SVD方法在气象场诊断分析中的普适性

本文首次从理论上推导证明两个气象场的奇异值分解（ＳＶＤ）在气象场时空分布耦合信号的诊断分析中具有普适性。结果表明，两个场的ＳＶＤ求解准则不同于典型相关分析（ＣＣＡ），且ＣＣＡ模型可视为ＳＶＤ之特例，尤其当各个场经ＰＣＡ滤波后，其ＣＣＡ完全与ＳＶＤ等价。ＳＶＤ分析的结果不但可完全代替ＣＣＡ，且计算更简便，所得耦合信号的物理解释更清晰，特别适合于大尺度气象场的遥相关型研究。     

风云静止与极轨卫星产品在湖北暴雨监测和预报方法中的应用研究

根据2010—2014年风云2号(FY 2)和风云3号(FY 3)气象卫星资料,结合雷达资料、常规观测资料和数值预报产品等,利用多阈值法、面积重叠法进行了湖北省暴雨云团的识别跟踪方法研究;利用配料法进行了湖北省6 h暴雨短时预报方法研究。建立了以网页形式的风云系列卫星资料的暴雨监测预报业务系统,定量监测和预预暴雨的发生、发展。2014年应用检验结果表明,该系统对于湖北省暴雨的监测和预报有指导作用。     

An investigation of flux-variance methods and universal functions applied to three land-use types in unstable conditions

Fluxes calculated from three flux-variance methods, which depend upon three different forms of the normalized standard deviation functions (referred to as universal functions) of the surface atmospheric stability have been tested and compared with measurements for temperature and water vapour. The flux measurements were made over a fully leafed deciduous forest, a leafless deciduous forest and over a wetland region during the summer. The first method (referred to as the variance method) allows for certain constants, which are associated with the universal functions, to vary with land-use type and the scalar for which the flux is computed; the second method uses the form of the universal function developed by Tillman, which depends upon two constants; and the third method, known as the Wyngaard method, is the simplest and depends upon one constant only. Flux estimates from the variance method yield the best agreement with observations over the three hand-use types and the Wyngaard method appears to yield estimates that are quite comparable. The measurements for the univeral functions agree better with the Wyngaard function for temperature and better with the Tillman function for water vapour, although both show some scatter. The simplest formula developed by Wyngaard may be considered adequate for computing fluxes of temperature and water vapour from their variances. The main advantage of the formulae is to help define an upper limit for actual fluxes.     

Recurrence method for calculation of atmospheric cooling rate due to infrared radiation

A computational method for the mean slab transmissivities of water vapour and CO2 and a recurrence me-thod for the atmospheric cooling rate due to infrared radiation are developed and discussed in some detail in this paper.At first the spectra of water vapour and CO2 are divided into 10 and 2 basic bands according to the experi-mental data; then an analytic and universal expression of the mean slab transmissivity in those bands is obtained and checked with the experimental data at 220o, 260o and 300oK. Results show that the computational method developed in this paper has quite good accuracy, and therefore it can be used in the GCMs for calculations of the atmospheric cooling rates.The recurrence method for calculations of the upward and the downward fluxes of infrared radiation is de-rived and checked. It is proved that the method has a similar accuracy as others, but saves a lot of computation time. At last a simplified method of the transmissivity calculation, i.e. the tabulation method, is developed and its accuracy is checked as well.     

Objective time-scale-dependent homogenization of early instrumental temperature series

Summary An objective method for homogenization of early (pre ∼ 1850) instrumental near surface air temperature records is developed. The method is grounded on the same variational principle as used in the objective analysis of meteorological fields; i.e. the method consists of a statistically optimal spatial-coherence-based adjustment of nearby station temperature records. The adjustments are made for several different ranges of time scales, where the wavelet transform is used for the decomposition. The method takes into account that early instrumental temperature records are supposed to contain observational disturbances which are more or less smooth functions of time as a result of summations of numerous sources of biases. The method differs from traditional homogenization techniques in that corrections are not only made for a discrete number of abrupt or linear changes, but for continuously changing errors. The power of the method is illustrated with an example of homogenization of three very long temperature records from Sweden. Received August 31, 2000 Revised October 22, 2001     

一种求解区域平均值的权重面积设计及其应用

针对求解物理量在一定区域内的平均值问题，设计了一种权重面积方法。并以求解西北区域年平均降水量、1月份和7月份的平均空中水汽含量为例，将该方法与算术平均法、泰森多边形法、网格插值法进行了对比试验。结果发现该方法在站点较多、但不均匀的大范围区域内计算气象场的平均分布是可行的，其优点是计算量小、受缺测站点影响较小。     

Finite-dimensional quasi-Hamiltonian structure in simple model equations

Summary A simple systematic method has been developed to investigate the laws of conservation for approximating model equations. The main purpose of this paper is to identify these model equations as approximations of continuous Hamiltonian systems. If this identification is possible, the laws of conservation of the model system can be investigated as for a finite dimensional Hamiltonian system. Obviously, this method can be applied only in the case where the original continuous equations are Hamiltonian. The applicability of the general method has been verified by using three well-known finite-difference schemes as examples. These examples show that this technique is a possible systematic way to construct new conservative finite-difference approximations, as well as to identify the conserved quantities of well-known schemes.     

一次人工增雨作业中CA—FCM与其他评估方案的比较研究

根据2002年4月5日河南省人工催化增雨作业数据,分别采用作业区域趋势对比双比分析评估方案、区域趋势相关回归评估方案、区域趋势协变量多元回归评估方案、FCM（浮动对比区历史回归）评估方案、以降水量为协变量的CA—FCM评估方案和以降水量与整层大气可降水量为协变量的CA—FCM评估方案进行效果评估。结果表明：协变量由降水量和整层大气降水量2个组成的CA—FCM方法,由于引入了不受催化影响的物理协变量作为控制因子．以及采用了聚类分析提高了对比区和影响区相关性,其评估效果最好,显著水平高于0．05;其他评估方法评估效果较差。     

择优法降水集合预报试验的研究

基于集合平均预报方法的基础上，提出了择优法降水集合预报方法，以多物理过程集合预报系统为例，对该方法进行阐述和试验。利用集合预报系统各成员过去24 h预报的500 hPa和700 hPa温度差（T500-700）与实况温度差的相关系数作为集合预报成员的筛选因子，选择相关系数较大的成员作为集合成员进行降水集合预报试验。初步试验结果表明，择优法降水集合预报要略优于集合平均法的预报，24 h降水集合预报有所改善。择优法降水集合预报简单易行，在计算资源有限的情况下，可优先计算择优的成员，因此比集合平均法节约计算时间，提高集合预报时效，具有一定的业务应用价值。     

A new simple method for estimating monthly and daily solar radiation. Performance and comparison with other methods at Lleida (NE Spain); a semiarid climate

Summary A simple new method is proposed for estimating relative sunshine duration and solar irradiance on both a monthly and daily basis. The method requires the occurrence of precipitation, and maximum and minimum air temperatures as input. Comparisons with two other published simple methods: Bristow and Campbell (1984); and Hargreaves et al. (1985), and a modified version of the method proposed by McCaskill (1990), were conducted for a weather station at Lleida (NE Spain), which has a continental semiarid climate. The new method performed slightly better than the others mentioned above, mainly as a result of a reduction in errors when estimating cases of high solar radiation. Received May 23, 2000/Revised February 14, 2001     

一次人工增雨作业中CA-FCM与其他评估方案的比较研究

根据2002年4月5日河南省人工催化增雨作业数据,分别采用作业区域趋势对比双比分析评估方案、区域趋势相关回归评估方案、区域趋势协变量多元回归评估方案、FCM(浮动对比区历史回归)评估方案、以降水量为协变量的CA-FCM评估方案和以降水量与整层大气可降水量为协变量的CA-FCM评估方案进行效果评估。结果表明:协变量由降水量和整层大气降水量2个组成的CA-FCM方法,由于引入了不受催化影响的物理协变量作为控制因子,以及采用了聚类分析提高了对比区和影响区相关性,其评估效果最好,显著水平高于0.05;其他评估方法评估效果较差。     

Compilation method for 1 km grid data of monthly mean air temperature for quantitative assessments of climate change impacts

A new method is proposed to compile 1 km grid data of monthly mean air temperature by dynamically downscaling general circulation model (GCM) data with a regional climate model (RCM). The downscaling method used is a technique referred to as the pseudoglobal warming method to reduce GCM bias. For the grid data, RCM data were corrected with data from an existing meteorological network. The correction model for the RCM bias was developed by stepwise multiple regression analysis using the difference in the monthly mean air temperatures between the observation and RCM output as a dependent variable and the geographical factors as independent variables. Our method corrected the RCM bias from 1.69°C to 0.58°C for the month of August in the 1990s (1990–1999).     

Testing of the bandpass eddy covariance method for a long-term measurement of water vapour flux over a forest

The bandpass eddy covariance method has been used to measure the turbulent flux of scalar quantities using a slow-responsescalar sensor. The method issimilar in principle to the traditional eddy correlation method but includes the estimation of high-frequency components of the flux on the basis of cospectral similarity in the atmospheric surface layer. In order to investigate the performance of the method, measurements of the water vapour flux over a forest with the bandpass eddy covariance method and the direct eddy correlation method were compared. The flux obtained by the bandpass eddy covariance method agreed with that by the eddy correlation method within ±20% for most cases, in spite of a rather slow sensor-response of the adopted hygrometer. This result supports its relevance to a long-term continuous operation, since a stable, low-maintenance,general-purpose sensor canbe utilized for scalar quantities. Oneweak point of the method isits difficulty in principle to measure the correct flux when the magnitude of the sensible heat flux is very small, because the method uses the sensible heat flux as a standard reference for the prediction of undetectable high-frequency components of the scalar flux. An advanced method is then presented to increase its robustness. In the new method, output signals from a slow-response sensor are corrected using empirical frequency-responsefunctions for the sensor,thereby extending the width of the bandpass frequency region where components of the flux are directly measured (not predicted). The advanced method produced correct fluxes for all cases including the cases of small sensible heat flux. The advanced bandpass eddy covariance method is thus appropriate for along-term measurement of the scalar fluxes.     

登陆台风短时定量降水预报方法初探

利用登陆台风的GMS-5 IR1 TBB资料及地面自动站逐时雨量资料,初步建立了适用于登陆台风的定量降水估计(QPE)方法,基于QPE结果,采用外推法,初步实现了对登陆台风未来0~3 h的短时定量降水预报(QPF)。应用于0104号登陆台风“尤特”和0414号登陆台风“云娜”两个例表明:对单站逐小时雨量定量预报而言,如果50%相对误差可以接受,01、、23、h的QPF准确率分别达20%~70%、30%~80%、30%~70%、20%~60%;对于单站过程雨量定量预报而言,如果50%相对误差可以接受,0、1、2、3 h的QPF准确率基本都达60%~80%;对未来0~3 h的面雨量也具有一定定量预报能力。0~3 h QPF结果对实际短时登陆台风降水业务预报工作具有一定的参考价值。     

中期延伸天气预报方法研究

针对未来8—17 d中期预报方法短缺的现状,将数值预报产品与历史资料有效结合和应用,以天气学、统计学为基础,通过关键区相似预报等方法,研制出了一种通过计算环流相似和气候概率实现中期延伸预报的方法。结果表明:中期延伸天气预报方法能够反映未来天气演变和降水、气温的总体变化趋势。经过检验,认为可以应用于中期天气预报业务。     

气候年景定量化评价方法

气候年景评价是气候业务服务的重要产品——气候年公报的重要内容,其中评价方法是关键。旨在以福建省为例介绍一种计算简单、业务适用性强且易推广的气候年景定量化评价模型。基于福建省66个国家级气象站1961—2010年共50 a逐日气温、降水观测数据和综合气象干旱指数（MCI）数据,在分别建立低温年景、高温年景、雨涝年景和气象干旱年景的评价指标、等级划分标准和历史序列基础上,构建了综合气候年景的评价模型、等级划分标准和历史序列,实现了对福建省低温、高温、雨涝、气象干旱及综合气候年景的定量化评价且评价结果具有历史可比性。业务应用和历史事件验证显示所建评价指标体系合理,与历史重大事件一致性良好,可为汛期雨强、冬季低温强度、夏季高温强度等定量化评估提供参考。      

Spectral analysis method for a limited area using the eigenmodes of the spherical Laplacian operator

We propose a spectral analysis method using the eigenmodes of the spherical Laplacian operator on the limited area domain. Two numerical methods are considered for the horizontal discretization: One uses the half-ranged Fourier series for both longitudinal and latitudinal directions, and the other uses the Fourier finite-element method with piecewise linear basis functions for the latitudinal direction. The field variable for the two numerical algorithms is represented as linear combinations of the eigenvectors of the Laplacian operator on the limited area domain; we define the one-dimensional spectrum with the eigenvector coefficients as a function of the indices equivalent to the total wavenumbers of the Laplacian operator on the global domain. The spatial robustness of this method was verified through the self-consistency test comparing the spectra of isotropic Gaussian bells on the sphere. We used the method in the kinetic energy spectral analysis for a limited area with global atmospheric data, and compared the results for different seasons. The kinetic energy spectra represented the well-known characteristics with scale and different powers with season.     

Improvement in Background Error Covariances Using Ensemble Forecasts for Assimilation of High-Resolution Satellite Data

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.     

利用区域气候模式RIEMS产品分析日蒸散量及其影响

利用区域气候模式RIEMS输出的各种气象参数,采用了BEF等4种不同方法计算了沂沭河上游流域的潜在蒸散量,并与该流域6个气象站实测蒸发数据计算的陆面潜在蒸散量进行了比较。结果表明,根据平均偏差、平均绝对偏差、均方根差和相关系数指标的综合判断,该4种方法的估测精度从高到低依次为双线性曲面回归经验函数法(BEF)、Hargreaves-Samani(Harg)法、Pristley-Tayler(P-T)法和Penman-Monteith(P-M)法。在时间序列上,4种方法计算的逐日蒸散量与观测值呈相同的变化趋势,但计算值在蒸散发最强、最弱和降水最多、气温最高的7-9月有较大差异。BEF法估测的精度最高,与观测值最接近,Harg法、P-M法和P-T法都有明显的偏高现象。BEF法只需要较少的参数就能得到较高的估测精度,因此可作为利用区域气候模式RIEMS产品计算沂沭河流域蒸散量的首选方法,进而为RIEMS模式中耦合的陆面水文过程模型TOPX提供满足精度要求的日蒸散量驱动参数。     

单多普勒雷达径向风同化的改进

基于现有的单多普勒雷达径向速度资料直接同化和间接同化方法,提出了一种改进同化方法,通过引入反演方程组作为观测算子,将分析单元内径向风的空间变化信息作为同化变量。同时,根据模式的分辨率和精度要求调整分析单元大小,从而能够有效地弥补数据稀释化所带来的高分辨率数据遗失问题。相对于直接同化只同化雷达观测径向风,改进方法不仅包含径向风信息,而且包含径向风的空间变化信息;相对于传统的间接同化,改进方法不直接使用强约束求解析风场,避免了将反演风场完全等同于"观测风场",能够较大程度地克服反演误差对同化效果的影响。通过理想实验和观测系统模拟试验表明:改进方法对于传统的直接同化和间接同化具有一定的兼容性,应用灵活,具有积极的改进意义。