大涡模拟模式研究对流层湍流

利用三维大涡模拟模式研究不同地面热力状况和风切变对湍流产生的影响，在对流层湍流发展过程中，这两种作用是同时存在的、同时起作用，水平风速的瞬时垂直切变可以在自由大气中激发湍流，但它不能维持很长时间，对流热泡也可以在自由大气中激发湍流，其湍流强度与地面的热量强度有关。     

数值模式垂直分辨率对台风大涡模拟的影响

随着计算能力的提升,台风数值模拟大量采用了大涡尺度模拟,其水平分辨率已达到数10 m的量级,而垂直分辨率提升不大,其问题是数值模式的垂直分辨率对台风大涡模拟的影响如何?因此,本文利用WRF(Weather Research and Forecasting)模式开展理想台风模拟,在不同的模式垂直层次(42,69和90层)...     

用大涡模式研究对流边界层湍流

利用三维对流边界层的大涡模拟模式研究对流边界层湍流统计特征量,模拟结果与前人的同类模拟工作及实验观测结果相比较,得到了一致的结论.       

大涡模式垂直分辨率在夹卷及示踪物垂直传输模拟结果分析中的作用

基于敦煌野外观测资料和大涡模式,研究了垂直方向不同尺度湍涡对夹卷及示踪物垂直传输的影响,明确了模式垂直分辨率在模拟结果分析中的作用。结果表明:垂直方向上小尺度湍涡对夹卷作用贡献更大,小尺度湍涡较多时夹卷层相对更暖,而夹卷层厚度、夹卷强度和风速变化受垂直方向湍涡尺度影响较小。当垂直分辨率为50 m时,越往夹卷层上部,上升气流和下沉气流分布较多且强度较大;分辨率为10、20和30 m时,夹卷层各高度垂直速度、位温和示踪物浓度分布较接近。另外,垂直方向湍涡尺度对示踪物垂直传输高度影响不大,而对示踪物的空间分布有一定作用。当大尺度湍涡较多且强度较强时,越有利于将高浓度的示踪物向上传输。综合考虑到模式采用较高分辨率模拟时产生的噪音及计算时间等问题,认为模式采用30 m的垂直分辨率,既能较好地模拟出夹卷层平均结构特征,又能模拟出夹卷层湍流的精细分布,是较为理想的选择。     

利用大涡模拟分析地表加热和动力作用对边界层结构的影响

大气边界层结构影响地气间物质能量交换、污染物扩散及人类健康。边界层结构受地表加热和动力作用影响显著,但实际观测中难以分离每种因素的影响,造成边界层结构和大气湍流参数化的困难。为此,利用中尺度天气模式WRF中的大涡模块WRF-LES,设置控制试验（Test1）,地表热通量试验（Test2）、低层风切变试验（Test3）、地表粗糙度试验（Test4）及同时改变上述变量的试验（Test5）,研究地表加热、低层风切变和地表粗糙度对平坦下垫面条件下的边界层结构的影响。模拟结果表明：（1）地表加热增强5倍使边界层升温,对流增强,夹卷层厚度增加120.8%,全边界层湍流动能增加45.7%,热力和动力边界层高度分别增大28.3%和29.9%。强烈的垂直混合作用有利于动量向下传递,使风速在边界层低层增大、中上层减小。（2）低层风切变增大0.5倍,使得热力和动力边界层高度分别增大11.9%和降低6%,夹卷层厚度增大31.2%,全边界层湍流动能增大25.7%。（3）粗糙度增加4倍,对湍流动能的影响主要集中在低层,动力边界层高度变化较小,但摩擦损耗作用使动力边界层内风速减小;同时,增加了边界层顶附近的夹卷作用...     

干湿地表的湍流特征及其对深对流影响的大涡模拟

利用大涡模式模拟了对流边界层结构演变以及深对流触发过程.通过改变鲍恩比的敏感性试验研究不同大气初始状况下湿润和干旱下垫面湍流特征及其对深对流触发过程的影响.结果表明:干旱下垫面的混合层干而暖,厚度较大;湿润下垫面相反.由于地表感热通量对热力湍流形成的作用更大,干旱下垫面上湍流混合和夹卷作用更强,使得水汽和相当位温在边界...     

南海卫星遥感海表湍流热通量资料的评估

利用现场观测资料、OAFlux的湍流热通量,评估了JOFURO（Japanese Ocean Flux Data Sets with use of Remote Sensing Observations）、HOAPS-2（Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data version 2）、GSSTF-2（Goddard Satellite-Based Surface Turbulent Fluxes version 2）3种卫星资料在南海区域的表现。3套卫星资料可以说各有千秋,总体而言JOFURO和GSSTF-2资料的空间分布和时间变化与OAFlux资料整体上较一致,但是这两套资料都在很大程度上低估了海盆平均的潜热和感热,前者低估约10%~20%,后者则可以达到50%以上。HOAPS-2资料与现场观测资料有较好的一致性,但在时间变化上和其他资料的差异则较大,特别是感热方面,季节变化振幅、年际变化位相等都与其他资料不一致。通过比较我们发现,海南岛周边以及南海南部区域估算的潜热和感热释放偏小是造成整体偏小的主要原因。     

关于大气涡动热通量参数化问题研究

用NCEP/NCAR等再分析资料计算和分析表明,月平均瞬变涡动热通量和月平均温度梯度的局域相关性很低,甚至在一些纬度是负相关,更严重的是二者之间存在非线性的多值对应函数关系.如果用非局域参数化,参数化水平将有所提高,但改进并不明显.通过与分子运动论输运理论进行数学、特别是物理类比提出了考虑"风暴路径"效应的瞬变涡动热通量的参数化方案,经再分析资料的检验,结果表明它能大大提高参数化的水平.其次,还证实采用空间非局域参数化仍然是进一步提高瞬变涡动热通量参数化水平的方法之一.此外,资料分析显示中高纬度纬向平均温度梯度和纬偏涡动温度通量之间也存在负相关及多值函数关系,说明仅用温度梯度去参数化纬向平均涡动热通量难以得到好的结果,需要考虑多元参数化或非同步参数化等.     

均匀裸土地表土壤热通量计算方法对比及对能量闭合的影响

利用"内蒙古微气象观测蒸发试验"的观测资料,对6种地表土壤热通量计算方法(Plate Cal法、TDEC法、谐波法、热传导对流法、振幅法和相位法)进行比较,检验了6种方法在不同干湿地表状况下的适用性,并研究了6种方法计算地表土壤热通量的差异以及对地表能量闭合度的影响。结果表明:一般情况下,Plate Cal法计算的2 cm土壤热通量与观测值最接近,计算结果的均方差为6.9 W/m2。在不同干湿地表状况下,干燥和降水条件下适合使用Plate Cal法,计算结果的均方差分别为14.0 W/m2和30.1 W/m2;湿润条件下适合使用谐波法,计算结果的均方差为21.4 W/m2。6种方法计算的地表土壤热通量存在明显差别,最大相差178.6 W/m2,不同方法计算地表土壤热通量的最大差值超过25 W/m2的时次占样本的96.3%。不同方法计算地表土壤热通量的差异对地表能量闭合度的大小有明显影响,但不影响近地层能量闭合度随湍流混合增强而增大的规律。     

黄河源区鄂陵湖湖面和湖边草地对流边界层湍流结构特征的大涡模拟研究

为研究黄河源区边界层湍流特征及其对物质和能量输送的影响,本文首次采用大涡模拟的方法,对比分析了黄河源区两种不同下垫面上(鄂陵湖和湖边草地)对流边界层(CBL)中精细的湍流结构特征.使用资料为2012年夏季黄河源区鄂陵湖流域野外观测实验的GPS探空资料、涡动相关观测资料.分析表明,模拟的黄河源区草地和湖上CBL的平均结构...     

Near-Surface Coherent Structures and The Vertical Momentum Flux in a Large-Eddy Simulation of the Neutrally-Stratified Boundary Layer

The near-surface flow of a well-resolved large-eddy simulation of the neutrally-stratified planetary boundary layer is used to explore the relationships between coherent structures and the vertical momentum flux. The near-surface flow is characterized by transient streaks, which are alternating bands of relatively higher and lower speed flow that form parallel to the mean shear direction in the lower part of the boundary layer. Although individual streaks are transient, the overall flow is in a quasi-equilibrium state in which the streaks form, grow, decay and regenerate over lifetimes on the order of tens of minutes. Coupled with the streaky flow is an overturning circulation with alternating bands of updrafts and downdrafts approximately centered on the streaks. The surface stress is dominated by upward ejections of slower moving near-surface air and downward sweeps of higher speed air from higher in the boundary layer. Conditional sampling of the ejection and sweep events shows that they are compact, coherent structures and are intimately related to the streaks: ejections (sweeps) preferentially form in the updrafts (downdrafts) of the three-dimensional streak flow. Hence, consistent with other recent studies, we propose that the streak motion plays an important role in the maintenance of the surface stress by establishing the preferential conditions for the ejections and sweeps that dominate the surface stress. The velocity fluctuation spectra in the model near the surface have a k ⁻¹ spectral slope over an intermediate range of wavenumbers. This behaviour is consistent with recent theoretical predictions that attempt to evaluate the effects of organized flow, such as near-surface streaks, on the variance spectra.     

Large-Eddy Simulation of Turbulent Flow Over a Rough Surface

A family of wall models is proposed that exhibits moresatisfactory performance than previousmodels for the large-eddy simulation (LES) of the turbulentboundary layer over a rough surface.The time and horizontally averaged statistics such asmean vertical profiles of windvelocity, Reynolds stress, turbulent intensities, turbulentkinetic energy and alsospectra are compared with wind-tunnel experimental data.The purpose of the present study is to obtain simulatedturbulent flows that are comparable with wind-tunnelmeasurements for use as the wind environment for thenumerical prediction by LES of source dispersion in theneutral atmospheric boundary layer.     

Turbulent Pressure Statistics in the Atmospheric Boundary Layer from Large-Eddy Simulation

We use large-eddy simulation (LES) to study the turbulent pressure field in atmospheric boundary layers with free convection, forced convection, and stable stratification. We use the Poisson equation for pressure to represent the pressure field as the sum of mean-shear, turbulence–turbulence, subfilter-scale, Coriolis, and buoyancy contributions. We isolate these contributions and study them separately. We find that in the energy-containing range in the free-convection case the turbulence–turbulence pressure dominates over the entire boundary layer. That part dominates also up to midlayer in the forced-convection case; above that the mean-shear pressure dominates. In the stable case the mean-shear pressure dominates over the entire boundary layer.We find evidence of an inertial subrange in the pressure spectrum in the free and forced-convection cases; it is dominated by the turbulence–turbulence pressure and has a three-dimensional spectral constant of about 4.0. This agrees well with quasi-Gaussian predictions but is a factor of 2 less than recent results from direct numerical simulations at moderate Reynolds numbers. Measurements of the inertial subrange pressure spectral constant at high Reynolds numbers, which might now be possible, would be most useful.     

Evaluating Source Area Contributions from Aircraft Flux Measurements Over Heterogeneous Land Using Large-Eddy Simulation

The estimation of spatial patterns in surface fluxes from aircraft observations poses several challenges in the presence of heterogeneous land cover. In particular, the effects of turbulence on scalar transport and the different behaviour of passive (e.g. water vapour) versus active (e.g. temperature) scalars may lead to large uncertainties in the source area/flux-footprint estimation for sensible (H) and latent (LE) heat-flux fields. This study uses large-eddy simulation (LES) of the land–atmosphere interactions to investigate the atmospheric boundary-layer (ABL) processes that are likely to create differences in airborne-estimated H and LE footprints. We focus on 32~m altitude aircraft flux observations collected over a study site in central Oklahoma during the Southern Great Plains experiment in 1997 (SGP97). Comparison between the aircraft data and traditional model estimates provide evidence of a difference in source area for turbulent sensible and latent heat fluxes. The LES produces reasonable representations of the observed fluxes, and hence provides credible evidence and explanation of the observed differences in the H and LE footprints. Those differences can be quantified by analyzing the change in the sign of the spatial correlation of the H and LE fields provided by the LES model as a function of height. Dry patterns in relatively moist surroundings are able to generate strong, but localized, sensible heating. However, whereas H at the aircraft altitude is still in phase with the surface, LE presents a more complicated connection to the surface as the dry updrafts force a convergence of the surrounding moist air. Both the observational and LES model evidence support the concept that under strongly advective conditions, H and LE measured at the top of the surface layer (≈50 m) can be associated with very different upwind source areas, effectively contradicting surface-layer self-similarity theory for scalars. The results indicate that, under certain environmental conditions, footprint models will need to predict differing source area/footprint contributions between active (H) and passive (LE) scalar fluxes by considering land-surface heterogeneity and ABL dynamics.     

西北干旱区感热异常对中国夏季降水影响的模拟

利用最新版的RegCM3模式通过增加西北干旱区地面向大气的感热输送,模拟了西北干旱区春、夏季感热异常对中国夏季降水的影响。结果表明:西北地区地面向大气的感热输送增加后,西北干旱区低层空气温度升高,空气密度减小使得空气有上升运动距平,减弱了空气的下沉运动,从而在新疆地区降水增加。西北地区下沉气流减弱使得高空气压更强,形成反气旋气流距平,导致高原地区上升气流减弱,在青藏高原降水减少。高原地区上升气流减弱导致在长江中下游和东北北部分别有负的气压距平中心,使得这里有气旋式距平环流,降水增加;而在华南、西南、华北南部和东北南部降水减少。     

A Large-Eddy Simulation Study of Turbulent Flow Over Multiscale Topography

Most natural landscapes are characterized by multiscale (often multifractal) topography with well-known scale-invariance properties. For example, the spectral density of landscape elevation fields is often found to have a power-law scaling behaviour (with a −2 slope on a log–log scale) over a wide span of spatial scales, typically ranging from tens of kilometres down to a few metres. Even though the effect of topography on the atmospheric boundary layer (ABL) has been the subject of numerous studies, few have focussed on multiscale topography. In this study, large-eddy simulation (LES) is used to investigate boundary-layer flow over multiscale topography, and guide the development of parametrizations needed to represent the effects of subgrid-scale (SGS) topography in numerical models of ABL flow. Particular emphasis is placed on the formulation of an effective roughness used to account for the increased aerodynamic roughness associated with SGS topography. The LES code uses the scale-dependent Lagrangian dynamic SGS model for the turbulent stresses and a terrain-following coordinate transformation to explicitly resolve the effects of the topography at scales larger than the LES resolution. The terrain used in the simulations is generated using a restricted solid-on-solid landscape evolution model, and it is characterized by a −2 slope of the elevation power spectrum. Results from simulations performed using elevation fields band-pass filtered at different spatial resolutions indicate a clear linear relation between the square of the effective roughness and the variance of elevation.     

Analysis of Vertical Turbulent Heat Flux Limit in Stable Conditions with a Local Equilibrium, Turbulence Closure Model

Assuming that the vertical turbulent heat flux vanishes at extremely stable conditions, one should expect its maximal absolute value to occur somewhere at moderate stability, between a neutral and extremely stable equilibrium. Consequently, in some situations duality of solutions may be encountered (e.g. two different values of temperature difference associated with the same values of heat flux and wind speed). A quantitative analysis of this feature with a local equilibrium Reynolds-stress model is presented. The fixed-wind / fixed-shear maximum has been identified both in the bulk and in single-point flux–gradient relationships (that is, in the vertical temperature gradient and wind-shear parameter domain). The value of the Richardson number corresponding to this maximum is derived from the model equations. To study the possible feedback in strongly stable conditions, weak and intense cooling scenarios have been simulated with a one-dimensional numerical, high-resolution atmospheric boundary-layer model. Despite the rapid cooling, flow decoupling at the surface has not been observed; instead, a stability-limited heat flux is maintained, with a gradual increase of the Richardson number towards the top of the turbulent layer, with some signs of oscillatory behaviour at intermediate heights. Vertical changes of wind shear and the Brunt–Väisälä frequency display a remarkably non-monotonic character, with some signs of a gradually developing instability.     

The Signature of Sea Spray in the Hexos Turbulent Heat Flux Data

The role of sea spray intransferring heat and moisture across the air-sea interface has remained elusive. Some studies have reported that sea spray does not affect the turbulent air-sea heat fluxes for 10-m wind speeds up to at least 25 m s^-1, while others have reported important spray contributions for wind speeds as low as 12 m s^-1. One goal of the HEXOS (Humidity Exchange over the Sea) program was to quantify spray's contribution to the turbulent air-sea heat fluxes, but original analyses of the HEXOS flux data found the spray signal to be too small to be reliably identified amid the scatter in the data. We look at the HEXOS data again in the context of the TOGA-COARE bulk flux algorithm and a sophisticated microphysical spray model. This combination of quality data andstate-of-the-art modelling reveals a distinct spray signature in virtually all HEXOS turbulent heat flux data collected in winds of 15 m s^-1 and higher. Spray effects are most evident in the latent heat flux data, where spray contributes roughly 10% of the total turbulent flux in winds of 10 m s^-1 and between 10 and 40% in winds of 15–18 m s^-1. The spray contribution to the total sensible heat flux is also at least 10% in winds above 15 m s^-1. These results lead to a new, unified parameterization for the turbulent air-sea heat fluxes that should be especially useful in high winds because it acknowledges both the interfacial and spray routes by which the sea exchanges heat and moisture with the atmosphere.     

Flux Footprints in the Convective Boundary Layer: Large-Eddy Simulation and Lagrangian Stochastic Modelling

We investigated the flux footprints of receptors at different heights in the convective boundary layer (CBL). The footprints were derived using a forward Lagrangian stochastic (LS) method coupled with the turbulent fields from a large-eddy simulation model. Crosswind-integrated flux footprints shown as a function of upstream distances and sensor heights in the CBL were derived and compared using two LS particle simulation methods: an instantaneous area release and a crosswind linear continuous release. We found that for almost all sensor heights in the CBL, a major positive flux footprint zone was located close to the sensor upstream, while a weak negative footprint zone was located further upstream, with the transition band in non-dimensional upwind distances −X between approximately 1.5 and 2.0. Two-dimensional (2D) flux footprints for a point sensor were also simulated. For a sensor height of 0.158 z _i, where z _i is the CBL depth, we found that a major positive flux footprint zone followed a weak negative zone in the upstream direction. Two even weaker positive zones were also present on either side of the footprint axis, where the latter was rotated slightly from the geostrophic wind direction. Using CBL scaling, the 2D footprint result was normalized to show the source areas and was applied to real parameters obtained using aircraft-based measurements. With a mean wind speed in the CBL of U = 5.1 m s⁻¹, convective velocity of w _* = 1.37 m s⁻¹, CBL depth of z _i = 1,000 m, and flight track height of 159 m above the surface, the total flux footprint contribution zone was estimated to range from about 0.1 to 4.5 km upstream, in the case where the wind was perpendicular to the flight track. When the wind was parallel to the flight track, the total footprint contribution zone covered approximately 0.5 km on one side and 0.8 km on the other side of the flight track.