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).     

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.     

10-30天延伸期预报及其策略思考

在当前的气象预报业务中,10~30 d的延伸期预报是“无缝隙预报”中的难点。由于理论基础尚不完备,致使延伸期的准确预报还存在诸多困难。但对10~30 d延伸期预报业务迫切的社会需求,使其成为众多气象专家关注的研究热点。本文对10~30 d延伸期预报的概念、意义进行了阐述,在此基础上对其物理过程性质和预报困难的原因进行了分析。讨论了延伸期预报的预报对象,并在借鉴前人成果的基础上,总结归纳出了低频振荡方法、经验波传播方法、相似预报方法、物理统计方法、动力学方法（集合预报方法）、大气环流模式和中期模式集合方法、动力统计方法、综合集成方法等8种做延伸期预报的方法。     

Effect of vertical overturning circulation scale and moist static energy tendency on MJO phase speed

本文通过对1979-2019年ERA-I再分析资料进行诊断分析,研究了MJO垂直环流(VOC)纬向尺度和湿静力能(MSE)趋势纬向不对称性对MJO传播速度的综合影响.研究结果表明,MJO传播速度与VOC的纬向尺度和MSE趋势纬向梯度之间存在显著的正相关关系.基于上述两个参数,本文建立了线性回归模型,该模型可以较好的估计...     

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.     

Impact of convective momentum transport by deep convection on simulation of tropical intraseasonal oscillation

This paper focuses on the impacts of convective momentum transport (CMT) on simulations of the tropical intraseasonal oscillation (TIO) in SAMIL. Two sets of experiments are performed, which give different reality of the Madden-Julian Oscillation (MJO). The Tiedtke cumulus parameterization scheme is used for all experiments. It is found that simulations of the TIO can be influenced by CMT, and the impacts on the simulated TIO depend on the model capability in simulating the MJO. CMT tends to have large influences to the model that can simulate the eastward propagation of the MJO. CMT can further influence the long-term mean of zonal wind and its vertical shear. Zonal wind suffers from easterlies biases at low level and westerlies biases at upper level when CMT is introduced. Such easterlies biases at low level reduce the reality of the simulated tropical intraseasonal oscillation. When CMT is introduced in the model, MJO signals disappear but the model’s mean state improves. Therefore, a more appropriate way is needed to introduce CMT to the model to balance the simulated mean state and TIO signals.     

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。     

MJO与中间层-低热层风场潮汐DE3季节内变化性的关联

本文结合TIMED-TIDI卫星与流星雷达子午链风场观测数据,分析了中间层-低热层（MLT）区域非迁移潮汐DE3的季节内变化性及其与对流层MJO的可能关联.结果揭示了DE3风场潮汐广泛存在显著的宽频带季节内变化信号,且强度存在季节依赖.纬向风DE3潮汐（DE3-U）季节内变化在北半球冬季具有较强幅值,可达季节平均的1~2倍,而在其他季节通常在20%以内.结合MJO指数进一步讨论了不同季节下DE3-U对MJO的响应.统计结果表明,在影响较大的北半球冬季,DE3-U通常在MJO第4—6位相时有更大的幅值（+10%~+40%）,而在其余位相时更小（-10%~-40%）.这表明对流层与MJO相关的对流活动通过潜热释放的纬向变化可影响高空大气非迁移潮汐的强度.

     

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.     

MJO对我国东部春季降水影响的分析

利用澳大利亚气象局的MJO(Madden-Julian Oscillation)指数,通过位相合成及对比分析研究了MJO对我国东部春季降水的影响.研究表明,当MJO传播至中东印度洋时,我国长江中下游地区的春季降水为正异常,当其进一步东传至中南半岛-印尼群岛一带时,我国华南地区的春季降水为正异常,而在其他活动阶段不利于我国东部的春季降水.对比分析表明,MJO的活动主要通过引起大尺度环流异常、对流层中低层涡度及水汽输送的异常,进而对我国东部春季降水产生明显的影响.