An Assessment of MJO and Tropical Waves Simulated by Different Versions of the GAMIL Model

Simulated outgoing longwave radiation (OLR) outputs by two versions of the grid-point atmospheric general circulation model (GAMIL) were analyzed to assess the influences of improvements in cloud microphysics and convective parameterization schemes on the simulation of the Madden-Julian oscillation (MJO) and other tropical waves. The wavenumber-frequency spectral analysis was applied to isolate dominant modes of convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and inertio-gravity (IG) waves. The performances of different versions of the GAMIL model (version 1.0 (GAMIL1.0) and version 2.0 (GAMIL2.0)) were evaluated by comparing the power spectrum distributions of these waves among GAMIL1.0, GAMIL2.0, and observational data. GAMIL1.0 shows a weak MJO signal, with the maximum variability occurring separately at wavenumbers 1 and 4 rather than being concentrated on wavenumbers 1–3, suggesting that GAMIL1.0 could not effectively capture the intraseasonal variability. However, GAMIL2.0 is able to effectively reproduce both the symmetric and anti-symmetric waves, and the significant spectra of the MJO, Kelvin, and MRG waves are in agreement with observational data, indicating that the ability of GAMIL2.0 to simulate the MJO and other tropical waves is enhanced by improving the cloud microphysics and convective parameterization schemes and implying that such improvements are crucial to further improving this model’s performance.     

热带大气季节内振荡对西北太平洋台风的调制作用

利用澳大利亚气象局的RMM-MJO (Real-time Multivariate MJO) 指数, 分析研究了热带大气季节内振荡 (简称MJO) 对西北太平洋台风的调制作用及其机理, 结果表明MJO活动对西北太平洋台风的生成有比较明显调制作用。在MJO活跃期, 对流中心位于赤道东印度洋 (即MJO第2、3位相) 和对流中心越过海洋性大陆来到西太平洋地区 (即MJO 第5、6位相) 时台风生成的个数比例为2∶1。本文对西太平洋地区的大气环流场进行了多种气象要素的合成分析, 在MJO的不同位相, 西太平洋地区的动力因子分布形势有很明显不同。在第2、3位相, 各种因子均呈现出抑制西太平洋地区对流及台风发展的态势; 而在第5、6位相则明显有促进对流发生发展, 为台风生成和发展创造了有利条件的大尺度环流动力场。这说明MJO 在不断东移的过程中, 将改变大气环流形势, 最终影响了台风的生成和发展。接着, 我们从积云对流这个联系台风和MJO的重要因子出发, 研究了不同MJO位相时凝结加热的水平和垂直分布, 以及与台风环流、 水汽通量的配置情况。结果表明在MJO不同位相, 热源分布明显不同, 而这种水平和垂直方向的不同分布特征必然反映潜热释放和有效位能向有效动能转换的差异, 再与水汽的辐合辐散相配合, 就从台风获得的能量角度揭示了大气MJO调节台风的生成和发展, 造成不同位相时台风生成有根本差别的原因。     

Simulation of state-dependent high-frequency atmospheric variability associated with ENSO

High-frequency atmospheric variability depends on the phase of El Nino/Southern Oscillation (ENSO). Recently, there is increasing evidence that state-dependent high-frequency atmospheric variability significantly modulates ENSO characteristics. Hence, in this study, we examine the model simulations of high-frequency atmospheric variability and, further, its dependency on the El Nino phase, using atmospheric and coupled GCMs (AGCM and CGCM). We use two versions of physical packages here—with and without convective momentum transport (CMT)—in both models. We found that the CMT simulation gives rise to a large climatological zonal wind difference over the Pacific. Also, both the climate models show a significantly improved performance in simulating the state-dependent noise when the CMT parameterization is implemented. We demonstrate that the better simulation of the state-dependent noise results from a better representation of anomalous, as well as climatological, zonal wind. Our further comparisons between the simulations, demonstrates that low-frequency wind is a crucial factor in determining the state-dependency of high-frequency wind variability. Therefore, it is suggested that the so-called state-dependent noise is directly induced by the low-frequency wind anomaly, which is caused by SST associated with ENSO.     

Implications from Subseasonal Prediction Skills of the Prolonged Heavy Snow Event over Southern China in Early 2008

An exceptionally prolonged heavy snow event(PHSE) occurred in southern China from 10 January to 3 February2008, which caused considerable economic losses and many casualties. To what extent any dynamical model can predict such an extreme event is crucial for disaster prevention and mitigation. Here, we found the three S2 S models(ECMWF,CMA1.0 and CMA2.0) can predict the distribution and intensity of precipitation and surface air temperature(SAT)associated with the PHSE at 10-day lead and 10-15-day lead, respectively. The success is attributed to the models' capability in forecasting the evolution of two important low-frequency systems in the tropics and mid-latitudes [the persistent Siberian High and the suppressed phase of the Madden-Julian Oscillation(MJO)], especially in the ECMWF model. However, beyond the 15-day lead, the three models show almost no skill in forecasting this PHSE.The bias in capturing the two critical circulation systems is responsible for the low skill in forecasting the 2008 PHSE beyond the 15-day lead. On one hand, the models cannot reproduce the persistence of the Siberian High, which results in the underestimation of negative SAT anomalies over southern China. On the other hand, the models cannot accurately capture the suppressed convection of the MJO, leading to weak anomalous southerly and moisture transport, and therefore the underestimation of precipitation over southern China.The Singular Value Decomposition(SVD) analyses between the critical circulation systems and SAT/precipitation over southern China shows a robust historical relation, indicating the fidelity of the predictability sources for both regular events and extreme events(e.g., the 2008 PHSE).     

Impacts of Two Types of El Ni o on the MJO during Boreal Winter

The features of the MJO during two types of El Ni no events are investigated in this paper using the daily NCEP-2reanalysis data, OLR data from NOAA, and Real-time Multivariate MJO index for the period 1979–2012. The results indicate that the MJO exhibits distinct features during eastern Pacific(EP) El Ni no events, as compared to central Pacific(CP) El Ni no events. First, the intensity of the MJO is weakened during EP El Ni no winters from the tropical eastern Indian Ocean to the western Pacific, but enhanced during CP El Ni no winters. Second, the range of the MJO eastward propagation is different during the two types of El Ni no events. During EP El Ni no winters, the MJO propagates eastwards to 120?W, but only to 180?during CP El Ni no winters. Finally, the frequency in eight phases of the MJO may be affected by the two types of El Ni no. Phases 2 and 3 display a stronger MJO frequency during EP El Ni no winters, but phases 4 and 5 during CP El Ni no winters.     

DECADAL CHANGES IN WESTERN NORTH PACIFIC TROPICAL CYCLONES ASSOCIATED WITH MADDEN–JULIAN OSCILLATION

This study focuses on the decadal variability of tropical cyclones (TC) over the Western North Pacific (WNP) and how these changes are related to the Madden–Julian Oscillation (MJO). It was done with the help of the Real-time Multivariate MJO index from the Australian Government Bureau of Meteorology of the Centre for Australian Weather and Climate Research, TC data from the Joint Typhoon Warming Center best track datasets, and daily and monthly datasets from the NCEP/NCAR reanalysis center. The results show that the TC frequency in the WNP exhibited a statistically significant decrease during 1998–2010 compared to during 1979–1997. The decrease in TC frequency in the WNP mainly occurred during MJO active phases (i.e., phases 4, 5, 6, and 7). Further investigation of the climate background and the propagation differences of the MJO between 1979–1997 and 1998–2010 was performed. The La Ni?a-like tropical sea surface temperature cooling caused stronger Walker circulation and thus induced unfavorable atmosphere conditions for WNP TC genesis including a low-level easterly anomaly, a negative relative vorticity anomaly, an increase in sea-level pressure, and stronger vertical wind shear. Moreover, shortening of the MJO cycle, decline in the duration of the active phases in the WNP, and easterly anomaly and shrinkage of the convection area during MJO active phases may also partly explain the decadal variation of TC.     

CAS FGOALS-f3-L Model Datasets for CMIP6 Historical Atmospheric Model Intercomparison Project Simulation

The outputs of the Chinese Academy of Sciences(CAS) Flexible Global Ocean–Atmosphere–Land System(FGOALS-f3-L) model for the baseline experiment of the Atmospheric Model Intercomparison Project simulation in the Diagnostic,Evaluation and Characterization of Klima common experiments of phase 6 of the Coupled Model Intercomparison Project(CMIP6) are described in this paper. The CAS FGOALS-f3-L model, experiment settings, and outputs are all given. In total,there are three ensemble experiments over the period 1979–2014, which are performed with different initial states. The model outputs contain a total of 37 variables and include the required three-hourly mean, six-hourly transient, daily and monthly mean datasets. The baseline performances of the model are validated at different time scales. The preliminary evaluation suggests that the CAS FGOALS-f3-L model can capture the basic patterns of atmospheric circulation and precipitation well, including the propagation of the Madden–Julian Oscillation, activities of tropical cyclones, and the characterization of extreme precipitation. These datasets contribute to the benchmark of current model behaviors for the desired continuity of CMIP.     

2个耦合模式中MJO的预报技巧

本文使用加拿大气候模拟与分析中心(Canadian Center for Climate Modeling and Analysis,CCCma)的耦合模式预报产品,应用以信息论为基础的可预报性理论框架,诊断、分析了耦合模式中Madden-Julian Oscillation(MJO)的预报率,包括实际预报技巧和潜在预报率,以及热带季节内尺度变率(Intraseasonal Variability,ISV)最可预报模态的空间分布。并在此基础上讨论了不同时间尺度平均对MJO预报技巧的影响。结果表明:本文使用的2个耦合模式中,MJO的预报技巧与目前全球主要使用的预报模式相近,约为10 d。潜在可预报技巧可以达到30 d以上。随着时间尺度从日平均增加到10 d平均,MJO的实际预报技巧与潜在可预报技巧都相应提高,尤其是潜在可预报技巧的提高更加显著。进一步分析发现,影响实际预报技巧的一个重要因素是初始条件MJO信号的强弱,当MJO信号很强时,预报技巧较高,反之则较低。本文最后分析了模式中ISV最可预报模态的空间分布,并讨论了如何利用这种最可预报空间分布提高ISV的实际预报技巧。     

2018年春末南方极端持续高温及MJO影响

本文分析了2018年春末我国南方地区持续性极端高温过程及其影响系统。本次事件自5月15日首先在江淮等地迅速发展,17日之后扩展至华南并在该地区维持至6月初。江南南部和华南东部等地高温日数比常年同期偏多6～10 d,累计近两千站次出现了35℃以上的高温天气,约是之前最多年（1991年）的2.6倍。研究区域内有超过三分之一的测站高温日数突破5月历史极值。统计分析结果显示,春末南方高温日数与该地区上空位势高度、其西侧经向风及其上空对流活动均有显著关系,但对流的影响更为超前,约在一周左右。除和华南地区对流呈显著正相关外,春末南方高温还和热带印度洋OLR（Outgoing Longwave Radiation）呈显著的负相关,这种相关模态和MJO（Madden-Julian Oscillation）的第一、二位相对应的对流异常分布一致。对2018年的个例分析支持这一统计结果。2018年5月,MJO有20 d持续位于这两个位相,且振幅均超过1,是有MJO监测以来5月这两个位相最多的一年。因此,无论是统计分析还是个例都表明MJO对本次春末南方高温有重要影响。     

赤道MJO活动对南海夏季风爆发的影响

利用1979—2013年NCEP/DOE再分析资料的大气多要素日平均资料、美国NOAA日平均向外长波辐射资料和ERSST月平均海温资料,分析赤道大气季节内振荡(简称MJO)活动对南海夏季风爆发的影响及其与热带海温信号等的协同作用.结果表明,赤道MJO活动与南海夏季风爆发密切联系,MJO的湿位相(即对流活跃位相)处于西太平洋位相时,有利于南海夏季风爆发,而MJO湿位相处于印度洋位相时,则不利于南海夏季风爆发.赤道MJO活动影响南海夏季风爆发的物理过程主要是大气对热源响应的结果,当MJO湿位相处于西太平洋位相时,一方面热带西太平洋对流加强使潜热释放增加,导致处于热源西北侧的南海—西北太平洋地区对流层低层由于Rossby响应产生气旋性环流异常,气旋性环流异常则有利于西太平洋副热带高压的东退,另一方面菲律宾附近热源促进对流层高层南亚高压在中南半岛和南海北部的建立,使南海地区高层为偏东风,从而有利于南海夏季风建立;当湿位相MJO处于印度洋位相时,热带西太平洋对流减弱转为大气冷源,情况基本相反,不利于南海夏季风建立.MJO活动、孟加拉湾气旋性环流与年际尺度海温变化协同作用,共同对南海夏季风爆发迟早产生影响,近35年南海夏季风爆发时间与海温信号不一致的年份,基本上是由于季节转换期间的MJO活动特征及孟加拉湾气旋性环流是否形成而造成,因此三者综合考虑对于提高季风爆发时间预测水平具有重要意义.