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西北太平洋热带气旋频数的年际、年代际变化及预测 总被引：4，自引：0，他引：4
利用1950-2009年60 a的热带气旋资料、NOAA海温、NCEP再分析资料及74项环流指数等资料,研究了西北太平洋热带气旋频数的年际、年代际变化特征,结果表明,西北太平洋热带气旋生成频数既有显著的年际变化,同时也存在明显的年代际变化。自1950年以来,西北太平洋热带气旋频数经历了一个先增加再减少的过程,其中转折点在20世纪70年代中后期,与之相对应,热带气旋路径频数也呈现明显年代际变化。在此基础上,通过分析前期春季海温场、大气环流异常及环流指数与夏季(6-10月)热带气旋生成频数的相关关系,选取了影响夏季西北太平洋热带气旋活动频数的预测因子,建立了一个夏季西北太平洋热带气旋生成频数的多元回归预测模型。检验结果表明,该模型能较好地拟合1951-2003年夏季西北太平洋热带气旋生成频数的年际变化,拟合率为0.6。对2004-2009年夏季热带气旋生成频数的独立样本预测试验表明,该模型对夏季西北太平洋热带气旋活动频数具有较好的预测能力,可以为热带气旋业务预报提供一定参考。 相似文献
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利用海气耦合模式预测的大尺度环流进行热带气旋年频数的预测试验 总被引：2，自引：1，他引：1
基于对热带气旋生成频数和大尺度环流相关关系的分析,利用SINTEX-F海气耦合模式预测的大尺度大气环流信息,通过提取模式预测较好与热带气旋生成密切相关的有用信息,建立了一个基于动力模式预测结果的南海和西太平洋热带气旋年频数预测模型,并对1982—2010年的热带气旋生成频数进行预测试验与检验。SINTEX-F海气耦合模式能够较好预测部分与热带气旋生成密切相关的大尺度环流特征,其中包括热带气旋活动区域的海平面气压、对流层风垂直切变、850 hPa热带辐合带和850 hPa 90°E附近的越赤道气流。利用这些大尺度环流建立的预测因子与热带气旋生成频数有很好的相关关系,利用这些预测因子建立的多元回归预测模型对热带气旋频数的拟合率为0.8(相关系数,超过99.9%的信度检验)。预测模型的交叉检验结果表明模型整体预测效果较好。交叉检验预测结果与实况热带气旋频数的相关为0.71(超过了99.9%的信度检验),距平同号率为82.8%。但模型对热带气旋异常年的预测误差较大。 相似文献
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《湖北气象》2016,(3)
利用1982—2013年海南岛18个自动站日降水量、NCEP/NCAR逐月2.5°×2.5°再分析资料、NOAA海温及CFSv2模式的历史回报数据,分析海南秋季暴雨异常的同期环流特征及其与海温的关系。并利用模式预测较好的与秋季暴雨日数密切相关的环流因子、海温构建秋季暴雨日数预测模型。结果表明:(1)秋季暴雨多寡与环流异常关系密切。秋季暴雨偏多年,海南附近盛行偏东风;热带西太平洋-南海气压偏低,热带系统趋于活跃,且该区为东南风异常,带来充沛水汽;西太平洋纬向风切变偏弱,易形成暖心结构,对应有台风的发生发展。另一方面,海温强迫影响显著,热带中东太平洋海温异常影响着大气环流和热带对流活动,造成秋季降水异常。(2)热带太平洋地区中低层高度场、海平面气压、低层风及纬向风切变与秋季暴雨日数关系密切,且CFSv2模式能较好预测这些环流场上的高影响区。(3)利用最优子集回归构建基于模式有效信息的秋季暴雨日数模型,交叉检验和独立样本试验均表明,该预测方法与模型整体预测效果较好,可为秋季暴雨日数的预测提供参考。 相似文献
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温室气体浓度增加情景下西北太平洋热带气旋变化的模拟分析 总被引：3，自引：1，他引：2
利用德国Max-Planck气象研究所参与政府间气候变化委员会(The Intergovernmental Panelon Cli-mate Change,IPCC)第四次评估报告的气候系统模式(ECHAM5/MPI-OM)的数值模拟结果,分析研究了全球增暖背景下西北太平洋热带气旋的变化。结果表明,ECHAM5模式较好的模拟出了热带气旋的基本结构和频数的分布特征。当大气中CO2浓度增加时,热带气旋中心的最低气压升高,850hPa正涡度降低,风速减小,风场出现反气旋性环流异常,暖心强度减弱,气旋的低层径向流入和高层径向流出减少,气旋总体强度减弱。CO2浓度的增加会总体上减少西北太平洋热带气旋的生成频数,从模拟结果看年均减少10个左右。就CO2浓度增加对热带气旋频数季节变化的影响而言,CO2浓度增加所引起气旋频数减少较平均的分配到多个月份里,表明CO2浓度增加引起的大气环流异常在全年都会对西北太平洋热带气旋的发生频数产生影响。分析加拿大参加IPCC第四次评估报告的CGCM3.1(T47)模拟资料,其结果与ECHAM5资料得到的结果大致相似。 相似文献
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利用夏威夷大学IPRC高分辨率区域气候模式,对西北太平洋热带主要气旋活动季节(6—10月)热带气旋活动的特征及其大尺度环境场进行了17年的模拟试验,检验了模式对西北太平洋热带气旋的潜在季节预测能力。试验结果表明,该模式对西北太平洋热带气旋大尺度环境场具有较好的刻画能力,模拟的热带气旋年生成频数与实况的相关系数为0.77,季节内各月生成频数相关系数为0.82,显示出良好的潜在预测能力;生成源地分布与实况较一致;总能量(PDI)的年际变化趋势模拟也较为理想。但模拟的路径频数在南海地区明显偏多,北上热带气旋偏少,最大风速的峰值区间模拟效果较差。 相似文献
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高低层纬向风异常与西北太平洋热带气旋生成年频数关系的研究 总被引：5，自引：6，他引：5
采用相关和合成分析方法,研究了热带太平洋地区大尺度高低层纬向风异常与西北太平洋热带气旋生成年频数的关系及其影响的可能机理。结果表明：赤道东太平洋地区ΔU200-ΔU850〉0,西太平洋热带地区ΔU200-ΔU850〈0,热带太平洋地区沃克环流偏强,西北太平洋热带气旋生成年频数偏多。高低层纬向风异常年,对流层上、下部环流和对流层中垂直运动有显著的特征。在短期气候预测的时间尺度上,前期高低层纬向风异常可以作为预测热带气旋生成年频数的前兆信号。 相似文献
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在分析研究太平洋海气耦合经向模（Pacific Meridional Mode——PMM）和西北太平洋生成热带气旋频数变化关系的基础上,利用NCAR的大气环流模式CAM3模拟研究了太平洋海气耦合经向模态对西北太平洋生成热带气旋的影响。结果表明,海气耦合的经向模态通过影响热带气旋生成的大尺度环境从而影响热带气旋的频数和强度。在模式中当增加了PMM的海温强迫后,纬向风切变变小,对流层中低层相对湿度变大,热带西太平洋对流层低层出现西风异常,在西北太平洋地区形成一个异常的气旋性环流,并且匹配有较大的正涡度异常;对流层高层出现赤道东风异常和一个与低层气旋性环流相匹配的反气旋性环流,有利于对流活动的发展,从而有利于热带气旋的生成和发展。在增加了PMM的海温强迫的试验中,热带气旋中心的海平面最低气压降低,850 hPa中心附近最大切向风速增加,气旋中高层的暖心强度增强。热带气旋强度总体增加。数值模拟结果与资料分析相互映证,揭示了太平洋经向模态对西北太平洋热带气旋有重要影响。 相似文献
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使用1951-1997年影响广西的热带气旋年频数与前期和同期的海温场、500hPa高度场进行相关分析,结果表明,赤道太平洋海区的海温与影响广西的热带气旋年频数有密切关系,厄尔尼诺年副高强度偏强,西伸脊点偏西,影响广西的热带气旋偏少,拉尼娜年副高偏弱,影响广西的热带气旋偏多.然后挑选相关系数高的高相关区,以其为预报因子,利用相似分析方法和逐步回归方法对影响广西的热带气旋年频数作预报试验.结果表明,用相似离度方法做预报时,第1相似对特多特少年的预报基本可信,而第2、3相似预报不稳定;用逐步回归建立的预报方程平均拟合误差约为1个,1998和1999年的试报效果较好. 相似文献
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Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SINTEX-F coupled model is used to build a statistical model to predict the cyclogenesis frequency over the South China Sea and the western North Pacific. The SINTEX-F coupled model has relatively good prediction skill for some circulation features associated with the cyclogenesis frequency including sea level pressure, wind vertical shear, Intertropical Convergence Zone and cross-equatorial air flows. Predictors derived from these large-scale circulations have good relationships with the cyclogenesis frequency over the South China Sea and the western North Pacific. A multivariate linear regression （MLR） model is further designed using these predictors. This model shows good prediction skill with the anomaly correlation coefficient reaching, based on the cross validation, 0.71 between the observed and predicted cyclogenesis frequency. However, it also shows relatively large prediction errors in extreme tropical cyclone years （1994 and 1998, for example）. 相似文献
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MJO prediction in the NCEP Climate Forecast System version 2 总被引：3，自引：0，他引：3
Wanqiu Wang Meng-Pai Hung Scott J. Weaver Arun Kumar Xiouhua Fu 《Climate Dynamics》2014,42(9-10):2509-2520
The Madden–Julian Oscillation (MJO) is the primary mode of tropical intraseasonal climate variability and has significant modulation of global climate variations and attendant societal impacts. Advancing prediction of the MJO using state of the art observational data and modeling systems is thus a necessary goal for improving global intraseasonal climate prediction. MJO prediction is assessed in the NOAA Climate Forecast System version 2 (CFSv2) based on its hindcasts initialized daily for 1999–2010. The analysis focuses on MJO indices taken as the principal components of the two leading EOFs of combined 15°S–15°N average of 200-hPa zonal wind, 850-hPa zonal wind and outgoing longwave radiation at the top of the atmosphere. The CFSv2 has useful MJO prediction skill out to 20 days at which the bivariate anomaly correlation coefficient (ACC) drops to 0.5 and root-mean-square error (RMSE) increases to the level of the prediction with climatology. The prediction skill also shows a seasonal variation with the lowest ACC during the boreal summer and highest ACC during boreal winter. The prediction skills are evaluated according to the target as well as initial phases. Within the lead time of 10 days the ACC is generally greater than 0.8 and RMSE is less than 1 for all initial and target phases. At longer lead time, the model shows lower skills for predicting enhanced convection over the Maritime Continent and from the eastern Pacific to western Indian Ocean. The prediction skills are relatively higher for target phases when enhanced convection is in the central Indian Ocean and the central Pacific. While the MJO prediction skills are improved in CFSv2 compared to its previous version, systematic errors still exist in the CFSv2 in the maintenance and propagation of the MJO including (1) the MJO amplitude in the CFSv2 drops dramatically at the beginning of the prediction and remains weaker than the observed during the target period and (2) the propagation in the CFSv2 is too slow. Reducing these errors will be necessary for further improvement of the MJO prediction. 相似文献
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The seasonal footprinting mechanism (SFM) is thought to be a pre-cursor to the El Nino Southern Oscillation (ENSO). Fluctuations in the North Pacific Oscillation (NPO) impact the ocean via surface heat fluxes during winter, leaving a sea-surface temperature (SST) “footprint” in the subtropics. This footprint persists through the spring, impacting the tropical Pacific atmosphere–ocean circulation throughout the following year. The simulation of the SFM in the National Centers for Environmental Prediction (NCEP)/Climate Forecast System, version 2 (CFSv2) is likely to have an impact on operational predictions of ENSO and potentially seasonal predictions in the United States associated with ENSO teleconnection patterns. The ability of the CFSv2 to simulate the SFM and the relationship between the SFM and ENSO prediction skill in the NCEP/CFSv2 are investigated. Results indicate that the CFSv2 is able to simulate the basic characteristics of the SFM and its relationship with ENSO, including extratropical sea level pressure anomalies associated with the NPO in the winter, corresponding wind and SST anomalies that impact the tropics, and the development of ENSO-related SST anomalies the following winter. Although the model is able to predict the correct sign of ENSO associated with the SFM in a composite sense, probabilistic predictions of ENSO following a positive or negative NPO event are generally less reliable than when the NPO is not active. 相似文献
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This study investigates the variation and prediction of the west China autumn rainfall (WCAR) and their associated atmospheric circulation features, focusing on the transitional stages of onset and demise of the WCAR. Output from the 45-day hindcast by the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) and several observational data sets are used. The onset of WCAR generally occurs at pentad 46 and decays at pentad 56, with heavy rainfall over the northwestern China and moderate rainfall over the south. Before that, southerly wind changes into southeasterly wind, accompanied by a westward expansion and intensification of the western Pacific subtropical high (WPSH), favoring rainfall over west China. On the other hand, during the decay of WCAR, a continental cold high develops and the WPSH weakens and shifts eastward, accompanied by a demise of southwest monsoon flow, leading to decay of rainfall over west China. The CFSv2 generally well captures the variation of WCAR owing to the high skill in capturing the associated atmospheric circulation, despite an overestimation of rainfall. This overestimation occurs at all time leads due to the overestimated low-level southerly wind. The CFSv2 can pinpoint the dates of onset and demise of WCAR at the leads up to 5 days and 40 days, respectively. The lower prediction skill for WCAR onset is due to the unrealistically predicted northerly wind anomaly over the lower branch of the Yangtze River and the underestimated movement of WPSH after lead time of 5 days. 相似文献
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Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts 总被引：3，自引：1，他引：2
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. 相似文献
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Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter 总被引：1，自引：1，他引：0
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. 相似文献
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2013年影响海南热带气旋异常偏多成因分析 总被引：1，自引：0，他引：1
利用1983-2013年热带气旋年鉴、NCEP/NCAR全球再分析格点资料及国家气候中心74项环流指数资料等,统计分析了近30a西太平洋以及影响海南的热带气旋特征,并对2013年西太平洋热带气旋偏多、秋台集中以及影响海南热带气旋偏多的异常特征从天气学等方面进行了分析。结果表明,副热带高压、夏季风、越赤道气流、海表温度及北半球极涡等环流系统异常,是形成2013年西太平洋热带气旋偏多的主要原因。南半球冷高压发展激发越赤道气流增强,引发赤道西风加强;副热带高压偏北偏弱,夏季风增强,副高南侧热带辐合带对流活跃;南海-西太平洋海表温度偏高;极涡偏弱偏西,经向环流偏弱,中纬度冷空气活动不频繁等。多条件共同作用,有利于西太平洋热带气旋的生成。另外,副高呈东西向分布,南海海表温度偏高使得南海及菲律宾以东生成的热带气旋易于向西移动影响海南。 相似文献
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本文研制建立了一个预测青海省夏季降水的动力—统计相结合的组合降尺度预测方法（Hybrid Statistical Downscaling Prediction，HSDP），该方法综合利用了气候模式Climate Forecast System 2.0版本（CFSv2）实时预测的高可预报性环流信息及前期观测的与青海夏季降水具有高相关性的气候因子，采用年际增量方法，基于气候变量的年际增量规律建立统计模型，从而实现对青海夏季降水进行动力—统计相结合的气候预测。根据全球气候因子的年际增量与青海省夏季降水年际增量的相关系数，以及CFSv2预测产品对实况模拟能力的评估，选取以下关键区气候变量的年际增量作为预测因子：（1） CFSv2模式预测当年夏季包含贝加尔湖脊、乌拉尔山脊和新疆脊区域的500 hPa高度场；（2） CFSv2模式预测青藏高原以西200 hPa纬向风场；（3）观测资料中前1 a秋、冬季热带太平洋地区海表面温度场；（4）观测资料中前1 a秋、冬季西伯利亚地区的海平面气压场，对青海省夏季降水进行统计降尺度预测。统计降尺度模型利用1983—2011年进行建模，回报2012—2018年夏季青海省降水的空间分布和时间变化，并对该模型对1983—2011年的夏季青海省降水的回报能力进行了交叉检验。回报结果表明该统计降尺度模型对CFSv2的青海省夏季降水预测能力有显著的提高，能够很好地再现青海省夏季降水西北部的高原地区偏少，而在东南部偏多的特点。该模型预测所得2012—2018年夏季青海省降水的时间变化也与实况有着较高的相关系数（0.76），对于降水显著偏少的年份（如2015年）和显著偏多的年份（如2012、2018年）的降水预测都有很好的表现。对于建模时段的交叉检验结果（相关系数为0.46，比模型回报结果与实况的相关系数0.48略低）表明，该模型具有较高的稳定性和可靠性。 相似文献
19.
利用中国气象局热带气旋（TC）资料、NCEP/NCAR 再分析资料和美国 NOAA 向外长波辐射（OLR）等资料,分析了2010年西北太平洋（WNP）及南海（SCS）热带气旋活动异常的可能成因,讨论了同期大气环流配置和海温外强迫对TC生成和登陆的动力和热力条件的影响。结果表明,2010年生成TC频数明显偏少,生成源地显著偏西,而登陆TC频数与常年持平。导致7～10月TC频数明显偏少的大尺度环境场特征为：副热带高压较常年异常偏强、西伸脊点偏西,季风槽位置异常偏西,弱垂直风切变带位置也较常年偏西且范围偏小,南亚高压异常偏强,贝加尔湖附近对流层低高层均为反气旋距平环流,这些关键环流因子的特征和配置都不利于 TC 在WNP的东部生成。影响TC活动的外强迫场特征为：2010年热带太平洋经历了El Ni?o事件于春末夏初消亡、La Ni?a事件于7月形成的转换;7～10月,WNP海表温度维持正距平,140°E以东为负距平且对流活动受到抑制;暖池次表层海温异常偏暖,对应上空850 hPa为东风距平,有利于季风槽偏西和TC在WNP的西北侧海域生成。WNP海表温度和暖池次表层海温的特征是2010年TC生成频数偏少、生成源地异常偏西的重要外强迫信号。有利于7～10月热带气旋西行和登陆的500 hPa风场特征为：北太平洋为反气旋环流距平,其南侧为东风异常,该东风异常南缘可到25°N,并向西扩展至中国大陆地区;南海和西北太平洋地区15°N以南的低纬也为东风异常;在这样的风场分布型下,TC容易受偏东气流引导西行并登陆我国沿海地区。这是2010年生成TC偏少但登陆TC并不少的重要环流条件。 相似文献
20.
Zhiyan Zuo Song Yang Zeng-Zhen Hu Renhe Zhang Wanqiu Wang Bohua Huang Fang Wang 《Climate Dynamics》2013,40(11-12):3071-3088
The predictable patterns and predictive skills of monsoon precipitation in the Northern Hemisphere summer (June–July–August) are examined using reforecasts (1983–2010) from the National Center for Environmental Prediction Climate Forecast System version 2 (CFSv2). The possible connections of these predictable patterns with global sea surface temperature (SST) are investigated. The empirical orthogonal function analysis with maximized signal-to-noise ratio is used to isolate the predictable patterns of the precipitation for three regional monsoons: the Asian and Indo-Pacific monsoon (AIPM), the Africa monsoon (AFM), and the North America monsoon (NAM). Overall, the CFSv2 well predicts the monsoon precipitation patterns associated with El Niño-South Oscillation (ENSO) due to its good prediction skill for ENSO. For AIPM, two identified predictable patterns are an equatorial dipole pattern characterized by opposite variations between the equatorial western Pacific and eastern Indian Ocean, and a tropical western Pacific pattern characterized by opposite variations over the tropical northwestern Pacific and the Philippines and over the regions to its west, north, and southeast. For NAM, the predictable patterns are a tropical eastern Pacific pattern with opposite variations in the tropical eastern Pacific and in Mexico, the Guyana Plateau and the equatorial Atlantic, and a Central American pattern with opposite variations in the eastern Pacific and the North Atlantic and in the Amazon Plains. The CFSv2 can predict these patterns at least 5 months in advance. However, compared with the good skill in predicting AIPM and NAM precipitation patterns, the CFSv2 exhibits little predictive skill for AFM precipitation, probably because the variability of the tropical Atlantic SST plays a more important than ENSO in the AFM precipitation variation and the prediction skill is lower for the tropical Atlantic SST than the tropical Pacific SST. 相似文献