Possible influence of western North Pacific monsoon on TC activity in mid-latitudes of East Asia

The interannual variation of East Asia summer monsoon (EASM) rainfall exhibits considerable differences between early summer [May–June (MJ)] and peak summer [July–August (JA)]. The present study focuses on peak summer. During JA, the mean ridge line of the western Pacific subtropical High (WPSH) divides EASM domain into two sub-domains: the tropical EA (5°N–26.5°N) and subtropical-extratropical EA (26.5°N–50°N). Since the major variability patterns in the two sub-domains and their origins are substantially different, the Part I of this study concentrates on the tropical EA or Southeast Asia (SEA). We apply the predictable mode analysis approach to explore the predictability and prediction of the SEA peak summer rainfall. Four principal modes of interannual rainfall variability during 1979–2013 are identified by EOF analysis: (1) the WPSH-dipole sea surface temperature (SST) feedback mode in the Northern Indo-western Pacific warm pool associated with the decay of eastern Pacific El Niño/Southern Oscillation (ENSO), (2) the central Pacific-ENSO mode, (3) the Maritime continent SST-Australian High coupled mode, which is sustained by a positive feedback between anomalous Australian high and sea surface temperature anomalies (SSTA) over Indian Ocean, and (4) the ENSO developing mode. Based on understanding of the sources of the predictability for each mode, a set of physics-based empirical (P-E) models is established for prediction of the first four leading principal components (PCs). All predictors are selected from either persistent atmospheric lower boundary anomalies from March to June or the tendency from spring to early summer. We show that these four modes can be predicted reasonably well by the P-E models, thus they are identified as the predictable modes. Using the predicted PCs and the corresponding observed spatial patterns, we have made a 35-year cross-validated hindcast, setting up a bench mark for dynamic models’ predictions. The P-E hindcast prediction skill represented by domain-averaged temporal correlation coefficient is 0.44, which is twice higher than the skill of the current dynamical hindcast, suggesting that the dynamical models have large rooms to improve. The maximum potential attainable prediction skills for the peak summer SEA rainfall is also estimated and discussed by using the PMA. High predictability regions are found over several climatological rainfall centers like Indo-China peninsula, southern coast of China, southeastern SCS, and Philippine Sea.     

Dominant Modes of Interannual Variability in Atmospheric Water Vapor Content over East Asia during Winter and Their Associated Mechanisms

Atmospheric water vapor content(WVC) is a critical factor for East Asian winter precipitation. This study investigates the dominant modes of interannual variability in WVC over East Asia during winter and their underlying mechanisms.Based on the empirical orthogonal function(EOF) method, the leading mode(EOF1, R~2 = 28.9%) of the interannual variability in the East Asian winter WVC exhibits a meridional dipole pattern characterized by opposite WVC anomalies over northeastern China and eastern China; the second mode(EOF2, R~2 = 24.3%) of the interannual variability in the East Asian winter WVC exhibits a monopole pattern characterized by consistent WVC anomalies over eastern China. EOF1 is mainly modulated by two anomalous zonal water vapor transport(WVT) branches over northeastern China and eastern China, which are associated with an anomalous atmospheric wave train over Eurasia affected by sea ice cover in the Kara Sea-Barents Sea(SIC-KSBS) area in the preceding October-November(ON). EOF2 is mainly modulated by an anomalous westerly WVT branch over eastern China, which is associated with a circumglobal atmospheric zonal wave train in the Northern Hemisphere. This circumglobal zonal wave train is modulated by concurrent central and eastern tropical Pacific sea surface temperature anomalies. The SIC-KSBS anomalies in ON and the concurrent SST anomalies over tropical Pacific may partially account for the interannual variability of EOF1 and EOF2 winter WVC, and thus may provide a theoretical basis for improving the prediction of winter climate over East Asia.     

A STATISTICAL PREDICTION MODEL FOR SPRING RAINFALL OVER NORTHERN CHINA BASED ON THE INTERANNUAL INCREMENT APPROACH

The spring (March-April-May) rainfall over northern China (SPRNC) is predicted by using the interannual increment approach. DY denotes the difference between the current year and previous years. The seasonal forecast model for the DY of SPRNC is constructed based on the data that are taken from the 1965-2002 period (38 years), in which six predictors are available no later than the current month of February. This is favorable so that the seasonal forecasts can be made one month ahead. Then, SPRNC and the percentage anomaly of SPRNC are obtained by the predicted DY of SPRNC. The model performs well in the prediction of the inter-annual variation of the DY of SPRNC during 1965-2002, with a correlation coefficient between the predicted and observed DY of SPRNC of 0.87. This accounts for 76% of the total variance, with a low value for the average root mean square error (RMSE) of 20%. Both the results of the hindcast for the period of 2003-2010 (eight years) and the cross-validation test for the period of 1965-2009 (45 years) illustrate the good prediction capability of the model, with a small mean relative error of 10%, an RMSE of 17% and a high rate of coherence of 87.5% for the hindcasts of the percentage anomaly of SPRNC.     

Improve the prediction of summer precipitation in the Southeastern China by a hybrid statistical downscaling model

We attempt to apply year-to-year increment prediction to develop an effective statistical downscaling scheme for summer (JJA, June–July–August) rainfall prediction at the station-to-station scale in Southeastern China (SEC). The year-to-year increment in a variable was defined as the difference between the current year and the previous year. This difference is related to the quasi-biennial oscillation in interannual variations in precipitation. Three predictors from observations and six from three general circulation models (GCMs) outputs of the development of a European multi-model ensemble system for seasonal to interannual prediction (DEMETER) project were used to establish this downscaling model. The independent sample test and the cross-validation test show that the downscaling scheme yields better predicted skill for summer precipitation at most stations over SEC than the original DEMETER GCM outputs, with greater temporal correlation coefficients and spatial anomaly correlation coefficients, as well as lower root-mean-square errors.     

基于年际增量方法的云南省普洱雨季开始期气候预测

基于普洱雨季开始期年际增量变化规律和影响雨季开始期的环流形势及物理过程,采用年际增量方法和多元线性回归分析方法,选取5个具有物理意义的预测因子(包括前期1月南半球绕极环流、前期2月南太平洋高压、前期4月孟加拉湾至南海海平面气压、前期冬季加拿大北部海冰和前期冬季伊朗高原积雪深度),建立了普洱雨季开始期的预测模型,并对预测模型进行1967—2017年的交叉检验和1998—2017年的逐年独立样本检验。交叉检验中,雨季开始期预测值和观测值年际增量的相关系数为0.84,相对均方根误差为24%;独立样本检验中,雨季开始期年际增量的相对均方根误差为15%,模型对雨季开始期异常年份的预测误差小于7 d,表明该预测模型能很好再现1967—2017年雨季开始期的变化趋势。     

How predictable is the northern hemisphere summer upper-tropospheric circulation?

The retrospective forecast skill of three coupled climate models (NCEP CFS, GFDL CM2.1, and CAWCR POAMA 1.5) and their multi-model ensemble (MME) is evaluated, focusing on the Northern Hemisphere (NH) summer upper-tropospheric circulation along with surface temperature and precipitation for the 25-year period of 1981–2005. The seasonal prediction skill for the NH 200-hPa geopotential height basically comes from the coupled models’ ability in predicting the first two empirical orthogonal function (EOF) modes of interannual variability, because the models cannot replicate the residual higher modes. The first two leading EOF modes of the summer 200-hPa circulation account for about 84% (35.4%) of the total variability over the NH tropics (extratropics) and offer a hint of realizable potential predictability. The MME is able to predict both spatial and temporal characteristics of the first EOF mode (EOF1) even at a 5-month lead (January initial condition) with a pattern correlation coefficient (PCC) skill of 0.96 and a temporal correlation coefficient (TCC) skill of 0.62. This long-lead predictability of the EOF1 comes mainly from the prolonged impacts of El Niño-Southern Oscillation (ENSO) as the EOF1 tends to occur during the summer after the mature phase of ENSO. The second EOF mode (EOF2), on the other hand, is related to the developing ENSO and also the interdecadal variability of the sea surface temperature over the North Pacific and North Atlantic Ocean. The MME also captures the EOF2 at a 5-month lead with a PCC skill of 0.87 and a TCC skill of 0.67, but these skills are mainly obtained from the zonally symmetric component of the EOF2, not the prominent wavelike structure, the so-called circumglobal teleconnection (CGT) pattern. In both observation and the 1-month lead MME prediction, the first two leading modes are accompanied by significant rainfall and surface air temperature anomalies in the continental regions of the NH extratropics. The MME’s success in predicting the EOF1 (EOF2) is likely to lead to a better prediction of JJA precipitation anomalies over East Asia and the North Pacific (central and southern Europe and western North America).     

长江流域年降水预测动力-统计降尺度方法及其应用

基于站点资料、再分析数据和动力气候模式回报数据,利用经验正交函数分解（EOF,Empirical Orthogonal Function）迭代和年际增量方法,探讨了长江流域年尺度降水异常的动力-统计降尺度预测方法及其应用效果。结果表明,基于再分析数据的年尺度环流场,建立的长江流域年尺度降水异常增量的统计降尺度预测方案,其26 a回报检验的距平相关系数（ACC）平均达0.6,证明该方案具有较高的可预报性。进一步利用模式预测的年尺度环流场,建立了年降水异常增量的动力-统计降尺度预测方案,其ACC平均为0.42,显示了较高的回报技巧,远优于模式直接输出的年降水动力预报结果。通过分析调制年降水预报技巧高低的因素发现,赤道中东太平洋年平均海温距平为负值时,预报技巧更高,ACC平均达0.5以上。在拉尼娜发展年或拉尼娜持续年的冷水背景下,利用EOF迭代选取的特征向量偏多时,多尺度的大气环流信息被纳入预测模型中作为预测信号,预测技巧得到了提高。     

Predictability of the East Asian winter monsoon interannual variability as indicated by the DEMETER CGCMS

The interannual variability of East Asian winter monsoon(EAWM) circulation from the Development of a European Multi-Model Ensemble(MME) System for Seasonal to Inter-Annual Prediction(DEMETER) hindcasts was evaluated against observation reanalysis data.We evaluated the DEMETER coupled general circulation models(CGCMs)’ retrospective prediction of the typical EAWM and its associated atmospheric circulation.Results show that the EAWM can be reasonably predicted with statistically significant accuracy,yet the major bias of the hindcast models is the underestimation of the related anomalies.The temporal correlation coefficient(TCC) of the MME-produced EAWM index,defined as the first EOF mode of 850hPa air temperature within the EAWM domain(20-60 N,90-150 E),was 0.595.This coefficient was higher than those of the corresponding individual models(range:0.39-0.51) for the period 1969-2001;this result indicates the advantage of the super-ensemble approach.This study also showed that the ensemble models can reasonably reproduce the major modes and their interannual variabilities for sea level pressure,geopotential height,surface air temperature,and wind fields in Eurasia.Therefore,the prediction of EAWM interannual variability is feasible using multimodel ensemble systems and that they may also reveal the associated mechanisms of the EAWM interannual variability.     

北极海冰及其与气象要素年际关系的年代际变化

利用Hadley海冰密集度资料和NCEP/NCAR再分析资料,分析了北极海冰融冰量及其与大气变量年际关系的年代际变化。结果表明,北极海冰存在显著的年代际变化,且有较强的区域性。东西伯利亚海和波弗特海海冰融冰量的平均值变大且方差增大,格陵兰岛以东洋面海冰融冰量的量值和变率均在减弱。对3个不同气候时段内北极海冰融冰量进行EOF分解,前两个模态均在3个气候时段发生显著的年代际变化,东西伯利亚海海冰融冰量的增加与EOF第一模态年代际变化相关,而EOF第二模态则明显造成了波弗特海海冰的年代际消融。并且,与之相应的大气环流也出现了明显的年代际变化,它们与AO/NAO的年际关系也存在年代际转折,融冰量第二模态与AO的年际关系更为紧密,1960—1990年第二模态与AO的相关系数仅为0.186,而1980—2010年相关系数已升高至0.367。整个北冰洋的海冰融冰量与AO的年际关系也出现了年代际增强,尤其是东西伯利亚地区海冰融冰量与AO的年际关系发生了年代际增强,1980—2010年两者相关达到了0.4以上。而波弗特海融冰量与AO相关系数变化较大,1960—1990年其的相关系数高达-0.488,1980年后却减少至0.161。然而AO却未发生明显的年代际变化。造成北极海冰融冰量及其与大气变量年际关系发生年代际变化的主要因子之一是波弗特高压,其年代际减弱使得极区向东西伯利亚海和波弗特海的海冰输送减弱,导致这两个区域海冰减少,使得AO与北极海冰的年际关系发生了年代际转折。     

基于BCC_CSM模式的中国东部夏季降水预测检验及订正

基于国家气候中心第二代季节预测模式的历史回报试验数据,检验了模式对我国东部夏季降水的预测能力,探讨了预测误差形成的可能原因,并应用降尺度方法提高了模式的降水预测技巧。分析表明:（1）模式能在一定程度上把握我国东部夏季降水时空变率的两个主要模态（偶极子型模态和全区一致型模态）,但是不同超前时间的预测在刻画模态方差贡献、异常空间分布特征、时间系数的年际变化等方面存在明显误差;（2）模式能够合理预测大尺度环流和海表温度（SST）的变化特征,但是对中国东部夏季降水的总体预测技巧有限,这与模式不能准确刻画西太平洋副热带高压、大陆高压、中高纬阻塞高压等环流系统以及热带太平洋、印度洋SST变率对中国东部降水模态的影响有关;（3）针对1991~2003年回报试验数据中的500 hPa位势高度、850 hPa纬向风和经向风、SST变量,在全球范围内寻找并定位与中国东部站点降水关系最密切的预报因子,进而建立针对降水预测的单因子线性回归、多因子逐步和多元回归模型。采用2004~2013年回报试验对所建立的降水预测模型进行了独立检验,结果表明:所建立的降尺度预测模型能显著提高中国东部地区夏季降水的预报技巧。以6月1日起报试验为例,预测的第一模态（第二模态）与观测的空间相关系数由原始的0.12（0.48）提高到了0.58（0.80）,时间相关系数则从0.47（0.15）提高到0.80（0.67）;其它超前时间的预测试验中,降尺度预测模型的降水预测技巧相比模式原始预测技巧也同样明显提高。     

中高纬度地区500 hPa高度场动力预测统计订正

利用DEMETER多模式集合研究计划中Météo France模式的预报资料集,在分析其对冬季北半球中高纬度地区 (20°~90°N)500 hPa高度场预报效果的基础上,针对模式预测较差的模态分别运用最优子集回归修正方案和回归-相似相结合的修正方案对其进行订正。结果表明:数值模式对观测模态的预测能力并非随模态数的增加而递减,方差贡献较小的模态的预报效果可能好于方差贡献较大的模态;基于最优子集的回归订正方法未能改进原模式预报技巧;在最优子集回归基础上再经相似订正的方法 (DAP-OSR) 能够改进预测效果,独立试报的距平相关系数平均每年提高0.1。     

秋季喀拉海海冰对2020和2021年12月京津冀冷暖反相的影响

2020/2021和2021/2022年冬季京津冀气温呈明显相反的季节内变化特征,前者前冬气温异常偏低后冬偏高,而后者前冬气温极端偏高后冬转冷。这两年前冬冷暖反相的直接原因是亚洲冬季风环流异常。2020年12月欧亚地区为典型的经向环流,西伯利亚高压偏强,乌拉尔山高压脊亦偏强,造成京津冀上空对流层中低层气温一致性偏低,而2021年12月环流形势相反。这两年冬季均处在拉尼娜背景下,但夏秋季喀拉海海冰异常有明显差异,可能是京津冀这两年前冬气温异常相反潜在的外强迫信号。统计和个例分析结果均表明,喀拉海海冰偏多易导致前冬西伯利亚高压偏弱,青藏高原地区海平面气压和亚洲大陆中纬度地区500 hPa位势高度均为正距平,不利于冷空气活动,造成2021/2022年前冬京津冀气温偏高,反之海冰偏少造成2020/2021年前冬偏冷。     

西北偏湿背景下青海省夏季降水的统计降尺度方法研究

本文研制建立了一个预测青海省夏季降水的动力—统计相结合的组合降尺度预测方法（Hybrid Statistical Downscaling Prediction，HSDP），该方法综合利用了气候模式Climate Forecast System 2.0版本（CFSv2）实时预测的高可预报性环流信息及前期观测的与青海夏季降水具有高相关性的气候因子，采用年际增量方法，基于气候变量的年际增量规律建立统计模型，从而实现对青海夏季降水进行动力—统计相结合的气候预测。根据全球气候因子的年际增量与青海省夏季降水年际增量的相关系数，以及CFSv2预测产品对实况模拟能力的评估，选取以下关键区气候变量的年际增量作为预测因子：（1） CFSv2模式预测当年夏季包含贝加尔湖脊、乌拉尔山脊和新疆脊区域的500 hPa高度场；（2） CFSv2模式预测青藏高原以西200 hPa纬向风场；（3）观测资料中前1 a秋、冬季热带太平洋地区海表面温度场；（4）观测资料中前1 a秋、冬季西伯利亚地区的海平面气压场，对青海省夏季降水进行统计降尺度预测。统计降尺度模型利用1983—2011年进行建模，回报2012—2018年夏季青海省降水的空间分布和时间变化，并对该模型对1983—2011年的夏季青海省降水的回报能力进行了交叉检验。回报结果表明该统计降尺度模型对CFSv2的青海省夏季降水预测能力有显著的提高，能够很好地再现青海省夏季降水西北部的高原地区偏少，而在东南部偏多的特点。该模型预测所得2012—2018年夏季青海省降水的时间变化也与实况有着较高的相关系数（0.76），对于降水显著偏少的年份（如2015年）和显著偏多的年份（如2012、2018年）的降水预测都有很好的表现。对于建模时段的交叉检验结果（相关系数为0.46，比模型回报结果与实况的相关系数0.48略低）表明，该模型具有较高的稳定性和可靠性。     

Interannual variations of the boreal summer intraseasonal variability predicted by ten atmosphere–ocean coupled models

The reproducibility of boreal summer intraseasonal variability (ISV) and its interannual variation by dynamical models are assessed through diagnosing 21-year retrospective forecasts from ten state-of-the-art ocean–atmosphere coupled prediction models. To facilitate the assessment, we have defined the strength of ISV activity by the standard deviation of 20–90 days filtered precipitation during the boreal summer of each year. The observed climatological ISV activity exhibits its largest values over the western North Pacific and Indian monsoon regions. The notable interannual variation of ISV activity is found primarily over the western North Pacific in observation while most models have the largest variability over the central tropical Pacific and exhibit a wide range of variability in spatial patterns that are different from observation. Although the models have large systematic biases in spatial pattern of dominant variability, the leading EOF modes of the ISV activity in the models are closely linked to the models’ El Nino-Southern Oscillation (ENSO), which is a feature that resembles the observed ISV and ENSO relationship. The ENSO-induced easterly vertical shear anomalies in the western and central tropical Pacific, where the summer mean vertical wind shear is weak, result in ENSO-related changes of ISV activity in both observation and models. It is found that the principal components of the predicted dominant modes of ISV activity fluctuate in a very similar way with observed ones. The model biases in the dominant modes are systematic and related to the external SST forcing. Thus the statistical correction method of this study based on singular value decomposition is capable of removing a large portion of the systematic errors in the predicted spatial patterns. The 21-year-averaged pattern correlation skill increases from 0.25 to 0.65 over the entire Asian monsoon region after applying the bias correction method to the multi-model ensemble mean prediction.     

年际增量方法在西南夏季降水预测中的应用

利用中国西南地区80站逐月降水资料及NCEP/NCAR再分析资料等,采用降水预测新方法——年际增量法,考察影响中国西南地区夏季降水年际增量的前期冬、春季大气环流年际增量状况,并选取5个关键影响因子,采用多元回归法建立中国西南夏季降水年际增量预测模型。对降水年际增量进行预测,在1971—2010年的建模阶段,预测模型的拟合率为0.78,在2011—2017的后报检验7年中,有6年与实况值同位相。后报检验2011—2017年的降水距平百分率,均方根误差为16%。为考察对降水异常分布型的预报效果,逐站建立回归方程,并进行趋势预报检验,近5年的趋势异常综合评分高于发布预测,预报效果较好。因此,该方法的应用及模型的建立对提高西南地区夏季降水预测水平有重要意义。      

NCEP/NCAR再分析资料所揭示的全球季风降水变化

大气模式是研究气候变化的重要工具,当前的大气模式在模拟季风降水时均存在较大偏差,目前尚不清楚该偏差是来自模式环流场还是模式物理过程.再分析资料由于同化了各类观测和卫星资料,其大气环流近似可被视作是“真实”的.再分析资料中的降水场是在基本真实的环流场强迫下,由当前最先进的数值预报模式计算输出的.因此,再分析资料的降水场能...     

我国秋季降水的年际变化及与热带太平洋海温异常分布的关系

利用我国160个站点58年(1951～2008年)的降水资料、NCEP/NCAR再分析环流资料和Hadley海表温度资料,对我国秋季降水年际变化的特征和可能成因进行了分析。结果显示,秋季降水前两模态分别反映长江流域及以南地区和长江以北的江淮、黄淮、华北、四川盆地北部至河套等地降水的变化,两降水模态的变化都以年际尺度为主,年代际变化特征不明显。就环流形势而言,第一模态的年际变化主要与西太平洋副热带高压的强度及相应的对流层低层菲律宾群岛附近的异常气旋/反气旋联系紧密,第二模态的年际变化则可能受到副热带高压的南北位置和相应的日本岛附近的异常气旋/反气旋的影响。同时,两模态及相应的异常环流还分别与热带东印度洋和热带西太平洋附近的异常垂直运动关系密切,热带地区的异常垂直运动可能通过经圈方向的异常环流影响到东亚地区。此外,两降水模态不仅与热带地区的异常环流关系密切,而且与热带海温异常也存在紧密的联系。与两模态相关联的热带太平洋海温异常显示出不同的分布特征,当热带东太平洋偏暖/冷,西太平洋偏冷/暖时,长江以南地区降水偏多/少。而当热带东太平洋和中太平洋一致偏暖/冷时,长江以北地区降水易偏少/多。两降水模态与热带海温及热带地区异常环流之间的密切关系显示热带太平洋海温异常的不同分布可能通过激发不同的热带地区异常垂直环流形势而对降水产生影响。     

Predictability of the western North Pacific summer climate demonstrated by the coupled models of ENSEMBLES

The Asian monsoon system, including the western North Pacific (WNP), East Asian, and Indian monsoons, dominates the climate of the Asia-Indian Ocean-Pacific region, and plays a significant role in the global hydrological and energy cycles. The prediction of monsoons and associated climate features is a major challenge in seasonal time scale climate forecast. In this study, a comprehensive assessment of the interannual predictability of the WNP summer climate has been performed using the 1-month lead retrospective forecasts (hindcasts) of five state-of-the-art coupled models from ENSEMBLES for the period of 1960–2005. Spatial distribution of the temporal correlation coefficients shows that the interannual variation of precipitation is well predicted around the Maritime Continent and east of the Philippines. The high skills for the lower-tropospheric circulation and sea surface temperature (SST) spread over almost the whole WNP. These results indicate that the models in general successfully predict the interannual variation of the WNP summer climate. Two typical indices, the WNP summer precipitation index and the WNP lower-tropospheric circulation index (WNPMI), have been used to quantify the forecast skill. The correlation coefficient between five models’ multi-model ensemble (MME) mean prediction and observations for the WNP summer precipitation index reaches 0.66 during 1979–2005 while it is 0.68 for the WNPMI during 1960–2005. The WNPMI-regressed anomalies of lower-tropospheric winds, SSTs and precipitation are similar between observations and MME. Further analysis suggests that prediction reliability of the WNP summer climate mainly arises from the atmosphere–ocean interaction over the tropical Indian and the tropical Pacific Ocean, implying that continuing improvement in the representation of the air–sea interaction over these regions in CGCMs is a key for long-lead seasonal forecast over the WNP and East Asia. On the other hand, the prediction of the WNP summer climate anomalies exhibits a remarkable spread resulted from uncertainty in initial conditions. The summer anomalies related to the prediction spread, including the lower-tropospheric circulation, SST and precipitation anomalies, show a Pacific-Japan or East Asia-Pacific pattern in the meridional direction over the WNP. Our further investigations suggest that the WNPMI prediction spread arises mainly from the internal dynamics in air–sea interaction over the WNP and Indian Ocean, since the local relationships among the anomalous SST, circulation, and precipitation associated with the spread are similar to those associated with the interannual variation of the WNPMI in both observations and MME. However, the magnitudes of these anomalies related to the spread are weaker, ranging from one third to a half of those anomalies associated with the interannual variation of the WNPMI in MME over the tropical Indian Ocean and subtropical WNP. These results further support that the improvement in the representation of the air–sea interaction over the tropical Indian Ocean and subtropical WNP in CGCMs is a key for reducing the prediction spread and for improving the long-lead seasonal forecast over the WNP and East Asia.     

近50 a全球和三大洋海温距平的时空变化特征

利用49a(1950-1998年)NCEP/NCAR逐月SSTA资料和EOF方法,分别对太平洋、大西洋、印度洋和全球海洋SSTA主要特征向量的空间分布和相应的时间变化进行了讨论。利用Morlet小波进一步分析了要素场的周期变化和能量变化。发现经EOF分解后的SSTA场具有很好的空间整体性和明显的年际和年代际变化。各大洋海温变化存在明显的同期和时滞相关关系,很好地体现了大洋间的协同作用和太平洋的主导作用。从不同的空间分布模态中选择海温变化显著的区域作为关键区,进行同期和时滞相关分析,结果发现各关键区之间具有明显的同期和时滞相关关系。     

太平洋年代际振荡的年代际预测方法

太平洋年代际振荡（PDO）是北太平洋海表温度年代际变率的主模态。由于太平洋年代际振荡对区域乃至全球气候的显著影响,其合理的预测结果可以带来多方面收益。然而,针对太平洋年代际振荡及其有关的海表温度的年代际预测,目前气候模式的预测水平还十分有限,因此,提出了一个新的增量方法。一系列的验证结果表明,增量方法可以有效预测太平洋年代际振荡,其中包括成功预测出其振荡的年代际转折。增量方法的预测过程主要包括3个步骤:（1）采用5 a滑动平均得到太平洋年代际振荡的年代际变率;（2）利用3 a增量形式的预测因子构建预测模型,预测3 a增量的太平洋年代际振荡（DI_PDO）;（3）将预测得到的DI_PDO加上3 a前的观测PDO,得到最后预测的PDO。增量方法亦可以应用到气候系统年代际内部变率的其他模态（如:北大西洋年代际振荡）和其他气候变量的年代际预测（如:海表温度）。