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1.
热带大气季节内振荡 (Madden-Julian oscillation,MJO) 是次季节-季节时间尺度气候变率的支配模态。它不仅对低纬度地区天气气候产生重要影响,还能够通过经向传播和激发大气遥相关波列对中高纬度地区产生影响,是延伸期尺度最重要的可预报性来源。因此,MJO预报是次季节-季节气候预测中极为重要的部分,近年来受到国际学术界广泛关注。该文回顾了MJO预报发展历史,概述了当前国际上主要科研业务机构的MJO预报发展现状。目前基于统计方法和气候模式的MJO预报研究取得了较大进展,特别是多个耦合气候模式和一种基于时空投影方法的统计模型均能够显著提升MJO预报技巧 (有效预报可达20 d以上)。该文还介绍了中国气象局国家气候中心在MJO预报技术发展和业务系统研制方面的新进展,当前基于第2代大气环流模式的MJO业务预报填补了国内空白,技巧为16~17 d,而耦合气候模式试验的技巧已达到约20 d。总体来看,利用耦合模式预报MJO是未来发展的主要方向,其中,面向MJO的模式初始化和集合预报新方法研究将是关注重点。 相似文献
2.
《大气和海洋科学快报》2016,(1)
热带大气季节内振荡(MJO)预报是国际研究热点,我国尚处于起步阶段。近些年国际上MJO预报水平得到大幅提升,主要得益于包含海气耦合过程的气候模式的使用,这其中模式预报初始化和集合扰动生成方法至关重要。本文发展了适用于国家气候中心第二代气候预测业务模式BCC-CSM1.1(m)的MJO初始化方案,并在此基础上提出了基于不同初始化方案形成扰动的集合预报新方法,可以将MJO有技巧预报时效延长到约20天,为次季节-季节预报提供重要依据。 相似文献
3.
经过近60年的发展,我国短期气候预测技术和方法也有了长足进步。近年来,一些新的预报技术和机理认识不断应用于短期气候预测业务。ARGO海洋观测资料的使用大大提高了业务模式的预测技巧,新一代气候预测模式系统已经投入准业务化运行,研发了多种模式降尺度释用技术,多模式气候预测产品解释应用集成系统(MODES)和动力-统计结合的季节预测系统(FODAS)逐渐应用于业务中,大气季节内振荡(MJO)逐步在延伸期预报中得到应用。近年来,对全球海洋、北极海冰、欧亚积雪、南半球环流系统对东亚季风影响的新认识也不断引入到短期气候预测业务中。这些新技术和新认识的应用极大提高了我国短期气候预测的业务能力。 相似文献
4.
大气季节内振荡在华南降水预报中的应用 总被引：1，自引：0，他引：1
大气季节内振荡(ISO)在天气气候演变中扮演着重要角色,是中期和延伸期预报可预报性来源之一,同时大气ISO的年际变化与区域季节降水量的年际变化密切联系,对短期气候预测有指示意义。对热带大气ISO的年际变化研究做了简要回顾;重点介绍了ISO对华南降水的影响及其业务应用情况,主要包括赤道MJO对华南降水的影响、基于准两周振荡的汛期暴雨过程预报、热带ISO与热带外系统多尺度相互作用对强降水的影响、ISO对季节降水的影响、基于ISO建立的降水延伸期定量预测模型;最后对进一步加强ISO应用研究提出了几点思考。 相似文献
5.
中国热带大气季节内振荡研究进展 总被引：7，自引：1，他引：6
热带大气季节内振荡(包括MJO)是大气环流的重要系统,它的活动及异常既对其他系统有一定的作用,也对长期天气和短期气候有明显影响。因此,热带大气季节内振荡一直是大气科学的前沿研究课题之一。文中对近5—10年中国学者的有关研究工作及其进展做了简要回顾和综合,主要包括:(1)热带大气季节内振荡特别是MJO的动力学机制;(2)热带大气季节内振荡以及MJO的数值模拟问题,特别是大气非绝热加热廓线对模式模拟MJO的重要作用;(3)热带大气季节内振荡和MJO,特别是在赤道西太平洋地区,与ENSO的相互作用关系;(4)热带大气季节内振荡(包括MJO)及其流场形势对西太平洋台风活动的重要影响,即MJO对西北太平洋台风生成数的调制作用,以及热带大气季节内低频气旋性(LFC)和反气旋性(LFAC)流场对西太平洋台风路径的影响;(5)热带大气季节内振荡(包括MJO)的活动及异常对东亚和南亚夏季风建立、活动异常的影响,以及它们与中国降水异常的密切关系。 相似文献
6.
利用次季节—季节预报研究计划(Subseasonal to Seasonal Prediction Project, S2S)的多模式产品集,系统评估了产品集中11个模式对MJO的实际预报技巧。如果以距平相关系数ACC为0.5作为有效预报技巧的阈值,S2S各模式的MJO实际预报时效为8～32 d。S2S各模式预报普遍低估了MJO的振幅强度,且预报的MJO传播速度偏慢。通过分析发现,在一个集合预报系统中,集合离散度与均方根误差越接近,它的MJO预报技巧越高。此外,分析S2S各模式MJO预报技巧对起报时间、季节和起报时MJO信号强弱的敏感性发现,当起报时间为冬季且起报时MJO为强信号时,MJO的实际预报技巧较高。 相似文献
7.
采用1982—2009年美国国家海洋与大气管理局(National Oceanic and Atmospheric Administration,NOAA)逐日向外长波辐射(outgoing longwave radiation,OLR)资料,利用EOF方法,分析了20～70 d北半球夏季(6—9月)季节内振荡(boreal summer intraseasonal oscillation,BSISO)与冬季(12月—次年2月)季节内振荡(也称Madden-Julian Oscillation,MJO)不同的强度趋势。结果表明:BSISO指数有明显加强的趋势,而MJO指数的趋势则不明显。进一步利用频率—波数分析方法将季节内振荡(intraseasonal oscillation,ISO)分成西传和东传两部分。结果表明:东传的BSISO在其活动中心——热带印度洋地区有显著加强的趋势,而东传的MJO在其活动中心的趋势则不明显,仅在其活动中心西南部即热带印度洋西南部有减弱的趋势。为探究其原因,文章进一步分析了海表温度(sea surface temperature,SST)和纬向风垂直切变的趋势变化。结果表明:1982—2009年,西太平洋和印度洋SST无论冬夏均持续增暖,SST并不能解释冬夏两季ISO不同的趋势特征;而夏季热带印度洋地区对流层中低层东风垂直切变减弱,冬季海洋性大陆地区东风垂直切变增强。由此认为:热带印度洋东风垂直切变减弱有可能有利于东传的BSISO加强;而海洋性大陆地区东风垂直切变加强有可能削弱东传的MJO,但这种减弱效应被冬季海洋性大陆地区增强的上升运动产生的加强效应抵消,所以MJO的变化趋势并不显著。 相似文献
8.
基于MJO的延伸预报 总被引：30，自引：3，他引：27
近10年来,2～4周的延伸预报成为天气和气候业务预报发展的一个方向。目前比较有效的方法是根据季节内振荡的传播,尤其是MJO振荡(30～60天周期)的传播来制作延伸期预报。国际上一些天气-气候预报中通过数年的业务试验已取得了初步结果。作者首先介绍了MJO振荡及季风的季节内振荡(MISO)特征,并从季节内振荡与中纬度相互作用的角度讨论了制作延伸预报的理论依据;进一步对延伸预报的可预报性、预报方法及国内外业务应用进展进行了综述,并以江淮梅雨为例探讨了我国延伸预报的可预报性及信号;最后阐述了延伸预报的发展趋势。 相似文献
9.
采用奇异谱分析(SSA)与自回归向量(AR)预报模型相结合的方法,对热带地区大气季节内振荡(MJO)指数向量作自适应滤波意义下的预报试验。结果表明,通过对MJO原始序列进行SSA的分解重建,无论采用对重建的分量序列进行AR(P)建模的方案,还是利用对重建合成序列进行AR(P)建模的方案,均可得到两周以上的MJO指数预报能力,其提前20天指数预报值与实况之间平均相关系数达到0.5,与直接对MJO原始序列进行AR建模相比较,该方法有较高的预报技巧和超前预报能力,预报效果也较稳定,故将SSA-AR方案进一步完善,可望作为MJO指数业务预报的有效模型。 相似文献
10.
本文采用1981～2010年夏季5～10月逐日的（10°S～50°N,40°E～160°E）范围内向外长波辐射OLR（Outgoing Longwave Radiation）资料和850 hPa层纬向风速资料（简称U850）作经验EOF（Empirical Orthogonal Function）分解,重新计算北半球夏季大气低频振荡BSISO（Boreal Summer Intraseasonal Oscillation）指数,并分析了其演变特征及其对华北夏季降水的影响规律。结果表明:（1）在北半球夏季印度洋—西北太平洋地区存在两种明显的低频信号,一种是BSISO1,空间分布呈西北—东南倾斜状,从热带印度洋向东北方向传播,振荡周期约为45 d;另一种是BSISO2,空间分布呈西南—东北倾斜状,从西北太平洋向西北方向传播,振荡周期约为20 d。（2）BSISO主要是通过影响大气环流和水汽输送来影响华北夏季降水过程。在500 hPa层,BSISO信号会造成华北地区东部副热带高压位置南北移动和强度发生变化来影响华北夏季降水;在850 hPa层,BSISO信号会通过伴随的气旋性或反气旋性异常环流影响向华北的水汽输送来影响华北夏季降水。（3）虽然热带大气季节内振荡MJO（Madden-Julian Oscillation）信号在全年都存在,但其变化在冬半年尤其冬季振幅最大,在夏季最小。BSISO信号变化在夏半年尤其夏季振幅最大。因此,利用热带大气低频信号开展延伸期降水过程预测,冬半年可以重点考虑MJO的影响,夏半年重点考虑BSISO的影响。 相似文献
11.
Real-time multivariate indices for the boreal summer intraseasonal oscillation over the Asian summer monsoon region 总被引：3，自引：0，他引：3
June-Yi Lee Bin Wang Matthew C. Wheeler Xiouhua Fu Duane E. Waliser In-Sik Kang 《Climate Dynamics》2013,40(1-2):493-509
The boreal summer intraseasonal oscillation (BSISO) of the Asian summer monsoon (ASM) is one of the most prominent sources of short-term climate variability in the global monsoon system. Compared with the related Madden-Julian Oscillation (MJO) it is more complex in nature, with prominent northward propagation and variability extending much further from the equator. In order to facilitate detection, monitoring and prediction of the BSISO we suggest two real-time indices: BSISO1 and BSISO2, based on multivariate empirical orthogonal function (MV-EOF) analysis of daily anomalies of outgoing longwave radiation (OLR) and zonal wind at 850 hPa (U850) in the region 10°S–40°N, 40°–160°E, for the extended boreal summer (May–October) season over the 30-year period 1981–2010. BSISO1 is defined by the first two principal components (PCs) of the MV-EOF analysis, which together represent the canonical northward propagating variability that often occurs in conjunction with the eastward MJO with quasi-oscillating periods of 30–60 days. BSISO2 is defined by the third and fourth PCs, which together mainly capture the northward/northwestward propagating variability with periods of 10–30 days during primarily the pre-monsoon and monsoon-onset season. The BSISO1 circulation cells are more Rossby wave like with a northwest to southeast slope, whereas the circulation associated with BSISO2 is more elongated and front-like with a southwest to northeast slope. BSISO2 is shown to modulate the timing of the onset of Indian and South China Sea monsoons. Together, the two BSISO indices are capable of describing a large fraction of the total intraseasonal variability in the ASM region, and better represent the northward and northwestward propagation than the real-time multivariate MJO (RMM) index of Wheeler and Hendon. 相似文献
12.
Harun A. Rashid Harry H. Hendon Matthew C. Wheeler Oscar Alves 《Climate Dynamics》2011,36(3-4):649-661
Predictions of the Madden?CJulian oscillation (MJO) are assessed using a 10-member ensemble of hindcasts from POAMA, the Australian Bureau of Meteorology coupled ocean?Catmosphere seasonal prediction system. The ensemble of hindcasts was initialised from observed atmosphere and ocean initial conditions on the first of each month during 1980?C2006. The MJO is diagnosed using the Wheeler-Hendon Real-time Multivariate MJO (RMM) index, which involves projection of daily data onto the leading pair of eigenmodes from an analysis of zonal winds at 200 and 850?hPa and outgoing longwave radiation (OLR) averaged about the equator. Forecasts of the two component (RMM1 and RMM2) index are quantitatively compared with observed behaviour derived from NCEP reanalyses and satellite OLR using the bivariate correlation skill, root-mean-square error (RMSE), and measures of the MJO amplitude and phase error. Comparison is also made with a simple vector autoregressive (VAR) prediction model of RMM as a benchmark. Using the full hindcast set, we find that the MJO can be predicted with the POAMA ensemble out to about 21?days as measured by the bivariate correlation exceeding 0.5 and the bivariate RMSE remaining below ~1.4 (which is the value for a climatological forecast). The VAR model, by comparison, drops to a correlation of 0.5 by about 12?days. The prediction limit from POAMA increases by less than 2?days for times when the MJO has large initial amplitude, and has little sensitivity to the initial phase of the MJO. The VAR model, on the other hand, shows a somewhat larger increase in skill for times of strong MJO variability and has greater sensitivity to initial phase, with lower skill for times when MJO convection is developing in the Indian Ocean. The sensitivity to season is, however, greater for POAMA, with maximum skill occurring in the December?CJanuary?CFebruary season and minimum skill in June?CJuly?CAugust. Examination of the MJO amplitudes shows that individual POAMA members have slightly above observed amplitude after a spin-up of about 10?days, whereas examination of the MJO phase error reveals that the model has a consistent tendency to propagate the MJO slightly slower than observed. Finally, an estimate of potential predictability of the MJO in POAMA hindcasts suggests that actual MJO prediction skill may be further improved through continued development of the dynamical prediction system. 相似文献
13.
本文基于2001—2010年上海市11个基本气象站的逐日降水量和澳大利亚气象局的逐日大气低频振荡(MaddenJulian Oscillation,MJO)指数(包括RMM1和RMM2)资料,选取MJO指数作为预报因子,上海地区梅汛期降水量作为预报对象,建立了基于时空投影法(spatial-temporal projection model,STPM)的上海地区梅汛期降水延伸期预报模型。利用该模型对近6年(2011—2016年)的梅汛期降水进行回报试验,其预报技巧评估结果表明:该模型对未来10～25 d的降水具有较好预报效果,可较准确地预报出梅汛期3/4左右的降水量级和降水发生时段。其中,预报时效为10～20 d的预报技巧较高,而提前21～25 d的预报技巧略有下降。总体而言,基于MJO活动的STPM预报模型在上海地区梅汛期延伸期降水预报中具有较好的参考价值。 相似文献
14.
In this study,we evaluate the forecast skill of the subseasonal-to-seasonal(S2S)prediction model of the Beijing Climate Center(BCC)for the boreal summer intraseasonal oscillation(BSISO).We also discuss the key factors that inhibit the BSISO forecast skill in this model.Based on the bivariate anomaly correlation coefficient(ACC)of the BSISO index,defined by the first two EOF modes of outgoing longwave radiation and 850-hPa zonal wind anomalies over the Asian monsoon region,we found that the hindcast skill degraded as the lead time increased.The ACC dropped to below 0.5for lead times of 11 days and longer when the predicted BSISO showed weakened strength and insignificant northward propagation.To identify what causes the weakened forecast skill of BSISO at the forecast lead time of 11 days,we diagnosed the main mechanisms responsible for the BSISO northward propagation.The same analysis was also carried out using the observations and the outputs of the four-day forecast lead that successfully predicted the observed northward-propagating BSISO.We found that the lack of northward propagation at the 11-day forecast lead was due to insufficient increases in low-level cyclonic vorticity,moistening and warm temperature anomalies to the north of the convection,which were induced by the interaction between background mean flows and BSISO-related anomalous fields.The BCC S2S model can predict the background monsoon circulations,such as the low-level southerly and the northerly and easterly vertical shears,but has limited capability in forecasting the distributions of circulation and moisture anomalies. 相似文献
15.
The influence of ocean–atmosphere coupling on the simulation and prediction of the boreal winter Madden–Julian Oscillation
(MJO) is examined using the Seoul National University coupled general circulation model (CGCM) and atmospheric—only model
(AGCM). The AGCM is forced with daily SSTs interpolated from pentad mean CGCM SSTs. Forecast skill is examined using serial
extended simulations spanning 26 different winter seasons with 30-day forecasts commencing every 5 days providing a total
of 598 30-day simulations. By comparing both sets of experiments, which share the same atmospheric components, the influence
of coupled ocean–atmosphere processes on the simulation and prediction of MJO can be studied. The mean MJO intensity possesses
more realistic amplitude in the CGCM than in AGCM. In general, the ocean–atmosphere coupling acts to improve the simulation
of the spatio-temporal evolution of the eastward propagating MJO and the phase relationship between convection (OLR) and SST
over the equatorial Indian Ocean and the western Pacific. Both the CGCM and observations exhibit a near-quadrature relationship
between OLR and SST, with the former lagging by about two pentads. However, the AGCM shows a less realistic phase relationship.
As the initial conditions are the same in both models, the additional forcing by SST anomalies in the CGCM extends the prediction
skill beyond that of the AGCM. To test the applicability of the CGCM to real-time prediction, we compute the Real-time Multivariate
MJO (RMM) index and compared it with the index computed from observations. RMM1 (RMM2) falls away rapidly to 0.5 after 17–18
(15–16) days in the AGCM and 18–19 (16–17) days in the CGCM. The prediction skill is phase dependent in both the CGCM and
AGCM. 相似文献
16.
热带大气季节内振荡(MJO)实时监测预测业务 总被引：8，自引：2，他引：6
参考目前国际上普遍认可的Wheeler和Hendon设计的MJO监测指标,设计了适合开展实时业务监测的MJO计算方法,初步在国家气候中心建立了逐日的MJO实时监测业务,通过与国外同类监测结果的比较分析表明,监测指标可以很好地描述MJO的强度和传播特征,与国外同类监测产品有很好的一致性。另外,引入了两种统计方法进行了针对MJO指数的实时预测,对预测结果的检验表明,对MJO在两周内有较好的预测技巧,其中利用滞后线性回归方法（PCL）的预测技巧要高于自回归模型（ARM）。 相似文献
17.
Bimodal representation of the tropical intraseasonal oscillation 总被引：2，自引：1，他引：1
The tropical intraseasonal oscillation (ISO) shows distinct variability centers and propagation patterns between boreal winter and summer. To accurately represent the state of the ISO at any particular time of a year, a bimodal ISO index was developed. It consists of Madden-Julian Oscillation (MJO) mode with predominant eastward propagation along the equator and Boreal Summer ISO (BSISO) mode with prominent northward propagation and large variability in off-equatorial monsoon trough regions. The spatial–temporal patterns of the MJO and BSISO modes are identified with the extended empirical orthogonal function analysis of 31?years (1979–2009) OLR data for the December–February and June–August period, respectively. The dominant mode of the ISO at any given time can be judged by the proportions of the OLR anomalies projected onto the two modes. The bimodal ISO index provides objective and quantitative measures on the annual and interannual variations of the predominant ISO modes. It is shown that from December to April the MJO mode dominates while from June to October the BSISO mode dominates. May and November are transitional months when the predominant mode changes from one to the other. It is also shown that the fractional variance reconstructed based on the bimodal index is significantly higher than the counterpart reconstructed based on the Wheeler and Hendon’s index. The bimodal ISO index provides a reliable real time monitoring skill, too. The method and results provide critical information in assessing models’ performance to reproduce the ISO and developing further research on predictability of the ISO and are also useful for a variety of scientific and practical purposes. 相似文献
18.
The Madden–Julian Oscillation (MJO)/Boreal Summer Intraseasonal Oscillation (BSISO) has been considered an important climate mode of variability on subseasonal timescales for East Asian summer. However, it is unclear how well the MJO/BSISO indices would serve as guidance for subseasonal forecasts. Using a probabilistic forecast model determined through multiple linear regression (MLR) with MJO, ENSO, and long-term trend as predictors, we examine lagged impacts of each predictor on East Asia extended summer (May–October) climate from 1982 to 2015. The forecast skills of surface air temperature (T2m) contributed by each predictor is evaluated for lead times out to five weeks. We also provide a systematic evaluation of three commonly used, real-time MJO/BSISO indices in the context of lagged temperature impacts over East Asia. It is found that the influence of the trend provides substantial summertime skill over broad regions of East Asia on subseasonal timescales. In contrast, the MJO influence shows regional as well as phase dependence outside the tropical band of the main action centers of the MJO convective anomalies. All three MJO/BSISO indices generate forecasts that yield high skill scores for week 1 forecasts. For some initial phases of the MJO/BSISO, skill reemerges over some regions for lead times of 3–5 weeks. This emergence indicates the existence of windows of opportunity for skillful subseasonal forecasts over East Asia in summer. We also explore the dynamics that contribute to the elevated skills at long lead times over Tibet and Taiwan–Philippine regions following the initial state of phases 7 and 5, respectively. The elevated skill is rooted in a wave train forced by the MJO convective heating over the Arabian Sea and feedbacks between MJO convection and SSTs in Taiwan–Philippine region. Two out of the three commonly used MJO/BSISO indices tend to identify MJO events that evolve consistently in time, allowing them to serve as reliable predictors for subseasonal forecasts for up to 5 weeks.
相似文献19.
Ping Liu 《Climate Dynamics》2014,43(7-8):1939-1950
The real-time multivariate Madden–Julian oscillation (RMM; MJO) index has been widely employed to monitor the amplitude, phase, and time evolution of MJO events, as the index is formulated from the leading two combined-empirical orthogonal function (CEOF) modes of daily anomalous OLR and 850- and 200-hPa zonal winds, and the modes describe the MJO dynamics well. These two CEOF modes, however, are known to dominate in power spectra at zonal wavenumber one and may underestimate the power and structure at wavenumbers 2–5 where many MJO events are also prominent. This study approximated a baseline for MJO by applying band-pass filters to daily anomalies on 30–100 day periods and at 1–5 eastward propagating waves, as slightly different bands led to the same conclusions. Following the procedures to develop the RMM index, the daily anomalous data were derived and subjected to the CEOF analysis with all modes archived for diagnosis. Different numbers of the leading modes were compared in explained variance, standard deviation (STD), and wavenumber power spectra to describe the overall MJO magnitude and structure, and on the Hovmöller diagrams to represent the evolution of three distinct MJO events. Results show that the two leading CEOF modes explain only a small portion of the power spectra at wavenumbers 2–5. This spectral leakage notably reduces the MJO amplitude, particularly of the OLR in the western Pacific. The CEOF modes 3–10 can withhold power sufficiently such that the anomalies reconstructed by the first 10 modes contribute most of the baseline variance; their structures agree well with the baseline by constituting nearly the same proportion in the region from the central Indian Ocean to the dateline and by providing more complete evolutions of the three MJO events on the Hovmöller diagrams. Meanwhile, these modes introduce a notable amount of power for the equatorial Rossby and Kelvin waves that are partially embedded in the evolution of MJO. The first 50 of the total 432 CEOF modes retain all variance of the baseline MJO, while those higher than 10 contain less information and more noise and can be discarded. Furthermore, this study indicated that the longitudinal STD of the reconstructed anomalies detects the MJO phases and magnitudes in the western Pacific with more physical meaning and in better agreement with the Hovmöller diagrams than the RMM-like amplitude. The results provide an integral figure of the MJO structure from the CEOF analysis and a more robust RMM framework for monitoring the MJO’s evolution in real time and for validating its numerical forecast and simulations. 相似文献