÇø1988年间逐年演变(限于篇幅只给出偶数年份的分布). 可以看到20世纪70年代在北太平洋中部, 有一个正距平(暖信号)得到发展和维持45°N 的暖异常经过5年后传到了副热带地区(18°N 附近). 而恰巧与此同时, 热带西太平洋的暖异常也得到发展,热带西南太平洋附近信号图1 太平洋200 m 层次上海温年代际变化的标准方差(1960400 m X BT 共11层海温距平计算的热含量, 经过5年滑动平均(下同).粗黑点为本文分析所选的剖面位置810图2 太平洋400 m上层海洋热含量CEOF分析第一模态恢复场CEOF第一模态解释了总方差的43.55%. 等值线间隔为0.5s/m2. 阴影区为负距平811加强也很明显. 在上述5年中这个暖异常区的北缘向北挺进, 于1974年北进至15°N 附近. 随后这两个区域的暖异常互为承接北半球副热带(热带)海洋对热带太平洋的年代际影响可以借助一个特殊剖面上信号的时间-空间分布图来检验. 型剖面的选取参考了图1揭示的太平洋年代际变率的方差分布结构. 自北太平洋中部至热带南太平洋中部共选了20个资料格点, 南北两支略呈对称分布(关于4°N 纬向的轴线). 其中北支(30°<1991年该剖面上上层海洋热含量CEOF年代际时间尺度第一模态恢复图3 太平洋型垂直剖面时间演变图: CEOF 第一模态恢复场等值线间隔0.1s/m 2．　Ｘ轴为剖面上格点序号．　各格点的位置是812场的时空演变. 此图清晰地显示了19531959年是暖异常, 196070年代初至90年代初又是一个完整的年代际循环, 其中19711990年是冷异常. 慎重起见, 我们将图3与上层海洋热含量滑动平均后未经CEOF 分解的同一剖面时空演变进行比较(图略), 发现后者中这两个年代际冷暖循环也清晰可见, 只是叠加了若干ENSO 尺度年际变化信号.图3中还值得注意的是<¾¡¹Ü×ÜÌåÉÏÄÏÖ§ÉϵÄÐźűȱ±Ö§ÉϵÄÐźÅÈõÐí¶à.3.2垂向剖面合成图4 沿太平洋年代际海洋变率的通道上海温垂直剖面图等值线间隔0.219 psu. (a) 19661972年平均; (c) 19741981年平均; (e) 19831990年平均813为了验证上述的型剖面是太平洋年代际信号的经向通道, 我们需要分析未经CEOF分析的0ÀäÁ½¸ö¸öÀý, 且各用3个阶段来刻画信号的演变过程.北太平洋中部暖异常事件演变的垂向结构:在阶段1(图4(a), 1966¶ø´Ëʱ, 在热带南太平洋的温跃层上有更强的暖距平存在. 在阶段2(图4(b), 1970ÉÏÒ»½×¶Î±±Ì«Æ½ÑóÖв¿µÄÀäÒì³£ÒÆÏòÈÈ´ø̫ƽÑó, 标志着北太平洋中部暖异常年代的开始. 热带南太平洋温跃层上的暖距平沿着温跃层所在的等密度层次向北推进至西太平洋热带地区, 而热带太平洋和热带南太平洋的表层则有负的海温距平形成. 在阶段3(图4(c),1974±±Á½Ö§ÉϵÄůÒì³£ÔÚ18°N 的日期变更线附近汇聚.北太平洋中部冷异常事件演变的垂向结构１９８１年), 北太平洋中部维持的暖异常明显减弱１９８５年), 北太平洋中部冷异常强度快速增长, 并向南扩展. 热带南太平洋温跃层上下被大范围的冷距平占据, 沿着温跃层所在的等密度层次向北推进至西太平洋热带地区. 副热带北太平洋存在深厚的海温距平, 成为分割该通道南１９９０年), 北太平洋中部深厚的冷异常中心由(165°E, 28°N)移到(180°E, 20°N), 强度稍有增长. 与暖异常事件类似, 在温跃层上,该通道南Ｎ），　而热带西太平洋次表层的异常都是源于热带南太平洋大气模式和海气耦合模式被应用于北太平洋年代际气候变率的研究之中[1724], 我们试图分析这种海洋内部的交换在太平洋年代际海洋1) 俞永强. 海-冰-气耦合方案的设计及年代际气候变化的数值模拟研究. 中国科学院大气物理研究所博士论文, 1996814变率中的作用.本文主要分析太平洋海洋内部在年代际尺度上的若干交换过程. 一个过程是北太平洋中纬度海洋与副热带海域的交换, 另一个过程是热带南太平洋与热带西太平洋的交换.显然第一过程已经有过一些观测研究, 但关于北太平洋中部潜沉的异常信号是否传到近赤道海区这一问题未予置否, 甚至有过肯定的结论[9]. 本文图1Ò»ÊÇËùÓÃ×ÊÁÏ·¶Î§Ã»Óи²¸ÇÈÈ´øÄÏ̫ƽÑó, 没能关注到热带南太平洋与热带西太平洋的内在联系因此体现在垂向积分的上层海洋热含量中信号强度被削弱了.致谢 本工作为国家自然科学基金(批准号: 49705063)中国科学院国家知识创新试点工程项目和国家重点基础研究发展规划（G1999043806）资助项目．参 考 文 献1 Douglas A V, Cayan D R, Namias J. 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70印度洋–太平洋的海气相互作用通过影响印度季风和东亚季风进而调控着位于其北侧的中国低纬高原区的天气气候。

印太暖池区海气相互作用的异常往往造成低纬高原区天气气候的异常，进而产生显著的灾害效应，引起巨大的生态灾难、经济损失和人员伤亡。

因此，开展印度洋–太平洋地区海气相互作用变异及其在低纬高原区灾害效应研究一方面可以深化对我国和东亚地区的气候变异规律的理解，具有重要的科学研究意义；另一方面可通过提高我国低纬高原地区的气候预测水平、增强防灾减灾救灾能力，为云南加快建成面向南亚东南亚的辐射中心提供科学支撑，具有显著的应用价值。

在国家自然科学基金委员会-云南省政府联合基金重点（U0933603）等项目的支持下，项目组通过资料诊断、理论分析和数值模拟相结合的综合研究方法，系统开展了相关研究，取得了如下一系列重要科学发现：1）针对东亚季风系统提出以来，长期存在争议的印度夏季风和东亚夏季风分界的重大科学问题，引入具有守恒属性的物理量：假相当位温，在定义印度夏季风和东亚夏季风交界面处于假相当位温纬向一阶导数为零处的基础上（图1），率先定量化地确定了印度夏季风和东亚夏季风交界面（图2）；建立了印度夏季风和东亚夏季风交界面指数；揭示了①印度夏季风与东亚夏季风的分界不能逾越高黎贡山，哀牢山系对两支季风交互影响的阻隔作用明显但并不是它们的地理分界线，②印太海气相互作用是决定两季风交界面位置变化的关键外部热力强迫因素，③印度夏季风和东亚夏季风交界异常与东亚夏季降水关系密切（图3）；回答了印度、东亚两季风交界面形成和变异的重大科学问题[1–4]。

印太暖池海气相互作用及其在低纬高原区的灾害效应图1 20°–30°N，90°–110°E多年平均夏季的三维空间分布图2 近地等压面层多年平均印度夏季风和东亚夏季风交界的位置图3 平均印度夏季风和东亚夏季风交界指数与亚洲夏季降水的关系2019年度云南省科学技术奖自然科学奖一等奖成果云南大学 中国科学院大气物理研究所 云南省气象科学研究所712020年第4期低纬高原区汛期降水的异常，易引发旱涝及次生灾害（图6–图9）[8]。