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81.
This paper provides a comprehensive assessment of Asian summer monsoon prediction skill as a function of lead time and its relationship to sea surface temperature prediction using the seasonal hindcasts of the Beijing Climate Center Climate System Model, BCC_CSM1.1(m). For the South and Southeast Asian summer monsoon, reasonable skill is found in the model's forecasting of certain aspects of monsoon climatology and spatiotemporal variability. Nevertheless, deficiencies such as significant forecast errors over the tropical western North Pacific and the eastern equatorial Indian Ocean are also found. In particular, overestimation of the connections of some dynamical monsoon indices with large-scale circulation and precipitation patterns exists in most ensemble mean forecasts, even for short lead-time forecasts. Variations of SST, measured by the first mode over the tropical Pacific and Indian oceans, as well as the spatiotemporal features over the Niño3.4 region, are overall well predicted. However, this does not necessarily translate into successful forecasts of the Asian summer monsoon by the model. Diagnostics of the relationships between monsoon and SST show that difficulties in predicting the South Asian monsoon can be mainly attributed to the limited regional response of monsoon in observations but the extensive and exaggerated response in predictions due partially to the application of ensemble average forecasting methods. In contrast, in spite of a similar deficiency, the Southeast Asian monsoon can still be forecasted reasonably, probably because of its closer relationship with large-scale circulation patterns and El Niño-Southern Oscillation.  相似文献   
82.
The predictability of the position, spatial coverage and intensity of the East Asian subtropical westerly jet(EASWJ) in the summers of 2010 to 2012 was examined for ensemble prediction systems(EPSs) from four representative TIGGE centers,including the ECMWF, the NCEP, the CMA, and the JMA. Results showed that each EPS predicted all EASWJ properties well, while the levels of skill of all EPSs declined as the lead time extended. Overall, improvements from the control to the ensemble mean forecasts for predicting the EASWJ were apparent. For the deterministic forecasts of all EPSs, the prediction of the average axis was better than the prediction of the spatial coverage and intensity of the EASWJ. ECMWF performed best, with a lead of approximately 0.5–1 day in predictability over the second-best EPS for all EASWJ properties throughout the forecast range. For probabilistic forecasts, differences in skills among the different EPSs were more evident in the earlier part of the forecast for the EASWJ axis and spatial coverage, while they departed obviously throughout the forecast range for the intensity. ECMWF led JMA by about 0.5–1 day for the EASWJ axis, and by about 1–2 days for the spatial coverage and intensity at almost all lead times. The largest lead of ECMWF over the relatively worse EPSs, such as NCEP and CMA, was approximately 3–4 days for all EASWJ properties. In summary, ECMWF showed the highest level of skill for predicting the EASWJ, followed by JMA.  相似文献   
83.
The performances of various dynamical models from the Asia-Pacific Economic Cooperation(APEC) Climate Center(APCC) multi-model ensemble(MME) in predicting station-scale rainfall in South China(SC) in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME's ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output(DMO) over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.  相似文献   
84.
陈见  李佳颖  高安宁  梁维亮  赵金彪 《气象》2015,41(3):372-379
利用常规MICAPS数据资料,对广西“回南天”发生特征及预报着眼点进行分析研究。结果表明:(1) “回南天”发生在春季低温阴雨后期迅速回暖的转变过程中;(2) 有利“回南天”发生的环流形势共同特征为: 500 hPa我国北支西风气流转为纬向环流,南支槽加深并向东移动,850 hPa有西南急流,地面冷空气减弱,华南静止锋减弱北抬;(3) T lnp探空曲线中,锋区逆温层上限持续下降到850 hPa以下,次日落地消失;(4) 室外空气露点温度高于室内物体表面温度,暖湿空气中的水汽入室遇冷后,在物体表面发生相变凝结;(5) 根据前一天最低气温、当天露点温度及升幅,将“回南天”划分为重度、中度和轻度3个等级;(6)“回南天”有冷性结束和暖性结束两种方式。所得成果可应用到预报业务中。  相似文献   
85.
黄、渤海冷空气海浪场的集合预报试验   总被引:1,自引:0,他引:1  
利用欧洲集合天气预报系统51个预报风场驱动SWAN海浪模式,对黄、渤海2013年12月-2014年2月期间受冷空气影响的海浪场进行数值模拟试验,并利用浮标观测资料对海浪集合预报结果进行初步检验分析,结果显示:从逐时平均偏差结果可知,24h预报时效内集合平均与控制预报性能相近,48~72h预报时效内,集合平均明显优于控制预报,但均比实况偏小;集合分位值(75、90百分位值和极端值)明显优于集合平均,且预报时效越长,优势越明显,集合预报极端值与实况相当或略偏大;从逐24h平均偏差结果可知,集合分位值(75、90百分位值和极端值)比集合平均和控制预报更接近实况。总的分析表明:集合分位值(75、90百分位值和极端值)对受冷空气影响的海浪场具有较强的分辨能力,可以提高对海浪场的预报水平,且有较好的应用潜力。  相似文献   
86.
基于稀疏AR模型的潮流信号建模与预报   总被引:1,自引:0,他引:1  
潮流信号处理与预报在很多方面具有非常重要的意义和价值。本文引入信号稀疏表示理论,构建一种稀疏AR模型,寻找各潮流数据间的历史关联性,并进行预报分析。首先由实测潮流信号进行常规AR建模,获得一组过完备稀疏基;其次随机从该过完备稀疏基抽取部分建立欠定方程组,利用稀疏优化算法获得最稀疏的AR系数;多次重复上一步,获得稀疏AR系数的平均以增强稀疏AR模型的稳定性;最后利用这些稀疏AR系数来重构或预测潮流信号。文章针对实测潮流信号,特别是存在多峰值有回流现象的潮流信号,进行了稀疏AR建模与预测的多次实验。实验结果与传统的潮流信号调和预报方法相对比,发现基于稀疏AR模型的潮流预报对于潮流存在多变的现象时,具有明显优越性,从回报结果来看,稀疏AR模型的潮流预报均方差明显小于传统潮流调和分析预报方法。  相似文献   
87.
青岛近海大型水母漂移集合预测方法研究   总被引:1,自引:0,他引:1  
考虑水母垂直运动等自主运动,基于集合预报和拉格朗日粒子追踪方法,建立青岛近海大型水母的集合漂移预测模型。并利用2012—2013年青岛近海水母实时监测数据和集合漂移预测模型,快速预测水母集合漂移轨迹、速度、趋势和可能影响范围等要素。通过分析水母监测数据和数值模拟结果,在水母如何自主运动及其机理尚不十分清楚的情况下,多轨迹漂移预测结果比单轨迹的更合理、科学、可信,能够传达更多的信息量,对水母灾害的应急处置更具有指导意义。  相似文献   
88.
Regional deterministic and ensemble surge prediction systems (RDSPS and RESPS respectively) are used to forecast sea levels off the east of Canada and northeast US. The surge models for the RDSPS and RESPS have grid spacings of 1/30° and 1/12° respectively. The models are driven by surface air pressure and 10 m winds generated by operational global deterministic and ensemble prediction systems that are run operationally by the Canadian Meteorological Centre. Surge forecasts are evaluated for the period 1 March, 2013 to 31 March 2014. Based on traditional statistics (e.g., standard deviation of the difference between observations and predictions) both systems are shown to have skill in forecasting surges six days into the future. It is shown however that skill exists beyond six days if allowance is made for errors in the timing of large surges. The usefulness of the RESPS is demonstrated for two positive surges (important for coastal flooding and erosion) and a negative surge (important for safe navigation in shallow water). It is shown that the RESPS can identify events not forecast by the RDSPS, and can also add useful additional information on the timing of the surge, an important consideration in tidally dominated waters. Several new types of display are used to illustrate the sort of information that can be generated by the RESPS to support the issuers of warnings of unusually high and low total water levels.  相似文献   
89.
Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC (National Meteorological Center) method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data. In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors. The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated.  相似文献   
90.
韩佳芮  严中伟  矫梅燕  叶谦  赵琳娜 《气象》2011,37(6):649-658
基于近年来涌现的有关新一代气象预报系统发展的认识,本文提出用户导向的交互式预报系统的概念模型。新系统强调在用户信息分析的基础上,发展从用户出发再回到用户不断自我改善的预报流程。系统组成的关键模块包括:用户端风险决策动态需求分析模块、物理预测模块、用户目标量的降尺度模块,用户端专业耦合模块及用户风险决策模块。文中阐述了系统中各模块间的联系、用户端信息在系统中的反馈作用以及具体的“交互式”方式。以临沂地区水文用户为例,以引发洪涝的降水事件为预报对象,利用TIGGE全球超集合预报,初步构建了一个临沂水文用户导向的可能致洪降水交互式预报系统。这个具备迭代式自我完善功能的新型预报系统包含了汛期随时变化的用户决策信息、由前期影响雨量和当前水文条件决定的可变致洪降水阈值以及一个动态的用户端预报水平和不确定性评估模块。初步结果表明,结合用户端信息的预报优于未考虑用户信息的预报结果,从而更直接地帮助用户进行防汛决策。个例研究也为发展更完整的用户导向预报系统提供了参考。  相似文献   
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