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1.
Summary The interannual variability of sea surface temperature (SST) anomalies in the tropical Indian Ocean is dominated mainly by a basin-scale mode (BM) and partly by an east–west contrast mode (zonal mode, ZM). The BM reflects the basin-scale warming or cooling and is highly correlated with El Nino with 3- to 6-month lags, while the ZM is marginally correlated with El Nino with 9-month lags.During an El Nino, large-scale anomalous subsidence over the maritime continent occurs as a result of an eastward shift in the rising branch of the Walker circulation suppresses convection over the eastern Indian Ocean, allowing more solar radiation over the eastern Indian Ocean. At the same time, the anomalous southeasterly wind over the equatorial Indian Ocean forces the thermocline over the western Indian Ocean to deepen, especially in the southern part. As a result, SST over the whole basin increases. As El Nino decays, the subsidence over the maritime continent ceases and so does the anomalous southeasterly wind. However, the thermocline perturbation does not quickly shoal back to normal because of inertia and it disperses as Rossby waves. These Rossby waves are reflected back as an equatorial Kelvin wave, causing deepening of the thermocline in the eastern Indian Ocean, and preventing SSTs from cooling in that region. Moreover, the weaker wind speed of the monsoon circulation results in less latent heat loss, and thus warms the eastern Indian Ocean. These two processes therefore help to maintain warm SSTs over the eastern Indian Ocean until fall. During the fall, the warm SST over the eastern Indian Ocean and the cold SST over the western Indian Ocean are enhanced by air–sea interaction and the ZM returns. The ZM dissipates through the seasonal reversal of the monsoon atmospheric circulation and the boundary-reflected Kelvin wave. In the same manner, a basin-scale cooling in the tropical Indian Ocean can induce the ZM warming in the west and cooling in the east.  相似文献   

2.
利用1979—2019年Hadley中心的海表温度资料、GPCP的降水资料以及NCEP-DOE的再分析资料等,分析了北半球春季热带南大西洋海表温度异常与北半球夏季亚澳季风区降水异常的联系。研究表明,北半球春季热带南大西洋海表温度异常与随后夏季热带西太平洋到南海(澳大利亚东侧海域到热带东印度洋)地区的降水异常为显著负相关(正相关)关系。北半球春季热带南大西洋的海表温度正异常可以引起热带大西洋和热带太平洋间的异常垂直环流,其中异常上升支(下沉支)位于热带大西洋(热带中太平洋)。热带中太平洋的异常下沉气流和低层辐散气流引起热带中西太平洋低层的异常东风,后者有利于热带中东太平洋海表温度出现负异常。通过Bjerknes正反馈机制,热带中东太平洋海表温度异常从北半球春季到夏季得到发展。热带中东太平洋海表温度负异常激发的Rossby波使得北半球夏季热带西太平洋低层出现一对异常反气旋。此时,850 hPa上热带西太平洋到海洋性大陆地区为显著的异常东风,有利于热带西太平洋到南海(澳大利亚东侧海域到热带东印度洋)地区出现异常的水汽辐散(辐合),导致该地区降水减少(增加)。  相似文献   

3.
In this study, several advanced analysis methods are applied to understand the relationships between the Nino-3.4 sea surface temperatures (SST) and the SSTs related to the tropical Indian Ocean Dipole (IOD). By analyzing a long data record, the authors focus on the time-frequency characteristics of these relationships, and of the structure of IOD. They also focus on the seasonal dependence of those characteristics in both time and frequency domains. Among the Nino-3.4 SST, IOD, and SSTs over the tropical western Indian Ocean (WIO) and eastern Indian Ocean (EIO), the WIO SST has the strongest annual and semiannual oscillations. While the Nino-3.4 SST has large inter-annual variability that is only second to its annual variability, the IOD is characterized by the largest semiannual oscillation, which is even stronger than its annual oscillation. The IOD is strongly and stably related to the EIO SST in a wide range of frequency bands and in all seasons. However, it is less significantly related to the WIO SST in the boreal winter and spring. There exists a generally weak and unstable relationship between the WIO and EIO SSTs, especially in the biennial and higher frequency bands. The relationship is especially weak in summer and fall, when IOD is apparent, but appears highly positive in winter and spring, when the IOD is unimportantly weak and even disappears. This feature reflects a caution in the definition and application of IOD. The Nino-3.4 SST has a strong positive relationship with the WIO SST in all seasons, mainly in the biennial and longer frequency bands. However, it shows no significant relationship with the EIO SST in summer and fall, and with IOD in winter and spring.  相似文献   

4.
In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.  相似文献   

5.
The focus of this study is to document the possible role of the southern subtropical Indian Ocean in the transitions of the monsoon-ENSO system during recent decades. Composite analyses of sea surface temperature (SST) fields prior to El Niño-Southern Oscillation (ENSO), Indian summer monsoon (ISM), Australian summer monsoon (AUSM), tropical Indian Ocean dipole (TIOD) and Maritime Continent rainfall (MCR) indices reveal the southeast Indian Ocean (SEIO) SSTs during late boreal winter as the unique common SST precursor of these various phenomena after the 1976–1977 regime shift. Weak (strong) ISMs and AUSMs, El Niños (La Niñas) and positive (negative) TIOD events are preceded by significant negative (positive) SST anomalies in the SEIO, off Australia during boreal winter. These SST anomalies are mainly linked to subtropical Indian Ocean dipole events, recently studied by Behera and Yamagata (Geophys Res Lett 28:327–330, 2001). A wavelet analysis of a February–March SEIO SST time series shows significant spectral peaks at 2 and 4–8 years time scales as for ENSO, ISM or AUSM indices. A composite analysis with respect to February–March SEIO SSTs shows that cold (warm) SEIO SST anomalies are highly persistent and affect the westward translation of the Mascarene high from austral to boreal summer, inducing a weakening (strengthening) of the whole ISM circulation through a modulation of the local Hadley cell during late boreal summer. At the same time, these subtropical SST anomalies and the associated SEIO anomalous anticyclone may be a trigger for both the wind-evaporation-SST and wind-thermocline-SST positive feedbacks between Australia and Sumatra during boreal spring and early summer. These positive feedbacks explain the extraordinary persistence of the SEIO anomalous anticyclone from boreal spring to fall. Meanwhile, the SEIO anomalous anticyclone favors persistent southeasterly wind anomalies along the west coast of Sumatra and westerly wind anomalies over the western Pacific, which are well-known key factors for the evolution of positive TIOD and El Niño events, respectively. A correlation analysis supports these results and shows that SEIO SSTs in February–March has higher predictive skill than other well-established ENSO predictors for forecasting Niño3.4 SST at the end of the year. This suggests again that SEIO SST anomalies exert a fundamental influence on the transitions of the whole monsoon-ENSO system during recent decades.  相似文献   

6.
徐志清  范可 《大气科学》2012,36(5):879-888
印度洋热力状况是影响全球气候变化和亚洲季风变异的一个重要的因素,但以往研究更多关注热带印度洋海温的变化,对南印度洋中高纬地区海温变化关注不够,由此限制了我们对印度洋的全面认识.本文研究了年际尺度上整个印度洋海温异常主导模态的特征及其对我国东部地区夏季降水的可能影响过程,以期望为气候变异研究及预测提供理论依据.研究结果表明:全印度洋海温异常年际变率的主导模态特征是在南印度洋副热带地区海温异常呈现西南—东北反向变化的偶极子模态,西极子位于马达加斯加以东南洋面,东极子位于澳大利亚以西洋面;同时,热带印度洋海温异常与东极子一致.当西极子为正的海温异常,东极子、热带印度洋为负异常时定义为正的印度洋海温异常年际变率模态;反之,则为负的印度洋海温异常年际变率模态.从冬至春,印度洋海温异常年际变率模态具有较好的季节持续性;与我国长江中游地区夏季降水显著负相关,而与我国华南地区夏季降水显著正相关.其可能的影响过程为:对于正的冬、春季印度洋海温异常年际变率模态事件,印度洋地区异常纬向风的经向大气遥相关使得热带印度洋盛行西风异常,导致春、夏季海洋性大陆对流减弱,使夏季西太平洋副热带高压强度偏弱、位置偏东偏北,造成华南地区夏季降水增多,长江中游地区降水减少;反之亦然.同时,印度洋海温异常年际变率模态可通过改变印度洋和孟加拉湾向长江中游地区的水汽输送而影响其夏季降水.  相似文献   

7.
There is strong evidence that Indian Ocean sea surface temperatures (SSTs) influence the climate variability of Southern Asia and Africa; hence, accurate prediction of these SSTs is a high priority. In this study, we use canonical correlation analysis (CCA) to design empirical models to assess the predictability of tropical Indian Ocean SST from sea level pressure (SLP) and SST themselves with lead-times up to one year. One model uses the first twelve empirical orthogonal functions (EOFs) of SLP over the Indian Ocean using different lead-times to predict SST. A CCA model with EOFs of SST as the predictor at the same lead-times is compared to SLP as a predictor and shows the auto-correlation of the system. A CCA using the first five extended empirical orthogonal functions (EEOFs) of sea level pressure over the Indian Ocean basin for an interval of two years combined with SST EOFs as predictors is found to produce the greatest correlation between forecast and observed SSTs. This model obtains higher skill by explicitly considering the development in time of SLP anomalies in the region. The skill of this model, assessed from retroactive forecasts of an 18 year period, shows improvement relative to other empirical forecasts particularly for the central and eastern Indian Ocean and boreal autumn months preceding the Southern Hemisphere summer rainfall season. This is likely due to the limited domain of this model identifying modes of variability that are more pronounced in these areas during this season. Finally, a nonlinear canonical correlation analysis (NLCCA) derived from a neural network is used to analyze the leading nonlinear modes. These nonlinear modes differ from the linear CCA modes with distinct cold and warm SST phases suggesting a nonlinear relationship between SST and SLP over the tropical Indian Ocean.  相似文献   

8.
Shaolei TANG  Jing-Jia LUO  Jiaying HE  Jiye WU  Yu ZHOU  Wushan YING 《大气科学进展》2021,38(12):2023-2039,中插8-中插11
The extreme floods in the Middle/Lower Yangtze River Valley (MLYRV) during June?July 2020 caused more than 170 billion Chinese Yuan direct economic losses. Here, we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans. Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific, which brought tropical warm moisture northward that converged over the MLYRV. In addition, despite the absence of a strong El Ni?o in 2019/2020 winter, the mean SST anomaly in the tropical Indian Ocean during June?July 2020 reached its highest value over the last 40 years, and 43% (57%) of it is attributed to the multi-decadal warming trend (interannual variability). Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020 (albeit the magnitude of the predicted precipitation was only about one-seventh of the observed), sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods, compared to the contributions of SST anomalies in the Maritime Continent, central and eastern equatorial Pacific, and North Atlantic. Furthermore, both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods. Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.  相似文献   

9.
Shaolei TANG  Jing-Jia LUO  Jiaying HE  Jiye WU  Yu ZHOU  Wushan YING 《大气科学进展》2021,38(12):2023-2039,中插8-中插11
The extreme floods in the Middle/Lower Yangtze River Valley (MLYRV) during June?July 2020 caused more than 170 billion Chinese Yuan direct economic losses. Here, we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans. Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific, which brought tropical warm moisture northward that converged over the MLYRV. In addition, despite the absence of a strong El Ni?o in 2019/2020 winter, the mean SST anomaly in the tropical Indian Ocean during June?July 2020 reached its highest value over the last 40 years, and 43% (57%) of it is attributed to the multi-decadal warming trend (interannual variability). Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020 (albeit the magnitude of the predicted precipitation was only about one-seventh of the observed), sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods, compared to the contributions of SST anomalies in the Maritime Continent, central and eastern equatorial Pacific, and North Atlantic. Furthermore, both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods. Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.  相似文献   

10.
BCC S2S模式对亚洲夏季风准双周振荡预报评估   总被引:1,自引:1,他引:0       下载免费PDF全文
利用1994-2013年ERA-Interim及NCEP/NCAR再分析数据,对国家气候中心(BCC)次季节到季节尺度模式(S2S)1994-2013年的回报试验数据进行亚洲季风区准双周振荡(QBWO)预报能力评估,并诊断模式预报误差来源。结果表明:BCC S2S模式对QBWO的预报能力随着预报提前时间的增长而降低,9 d后预报技巧明显减弱,其周期、传播特征和强度出现误差;在提前9 d预报中,印度洋地区QBWO对流-环流系统结构松散,信号偏弱,对流向东传播,这与印度洋平均态的预报误差有关,夏季对流平均态低层水汽场在西太平洋和阿拉伯海较强,而东印度洋、孟加拉湾一带偏弱;西北太平洋地区QBWO具有向西北传播的特征,但强度偏弱,可能原因是预报低估了QBWO对流西北侧低层涡度的超前信号,经涡度方程诊断发现,地转涡度平流正贡献微弱,相对涡度平流在对流西北侧引发负涡度,从而减弱了对流西北侧由低层正涡度引发的有利条件。  相似文献   

11.
利用观测分析资料和SINTEX-F海气耦合长时间(70年)数值模拟结果,分析了印度洋海温年际异常与热带夏季季节内振荡(BSISO)各种传播模态之间关系及其物理过程。结果表明,印度洋海温年际异常与热带BSISO关系密切,当印度洋为正(负)偶极子情况,中东印度洋北传BSISO减弱(加强);当印度洋为正(负)海盆异常(BWA)情况,印度洋西太平洋赤道地区(40°E -180°)东传BSISO加强(减弱)。印度洋海温年际变化通过大气环流背景场和BSISO结构影响热带BSISO不同传播模态强度的年际变化。在负(正)偶极子年夏季,由于对流层大气垂直东风切变加强(减弱),对流扰动北侧的正压涡度、边界层水汽辐合加强更明显(不明显),导致形成BSISO较强(弱)的经向不对称结构,因此北传BSISO偏强(减弱)。印度洋BWA模态通过影响赤道西风背景以及海气界面热力交换,导致赤道东传BSISO强度产生变化。在正BWA年夏季,赤道地区西风较明显,当季节内振荡叠加在这种西风背景下,扰动中心的东侧(西侧)风速减弱(加强)更明显,海面蒸发及蒸发潜热减弱(加强)更明显,导致扰动中心的东侧(西侧)海温升高(降低)幅度更大,从而使边界层产生辐合(辐散)更强、水汽更多(少),因此赤道东传BSISO偏强;而在负BWA年,赤道地区西风背景减弱,以上物理过程受削弱使赤道东传BSISO偏弱。  相似文献   

12.
In 2010 eastern Australia received its highest springtime (September–November) rainfall since 1900. Based on historical relationships with sea surface temperatures (SST) and other climate indices, this record rainfall in 2010 was shown to be largely commensurate with the occurrence of a very strong La Niña event and an extreme positive excursion of the SAM. The pattern and magnitude of the tropical SST anomalies in austral spring 2010 were diagnosed to be nearly perfect to produce high rainfall across eastern Australia. Key aspects of this SST pattern were the strong cold anomaly in the central equatorial Pacific, and the strong warm anomalies in the eastern Indian Ocean and the far western Pacific to the north of Australia. Although the recent upward trend in SSTs in the western Pacific/eastern Indian Ocean warm pool accounted for about 50 % of the SST anomaly surrounding northern Australia in 2010, the contribution by the warming trend in these SSTs to the Australian rainfall anomaly in 2010 was assessed to be relatively modest. The strong positive swing in SAM was estimated to have accounted for upwards of 40 % of the regional anomaly along the central east coastal region and about 10 % of the area mean anomaly across eastern Australia. This contribution by the SAM suggests that a significant portion of the rainfall in 2010 may not have been seasonally predictable. However, predictability arising from the promotion of high SAM by the extreme La Nina event can not be ruled out.  相似文献   

13.
Ensembles of atmospheric general circulation model (AGCM) experiments are used in an effort to understand the boreal winter Northern Hemisphere (NH) extratropical climate response to the observed warming of tropical sea surface temperatures (SSTs) over the last half of the twentieth Century. Specifically, we inquire about the origins of unusual, if not unprecedented, changes in the wintertime North Atlantic and European climate that are well described by a linear trend in most indices of the North Atlantic Oscillation (NAO). The simulated NH atmospheric response to the linear trend component of tropic-wide SST change since 1950 projects strongly onto the positive polarity of the NAO and is a hemispheric pattern distinguished by decreased (increased) Arctic (middle latitude) sea level pressure. Progressive warming of the Indian Ocean is the principal contributor to this wintertime extratropical response, as shown through additional AGCM ensembles forced with only the SST trend in that sector. The Indian Ocean influence is further established through the reproducibility of results across three different models forced with identical, idealized patterns of the observed warming. Examination of the transient atmospheric adjustment to a sudden “switch-on” of an Indian Ocean SST anomaly reveals that the North Atlantic response is not consistent with linear theory and most likely involves synoptic eddy feedbacks associated with changes in the North Atlantic storm track. The tropical SST control exerted over twentieth century regional climate underlies the importance of determining the future course of tropical SST for regional climate change and its uncertainty. Better understanding of the extratropical responses to different, plausible trajectories of the tropical oceans is key to such efforts.  相似文献   

14.
Yamaura  Tsuyoshi  Kajikawa  Yoshiyuki 《Climate Dynamics》2017,48(9-10):3003-3014

A decadal change in activity of the boreal summer intraseasonal oscillation (BSISO) was identified at a broad scale. The change was more prominent during August–October in the boreal summer. The BSISO activity during 1999–2008 (P2) was significantly greater than that during 1984–1998 (P1). Compared to P1, convection in the BSISO was enhanced and the phase speed of northward-propagating convection was reduced in P2. Under background conditions, warm sea surface temperature (SST) anomalies in P2 were apparent over the tropical Indian Ocean and the western tropical Pacific. The former supplied favorable conditions for the active convection of the BSISO, whereas the latter led to a strengthened Walker circulation through enhanced convection. This induced descending anomalies over the tropical Indian Ocean. Thermal convection tends to be suppressed by descending anomalies, whereas once an active BSISO signal enters the Indian Ocean, convection is enhanced through convective instability by positive SST anomalies. After P2, the BSISO activity was weakened during 2009–2014 (P3). Compared to P2, convective activity in the BSISO tended to be inactive over the southern tropical Indian Ocean in P3. The phase speed of the northward-propagating convection was accelerated. Under background conditions during P3, warmer SST anomalies over the maritime continent enhance convection, which strengthened the local Hadley circulation between the western tropical Pacific and the southern tropical Indian Ocean. Hence, the convection in the BSISO over the southern tropical Indian Ocean was suppressed. The decadal change in BSISO activity correlates with the variability in seasonal mean SST over the tropical Asian monsoon region, which suggests that it is possible to predict the decadal change.

  相似文献   

15.
Summary The influence of the Indian Ocean Zonal Mode on the extreme summer monsoon rainfall over East Asia (China, Korea, Japan) has been investigated applying simple statistical techniques of correlation and composite analysis. While the observed rainfall data are used as a measure of rainfall activity, the NCEP-NCAR Reanalysis data are used to examine the circulation features associated with the extreme monsoon phases and the dynamics of the zonal mode – monsoon variability connections. The data used covers the period 1960 to 2000.The equatorial Indian Ocean is dominated by westerly winds blowing towards Indonesia. However, during the positive phase of the zonal mode, an anomalous, intensified easterly flow prevails, consistent with the positive (negative) sea surface temperature anomalies over the western (southeastern) equatorial Indian Ocean. This positive phase of the zonal mode enhances summer monsoon activity over China, but suppresses the monsoon activity over the Korea-Japan sector, 3 to 4 seasons later. The relationship is more consistent and stronger over the Korea-Japan region than over China.The Indian Ocean influences the monsoon variability over East Asia via the northern hemisphere mid-latitudes or via the eastern Indian Ocean/west Pacific route. The monsoon-desert mechanism induces strong subsidence northwest of India due to the anomalous convection over the Indian Ocean region associated with the positive phase of the zonal mode. This induces a zonal wave pattern over the mid-latitudes of Asia propagating eastwards and displacing the north Pacific subtropical high over East Asia. The warming over the eastern Indian Ocean/west Pacific inhibits the westward extension of the north Pacific sub-tropical high. The location and shape of this high plays a dominant role in the monsoon variability over East Asia. The memory for delayed impact, three to four seasons later, could be carried by the surface boundary conditions of Eurasian snow cover via the northern channel or the equatorial SSTs near the Indonesian Through Flow via the southern channel.  相似文献   

16.
Lu Riyu 《大气科学进展》2000,17(2):205-220
1.IntroductionInthesummerof1998,theYangtzeRiverbasin,includingNenjiangRiverValleyinNortheastChinasufferedaseverelarge--scalefloodonlynexttothatinthesummerof1954inthiscentury.Thefloodcausedapproximatelythedeathof3000individualsandthedirecteconomicdamageof250billionRMByuans(Yan,1998).Thisextremedisasterpromptedaseriesofimmediatestudiesonit(e.g.,Iluangetal.,1998;Taoetal.,1998).TheevolutionoftheEastAsiansupsmermonsoonshowsagreatvariabilityfromyeartoOThisstudywassupportedbytheNationalNatura…  相似文献   

17.
利用1979~2015年NCEP/NCAR发布的月平均全球再分析资料,分析了热带印度洋-西太平洋水汽输送异常对中国东部夏季降水的影响及其形成机理。研究结果表明:热带印度洋-西太平洋地区(10°S~30°N,60°~140°E)夏季异常水汽输送主要包括两个模态,他们可以解释总的水汽输送异常34%的方差。其中,第一模态(EOF1)表现为异常水汽沿反气旋从热带西太平洋经过南海及孟加拉湾输送到中国东部上空,对应南海、孟加拉湾水汽路径输送均偏多,此时西太平洋副热带高压显著偏强,异常水汽在长江中下游地区辐合并伴随显著上升运动,有利于长江中下游降水偏多;第二模态(EOF2)表现为异常水汽从热带印度洋沿阿拉伯海、印度半岛、中南半岛等呈反气旋式输送,华南上空相应出现气旋式水汽输送异常,并对应异常水汽辐合和上升运动,有利于华南降水偏多。就可能的外部成因而言,EOF1与ENSO关系密切,表现为前冬热带中东太平洋显著偏暖,夏季同期热带北印度洋、南海上空显著偏暖,造成西太平洋副热带高压显著偏强,异常水汽主要来源于热带西太平洋和南海;EOF2与同期热带印度洋偶极子(TIOD)异常有关,TIOD为正位相时热带印度洋上空出现异常东风,华南上空出现异常气旋并伴随水汽异常辐合,异常水汽主要来源于热带南印度洋。  相似文献   

18.
Based on 15 Coupled Model Intercomparison Project (CMIP) phase 3 (CMIP3) and 32 CMIP phase 5 (CMIP5) models, a detailed diagnosis was carried out to understand what compose the biases in simulation of the Indian Ocean basin mode (IOBM) and its capacitor effect. Cloud-radiation-SST (CRS) feedback and wind-evaporation-SST (WES) feedback are the two major atmospheric processes for SST changes. Most CMIP models simulate a stronger CRS feedback and a weaker WES feedback. During boreal fall of the El Niño/Southern Oscillation developing year and the following spring, there are weak biases of suppressed rainfall anomalies over the Maritime Continent and anomalous anticyclone over South Indian Ocean. Most CMIP models simulate reasonable short wave radiation (SWR) and weaker latent heat flux (LHF) anomalies. This leads to a weak bias of atmospheric processes. During winter, however, the rainfall anomalies are stronger due to west bias, and the anomalous anticyclone is comparable to observations. As such, most models simulate stronger SWR and reasonable LHF anomalies, leading to a strong bias of atmospheric processes. The thermocline feedback is stronger in most models. Though there is a deep bias of climatology thermocline, most models capture reasonable sea surface height-induced SST anomalies. Therefore, the effect of oceanic processes offset the weak bias of atmospheric processes in spring, and the tropical Indian Ocean warming persists into summer. However, anomalous northwest Pacific (NWP) anticyclone is weaker due to weak and west bias of the capacitor effect. The unrealistic western Pacific SST anomalies in models favor the westward extension of Rossby wave from the Pacific, weakening the effect of Kelvin wave from the Indian Ocean. Moreover, the western Pacific warming forces the NWP anticyclone move farther north than observations, suggesting a major forcing from the Pacific. Compared to CMIP3, CMIP5 models simulate the feedbacks more realistically and display less diversity. Thus, the overall performance of CMIP5 models is better than that of CMIP3 models.  相似文献   

19.
我国西南地区秋季降水年际变化的空间差异及其成因   总被引:3,自引:0,他引:3  
刘扬  刘屹岷 《大气科学》2016,40(6):1215-1226
使用1980~2010年全国站点降水资料、ERA-Interim再分析环流资料、哈德莱海表温度资料,运用聚类分析和旋转经验正交函数分解,对西南地区的秋季降水按照其年际变化规律进行分区,进而分析影响各区域降水变化的物理过程和机理。结果表明:西南地区被分为东、西两个区域。西南东、西区域秋季降水的年际变化、显著周期、旱涝异常年份、相关的环流系统都有明显差异。西南东部秋季降水主要与热带海温异常有关,受低纬度环流影响。当赤道东太平洋为暖海温异常,热带印度洋为西正东负的偶极子型海温异常时,分别激发出西北太平洋反气旋和孟加拉反气旋,共同向西南东部输送水汽,造成西南东部降水偏多。西南西部降水在秋季三个月份与不同的环流形势对应:9月降水由中南半岛反气旋输送的暖湿气流决定;10月降水受高原以东反气旋环流和孟加拉湾低槽共同影响;11月降水主要受中高纬环流异常的影响,与斯堪的纳维亚遥相关存在显著负相关。  相似文献   

20.
Summary In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO’s influence on the interannual sea-surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSO’s influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3–5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin-wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east–west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.  相似文献   

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