Interdecadal modulation of the relationship between ENSO,IPO and precipitation: insights from tree rings in Australia     

Ingo Heinrich  Kathrin Weidner  Gerhard Helle  Heinz Vos  Janette Lindesay  John C. G. Banks 《Climate Dynamics》2009,33(1):63-73

Australian climate-proxy reconstructions based on tree rings from tropical and subtropical forests have not been achieved so far due to the rarity of species producing anatomically distinct annual growth rings. Our study identifies the Australian Red Cedar (Toona ciliata) as one of the most promising tree species for tree-ring research in Australasia because this species exhibits distinct annual tree rings, a prerequisite for high quality tropical dendroclimatology. Based on these preliminary studies, we were able, for the first time in subtropical and tropical Australia, to develop a statistically robust, precisely dated and annually resolved chronology back to AD1854. We show that the variability in ring widths of T. ciliata is mainly dependent on annual precipitation. The developed proxy data series contains both high- and low-frequency climate signals which can be associated with the El Niño Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO). A comparison of different data sets (Brisbane precipitation, tree rings, coral luminescence record from the Great Barrier Reef, ENSO and IPO) revealed non-stationary correlation patterns throughout the twentieth century but little instability between the new tree-ring chronology and Brisbane precipitation.  相似文献   

印度洋偶极子研究进展综述   总被引：10，自引：2，他引：8  

肖莺  张祖强  何金海 《热带气象学报》2009,25(5):621-627

印度洋偶极子（IOD）是影响亚洲气候异常的重要系统之一。自1999年IOD提出以来,国内外学者对其形成机理及其与ENSO相互作用的研究取得了很大进展。综述了近年来国内外学者关于印度洋偶极子的定义、时空分布特征、形成机理、与ENSO的关系、对东亚气候的影响等问题的研究成果,提出了目前该领域存在的科学问题。  相似文献   

石家庄春季自然物候对气候变化的响应研究   总被引：1，自引：0，他引：1  

车少静  赵世林 《山东气象》2009,29(1):1-5

分析了石家庄1965-2007年杨絮始落、鸭梨始花和刺槐盛花3种植物物候期的变化特征以及对气候的响应规律。结果表明：（1）石家庄春季物候期普遍提早,早春的物候期提前天数多,晚春物候期提早天数少。石家庄春季物候现象普遍存在着2～3年的周期。（2）通过计算石家庄春季物候与气温、日照和降水量的相关关系,发现与气温的关系最好,与降水日数表现出弱的相关性,与日照关系不明显,说明气温是影响石家座春季物候的主导气象因子,GDD是衡量植物热量供应的较好指标,而日照对物候期影响表现出不同物种和不同物候现象间的差异性特征。（3）石家庄春季物候期与ENSO事件也表现出一定的关系,在暖事件年以物候期偏早为主,在冷事件年无明显早晚趋势。  相似文献   

浅析台山50a降水变化及其与ENSO的关系     

甘晓英  张新甲  叶朗明 《气象研究与应用》2009,30(Z2)

通过分析台山1955～2004年的降水变化特征,研究台山年、季降水量和旱涝年的分布规律和趋势变化.发现50年来,台山年降水和夏季降水都有明显的上升趋势,秋季降水减少,秋旱频发.分析ENS0信号和台山四季降水的联系,结果表明暖事件发生时,春、夏、冬三季降水偏多,冷事件发生时降水偏少.秋季与冷暖事件的关系正好相反.夏季降水偏多与暖事件关系非常显著.  相似文献   

副热带北太平洋SST在ENSO冷暖位相转变中的作用     

韦圣标  陈昇  王鑫 《气候与环境研究》2018,23(4):453-462

2015/2016年发生的极端El Ni?o事件,与1997/1998年El Ni?o事件具有可比拟的强度,但是2016年事件转变为弱La Ni?a,而1998年事件则为强La Ni?a。本文通过对比这两次极端El Ni?o事件,揭示其转变为不同强度La Ni?a事件的物理机制。混合层热收支分析的结果表明,在El Ni?o衰减年的4~11月,2016年平流反馈和温跃层反馈相对较弱,混合层温度衰减速率慢,其产生的主要原因是赤道中西太平洋的东风异常较弱。进一步分析表明,赤道中西太平洋的东风异常与副热带东北太平洋的海表温度异常（SSTA）有关,该地区的SST在1998年表现为冷异常,2016年为暖异常。副热带东北太平洋冷的SSTA有利于信风加强,从而加强中西太平洋的东风异常;而暖的SSTA使得赤道以北出现西南风异常,从而削弱中西太平洋的东风异常。此外,合成分析也表明,副热带东北太平洋SSTA与转变的La Ni?a的强度具有关联,El Ni?o转变为强La Ni?a的情况在位相转变期伴随着副热带北太平洋冷的SSTA,而El Ni?o转变为弱La Ni?a的情况没有明显的冷SSTA。  相似文献   

Assessing the Influence of the ENSO on Tropical Cyclone Prevailing Tracks in the Western North Pacific   总被引：3，自引：0，他引：3  

ZHAO Haikun  WU Liguang  ZHOU Weican 《大气科学进展》2010,27(6):1361-1371

Using a statistical model for simulating tropical cyclone (TC) formation and a trajectory model for simulating TC tracks, the influence of the El Nino-Southern Oscillation (ENSO) on the peak-season (July-September) TC prevailing tracks in the western North Pacific basin is assessed based on 14 selected El Nino and 14 selected La Nina years during the period 1950-2007. It is found that the combination of statistical formation model and a trajectory model can simulate well the primary features of TC prevai...  相似文献   

南太平洋6—8月SST异常的主要模态及其与ENSO和SAM的联系   总被引：1，自引：0，他引：1  

孙密娜  ;管兆勇;张蓬勃 《热带气象学报》2010,26(2):174-180

利用1951—2006年NCEP/NCAR再分析资料,采用EOF分析方法提取了南太平洋6—8月SST异常变化的两个主要模态,结果表明:EOF1主要反映了ENSO信息,EOF2与南半球环状模(SAM)存在关联。EOF1以年际时间尺度变化为主,EOF2的周期接近于年代变化。EOF1的时间序列与同期Ni?o3指数存在显著相关,EOF2的时间序列与3—5月SAM指数存在显著相关。分析EOF1、EOF2与我国夏季降水的相关场,得出6—8月南太平洋SST出现西低东高型分布的年份我国华北地区夏季降水偏少,出现西高东低型分布的年份则降水偏多。3—5月出现中纬度和赤道东太平洋SST异常偏低,而赤道中太平洋SST异常偏高分布型的年份,我国江南地区夏季降水偏多;出现相反的分布型则降水偏少。  相似文献   

Prediction of the Asian-Australian Monsoon Interannual Variations with the Grid-Point Atmospheric Model of IAP LASG （GAMIL）   总被引：8，自引：2，他引：6  

吴志伟  李建平 《大气科学进展》2008,25(3):387-394

Seasonal prediction of Asian-Australian monsoon （A-AM） precipitation is one of the most important and challenging tasks in climate prediction. In this paper, we evaluate the performance of Grid Atmospheric Model of IAP LASG （GAMIL） on retrospective prediction of the A-AM interannual variation （IAV）, and determine to what extent GAMIL can capture the two major observed modes of A-AM rainfall IAV for the period 1979-2003. The first mode is associated with the turnabout of warming （cooling） in the Nifio 3.4 region, whereas the second mode leads the warming/cooling by about one year, signaling precursory conditions for ENSO.
We show that the GAMIL one-month lead prediction of the seasonal precipitation anomalies is primarily able to capture major features of the two observed leading modes of the IAV, with the first mode better predicted than the second. It also depicts the relationship between the first mode and ENSO rather well. On the other hand, the GAMIL has deficiencies in capturing the relationship between the second mode and ENSO. We conclude： （1） successful reproduction of the E1 Nifio-excited monsoon-ocean interaction and E1 Nifio forcing may be critical for the seasonal prediction of the A-AM rainfall IAV with the GAMIL; （2） more efforts are needed to improve the simulation not only in the Nifio 3.4 region but also in the joining area of Asia and the Indian-Pacific Ocean; （3） the selection of a one-tier system may improve the ultimate prediction of the A-AM rainfall IAV. These results offer some references for improvement of the GAMIL and associated seasonal prediction skill.  相似文献   

What Kind of Initial Errors Cause the Severest Prediction Uncertainty of El Nino in Zebiak-Cane Model     

XU Huiand DUAN Wansuo State Laboratory of Numerical Modeling for Atmospheric Sciences  Geophysical Fluid Dynamics 《大气科学进展》2008,(4)

With the Zebiak-Cane(ZC)model,the initial error that has the largest effect on ENSO prediction is explored by conditional nonlinear optimal perturbation(CNOP).The results demonstrate that CNOP-type errors cause the largest prediction error of ENSO in the ZC model.By analyzing the behavior of CNOP- type errors,we find that for the normal states and the relatively weak El Nino events in the ZC model,the predictions tend to yield false alarms due to the uncertainties caused by CNOP.For the relatively strong El Nino events,the ZC model largely underestimates their intensities.Also,our results suggest that the error growth of El Nino in the ZC model depends on the phases of both the annual cycle and ENSO.The condition during northern spring and summer is most favorable for the error growth.The ENSO prediction bestriding these two seasons may be the most diffcult.A linear singular vector(LSV)approach is also used to estimate the error growth of ENSO,but it underestimates the prediction uncertainties of ENSO in the ZC model.This result indicates that the different initial errors cause different amplitudes of prediction errors though they have same magnitudes.CNOP yields the severest prediction uncertainty.That is to say,the prediction skill of ENSO is closely related to the types of initial error.This finding illustrates a theoretical basis of data assimilation.It is expected that a data assimilation method can filter the initial errors related to CNOP and improve the ENSO forecast skill.  相似文献   

Current status of ENSO prediction skill in coupled ocean–atmosphere models     

Emilia K. Jin  James L. Kinter III  B. Wang  C.-K. Park  I.-S. Kang  B. P. Kirtman  J.-S. Kug  A. Kumar  J.-J. Luo  J. Schemm  J. Shukla  T. Yamagata 《Climate Dynamics》2008,31(6):647-664

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.  相似文献