湍流大气中水平风速模涨落的相关

推导出湍流度不大时,水平风速模涨落的相关,方差等量与分量风速涨落相应量联系的近似式。計算表明,在大气湍流微結构研究通常遇到的湍流度下,模量的相关与順风分量相关差不多. 說明了小尺度大气湍流中,风速模涨落的空間相关也可以近似地以时間相关来代替. 討論了推导时引入的附加条件在大气中的合理性。     

降落雨滴中稳定同位素比率变化的数学模拟

根据扩散定律和热量平衡理论,运用云物理学模式,对降落雨滴中稳定同位素比率的变化进行了数值模拟,发现降落雨滴中稳定同位素比率的变化除受湿度条件的影响外,还受大气水汽中稳定同位素比率的影响。在非饱和大气中,受蒸发过程的影响,降落雨滴中稳定同位素比率随降落距离而不断增大,空气湿度越小,增大幅度越明显。平均而言,大气湿度与ｄδＤ／ｄδ１８Ｏ和Ｅｘｄ呈正比。ｄδＤ／ｄδ１８Ｏ以８为渐近线,Ｅｘｄ则在高湿和较大半径条件下逐渐趋近于一个常数;在饱和大气中,半径较小的雨滴或在湿度较高的环境中,雨滴中稳定同位素达到平衡的时间较短。反之,达到平衡的时间较长。     

夏季不同天气条件下风廓线雷达探测精度分析

利用2016年6—8月沈阳地区TWP8-L型风廓线雷达观测资料,判断大气的均匀性,计算风廓线雷达的探测精度,并与探空气球的观测资料进行对比分析,得到晴空和不同降水条件下的风廓线雷达探测精度随高度的变化情况。研究结果表明,1000m高度以下风廓线雷达的探测精度较高。在无降水和均匀降水条件下,风廓线雷达的水平探测范围内大气均匀稳定,东西波束和南北波束测得的径向风对称性较好,(U_W-U_E)和(V_S-V_N)的平均差和标准差值较小;与GTS1型探空仪风速精度相差小于2.9m/s,两者相关性较好,风廓线雷达探测水平风的准确性较高。在探测范围不均匀的降水条件下,大气在风廓线雷达的水平探测范围内不均匀,东西波束和南北波束测得的径向风的对称性较差,垂直速度变化差异较大;U_W-U_E和V_S-V_N平均差和标准差值较大;与GTS1型探空仪风速精度相差大于2.0m/s,两者相关性较差,风廓线雷达探测水平风的准确性较低,需要进一步改进算法,改善数据质量,提高探测性能。     

非定常过程对大气边界层的内参数与风廓线的影响(二)

本文用大气边界层运动方程的数值积分研究了当边界层顶风向不变但风速变化时对大气边界层的内参数u_*/A(u_*为摩擦速度,A为上界风速)和α角(地面风与上界风向的交角)的影响。设上界处风速随时间指数增加及减少,最后趋于定常。在大气正、斜压时,u_*/A及α角的时间变化均是振幅衰减的振荡,最后趋于定常时相应的值。在时间变化过程中的任一时刻,内参数值与当上界条件取该时刻上界风时的定常解结果有一定的差别,严格说,定常时的内参数值并不能直接用于当上界风非定常时。本文还考虑了上界风速非定常对风廓线的影响。     

北京冬季二氧化硫污染和气象条件的关系

利用2000年1月25日～2月3日北京地区冬季二氧化硫体积分数的梯度监测资料,结合北京325m气象塔的同期气象资料,分析了观测期间北京地区二氧化硫的体积分数变化趋势及垂直分布情况,讨论了大气二氧化硫体积分数变化和气象条件的关系及二氧化硫的来源问题.研究表明:二氧化硫的体积分数变化及垂直输送与风速、风向、大气稳定度密切相关.风速越小,大气越稳定,近地层大气的二氧化硫污染就越严重;当北京冬季吹SSW、SW、WSW和W风时有较高的二氧化硫.     

名词解释

地转风 空气质点受水平气压梯度力与水平地转偏向力的共同作用而运动,当二力达到平衡时的风叫做地转风。地转风是理论条件下的风,风速的大小与方向不随时间变化。离地面1—2千米以上,不受地面摩擦影响的自由大气的风与地转风接近,可称为准地转风。地转风平行于等压线吹,当我们背风而立,右手一方     

一次强沙尘暴的近地层气象要素及内部热力、动力结构特征

针对2009年4月23-24日出现在我国内蒙古中西部的一次强沙尘暴天气过程,利用专门组织观测实验得到的加密探空资料、地面自动观测站资料和其他常规观测资料,深入分析研究了此次沙尘暴发生前后及发生期间,近地层气象要素变化及其内部热力、动力结构特征变化.结果表明,1）沙尘暴发生前,大气的温度垂直递减率大,湿度较大,近地层风速小,风向偏东;在沙尘暴发生期间,大气中出现逆温现象,大气湿度很小,各层风速明显增强,风向偏西且稳定;之后,低层温度显著下降,大气湿度迅速增大,各层风速减小,沙尘暴天气结束.2）沙尘暴发生前,大气层结是条件不稳定的,在沙尘暴过境时,低层大气层结是稳定的,在800600 hPa之间大气层结是中性的,此时低层大气干燥,而在沙尘暴移出测站后,湿度明显增大,因此,“3θ”曲线可以为沙尘暴的监测和预报提供一个有价值的参考数据.3）沙尘暴爆发时的螺旋度是所有观测时次中的最大值,螺旋度与沙尘暴的强度在时间上具有良好的对应关系,即螺旋度越大,对应沙尘暴越强.4）此次强沙尘暴的形成与发展不仅受到环境风速的影响,沙尘暴内部的切向旋转速度和垂直运动速度也对其起到重要的作用.     

边界层大气水平风速低频谱的垂直分布特征

本文根据320米气象塔上水平风速的观测资料,分析了不同天气条件下边界层大气中湍流的宽谱特性及其垂直分布结构. 结果表明,大气边界层水平风速低频谱的垂直分布是很复杂的,在不同的天气条件下,这种垂直分布特征具有明显的差异.边界层温度和风速的垂直结构也会影响到水平风速低频谱的垂直分布. 在水平风速低频谱中,除了与天气过程有关的4天周期峰值和反映气象要素日变化频率的峰值外,在十几分钟到几十分钟频率范围内还存在着几个峰值,而且有时在不同的高度上,峰值频率有所不同.这可能反映了一些中尺度系统的特征,也可能是这些中尺度系统与局地地形的综合作用所引起的.     

利用Ka波段毫米波雷达功率谱反演云降水大气垂直速度和雨滴谱分布研究

利用中国气象科学研究院2016年华南云降水试验中Ka波段毫米波雷达探测一次层状云降水过程,开展了云内大气垂直速度和雨滴谱的反演研究,并与地面激光雨滴谱仪和微降水雷达的测量雨滴谱结果进行对比分析。首先,采用小粒子示踪法从功率谱密度中反演大气垂直速度以得到静止空气条件下的功率谱密度,进而利用粒子下落末速度-粒子直径关系反演出雨滴谱,最后进行标准化的Gamma分布拟合。研究表明:(1)云降水从零度层到地面1 km,主要由下沉气流主导,近地面大气浮游粒子和直流干扰造成的晴空杂波会影响雷达的功率谱分布;受动态范围限制,回波强度过饱和现象会影响近地面大气垂直速度的反演结果;(2)毫米波雷达CR、微雨雷达MRR和地面雨滴谱仪测量回波强度存在一定差异,MRR相较于CR与地面雨滴谱仪测量偏差较小;在稳定降水时CR和MRR功率谱密度对比较为一致;(3) CR和MRR反演雨滴谱对比实验中,雨滴谱反演对大气垂直速度十分敏感,大气垂直速度的变化,会使CR反演雨滴谱随着高度增加数浓度量级变大、粒子平均半径变小。CR反演的雨滴谱与M RR反演结果基本一致,验证了CR功率谱反演雨滴谱方法的可靠性;(4) CR与地面雨滴谱仪雨滴谱拟合参数的对比表明,CR大气垂直反演的雨滴谱与地面雨滴谱相比粒子平均直径Dm较小,数浓度则较为一致。     

环境风场与对流风暴相互关系的动力分析

在前期提出大气多尺度分析理论基础上,利用动力学方法研究了大气环境风场与中尺度对流天气系统之间的关系,从微团的分离和运动的角度分析了高空急流、低空急流、水平涡度和垂直涡度在中尺度天气系统的形成和发展中的作用。结果发现,环境风场对微团的动力分离作用主要发生在高、低空急流附近,因为在高、低空急流的下方风动能随高度增加明显,在急流的左侧(背风而立)正涡度与地转涡度迭加使绝对涡度变大,因此,这两个区域是环境场对微团分离力最大的区域,也是对流最容易发展的地区。微团在上升过程中的运动轨迹与其环境密度比率有关,当微团的密度小于(大于)环境密度时,微团运动的旋转方向与水平涡度的方向一致(相反);平衡高度(微团密度与环境密度相等)越高,形成的系统越强,水平、垂直旋转的程度越强,范围越大。因为初始密度和平衡高度的不同,多单体风暴和超级单体中微团的运动形态存在明显区别。根据大气微团的运动方程推出了水平风随高度变化的公式,结果表明,微团水平运动垂直变化的大小与微团环境相对密度比、水平风速、垂直涡度成正比;与垂直运动速度大小成反比;风矢量由低到高的转向与绝对涡度垂直分量的旋转方向相反,即正(负)涡度与亚微团的顺(逆)转相对应。由公式解释了超级单体低空垂直切变明显大于高空的原因。进一步分析认为,风垂直切变对风暴的作用只表现在风速大小随高度的变化和水平涡度的作用上,而风向随高度的变化是大气对流的结果而不是对流的原因,对流越强,风向垂直切变越强。     

不同天气条件下脉冲激光风廓线仪测风性能

将2012年5月21日-8月16日广东省湛江市东海岛气象观测站内脉冲激光风廓线仪WINDCUBE V2与气象站内的100 m测风塔进行同步观测试验,在经过观测数据同步性调整、有效性检验和代表性样本筛选基础上,分大小风和有无降雨天气过程,对杯式测风仪、超声风速仪与激光风廓线仪的同步测风数据进行比较,结果显示:脉冲激光风廓线仪与杯式测风仪测量水平风参数的相关性较好,10 min平均风速、风向的线性拟合度均大于0.99,3 s阵风风速的拟合度大于0.96,湍流强度的拟合度大于0.67,风速标准差的拟合度大于0.79;大风情况下,激光风廓线仪对风参数的测量效果更佳。无降雨情况下,激光风廓线仪的测量效果较降雨时略好,10 min降水量小于15 mm的降雨对这款激光风廓线仪的风速、风向、湍流强度、3 s阵风风速的测量没有显著影响,对风速标准差有一定影响。当水平风速增大和有降雨时,激光风廓线仪对垂直速度的测量效果欠佳。该对比分析可为激光风廓线仪观测数据的可靠性提供参考。     

基于双高斯拟合的风廓线雷达反演雨滴谱

在降水条件下,风廓线雷达返回信号是湍流信号和降水信号的叠加,其功率谱数据中通常会出现双峰结构。该文通过双高斯拟合方法区分大气湍流信号功率谱和降水信号功率谱,去除大气湍流对降水信号谱的影响,反演得到较为精确的雨滴谱分布。研究表明:在风廓线雷达估算雨滴谱的过程中,双高斯拟合可将两峰有效分离,利用处理后的降水谱反演得到的雨滴谱均呈指数分布。选取北京延庆地区2006年和2012年具有代表性的降水资料,对比反演得到的不同强度和不同类型降雨的雨滴谱资料显示,这种估算雨滴谱的方法可行且可靠,利用双高斯拟合将双峰分离,可以达到风廓线雷达数据质量控制的目的,对于风廓线雷达在更为复杂的天气条件下应用具有借鉴意义。     

Analysis of the Microphysical Properties of a Stratiform Rain Event Using an L-Band Profiler Radar

This paper investigates spatial and temporal distributions of the microphysical properties of precipitating stratiform clouds based on Doppler spectra of rain particles observed by an L-band profiler radar.The retrieval of raindrop size distributions（RSDs） is accomplished through eliminating vertical air motion and isolating the terminal fall velocity of raindrops in the observed Doppler velocity spectrum.The microphysical properties of raindrops in a broad stratiform region with weak convective cells are studied using data collected from a 1320-MHz wind profiler radar in Huayin,Shaanxi Province on 14 May 2009.RSDs and gamma function parameters are retrieved at altitudes between 700 and 3000 m above the surface,below a melting layer.It is found that the altitude of the maximum number of raindrops was closely related to the surface rain rate.The maximum number of large drops was observed at lower altitudes earlier in the precipitation event but at higher altitudes in later periods,suggesting decreases in the numbers of large and medium size raindrops.These decreases may have been caused by the breakup of larger drops and evaporation of smaller drops as they fell.The number of medium size drops decreased with increasing altitude.The relationship between reflectivity and liquid water content during this precipitation event was Z = 1.69×10~4M~（1.5）,and the relationship between reflectivity and rain intensity was Z = 256I~（1.4）.     

Thermal Image Velocimetry

A method for measuring the two-dimensional distribution of wind velocity vectors near a surface exposed to solar radiation, by tracking brightness temperature images instead of particle images, is proposed. It is based on time-sequential thermography with the algorithm used for particle image velocimetry. This thermal image velocimetry (TIV) was tested on a full-scale building wall covered by polystyrene boards attached side-by-side over a vertically elongated area measuring 22.2 m by 2.73 m. A thermal infrared camera was installed 8 m from the test wall to capture the wall-surface temperature at 30 Hz frequency. A sonic anemometer was also installed 35 mm from the surface used for validation of the TIV. The advection velocity estimated from thermal infrared imagery had a linear relationship with the wind velocity measured by the sonic anemometer, irrespective of the wind speed and direction. This linear slope was multiplied by the advection velocity of the thermal infrared image to rescale it to the wind velocity, and the term ‘TIV velocity’ was then used. A histogram and power spectra of the TIV velocity showed quantitatively good agreement with the velocity measured by the sonic anemometer, except for the high-frequency region of the spectra, where the TIV velocity was overestimated compared with that of the sonic anemometer. The method was also tested on ground covered by artificial turf to demonstrate its application to a horizontal plane with a wider area, extending for more than 80 m by 60 m.     

Cloud microphysical properties in tropical convective and stratiform regions

Summary Cloud microphysical properties in tropical convective and stratiform regions are examined based on hourly zonal-mean data from a two-dimensional cloud-resolving simulation. The model is integrated for 21 days with the imposed large-scale vertical velocity, zonal wind and horizontal advections obtained from Tropical Ocean Global Atmosphere Coupled Ocean-atmosphere Response Experiment (TOGA COARE). Time-mean cloud microphysical budgets are analyzed in raining stratiform regions, convective regions, and non-raining stratiform regions, respectively. In raining stratiform regions, ice water path (IWP) and liquid water path (LWP) have similar magnitudes. The collection process contributes slightly more to the growth of raindrops than the melting processes do, and surface rain rate is higher than the raindrop-related microphysical rate, indicating that the hydrometeor convergence from the convective regions plays a role in surface rainfall processes. In convective regions, IWP is much smaller than LWP, the collection process is dominant in producing raindrops, and surface rain rate is lower than the raindrop-related microphysical rate. In non-raining stratiform regions, IWP is much larger than LWP, and the melting processes are important in maintaining the raindrop budget. The statistical analysis of hourly data suggests that the slopes of linear regression equations between IWP and LWP in three regions are different. Rain producing processes in convective regions are associated with the water cloud processes regardless of convection intensity.     

风廓线雷达组网资料初步对比分析

以L波段探空雷达探测到的水平风为标准对全国风廓线雷达探测到的水平风的可信度进行评估,得到:风廓线雷达探测到的水平风在700 hPa高度以下与L波段探空雷达测风有较好的一致性;并且将风廓线雷达探测到的垂直速度与同址地面自动气象站观测到的1 h雨量进行相关性分析,得出垂直速度大小能很清楚地反映降水的开始、结束以及降水的强度;最后将全国风廓线雷达探测到的水平风进行组网对比分析,得出全国风廓线雷达探测得到的水平风在700 hPa高度下是可信的,风向可信度随探测高度的增加而增大。风速可信度随探测高度的增加而降低。     

边界层风廓线雷达测风精度分析

利用CLC-11-D型边界层风廓线雷达的5波束观测数据,对比分析了晴空、稳定性降水和对流性降水等不同类型气象条件下边界层风廓线雷达测风的准确性,并对2016年3月1日—2017年2月28日共计7300时次的晴空观测资料进行了测风质量评估,得出结论如下:在晴空条件下大气均匀稳定,水平风速和风向测量精度要优于稳定性降水和对流性降水天气,降水出现前后环境大气扰动较大是导致稳定性降水和对流性降水天气下测风精度较差的原因;150 m以下近地层高度的测风质量较差,与地杂波干扰较强有关;夏季有效探测高度最高可达6300 m左右,春秋季有效探测高度比较接近,分别为2000 m和2500 m左右,冬季有效探测高度最低,仅为1100 m左右;4个季节测风质量评估达标高度分别为900、4000、2200 m和1100 m,大气环境的湿度条件和水平风速、风向标准差的波动是影响测风质量评估的重要因素。     

雨滴谱仪与风廓线雷达反射率对比试验

针对风廓线雷达估算的反射率数据需要进行验证。开展雨滴谱仪与风廓线雷达反射率对比试验,通过两种不同探测设备观测数据的对比,以验证风廓线反射率数据的可靠性和可用性。结果表明:确定了以风廓线低模360~1440 m采样体积内的反射率与3 min雨滴谱反射率数据对比方法能最大程度的减少时空差异;在雨滴谱仪反射率小于40 dBz时,对应的风廓线雷达反射率数据是可靠和可用的;同时由于风廓线雷达有限的动态范围造成反射率低估的现象,使得风廓线雷达反射率在大气垂直结构以及微物理特性等方面应用受到一定的局限性。     

Remarks on the Definition and Estimation of Friction Velocity

One of the mainscaling parameters in similarity theory of the atmospheric boundary layer is friction velocity. Unfortunately, several definitions of friction velocity exist in the literature. Some authors use the component of the horizontal Reynolds stress vector in the direction of the mean wind vector to define friction velocity. Others define the friction velocity by means of the absolute value of the horizontal Reynolds stress vector. The two definitions coincide only if the direction of the mean wind vector is parallel to the horizontal Reynolds stress vector. In general, the second definition gives larger values for the friction velocity. Over complex terrain the situation is further complicated by the fact that the terrain following flow is not necessarily horizontal. Thus, several authors have proposed to use terrain following coordinate systems for the definition of friction velocity. By means of a large dataset of fast-response wind measurements with an ultrasonic anemometer the friction velocities resulting from the different definitions are compared. Furthermore, it is shown that friction velocity can be well estimated from horizontal wind speed, and even better from simple horizontal or vertical turbulence parameters.     

Stationarity of Turbulence in Light Winds during the Maritime Continent Thunderstorm Experiment

Non-stationary turbulence can invalidate eddy flux calculations. Two-hour longrecords of wind velocity, temperature and humidity are classified as stationaryor non-stationary based on the behaviour of the flux as a function of Reynoldsaveraging period; a number of indicators of stationarity are investigated. Thetwo-hour Maritime Continent Thunderstorm Experiment wind datasets are notcompletely stationary, as indicated by the lack of a spectral gap, but can beclassified as approximately stationary, when the mean wind speed is greaterthan 3.8 m s^-1, or the standard deviation of true wind direction is 10°, or the ratio of horizontal wind variance to wind speed is <0.25. In the stationary case the calculated friction velocity exhibits a 7% decrease on average when the Reynolds averaging period is doubled, while data classified as non-stationaryexhibit an increase of 32%. There is little non-stationary behaviour in the kinematicheat fluxes, and is independent of the non-stationarity of the friction velocity. Thekinematic heat fluxes show small decreases (around 3%) when the Reynolds averagingperiod is doubled.