The experiment of monthly mean circulation prediction using the analogy-dynamical model

Based on the past related research work, a new nalogy-dynamical monthly prediction model is established ith the operational dynamic extended-range forecast model 63L16 (hereafter T63) as a dynamic kernel. The monthly ean circulation prediction with T63 is considered as a control experiment, and the prediction with the analogy-dynamical model as a contrast one. It is found that the nalogy-dynamical model has more precise forecast skill han the T63 model through monthly mean numerical prediction experiment.     

Forming proper ensemble forecast initial members with four-dimensional variational data assimilation method

A method has been presented to improve ensemble forecast by utilizing these initial members generated by four-dimensional variational data assimilation (4-D VDA), to conquer limitation of those initial members generated by Monte Carlo forecast (MCF) or lagged average forecast (LAF). This method possesses significant statistical characteristic of MCF, and by virtue of LAP that contains multi-time information and its initial members are harmonic with the dynamic model, six groups of numerical control and contrast experiments were performed with T42 spectral 4-D VDA system. The results show that in dekad range ensemble forecast with initial members generated by this method is prior to that by LAP. The anomaly correlation coefficient (ACC) of 500 hPa height in 10-d average by employing this method is 0.01-0.04 larger than by LAP, and root mean square error (RMSE) less than 0.2-0.4 dagpm.     

MODIS近红外资料反演大气水汽总含量

遥感反演大气水汽总含量对于研究水循环、全球气候变化、天气预报、遥感大气校正等具有重要意义。本文考虑了卫星扫描视场角的影响,实现并改进了用MODIS近红外资料反演大气水汽总含量的两通道比值反演模式,并用辐射传输模式定量讨论了误差。结果表明,反演值和探空均方根误差RMS=0.29 g/cm2,相关系数在92%。对月平均水汽分布的比较显示,反演水汽总含量与MODIS产品的分布是一致的,且更为合理。     

集合预报中初始扰动生成方法的探讨

阐述了4种生成集合预报初始扰动的方法,用其中的3种方法在微机版本的T63L9全球谱模式上进行了中期数值预报的集合预报试验,通过集合预报效果来检验初始扰动的优劣。结果表明：初始扰动的好坏对集合预报效果有至关重要的影响,总体而言,增长模繁殖法优于控制预报、蒙特卡洛法和时间滞后法,且集合预报的确能起到提高数值预报效果的作用。     

基于CAM3T42的云南5月降水的可预报性试验研究

取逐月地表温度作外强迫,用NCAR CAM3T42模式积分50a,获得1951～2000年的模式大气环流资料,截取40a的5月500hPa高度场与云南124个测站5月降水资料建立的基于CAM3T42公共预报因子集具有很好的一致性,可以用来讨论云南5月降水的可预报性.CAM3T42的5月500hPa高度场影响云南5月雨量的关键区主要分布在地中海、印度次大陆、西太平洋暖池、东北太平洋、北美等区域以及南印度洋、南太平洋和南大西洋等区域.应用公共预报因子集建立的云南124个测站5月雨量预报试验表明有113个复相关系数通过0.05的显著性检验,占总测站数的91%左右.利用10a样本作为独立预报检验表明复相关系数的量值与非独立样本检验的相比略有减小.试验结果和独立样本检验结果表明:5月CAMT42的500hPa高度场的变化与云南124测站5月降水间具有良好且稳定的关系,CAMT42对云南5月降水具有一定的预报能力.     

多层次降尺度方法对安徽省月降水量预测的研究

 利用1961～2004年多层次的NCEP环流资料初选出与台站月降水量的显著相关区,通过最优子集回归模型对各初选因子进行筛选和组合,形成了安徽省35个台站的月降水量回归模型,并分别利用NCEP资料和月动力延伸模式环流预报作为输入场对2005～2009年安徽省月降水量进行了回报.结果表明,该降尺度模型包含高低层的多种资料,各因子组合起来可以从统计上反映出一些影响降水的环流配置型,较传统的仅用500hPa资料的降尺度模型内容更为丰富.从回报的效果来看,预测值与实况值平均距平符号一致率为63%,PS评分为75分,其中对涝月的预测效果要好于旱月.     

基于主成分分析的BP神经网络长期预报模型

MATLAB是进行神经网络系统设计及多元统计分析的有力工具.利用MATLAB6.5对月平均降水量的前期预报因子进行主成分分析,实现样本的最优压缩,从而降低样本的维数,建立起基于主成分分析的神经网络广西北部地区5月平均降水预测模型.计算结果表明,基于主成分分析的神经网络模型在预测中与多元回归模型相比有较好效果.     

A physically-based statistical forecast model for the middle-lower reaches of the Yangtze River Valley summer rainfall

A new approach to forecast the middle-lower reaches of the Yangtze River Valley summer rainfall in June-August （JJA） is proposed in this paper. The year-to-year increment of the middle-lower reaches of the Yangtze River Valley is forecasted and hence the summer precipitation could be predicted. In this paper, DY is defined as the difference of a variable between the current year and the preceding year （year-to-year increment）. YR denotes the seasonal mean precipitation rate of the middle-lower reaches of the Yangtze River Valley summer rainfall. After analyzing the atmospheric circulation anomalies in winter and spring that were associated with the DY of YR, six key predictors for the DY of YR have been identified. Then the forecast model for the DY of YR is established by using the multi-linear regression method. The predictors for the DY of YR are Antarctic Oscillation, the meridional wind shear between 850hPa and 200hPa over the Indo-Australian region, and so on. The prediction model shows a high skill for the hindcast during 1997-2006, with the average relative root mean square error is at 18%. The model can even reproduce the upward and downward trends of YR during 1984--1998 and 1998--2006. Considering that the current operational forecast models of the summer precipitation over the China region have the average forecast scores at 60%--70% and that the prediction skill for the middle-lower reaches of Yangtze River Valley summer precipitation remains quite limited up to now, thus this new approach to predict the year-to-year increment of the summer precipitation over the Yangtze River Valley （and hence the summer precipitation itself） has the potential to significantly increase the operational forecast skill of the summer precipitation.     

南海夏季风建立日期的预报研究

利用1958-2001年ECMWF和1948-2006年NCEP的全球再分析气象资料,研究南海夏季风爆发迟早与前期气象要素场之间的关系。结果表明,南海夏季风建立日期与当年2月份全球风场(u、v、ω分量)、位势高度场、气温场等气象要素场之间都存在显著相关区。把各要素场中的显著高相关区视为影响季风建立日期的关键区,并定义关键区内的要素平均值为建立日期的预报因子,从中选取10个与建立日期关系最为紧密的预报因子建立预报方程,对季风建立日期进行预测。分析发现,有10个预报因子与季风建立日期有密切联系,对季风爆发迟早有一定的指示能力和预测作用。最后,经过SAS系统的分析和试验选择最好的回归预测方案,利用10个预测因子建立南海夏季风建立日期回归预报方程(简称回归预报方程)。对回归预测方程进行回报实验发现,拟合得到的南海夏季风建立日期与许多学者确定的建立日期之间的相关系数都达到95%以上的置信度,拟合误差基本控制在2候以内,有一定的预报能力。可以说,该方法是作为预报南海夏季风爆发迟早的一种新的尝试。     

东亚低纬地区大气臭氧时空分布特征

利用1979～1992年和1997～2008年2个时间段(分别称为Ⅰ期和Ⅱ期)的TOMS臭氧总量月平均网格资料,对东亚低纬地区大气臭氧的分布变化和纬度带特征进行了较为详细的对比研究.结果表明:①Ⅱ期较Ⅰ期区域大气臭氧浓度水平整体降低;区域臭氧浓度普遍低于同纬度其它区域,受地形和环流影响显著;②Ⅰ期和Ⅱ期区域平均及纬带平均臭氧浓度均表现为不同的季节和年际变化特征,南北有别,近赤道纬带和较高纬带有异;③Ⅰ期和Ⅱ期区域平均臭氧浓度时间序列除典型的年变化周期外,还有略低于QBO振荡的1.3～2.3a主周期,而区域赤道纬度带臭氧浓度QBO振荡却特别明显.值得注意的是,该1.3～2.3a主周期呈现区域南北半球部分的跷跷板式强弱振荡.     

T511L60全球中期数值预报性能统计评估

为了客观研究T511L60全球中期数值预报系统的性能特征,采用WMO（World Meteorological Organization）推荐的标准化的统计方法,对2008年5月到2010年5月累积2年的500 hPa形势场和降水预报资料进行了检验评估。形势场检验结果表明,T511L60全球中期数值预报在北半球的可用天数非常接近7 d,在亚洲地区的可用天数在6～7 d。降水检验结果表明,T511L60模式在中国地区的5 d小雨预报TS评分和预报偏差评分优于日本模式降水预报。     

Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing

Since the mid-nineteenth century the Earth's surface has warmed, and models indicate that human activities have caused part of the warming by altering the radiative balance of the atmosphere. Simple theories suggest that global warming will reduce the strength of the mean tropical atmospheric circulation. An important aspect of this tropical circulation is a large-scale zonal (east-west) overturning of air across the equatorial Pacific Ocean--driven by convection to the west and subsidence to the east--known as the Walker circulation. Here we explore changes in tropical Pacific circulation since the mid-nineteenth century using observations and a suite of global climate model experiments. Observed Indo-Pacific sea level pressure reveals a weakening of the Walker circulation. The size of this trend is consistent with theoretical predictions, is accurately reproduced by climate model simulations and, within the climate models, is largely due to anthropogenic forcing. The climate model indicates that the weakened surface winds have altered the thermal structure and circulation of the tropical Pacific Ocean. These results support model projections of further weakening of tropical atmospheric circulation during the twenty-first century.     

基于时变关键区和时滞多变量的长江下游10-30d低频降水实时预报

利用NCEP/NCAR逐日850 hPa再分析风场资料和长江下游地区25站逐日降水资料,采用Butterworth二阶20~30 d滤波,通过变系数时滞回归和关键区自动筛选方法,构建了长江下游地区汛期(5~8月)的延伸期低频降水实时预报模型方案,对1979、2013年的汛期降水分别做了回报和预报试验。结果表明,基于多变量时滞回归方程(MLR)的实时预报方案,能客观地反映影响长江下游夏季强降水的欧亚环流季节内振荡(ISO)传播特性的时间变化,为长江下游地区强降水延伸期预报提供主要信号。提出的实时预测方案中,关键区的选择随建模样本而变化,体现了ISO变化的多样性和一定程度的不稳定性,预测模型能及时适应大气内部动力过程和外部强迫引起的时滞相关结构的改变,在一定程度上提高了延伸期预报的能力。     

旱涝灾害的遗传-神经网络集成预测方法研究

利用遗传算法的全局搜索能力同时进化设计三层BP神经网络的结构和连接权,并以进化后的网络结构和连接权作为新的神经网络结构和初始连接权,再进行新一轮附加动量的BP神经网络训练,把训练后的结果简单平均集成,以此建立旱涝灾害的遗传-神经网络集成预测新方法。应用该方法对广西桂林6月(主汛期1995~2005年)的降水量进行实例预测的结果表明,该方法的收敛速度快,预报精度高,易于操作,是一种具有较高应用价值的预测方法。     

新丰江水库月径流预报模型

通过对研究的气候、水文气象物理因子的分析,挑选出与月径流关系最好的物理因子作为预报因子;利用逐步回归分析和预报集成方法建立月径流预报模型;模型应用结果表明,预报精度满足生产要求。     

基于EWT-PSO-Elman耦合模型在径流预测中的应用

由于径流序列的非线性和非平稳性,单一预测模型能力有限,难以做出准确预测。因此,论文基于澄碧河流域坝首站1979-2019年共41a的实测月径流序列,引入经验小波变换分解(EWT)、粒子群算法(PSO),建立一种基于Elman神经网络的组合月径流预测模型(EWT-PSO-Elman),并采用纳什效率系数(NSE)、平均相对误差绝对值(MAPE)和均方根误差(RMSE)对测试集的预测结果进行评价与分析,并将预测结果与EWT-PSO-BP、PSO-Elman、PSO-BP、Elman、BP模型进行比较。结果表明：EWT-PSO-Elman模型的纳什效率系数为0.9135,均方根误差为19.4511,预报等级为甲级,具有较好的预测精度和泛化能力;EWT-PSO-Elman模型的预测精度优于EWT-PSO-BP、PSO-Elman、PSO-BP、Elman、BP模型。可见,EWT-PSO-Elman模型具有更好的预测精度,可应用于径流预测研究中。     

桂林地区气温与降水量的时间序列预测模型

根据桂林地区2001～2010年各月平均气温和1987～2010年每年6月份降水量的实测数据,利用时间序列的季节指数法和线性外推法分别建立气温预测模型和降水量预测模型,再利用模型对桂林市2011年各月的气温和2011年9、11、12月的降水进行预测,得到比较理想的预测效果.     

An approach to improving the dynamical extended—range（monthly） prediction

Focusing on common and significant forecast errors-the zonal mean errors in the numerical prediction model,this report proposes an approach to improving the dynamical extended-range(monthly) prediction.Firstly,the monthly pentad-mean nonlinear dynamical regional predic-tion model of the zonal-mean haight based on a large number of historical data is constituted by employing the reconstruc-tion phase space theory and the spatio-temporal series pre-dictive method.The zonal height thus produced is trans-formed to its counterpart in the numerical model and fur-ther used to revise the numerical model prediction during the integration process.In this way,the two different kinds of prediction are combined.The forecasting experimenal results show that the above hybrid approach not only re-duces the systematical reeor of the numerical model,but also improves the forecast of the non-axisymmetric components due to the wave-flow interaction.     

淮河流域典型洪水年流量空间分布的季节特征

为了分析淮河流域洪水过程空间分布的季节变化特征,提高对典型洪水过程的认识,以TRMM 3B42卫星降水数据为驱动资料,利用分布式陆面-水文模型(LSX-HMS)模拟淮河流域典型洪水年(以2003年为例)的流量过程.结果表明:TRMM 3B42卫星数据能够较好地反映淮河流域降水的时空分布;LSX-HMS模型对流量时间变化过程的模拟精度较高;逐月流量空间分布给出了流域洪水过程的季节变化特征,准确反映了流量从南向北推进进而消退的空间演变过程.分布式水文模型对流量空间分布的模拟预测有助于流域洪水事件的预警与管理.     

Periodicity of sunspot activity in the modern solar cycles

Sunspot number, sunspot area and sunspot unit area are usually used to show sunspot activity. In this paper,periodicity of sunspot activity of modern solar cycles has been investigated through analyzing the monthly mean values of the three indices in the time interval of May 1874 to May 2004 by use of the wavelet transform. Their global power spectra and local power spectra are given while the statistical tests of these spectra are taken into account. The main results are (1) the local wavelet power spectrum of the sunspot number seems like that of the sunspot area, indicating that the periodicity of the both indices is similar. The local power spectrum of the sunspot unit area resembles the local power spectra of the previous two indices, but looks more complicated. (2) the possible periods in sunspot activity are about 10.6 (or 10.9 years for the sunspot unit area), 31,and 42 years, and the period of about 10.6 years is statistically significant in the considered time. For the periods of about 31 and 42 years, their power peaks are under the 95% confidence level line but over the mean red-noise spectral line, and for the other rest periods, their power peaks are even under the mean red-noise spectral line, which are statistically insignificant. (3) the local power of the three periods is higher in the late stage than in the early stage of the considered time. (4) the period characteristics of the three indices, shown in the global power spectra and the local power spectra, are similar but there is difference in detail.