Wind-Tunnel and Numerical Simulations of the Coastal Thermal Internal Boundary Layer

Wind-tunnel experiments in a thermally stratified wind tunnel and direct numerical simulations were performed to simulate the thermal internal boundary layer (TIBL) that developed over a coastal area in a sea-breeze flow. The results of the simulations were analyzed to investigate turbulence structure in the TIBL. To study the effects of the atmospheric stability over the sea on the TIBL, two vertical profiles of temperature were created in the upstream portion of the wind-tunnel experiment and the direct numerical simulation. Turbulence statistics of the TIBL changed significantly according to the temperature profile over the sea, indicating that the stability of the flow over the sea has a significant effect on the structure and turbulence characteristics of the TIBL. Furthermore, the TIBL heights were estimated from the vertical profiles of the local Richardson number. The estimated TIBL heights agreed with those predicted by a pre-existing relation, suggesting that both the wind-tunnel experiment and the direct numerical simulation accurately reproduced the growth of the TIBL.     

台风“桑美”的数值模拟和地形敏感性试验

用WRF模式对0608号台风“桑美”进行了数值模拟研究,较为成功地模拟出了台风路径和降水,但模拟的台风中心气压远高于实况。为研究“桑美”登陆期间地形的抬升作用对其降水及结构的影响,通过改变特定区域内的地形高度设计了一组敏感性试验。结果表明,台风登陆过程中地形抬升作用对台风降雨量有显著的增幅作用;台风中心位势涡度、气流垂直上升速度、水平水汽通量散度明显增大;地形抬升机制在台风登陆时刻达到最强。     

THE CHARACTERISTICS OF THUNDERSTORM FREQUENCY VARIATION AND THEIR POSSIBLE RELATION WITH THE ADJUSTMENT OF CROP DISTRIBUTION IN THE LEIZHOU PENINSULA

In order to research possible influences of the adjustment of plant distribution on the development frequency of thunderstorms over the Leizhou Peninsula, mathematic statistic methods, including correlation analyses, 11 kinds of fitting models and all-variable regression methods, were used for analyses and research. The results show that the average trend of the number of annual thunderstorm days is descending obviously, and there are thunderstorms in all seasons, in which warm post-midday thunderstorms have taken up the most part, and high frequency is found from May to September, and the starting and ending dates of thunderstorms have a great annual discrepancy. The vegetation structure has been improved along with the reduction of rice fields and the area increment of sugarcane and fruits planting, which results in the decrease of the number of thunderstorm days; the change in the characteristics of winter spare fields, which is caused by the planting of vegetables, limits the formation of thunderstorms in early winter and late spring. Meanwhile, the area adjustment of peanut planting has little influence on the variation of thunderstorm days. The adjustment of principal crop distribution, such as rice, sugarcane, fruits and vegetables, may have obvious influence on the formation of thunderstorms, and sugarcane has the largest effect, followed in turn by rice, vegetables and fruits, and the adjustment of crop distribution has little influence on the starting and ending dates of thunderstorms.     

碘化银播撒对云和降水影响的中尺度数值模拟研究

通过在WRF (Weather Research and Forecasting) 中尺度天气数值模式中引入碘化银与云相互作用过程, 建立了中尺度播撒碘化银数值模式。研究了碘化银播撒对于中尺度对流天气过程中云和降水的影响, 研究了不同播撒部位、 播撒时间和播撒剂量情况下碘化银的扩散、 传输及其对云中水成物和降水量的影响。研究结果表明, 碘化银在云中的扩散传输过程与播撒的位置有很大关系, 在最大上升气流区播撒的碘化银能随着气流更快地扩散到云体上部过冷水含量丰富的区域, 播撒在云上层入流区和云下层入流区的碘化银扩散到云中过冷水区需要时间更长, 同时有大部分停留在云体边缘。碘化银能与云中过冷水相互作用, 消耗过冷水使云中冰晶数浓度明显增加, 从而使霰粒子转化减少, 过冷水更多地转化为雪粒子, 过冷水凝结释放出潜热使上升气流增强, 促进了对流发展。由于雨水含量的增加, 地面降水也出现增加。碘化银播撒率对地面降水量影响很大, 当播撒率为0.6 g/s时, 播撒对降水的影响时间超过4小时, 增雨的效果更好。播撒率为0.1 g/s时增雨效果不明显, 当播撒率为1.2 g/s 时, 对总降水可能出现抑止作用。对比碘化银播撒率为0.6 g/s时12小时地面增雨量, 在云上层入流区播撒碘化银试验中, 地面增雨量比对最大过冷水含量区的催化试验提高了48.7%, 最大上升气流区播撒试验增雨效果最好, 地面增雨量比在最大过冷水区域播撒提高了72.1%。     

祁连山夏季西南气流背景下地形云形成和演化的观测研究

利用2007年祁连山地形云的观测试验资料,分析了祁连山夏季西南气流背景下地形云的演化过程,得到了祁连山地形云发展和演变的概念模型。(1)祁连山地形云的水汽主要分布在3500～6500m的范围内,对流层中层的西南气流将水汽由南向北输送到祁连山区。(2)祁连山区水汽比较丰沛,凝结高度和自由对流高度均较低,当湿气团抬升到凝结高度以上时对流有效位能很容易释放,形成有利于产生降水的云系。(3)祁连山每个山峰南北侧昼间的谷风会在山峰辐合抬升,众多山峰形成的祁连山群谷风的抬升作用下容易形成沿山脊排列的中β对流云带,在高空西南气流的推动下移到北侧,是造成北侧降水比南侧大的原因之一。     

An Economical Approach to Four-dimensional Variational Data Assimilation

Four-dimensional variational data assimilation (4DVar) is one of the most promising methods to provide optimal analysis for numerical weather prediction (NWP). Five national NWP centers in the world have successfully applied 4DVar methods in their global NWPs, thanks to the increment method and adjoint technique. However, the application of 4DVar is still limited by the computer resources available at many NWP centers and research institutes. It is essential, therefore, to further reduce the computational cost of 4DVar. Here, an economical approach to implement 4DVar is proposed, using the technique of dimension-reduced projection (DRP), which is called ``DRP-4DVar." The proposed approach is based on dimension reduction using an ensemble of historical samples to define a subspace. It directly obtains an optimal solution in the reduced space by fitting observations with historical time series generated by the model to form consistent forecast states, and therefore does not require implementation of the adjoint of tangent linear approximation. To evaluate the performance of the DRP-4DVar on assimilating different types of mesoscale observations, some observing system simulation experiments are conducted using MM5 and a comparison is made between adjoint-based 4DVar and DRP-4DVar using a 6-hour assimilation window.     

The Structure of Background-error Covariance in a Four-dimensional Variational Data Assimilation System: Single-point Experiment

A four dimensional variational data assimilation (4DVar) based on a dimension-reduced projection (DRP-4DVar) has been developed as a hybrid of the 4DVar and Ensemble Kalman filter (EnKF) concepts. Its good flow-dependent features are demonstrated in single-point experiments through comparisons with adjoint-based 4DVar and three-dimensional variational data (3DVar) assimilations using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The results reveal that DRP-4DVar can reasonably generate a background error covariance matrix (simply B-matrix) during the assimilation window from an initial estimation using a number of initial condition dependent historical forecast samples. In contrast, flow-dependence in the B-matrix of MM5 4DVar is barely detectable. It is argued that use of diagonal estimation in the B-matrix of the MM5 4DVar method at the initial time leads to this failure. The experiments also show that the increments produced by DRP-4DVar are anisotropic and no longer symmetric with respect to observation location due to the effects of the weather trends captured in its B-matrix. This differs from the MM5 3DVar which does not consider the influence of heterogeneous forcing on the correlation structure of the B-matrix, a condition that is realistic for many situations. Thus, the MM5 3DVar assimilation could only present an isotropic and homogeneous structure in its increments.     

Impact of Different Guidances on Sensitive Areas of Targeting Observations Based on the CNOP Method

The conditional nonlinear optimal perturbations(CNOPs) obtained by a fast algorithm are applied to determining the sensitive area for the targeting observation of Typhoon Matsa in 2005 using an operational regional prediction model-the Global/Regional Assimilation and PrEdiction System(GRAPES).Through a series of sensitivity experiments,several issues on targeting strategy design are discussed,including the effectivity of different guidances to determine the sensitive area(or targeting area) and the impa...     

混合误差协方差用于集合平方根滤波同化的试验

在集合卡尔曼滤波方法中, 根据预报集合统计提供的依流型而变的预报误差协方差对同化起到决定性的作用。但在集合样本容量不足及模式存在系统误差时, 由预报集合估计的预报误差协方差会出现明显偏差。既要减小这种估计偏差对同化产生的影响而又不增加计算量, 一种可供选择的方法是将定常或准定常的高斯型预报误差协方差和由预报集合估计的预报误差协方差加权平均用于集合卡尔曼滤波同化。利用浅水方程模式, 通过观测系统模拟试验检验在不同的模式误差、 集合成员数以及观测密度条件下, 将这种混合预报误差协方差矩阵用于在集合平方根滤波的效果。试验结果表明, 当预报集合成员数较多而模式又无误差时, 不必采用混合的预报误差协方差矩阵, 否则, 采用混合的预报误差协方差矩阵都有可能改进分析和预报。混合预报误差协方差的最优的权重系数与模式误差关系密切, 模式误差越大, 定常预报误差协方差的权重越大。最优的权重系数与集合成员数及观测密度也有一定关系。     

非对称性增温对农业生态系统影响研究进展

该文概述了北半球和我国气候变暖中增温的非对称性特征:北半球气候变暖存在明显的季节差异和昼夜不同步性, 大部分地区冬、春季升温高于夏、秋季, 日最低气温升幅是日最高气温升幅的2~3倍; 近50年我国近地表气温升高主要是最低气温明显上升的结果, 日最低气温升幅是日最气高温升幅的2~3倍, 与北半球基本一致; 升温最显著的季节为冬季和春季。在此基础上概述了非对称性增温对农业生态系统的影响, 论述了非对称性增温对农作物物候和农作物产量的影响, 得出最低气温升高促使整个生长季延长, 促使早春作物物候期提前, 但最低气温和最高气温对不同作物的物候以及同一作物的不同发育阶段影响不同。现有研究多采用模型或统计的方法研究气候变暖对作物生长的影响, 认为温度升高对作物有“强迫成熟”效应; 而现有的最低气温升高和最高气温升高对作物生长影响的研究结果并不一致。非对称性增温对农作物影响的实验研究极少, 且缺乏对模型模拟结果的实验验证。