POSSIBLE INFLUENCES OF THE TROPICAL INDIAN OCEAN DIPOLE ON THE EASTWARD PROPAGATION OF MJO

Based on multiple datasets, correlation and composite analyses, and case studies, this paper investigated possible influences of the Indian Ocean dipole （IOD） mode on the eastward propagation of intraseasonal oscillation in the tropical atmosphere. The results showed that （1） the 30-60 day outgoing longwave radiation anomalies in the southeastern Indian Ocean and the 30-60 day 850-hPa zonal wind anomalies over the equatorial central Indian Ocean were significantly correlated with the IOD index; （2） during positive IOD years, the anomalously cold water in the southeastern Indian Ocean and the 850-hPa anomalous easterlies over the equatorial central Indian Ocean might act as barriers to the continuously eastward propagation of the intraseasonal convection, which interrupts the Madden-Julian oscillation （MJO） propagation in the eastern equatorial Indian Ocean and western Pacific; and （3） during negative IOD years, the anomalously warm water in the southeastern Indian Ocean and the low-level westerly anomalies over the equatorial central Indian Ocean favor the eastward movement of MJO.     

热带对流和环流季内振荡强度与海表温度关系对比研究

利用外逸长波辐射(OLR）、风场和海表温度(SST)资料, 研究了热带大气季节内振荡(ISO)强度的季节变化特征, 发现热带印度洋和热带西太平洋区域是OLR和风场季内振荡最主要的共同活跃区。对比分析了OLR和风场季内振荡强度与海表温度异常之间的年际异常关系, 发现OLR季内振荡强度异常与海表温度异常之间存在显著局地正相关关系, 即在热带中东太平洋区域、热带西北太平洋区域和热带西南太平洋区域, 当海表温度正(负)异常时, OLR季内振荡增强(减弱),特别在冬春季节这一关系更清楚。除个别区域外, 风场季内振荡强度异常与海表温度异常不存在类似OLR的局地关系。OLR和风场季内振荡强度异常与海表温度异常之间局地和非局地关系的差异, 体现了两种要素特性的本质差异。但两种要素季内振荡强度在El Niño事件发展过程中的变化基本一致, 即在气候场中季内振荡活跃的区域, 事件发生之前季内振荡会增强, 并逐渐向东传播, 事件发生之后这些区域振荡减弱。     

全球变化背景下北半球冬季MJO传播的年代际变化

利用1979~2013年实时多要素MJO（Madden-Julian Oscillation）监测（RMM）指数,美国NOAA逐日长波辐射资料和NCEP/NCAR再分析资料等,分析了全球变化背景下北半球冬季MJO传播的年代际变化特征。从全球平均气温快速增暖期（1985~1997）到变暖趋缓期（2000~2012）,MJO 2~4位相频次减少,5~7位相频次增多,即MJO对流活跃区在热带印度洋地区停留时间缩短、传播速度加快,而在热带西太平洋停留时间加长、传播明显减缓。进一步分析发现,以上MJO的年代际变化特征与全球变化年代际波动有关。当太平洋年代际涛动（PDO）处于负位相时,全球变暖趋缓,热带东印度洋—西太平洋海温异常偏暖,使其上空对流加强,垂直上升运动加强,对流层低层辐合,大气中的水汽含量增多,该区域的湿静力能（MSE）为正异常。当MJO对流活跃区位于热带印度洋地区时,MJO异常环流对季节平均MSE的输送在强对流中心东侧为正、西侧为负,有利于东侧MSE扰动增加,使得MJO对流扰动东移加快;而当MJO对流活跃区在热带西太平洋地区,MJO异常环流对平均MSE的输送形成东负西正的形势,东侧MSE扰动减小,不利于MJO快速东传。因此,全球变化背景下PDO引起的大气中水汽含量及MSE的变化可能是MJO传播年代际变化的重要原因。     

Examination of multi-perturbation methods for ensemble prediction of the MJO during boreal summer

The impact of initialization and perturbation methods on the ensemble prediction of the boreal summer intraseasonal oscillation was investigated using 20-year hindcast predictions of a coupled general circulation model. The three perturbation methods used in the present study are the lagged-averaged forecast (LAF) method, the breeding method, and the empirical singular vector (ESV) method. Hindcast experiments were performed with a prediction interval of 10 days for extended boreal summer (May–October) seasons over a 20 year period. The empirical orthogonal function (EOF) eigenvectors of the initial perturbations depend on the individual perturbation method used. The leading EOF eigenvectors of the LAF perturbations exhibit large variances in the extratropics. Bred vectors with a breeding interval of 3 days represent the local unstable mode moving northward and eastward over the Indian and western Pacific region, and the leading EOF modes of the ESV perturbations represent planetary-scale eastward moving perturbations over the tropics. By combining the three perturbation methods, a multi-perturbation (MP) ensemble prediction system for the intraseasonal time scale was constructed, and the effectiveness of the MP prediction system for the Madden and Julian oscillation (MJO) prediction was examined in the present study. The MJO prediction skills of the individual perturbation methods are all similar; however, the MP‐based prediction has a higher level of correlation skill for predicting the real-time multivariate MJO indices compared to those of the other individual perturbation methods. The predictability of the intraseasonal oscillation is sensitive to the MJO amplitude and to the location of the dominant convective anomaly in the initial state. The improvement in the skill of the MP prediction system is more effective during periods of weak MJO activity.     

The Extreme Mei-yu Season in 2020: Role of the Madden-Julian Oscillation and the Cooperative Influence of the Pacific and Indian Oceans※

The middle and lower reaches of the Yangtze River in eastern China during summer 2020 suffered the strongest mei-yu since 1961. In this work, we comprehensively analyzed the mechanism of the extreme mei-yu season in 2020, with focuses on the combined effects of the Madden-Julian Oscillation (MJO) and the cooperative influence of the Pacific and Indian Oceans in 2020 and from a historical perspective. The prediction and predictability of the extreme mei-yu are further investigated by assessing the performances of the climate model operational predictions and simulations. 　 It is noted that persistent MJO phases 1?2 during June?July 2020 played a crucial role for the extreme mei-yu by strengthening the western Pacific subtropical high. Both the development of La Ni?a conditions and sea surface temperature (SST) warming in the tropical Indian Ocean exerted important influences on the long-lived MJO phases 1?2 by slowing down the eastward propagation of the MJO and activating convection related to the MJO over the tropical Indian Ocean. The spatial distribution of the 2020 mei-yu can be qualitatively captured in model real-time forecasts with a one-month lead. This can be attributed to the contributions of both the tropical Indian Ocean warming and La Ni?a development. Nevertheless, the mei-yu rainfall amounts are seriously underestimated. Model simulations forced with observed SST suggest that internal processes of the atmosphere play a more important role than boundary forcing (e.g., SST) in the variability of mei-yu anomaly, implying a challenge in quantitatively predicting an extreme mei-yu season, like the one in 2020.     

BCC S2S模式对亚洲夏季风准双周振荡预报评估

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。     

Modulation of Madden-Julian Oscillation Activity by the Tropical Pacific-Indian Ocean Associated Mode

In this study, the impacts of the tropical Pacific–Indian Ocean associated mode (PIOAM) on Madden–Julian Oscillation (MJO) activity were investigated using reanalysis data. In the positive (negative) phase of the PIOAM, the amplitudes of MJO zonal wind and outgoing longwave radiation are significantly weakened (enhanced) over the Indian Ocean, while they are enhanced (weakened) over the central and eastern Pacific. The eastward propagation of the MJO can extend to the central Pacific in the positive phase of the PIOAM, whereas it is mainly confined to west of 160°E in the negative phase. The PIOAM impacts MJO activity by modifying the atmospheric circulation and moisture budget. Anomalous ascending (descending) motion and positive (negative) moisture anomalies occur over the western Indian Ocean and central-eastern Pacific (Maritime Continent and western Pacific) during the positive phase of the PIOAM. The anomalous circulation is almost the opposite in the negative phases of the PIOAM. This anomalous circulation and moisture can modulate the activity of the MJO. The stronger moistening over the Indian Ocean induced by zonal and vertical moisture advection leads to the stronger MJO activity over the Indian Ocean in the negative phase of the PIOAM. During the positive phase of the PIOAM, the MJO propagates farther east over the central Pacific owing to the stronger moistening there, which is mainly attributable to the meridional and vertical moisture advection, especially low-frequency background state moisture advection by the MJO’s meridional and vertical velocities.     

Origins of Quasi-Biweekly and Intraseasonal Oscillations over the South China Sea and Bay of Bengal and Scale Selection of Unstable Equatorial and Off-Equatorial Modes

The daily outgoing longwave radiation (OLR) field in boreal summer shows significant power spectrum peaks on quasi-biweekly (10–20-day) and intraseasonal (20-80-day) timescales over the Indo-western Pacific warm pool, especially over the South China Sea and Bay of Bengal. The quasi-biweekly oscillation (QBWO) originates from off-equatorial western North Pacific, and is characterized by a northwest-southeast oriented wave train pattern, propagating northwestward. The intraseasonal oscillation (ISO), on the other hand, originates from the equatorial Indian Ocean and propagates eastward and northward. Why the equatorial mode possesses a 20–80-day periodicity while the off-equatorial mode favors a 10–20-day periodicity is investigated through idealized numerical experiments with a 2.5-layer atmospheric model. In the off-equatorial region, the model simulates, under a realistic three-dimensional summer mean flow, the most unstable mode that has a wave train pattern with a typical zonal wavelength of 6000 km and a period of 10–20 days, propagating northwestward. This is in contrast to the equatorial region, where a Madden-Julian oscillation (MJO) like mode with a planetary (wavenumber-1) zonal scale and a period ranging from 20 to 80 days is simulated. Sensitivity experiments with different initial conditions indicate that the QBWO is an intrinsic mode of the atmosphere in boreal summer in the off-equatorial Indo-western Pacific region under the summer mean state, while the MJO is the most unstable mode in the equatorial region.     

The MJO and global warming: a study in CCSM4

The change in Madden–Julian oscillation (MJO) amplitude and variance in response to anthropogenic climate change is assessed in the 1° nominal resolution community climate system model, version 4 (CCSM4), which has a reasonable representation of the MJO characteristics both dynamically and statistically. The twentieth century CCSM4 run is compared with the warmest twenty-first century projection (representative concentration pathway 8.5, or RCP8.5). The last 20 years of each simulation are compared in their MJO characteristics, including spatial variance distributions of winds, precipitation and outgoing longwave radiation, histograms of event amplitude, phase and duration, and composite maps of phases. The RCP8.5 run exhibits increased variance in intraseasonal precipitation, larger-amplitude MJO events, stronger MJO rainfall in the central and eastern tropical Pacific, and a greater frequency of MJO occurrence for phases corresponding to enhanced rainfall in the Indian Ocean sector. These features are consistent with the concept of an increased magnitude for the hydrological cycle under greenhouse warming conditions. Conversely, the number of active MJO days decreases and fewer weak MJO events occur in the future climate state. These results motivate further study of these changes since tropical rainfall variability plays such an important role in the region’s socio-economic well being.     

MJO与北半球高纬地区冬季地表气温异常的联系

基于1979—2016年NCEP-NCAR逐日再分析资料研究了热带季节内振荡(MJO)和北半球冬季高纬地区地表气温(SAT)之间的联系。利用实时多变量MJO(RMM)指数,将MJO分为8个位相,其中位相2(位相6)对应于位于印度洋地区的正(负)对流。不同MJO位相下的SAT合成结果显示MJO第二位相后的5~15 d,北半球高纬地区(60°~90°N、180°~60°W)有明显的负SAT异常;由于热带异常加热信号的改变,在MJO第六位相后的5~15 d该地区则对应于显著的正SAT异常。该地区温度的垂直结构在各个位相下也表现出类似的分布特征。合成的500 hPa位势高度异常场显示,在温度负(正)异常的位相对应有明显的位势高度负(正)异常,这种环流异常主要是由与热带对流异常相联系的向东北方向传播的罗斯贝波列所引起的。通过对波活动通量的计算,推断该东北方向传播的罗斯贝波列很可能是罗斯贝波能量频散的结果。合成的700 hPa比湿异常场和SAT之间在存在着较好的对应关系,考虑到对流层中层的比湿与向下长波辐射之间存在着正相关关系,说明该温度异常也可能与辐射过程相关。上述分析表明与MJO对流相关的大尺度环流异常对高纬地区季节内SAT变率有重要影响,该异常SAT信号可能来自平流输送和辐射过程等。准确把握MJO位相与SAT异常信号的联系也可以为北半球高纬地区SAT的延伸期预报提供一些可靠线索。     

IAP AGCM4.0模式对热带大气季节内振荡的模拟评估

基于中国科学院大气物理所大气环流模式IAP AGCM4.0总共30年(1979~2008年)的模拟结果,评估了IAP AGCM4.0模式对热带大气季节内振荡的模拟能力。分析结果表明IAP AGCM4.0模式可以在一定程度上模拟出热带大气季节内振荡的主要时空谱结构特征,在周期30~80天处存在明显的谱能量中心;模式模拟的季节内振荡东传的主要特征与观测基本一致,东移波的能量远大于西移波。基于RMM指数(All-season Real-time Multivariate MJO Index)的分析表明,模式模拟的850 h Pa和200 h Pa季节内尺度风场和对流活动在赤道地区的空间分布与观测基本一致。但与观测相比,模式模拟的热带大气季节内振荡的周期较短,东传速度快于观测,虚假的西传特征过强,对流活跃区域范围较小、强度较弱。就非绝热加热而言,模式模拟结果与再分析资料比较接近,但最大加热在印度洋和西太平洋地区出现的位相较晚。进一步分析表明,模式中影响对流触发的相对湿度阈值(RHc)的不同取值(RHc分别取为85%、90%、95%和100%),可以显著影响热带大气非绝热加热垂直廓线,从而影响模式对热带大气季节内振荡的模拟;当对流触发相对湿度阈值取为90%时,IAP AGCM4.0模式对热带大气季节内振荡模拟的能力相对最好,非绝热加热垂直廓线在不同位相的分布特征也与再分析资料最为接近。这说明模式对流参数化方案中不同参数的合适选取,可以改进模式对热带大气季节内振荡的模拟能力。     

Prediction skill of the Madden and Julian Oscillation in dynamical extended range forecasts

The Madden and Julian Oscillation (MJO) is the most prominent mode of intraseasonal variations in the tropical region. It plays an important role in climate variability and has a significant influence on medium-to-extended ranges weather forecasting in the tropics. This study examines the forecast skill of the oscillation in a set of recent dynamical extended range forecasts (DERF) experiments performed by the National Centers for Environmental Prediction (NCEP). The present DERF experiments were done with the reanalysis version of the medium range forecast (MRF) model and include 50-day forecasts, initialized once-a-day (0Z) with reanalyses fields, for the period between 1 January, 1985, and 31 December, 1989. The MRF model shows large mean errors in representing intraseasonal variations of the large-scale circulation, especially over the equatorial eastern Pacific Ocean. A diagnostic analysis has considered the different phases of the MJO and the associated forecast skill of the MRF model. Anomaly correlations on the order of 0.3 to 0.4 indicate that skillful forecasts extend out to 5 to 7 days lead-time. Furthermore, the results show a slight increase in the forecast skill for periods when convective anomalies associated with the MJO are intense. By removing the mean errors, the analysis shows systematic errors in the representation of the MJO with weaker than observed upper level zonal circulations. The examination of the climate run of the MRF model shows the existence of an intraseasonal oscillation, although less intense (50–70%) and with faster (nearly twice as fast) eastward propagation than the observed MJO. The results indicate that the MRF model likely has difficulty maintaining the MJO, which impacts its forecast. A discussion of future work to improve the representation of the MJO in dynamical models and assess its prediction is presented. Received: 28 December 1998 / Accepted: 27 September 1999     

POSSIBLE IMPACTS OF MADDEN-JULIAN OSCILLATION ON THE SEVERE RAIN-SNOW WEATHER IN CHINA DURING NOVEMBER 2009

Possible relationships between MJO and the severe rain-snow weather in Eastern China during November of 2009 are analyzed and results show that a strong MJO process is one of the strong impact factors.MJO is very active over the Indian Ocean in November 2009.Especially,it maintains 9 days in MJO phase 3,just corresponding to the two strongest rain-snow processes.Composites of MJO events show that when the MJO convective center is located over the Indian Ocean,the probability of rainfall is significantly increased and the temperature is lower than normal in eastern China,which is consistent with the situation in November of 2009.Atmospheric circulation anomalies of mid-and higher-latitudes can be influenced by the tropical MJO convection forcing and this influence could be realized by teleconnection.When the MJO is over the Indian Ocean,it is favorable for the maintenance of a circulation pattern of two ridges versus one trough at mid-and higher-latitudes.Meanwhile,the western Pacific subtropical high is stronger and more westward than normal,and a significant convective belt appears over eastern East Asia.All these circulation anomalies shown in the composite result also appeared in the observations in November 2009,which indicates the general features of relationships between the MJO and the circulation anomalies over the extratropics.Besides the zonal circulation anomalies,the MJO convection can also lead to meridional circulation anomalies.When the MJO convection is located over the Indian Ocean,the western Pacific is dominated by anomalous descending motion,and the eastern East Asia is controlled by strong convergence and ascending motion.Therefore,an anomalous meridional circulation is formed between the tropics and middle latitudes,enhancing the northward transportation of low-level moisture.It is potentially helpful to understanding and even forecasting such kind of rain-snow weather anomalies as that in November 2009 using MJO.     

Evidence of Specific MJO Phase Occurrence with Summertime California Central Valley Extreme Hot Weather

This study examines associations between California Central Valley(CCV) heat waves and the Madden Julian Oscillation(MJO). These heat waves have major economic impact. Our prior work showed that CCV heat waves are frequently preceded by convection over the tropical Indian and eastern Pacific oceans, in patterns identifiable with MJO phases. The main analysis method is lagged composites(formed after each MJO phase pair) of CCV synoptic station temperature, outgoing longwave radiation(OLR), and velocity potential(VP). Over the CCV, positive temperature anomalies occur only after the Indian Ocean(phases 2-3) or eastern Pacific Ocean(phases 8-1) convection(implied by OLR and VP fields). The largest fractions of CCV hot days occur in the two weeks after onset of those two phase pairs. OLR and VP composites have significant subsidence and convergence above divergence over the CCV during heat waves, and these structures are each part of larger patterns having significant areas over the Indian and Pacific Oceans. Prior studies showed that CCV heat waves can be roughly grouped into two clusters: Cluster 2 is preceded by a heat wave over northwestern North America, while Cluster 1 is not. OLR and VP composite analyses are applied separately to these two clusters. However, for Cluster 2, the subsidence and VP over the CCV are not significant, and the large-scale VP pattern has low correlation with the MJO lagged composite field. Therefore, the association between the MJO convection and subsequent CCV heat wave is more evident in Cluster 1 than Cluster 2.     

海气耦合对MJO数值模拟的影响

采用一种基于降水异常追踪MJO（Madden–Julian Oscillation）东传的MJO识别方法（MJO Tracking）评估了参与MJOTF/GASS（MJO Task Force/Global Energy and Water Cycle Experiment Atmospheric System Study）全球模式比较计划的全海气耦合模式（CNRM-CM）、半海气耦合模式（CNRM-ACM）和大气模式（CNRM-AM）1991～2010年模拟MJO的能力,探究了海气耦合过程对模式模拟MJO能力的影响机理。CNRM-CM模式模拟的MJO结构更加接近观测,该模式不仅具有最高的MJO生成频率,也能够模拟较强的MJO强度以及较远的传播距离。海气耦合过程会造成CNRM-CM和CNRM-ACM模式中印度洋—太平洋暖池区域海温气候态的冷偏差。但是这种海温气候态的偏差基本没有改变模式模拟MJO的能力。CNRM-CM中MJO对流中心东（西）侧存在较强的季节内尺度海温暖（冷）异常,纬向梯度明显,而CNRM-ACM和CNRM-AM中不存在这样的海温东西不对称结构。结果表明在CNRM模式中海气耦合过程调控模式海温季节内尺度变率对模式MJO模拟能力的影响比调控模式海温气候态更加重要。     

The self-organizing map,a new approach to apprehend the Madden–Julian Oscillation influence on the intraseasonal variability of rainfall in the southern African region

The Madden–Julian Oscillation (MJO) is the major mode of intraseasonal variability (30–60 days) in the tropics, having large rainfall impacts globally, and possibly on southern Africa. However, the latter impact is not well understood and needs to be further explored. The life cycle of the MJO, known to be asymmetric, has been nevertheless analyzed usually through methods constrained by both linearity and orthogonality, such as empirical orthogonal function analysis. Here we explore a non-linear classification method, the self-organizing map (SOM), a type of artificial neural network used to produce a low-dimensional representation of high-dimensional datasets, to capture more accurately the life cycle of the MJO and its global impacts. The classification is applied on intraseasonal anomalies of outgoing longwave radiation within the tropical region over the 1980–2009 period. Using the SOM to describe the MJO is a new approach, complimentary to the usual real-time multivariate MJO index. It efficiently captures this propagative phenomenon and its seasonality, and is shown to provide additional temporal and spatial information on MJO activity. For each node, the subtropical convection is analyzed, with a particular focus on the southern Africa region. Results show that the convection activity over the central tropical Indian Ocean is a key factor influencing the intraseasonal convective activity over the southern African region. Enhanced (suppressed) convection over the central Indian Ocean tends to suppress (enhance) convection over the southern African region with a 10-day lag by modulating the moisture transport.     

Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter

The seasonal prediction skill for the Northern Hemisphere winter is assessed using retrospective predictions (1982–2010) from the ECMWF System 4 (Sys4) and National Center for Environmental Prediction (NCEP) CFS version 2 (CFSv2) coupled atmosphere–ocean seasonal climate prediction systems. Sys4 shows a cold bias in the equatorial Pacific but a warm bias is found in the North Pacific and part of the North Atlantic. The CFSv2 has strong warm bias from the cold tongue region of the eastern Pacific to the equatorial central Pacific and cold bias in broad areas over the North Pacific and the North Atlantic. A cold bias in the Southern Hemisphere is common in both reforecasts. In addition, excessive precipitation is found in the equatorial Pacific, the equatorial Indian Ocean and the western Pacific in Sys4, and in the South Pacific, the southern Indian Ocean and the western Pacific in CFSv2. A dry bias is found for both modeling systems over South America and northern Australia. The mean prediction skill of 2 meter temperature (2mT) and precipitation anomalies are greater over the tropics than the extra-tropics and also greater over ocean than land. The prediction skill of tropical 2mT and precipitation is greater in strong El Nino Southern Oscillation (ENSO) winters than in weak ENSO winters. Both models predict the year-to-year ENSO variation quite accurately, although sea surface temperature trend bias in CFSv2 over the tropical Pacific results in lower prediction skill for the CFSv2 relative to the Sys4. Both models capture the main ENSO teleconnection pattern of strong anomalies over the tropics, the North Pacific and the North America. However, both models have difficulty in forecasting the year-to-year winter temperature variability over the US and northern Europe.     

北半球夏季大气低频振荡演变特征及其与华北夏季降水的关系

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。     

Simulation of monsoon intraseasonal variability in NCEP CFSv2 and its role on systematic bias

We have evaluated the simulation of Indian summer monsoon and its intraseasonal oscillations in the National Centers for Environmental Prediction climate forecast system model version 2 (CFSv2). The dry bias over the Indian landmass in the mean monsoon rainfall is one of the major concerns. In spite of this dry bias, CFSv2 shows a reasonable northward propagation of convection at intraseasonal (30–60 day) time scale. In order to document and understand this dry bias over the Indian landmass in CFSv2 simulations, a two pronged investigation is carried out on the two major facets of Indian summer monsoon: one, the air–sea interactions and two, the large scale vertical heating structure in the model. Our analysis shows a possible bias in the co-evolution of convection and sea surface temperature in CFSv2 over the equatorial Indian Ocean. It is also found that the simulated large scale vertical heat source (Q1) and moisture sink (Q2) over the Indian region are biased relative to observational estimates. Finally, this study provides a possible explanation for the dry precipitation bias over the Indian landmass in the simulated mean monsoon on the basis of the biases associated with the simulated ocean–atmospheric processes and the vertical heating structure. This study also throws some light on the puzzle of CFSv2 exhibiting a reasonable northward propagation at the intraseasonal time scale (30–60 day) despite a drier monsoon over the Indian land mass.     

Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts

The seasonal prediction skill of the Asian summer monsoon is assessed using retrospective predictions (1982–2009) from the ECMWF System 4 (SYS4) and NCEP CFS version 2 (CFSv2) seasonal prediction systems. In both SYS4 and CFSv2, a cold bias of sea-surface temperature (SST) is found over the equatorial Pacific, North Atlantic, Indian Oceans and over a broad region in the Southern Hemisphere relative to observations. In contrast, a warm bias is found over the northern part of North Pacific and North Atlantic. Excessive precipitation is found along the ITCZ, equatorial Atlantic, equatorial Indian Ocean and the maritime continent. The southwest monsoon flow and the Somali Jet are stronger in SYS4, while the south-easterly trade winds over the tropical Indian Ocean, the Somali Jet and the subtropical northwestern Pacific high are weaker in CFSv2 relative to the reanalysis. In both systems, the prediction of SST, precipitation and low-level zonal wind has greatest skill in the tropical belt, especially over the central and eastern Pacific where the influence of El Nino-Southern Oscillation (ENSO) is dominant. Both modeling systems capture the global monsoon and the large-scale monsoon wind variability well, while at the same time performing poorly in simulating monsoon precipitation. The Asian monsoon prediction skill increases with the ENSO amplitude, although the models simulate an overly strong impact of ENSO on the monsoon. Overall, the monsoon predictive skill is lower than the ENSO skill in both modeling systems but both systems show greater predictive skill compared to persistence.