太湖波浪数值模拟

在太湖实际波浪观测的基础上,采用率定验证后的第三代动谱平衡方程,考虑实际水底地形、波浪折射、浅化、反射、破碎、湖流等条件下,对太湖波浪进行数值模拟,研究太湖波浪的主要影响因素.结果表明:SWAN模型可以较好地模拟风作用下太湖风浪的生成和传播过程,模型在太湖应用是合适的;波高、波长、波周期等波浪参数在太湖的分布与风速、风向、水深等因素密切相关;在相同风向、不同风速情况下,太湖波浪发展至稳定状态的时间不一样;在不同风向,相同风速持续作用下,有效波高达到稳定的时间差不多,变化趋势也比较相同.说明波浪的发展不光取决于风速的大小,还同风的持续吹的时间和风区长度有关.     

一种用于微波辐射计遥感海表面盐度和温度的反演算法

海面的微波辐射除了与海表面温度和盐度有关外, 还受海面风的影响. 海面风的观测误差严重地影响了海表面温度和盐度的遥感精度. 通过研究海面风因子对海表面辐射影响, 建立了海面风(包括风速和风向)与海表面的微波亮温T以及风导致的亮温修正量DT之间的关系; 在此基础上, 提出了利用微波辐射计的单卫星、多角度观测数据反演海表面盐度和温度的算法. 在这个算法中, 风对海表面辐射影响已经被剔除, 风速和风向不再是反演算法的输入参数. 因此, 该算法不受制于海面风速和风向的影响导致的误差. 这样, 为利用单卫星、多角度微波辐射计遥感海表面盐度和温度提供了一个新途径.     

海陆风及沿海风速廓线在风电场风速预报中的应用

为了建立沿海风功率预报系统,本文探讨了中国沿海风电场风速预报问题,并利用数值模式RAMS对海陆风进行了模拟研究.发现海陆风发生时,海风和陆风阶段风速廓线存在较大差异,海风阶段风速的垂直切变明显小于陆风阶段.海陆风发生时,风速会呈现有规律的变化,即海风和陆风分别有两个时段：风速增加时段和风速减少时段.在为沿海风电场提供风速预报时,当模式预报到海陆风发生时,可以利用海陆风的这种特点,使用统计方法对预报出的风速进行有效的订正.并发现即使没有海陆风发生,当风向为海洋吹向陆地时,风速随高度的垂直切变同样小于陆地吹向海洋的时段.利用统计方法根据不同风向时风速廓线的特性,把数值模式计算高度上的预报结果,精确地插值到风机涡轮高度,会很大程度上减少风速预报的误差及风功率预报环节的误差.     

合成孔径雷达风场反演变分方案评估

利用合成孔径雷达获取高空间分辨率的海面风场,对于研究沿岸海域大气海洋过程具有重要意义.应用CMOD地球物理模型直接反演风速受先验风向误差影响较大,30°的风向误差可导致高达40%的风速误差.变分方法考虑了雷达观测值及背景风场的不确定性,能够较好地降低先验风向对反演风速的影响.但不同的观测误差或地球物理模型选择会形成不同的变分方案,使得反演风场存在差异.本文基于Sentinel-1合成孔径雷达数据及NDBC浮标数据,对不同变分方案进行了系统评估.试验结果表明,当观测误差选取常值0.1 dB、地球物理模型选取CMOD7时,反演风速均方根误差为1.11 m·s^-1,总体最小;但在特定风速区间内,其他变分方案能获得相对更好的反演精度;各变分方案反演风速精度均显著高于背景风速及CMOD直接反演风速精度,但反演风向相对背景风向没有明显改善.试验结果可为变分方法在不同应用需求下的选择提供参考依据.

     

总体样本风速风向联合概率分析方法

提出了针对总体样本的风速风向联合分布的实用统计分析方法。假定任意给定风向上的风速符合某一概型分布、风向间的关联以风速资料的相对发生频率反映、不同风向间的概型参数及频率分布的变化满足谐波函数,在此基础上,利用风速风向资料的总体样本可以得到一个能够反映任意方向的风速风向联合分布函数。利用澳门地区的百年风资料与某风站连续5年的风速观测记录,对该方法的可行性进行了验证。分析表明,该方法具有一定的适用性,便于结构的抗风可靠性分析,具有一定的工程应用价值。     

机载SAR探测图像中归一化雷达截面随入射角变化规律应用

机载SAR对海探测时, 探测范围小和时空匹配难等局限使其无法借助风条纹和辅助资料反演海面风矢量.本文在仿真研究CMOD5.N地球物理模型参数的函数关系, 实例分析机载SAR探测图像中距离向均值曲线变化规律的基础上, 发现相同风向、风速条件下, CMOD5.N模型构建的标准曲线和探测图像的距离向均值曲线遵循统一的归一化雷达截面随入射角变化规律, 且两者具有良好的相关性.据此, 本文提出将距离向均值曲线与标准曲线逐条匹配, 采用相关系数判定两者的相关程度, 选择使得相关系数绝对值最大的标准曲线作为最优匹配曲线, 进而直接确定风向和风速的海面风矢量反演方法.机载SAR飞行探测实验结果表明, 海面风矢量反演结果与浮标观测结果的均方根误差为风向11.3°, 风速0.9 m·s-1, 高于反演精度指标要求, 原因在于该方法既避免了机载SAR探测图像中斑点噪声的影响, 又不会产生局部最优解, 提高了海面风矢量反演精度.     

京津冀城市群地区夏季低层大气风速谱特征分析

利用京津冀城市群地区6个观测站风廓线雷达夏季一个月同步观测资料,对其进行了风功率谱和小波分析.越接近地面,测站之间风的周期变化特征差异越明显,离地面越远,差异不显著.各站大于1天周期的频谱特征差异小,而小于1天周期的频谱特征差异大.各站频谱在几百米高度有明显日变化.不同位置的测站其日变化周期信号随高度分布表现为不同程度的地形影响效应.部分测站1 km高度以下风功率谱在大于1天高频区近似满足-5/3幂分布规律.降水过程风频谱在低层普遍有小于1天的高频周期,这与降水过程高低空风速起伏和变化密切相关.各站平均风矢量日变化在5:00—6:00、20:00—21:00有明显风速变化和风向转换,1500 m以下风向变化差异显著,偏南风出现时间及影响高度与该地区的山谷风和海陆风相联系.各站之间风速相关系数随高度分布呈现出低层低、上层高的特点.最后还给出了风廓线雷达布网建议.     

90°螺旋型和方形截面高层建筑气弹效应对比研究

设计并制作了动力特性基本一致的90°螺旋型和方形截面高层建筑的多自由度气弹模型,对气弹模型进行了风洞试验。运用随机减量法识别了顺、横风向以及多风向角下的气动阻尼;对出现了"拍"现象的工况采用小波方法解耦模态后再进行气动阻尼识别。风洞试验结果表明,方形截面高层建筑顺、横风向气动阻尼比随折算风速的变化规律与相关研究结果类似;螺旋型高层建筑顺风向气动阻尼比随折算风速的变化规律与方形截面高层建筑较为接近,在高折算风速段的阻尼比值相比方形截面高层建筑偏小,横风向气动阻尼比在低折算风速段微弱上升,随后下降,在0值附近波动。对多个风向角的加速度响应进行研究,螺旋型高层建筑均表现出良好的气动性能,尤其在横风向折算风速为12.43时,其加速度均方根为方形截面高层建筑的25.48%。     

基于星载SAR数据的台风参数估计及风场构建

传统的星载SAR数据海面风场反演方法是利用海面风场与雷达后向散射系数之间的经验关系即CMOD5模式函数求解海面风场.但在台风条件下,由于降雨对雷达信号的影响及高风速条件下CMOD5模式函数的停滞效应,海面风场的反演精度迅速下降.针对降雨对雷达信号的影响,本文基于星载SAR卫星平台未搭载降雨测量载荷的特点,将多时次的静止气象卫星红外云图用于推导台风云系的运动矢量,并由该运动矢量及非同步观测降雨数据估算星载SAR数据过境时的降雨强度.最后,利用订正模型和降雨强度数据进行降雨订正.针对高风速条件下CMOD5模式函数的停滞效应,本文基于台风的SAR图像特征和改进的HOLLAND台风模型,提出了台风参数估计及风场构建方案.首先,利用基于小波分析的风向提取算法提取台风风场的海面风向信息,并通过地球物理模式函数和风向信息反演海面风速.然后,根据台风眼的SAR图像特征计算台风中心位置和最大风速半径,并将其代入改进的HOLLAND台风模型.最后,利用中低风速数据通过最小二乘法拟合台风中心气压和最大风速,并将台风风向、中心位置、最大风速半径、中心气压和最大风速等参量代入改进的HOLLAND模型构建台风海面风场.为了验证方案的精度,选择台风"艾利"、"卡努"和"奥菲利娅"的星载SAR数据进行试验,并利用美国联合台风预警中心和飓风研究中心的最佳路径数据和风场数据进行精度检验.结果表明,本文利用星载SAR数据估算的台风中心位置、中心气压、最大风速与最佳路径数据基本一致,构建的海面风场精度较高,其中,海面风速的均方差为1.4 m s-1,风向的均方差为2.1°,为台风监测提供了新的技术途径.     

北京城市化对夏季大气边界层结构及 降水的月平均影响

为克服针对一次或几次天气过程研究城市化对边界层结构及降水影响的局限性,尝试研究北京城市化对夏季大气边界层结构及降水的月平均影响,本文首先总结了2006年8月份的主要天气过程,分析了气象站观测的10 m高度风速、2 m高度气温、2 m高度比湿和24 h降水的月平均分布特征,然后利用WRF/Noah/UCM模拟系统,进行了该月30个个例的高分辨率数值模拟及检验分析,并通过多组不同城市化情景的敏感性试验对比分析了城市化对夏季大气边界层结构及降水的月平均影响.研究表明:本文所用对高分辨率数值模拟结果进行月平均的方法可以较合理地模拟出城市化对大气边界层结构及降水的影响,并再现观测到的各站风频差异.8月份,北京城市化对气温的影响高度白天约为800 m,近地面气温升高1℃以上;夜间约为200 m,对近地面气温的影响达到最大(1.4℃以上).白天,城市化使城市及下风向的一些区域风速略有减小;夜间,城市及周边区域200 m以下风速明显减小,且在100 m左右高度处风速减小最明显,减小达0.8 m/s以上.城市化白天使700 m以下比湿减小,近地面处减小达1.2g/kg以上,夜间使近地面空气比湿略有减小.城市化对城市区域平均降水量的影响随城市发展的不同阶段而不同.初步模拟分析表明, 北京城市化已使上风向区域以及城区三环以内降水量减少,海淀和昌平降水明显增加.     

The effect of wind averaging time on wind erosivity estimation

The Wind Erosion Prediction System (WEPS) and Revised Wind Erosion Equation (RWEQ) are widely used for estimating wind‐induced soil erosion at a field scale. Wind is the principal erosion driver in the two models. Wind erosivity, which describes the capacity of wind to cause soil erosion, is defined as erosive wind power density (WPD) in WEPS, and wind value (W) in RWEQ. In this study, the daily average WPD (AWPD) and the daily average W (Wf) were chosen to investigate the effect of averaging time on wind erosivity estimation based on observed wind data. We compare the daily AWPD and Wf calculated from 1, 5, 10, 15, 30, and 60 minute average wind speed data. The results of comparisons indicate that averaging wind speed can significantly influence estimates of wind erosivity. Compared with the daily AWPD and Wf calculated from one minute average wind speed data, all daily AWPD and Wf values calculated from 5, 10, 15, 30, and 60 minute averaged wind speeds tend to be significantly lower than values calculated from one minute values. In general, longer averaging times tend to produce smaller values of daily AWPD or Wf, which may lead to an under‐estimation of wind erosion. Further studies are needed to extend and apply the findings obtained in this study to actual wind erosion predictions. Copyright © 2012 John Wiley & Sons, Ltd.     

水体浊度对风速、风向及其时间累积效应的响应——以太湖贡湖湾为例

水体浊度是影响水下光场及营养盐循环的关键要素之一,其变化过程与水生生态环境演变关系密切.基于2015-2016年7个时段于太湖贡湖湾内外的金墅和上山村两站点的水体浊度及东山气象站的逐时风场数据,利用分位统计等方法,探讨了风速、风向及时间累积效应对水体浊度的影响.结果表明：在以风场驱动为主要动力来源的大型浅水湖泊中,春、秋两季水体浊度的变化频率高于夏、冬两季,且春季变率更为突出;冬季风场和水体浊度的变率均较夏季明显.风场（包括风速、风向及其累积时间）是影响水体浊度变化的关键因素.其中风速是主要决定性因子;风向对水体浊度有较明显的影响,其通过对风速效应的修正进而影响水体浊度,该修正作用可用三角函数表征;水体浊度变化同时还受前期风场累积的影响,其前期时间累积效应的有效时段为2~10 h.该研究给出了风速、风向及风场累积效应的耦合对水体浊度的影响模型,有助于弄清风场对水体浊度变化的影响机制.     

Oscillation of wind vane in a wind fluctuating both in direction and speed

Summary The equation of motion of wind vane in a wind fluctuating both in direction and speed is integrated by the graphical method of isocline and isocurvature. Two examples are given, one for the wind fluctuating only in speed and the other for the wind fluctuating both in direction and speed.     

Experimental study of wind solitons

A soliton mechanism of formation of rogue waves in the sea is considered. With this in view, a series of experiments was carried out in a ring aerohydrocanal. It was shown that, in the case of long waves (shallow water), a soliton may form under the effect of wind. With increasing wind velocity and decreasing liquid depth, the height of the soliton increases and its forward profile becomes steeper. The result is the formation of a bore. In a sea, such process of wind wave development can lead to the formation of rogue or freak waves. Measurements in the Setun R. have shown that the height of the rings induced by throwing a body into water always decreased in the field of counter flow.     

Adaptive neuro-fuzzy evaluation of wind farm power production as function of wind speed and direction

Wind velocity assumes a critical part for measuring the power created by the wind turbines. Nonetheless, power production from wind has a few weaknesses. One significant issue is that wind is a discontinuous energy source which implies that there exists substantial variability in the generation of vigor because of different variables, for example, wind speed. Wind direction is a significant variable for proficient turbine control for getting the most energy with a given wind speed. Taking into account the conjectures on wind heading, it might be conceivable to adjust the turbine to the wind bearing to get the most energy yield. Since both forecasts of wind speed and direction are basic for effective wind energy collecting it is crucial to develop a methodology for estimation of wind speed and direction and afterwards to estimate wind farm power production as function of wind pace and heading distribution. Despite the fact that various numerical functions have been proposed for demonstrating the wind speed and direction frequency distribution, there are still disadvantages of the models like very demanding in terms of calculation time. In this investigation adaptive neuro-fuzzy inference system (ANFIS), which is a particular sort of the artificial neural networks (ANN) family, was used to anticipate the wind speed and direction frequency dispersion. Thereafter, the ANFIS system was utilized to gauge wind homestead power creation as function of wind velocity and bearing. Neural system in ANFIS modifies parameters of enrollment capacity in the fuzzy logic of the fuzzy inference system. The reenactment outcomes exhibited in this paper demonstrate the adequacy of the created technique.     

通过刚性模型试验评价中庭采光顶风荷载及其响应的方法

当中庭采光顶的建筑设计完成以后,在结构形式上可能仍然存在多种方案,这就需要对每个设计方案的动力性能和风致响应进行评价,而通过气动弹性试验来测定每个方案是不现实的。因此,本文提出了采用刚性测压试验原始数据和有限元时程分析相结合的方法,通过一次刚性测压试验和多次有限元分析来解决,这显然更经济合理。本文将以上海世茂中庭采光顶项目为例,详细地介绍上述风致响应计算方法及其有关结论。     

Global empirical wind model for the upper mesosphere/lower thermosphere. I. Prevailing wind

An updated empirical climatic zonally averaged prevailing wind model for the upper mesosphere/lower thermosphere (70/110 km), extending from 80°N to 80°S is presented. The model is constructed from the fitting of monthly mean winds from meteor radar and MF radar measurements at more than 40 stations, well distributed over the globe. The height-latitude contour plots of monthly mean zonal and meridional winds for all months of the year, and of annual mean wind, amplitudes and phases of annual and semiannual harmonics of wind variations are analyzed to reveal the main features of the seasonal variation of the global wind structures in the Northern and Southern Hemispheres. Some results of comparison between the ground-based wind models and the space-based models are presented. It is shown that, with the exception of annual mean systematic bias between the zonal winds provided by the ground-based and space-based models, a good agreement between the models is observed. The possible origin of this bias is discussed.     

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.     

The stationary and non-stationary wind profile

Summary A method is presented which permits the separation of the non-stationary part of the wind profile from the stationary or smoothed profile. Very little a priori assumption is made, thus, the results can be considered to render information of general purpose. The establishment of the stationary wind profile creates a variable reference with altitude which is necessary for turbulence investigations.