结合毫米波雷达提取降水条件下风廓线雷达大气垂直速度的研究

风廓线雷达主要是利用大气湍流对电磁波的散射作用,在晴空条件下对大气风场等进行探测。在降水天气下,风廓线雷达能同时接收到大气湍流回波和雨滴的散射回波信号,其探测到的回波功率谱中降水信号谱和大气湍流信号谱叠加在一起,使得大气的运动被雨滴的运动信息所掩盖,给后续的大气风场反演带来误差。而毫米波云雷达在降水天气下仅能探测到云雨粒子的回波而无法探测到大气湍流回波,基于这一差异结合毫米波云雷达资料对风廓线雷达功率谱数据进行订正,剔除其中的降水回波信息,进而获取正确的大气运动垂直速度。通过一次典型弱降水天气过程的雷达资料对该方法进行了可行性验证,并将计算得出的大气垂直速度与传统双峰法提取的大气运动垂直速度及原始风廓线雷达垂直速度进行了对比分析,显示在弱降水天气下该方法能有效消除降水对风廓线雷达垂直速度测量的影响,提高弱降水天气下测速准确率,并且在湍流谱极其微弱的情况下该方法也能准确地获取到大气运动垂直速度信息。但是云雷达回波在降水时会有衰减,虽然是弱降水也会导致在高层距离库上的订正效果变差,故目前只适用于弱降水时低距库处的降水订正。      

TURBULENCE STRUCTURE IN A STRATIFIED BOUNDARY LAYER UNDER STABLE CONDITIONS

Turbulence structure in stably stratified boundary layers isexperimentally investigated by using a thermally stratified wind tunnel. Astably stratified flow is created by heating the wind tunnel airflow to atemperature of about 50 °C and by cooling the test-section floor to asurface temperature of about 3 °C. In order to study the effect ofbuoyancy on turbulent boundary layers for a wide range of stability, thevelocity and temperature fluctuations are measured simultaneously at adownwind position of 23.5 m from the tunnel entrance, where the boundarylayer is fully developed. The Reynolds number, Re, ranges from 3.14× 104 to 1.27 × 105, and the bulk Richardson number, Ri,ranges from 0 to 1.33. Stable stratification rapidly suppresses thefluctuations of streamwise velocity and temperature as well as the verticalvelocity fluctuation. Momentum and heat fluxes are also significantlydecreased with increasing stability and become nearly zero in the lowest partof the boundary layer with strong stability. The vertical profiles ofturbulence quantities exhibit different behaviour in three distinct stabilityregimes, the neutral flows, the stratified flows with weak stability(Ri = 0.12, 0.20) and those with strong stability (Ri= 0.39,0.47, 1.33). Of these, the two regimes of stratified flows clearly showdifferent vertical profiles of the local gradient Richardson number Ri,separated by the critical Richardson number Ri cr of about 0.25. Moreover,turbulence quantities in stable conditions are well correlated with Ri.     

孟加拉湾的叶绿素a,海表温度和风速的趋势

孟加拉湾（BoB）是一个高能量活跃的地区,其短期内的动态变化将对浮游环境产生巨大影响."风泵"能够在BoB海域导致垂直的混合从而影响海表温度和叶绿素浓度.本文对2006——2016年的月平均Aqua-MODIS叶绿素a （chl-a）浓度数据和Sea WiFS月度气候态数据进行了分析,研究了叶绿素浓度的时间/季节变化和温度以及风速的关系.基于季风期间的chl-a变异与海表温度（SST）,评估了在BoB海域它们之间的关系和变化.chl-a浓度值的趋势分析表明,该区域的垂直混合非常低,冬季最高,夏季最低.冬季最大chl-a浓度值为0.50 mg/m³,并且从2月开始下降到夏季季风期间.与冬季季风相比,夏季季风期间叶绿素表现出较低的浓度.在夏季季风期间,特别是在7月和8月,由于云层密集,卫星传感器无法准确捕获chl-a浓度值.chl-a浓度和SST之间相关系数R²值为0.218 1.     

基于ASCAT风场数据的中国近海风能资源评估

卫星反演海面风场资料能够弥补海上气象测风资料缺乏的不足,对近海风能资源评估具有重要意义。通过ASCAT(Advanced Scatterometer)风速数据与美国及中国近海岸浮标测风资料的对比分析,结果表明,ASCAT风速的均方根误差为1.27 m·s-1。比较利用近海岸浮标逐小时风速及与其相匹配ASCAT瞬时风速计算的各项风能参数,得出ASCAT与浮标的平均风速和风功率密度的残差分别在±0.5 m·s-1和±50 W·m-2以内,该残差占浮标计算结果的比例分别在±8%和±12%以内。使用ASCAT风速资料拟合的Weibull分布函数与浮标的结果较吻合。因此,ASCAT风速资料也能够为海上风能资源评估提供有用的风能参数信息。最后使用ASCAT瞬时风速数据分析了中国近海10 m及70 m高度处的风能资源的空间分布特征,结果表明,台湾海峡平均风速和风功率密度最大。     

海岸沙丘沙运动特征若干问题的研究——以闽江口南岸为例

在海岸带,沙粒粒径和水分含量是决定沙粒起动风速的最主要因素。闽江口南岸海滩沙的平均粒径为2.0Φ,水分含量多在0.3%~1.0%之间。运用Johnson的经验公式,可计算出海滩沙的起动风速为6~7m/s。这一结果与实际观测值十分吻合。由于海岸环境因素的影响,使得同等条件下海岸带沙粒的起动风速明显大于内陆沙漠沙,而风沙流的输沙率明显小于内陆沙漠沙。海岸带是风速剧变带,在引用陆地气象台站的风速记录分析海岸风况和研究风沙运动规律时,必须对风速进行订正。     

中国南海东部海域气候特征及风浪流极值参数的研究——LAGFD数值模式群的应用

本文采用先进的ＬＡＧＦＤ风、浪数值模式和ＰＯＭ（ＰｒｉｎｃｅｔｏｎＯｃｅａｎＭｏｄｅｌ）三维海流模式对自１９４５～１９９５年间发生并影响南海东部海域的２９９个历史最强热带气旋过程进行数值后报,给出了南海东部部分海域（１９°～２３°Ｎ,１１３°～１１８°Ｅ）中１０００ｍ等深线内６０个点的多年一遇风、浪、流和水位极值,并简要分析了南海东部（１５°～２７°Ｎ,１０８°～１２２°Ｅ）的气候特征,为该海域区域性海洋环境研究与工程开发提供了基础参考数据。     

近30年我国高空风速变化趋势分析

1980-2006年间采用全国119个探空站14个等压面的月平均风速资料,分析了我国高空对流层和平流层下层风速变化的时间和空间特征,并和同期地面风速变化进行了对比.结果表明,我国近27年对流层中下层和对流层上层风速呈下降趋势,年平均风速线性变化速率分别为-0.10 m·s-1·(10a)-1和-0.17 m·s-1·(10a)-1,均未通过0.05显著性水平检验;平流层下层全国年平均风速呈上升趋势,上升速率为0.24 m·s-1·(10a)-1,亦未通过O.05显著性水平检验.同期全国地面风速则呈现更显著的降低趋势,年平均风速线性变化速率为-0.16 m·s-1·(10a)-1,通过了0.05显著性水平检验.我国地面气象站记录的平均风速减弱可能受到大尺度大气环流变化的影响,更可能与台站附近观测环境变化和城市化等人为因素影响有密切关系.     

包头地区风能资源分布特征分析

利用1979—2008年包头地区各气象站近30年地面观测的风资料,对各地区平均风速、最大风速和风能资源进行了统计计算,给出了包头各地的平均风速、最大风速和风能资源的分布特征,为包头地区合理开发和利用风能资源提供依据。     

2008年10月的一次寒潮天气过程分析

文章选择常规天气以及物理量资料,利用天气学原理分析了2008年10月21—23日发生在包头地区的寒潮天气过程,从中寻求一些有物理意义的预报指标,为今后的预报提供可靠的预报依据。     

Relative quantification of wind erosion in argan woodlands in the Souss Basin,Morocco

The endemic argan woodlands cover large parts of South Morocco and create a characteristic landscape with areas of sparsely vegetated and bare soil surfaces between single trees. This unique ecosystem has been under extensive agrosilvopastoral management for centuries and is now at risk of degradation caused by overgrazing and increasing scarcity and variability of rainfall. To investigate susceptibility to wind erosion, we conducted an experimental–empirical study including wind tunnel tests and a drone-generated digital elevation model and quantified wind-erodible material on five different associated surface types by means of sediment catchers. The highest emission flux was measured on freshly ploughed surfaces (1875 g m^–2 h^–1), while older ploughed areas with a re-established crust produced a much lower emission flux (795 g m^–2 h^–1). Extensive tillage may have been a sustainable practice for generations, but increasing drought and uncertainty of rainfall now lead to an acute risk of severe soil erosion and dust production. The typical crusted surfaces characterized by residual rock fragment accumulation and wash processes produced the second highest emission flux (1,354 g m^–2 h^–1). Material collected from tree-shaded areas (933 g m^–2 h^–1) was revealed to be a considerable source of organic material, possibly affecting substrate conditions positively on a larger regional scale. The lowest flux was measured on rock fragment-covered surfaces (301 g m^–2 h^–1). The data show that open argan woodland may be a considerable source for wind erosion and dust production, depending on surface characteristics strongly related to management. An adapted management must include the conservation of argan trees to offer a promising approach to prevent severe wind erosion and dust production and mitigate possible impacts of land-use change and climate change related shifts in wind and rainfall patterns. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd