The observed relation between the Kolmogorov and von Karman constants in the surface boundary layer

In steady, neutrally-stratified flow over uniform terrain, the Kolmogorov constant for the one-dimensional spectrum in the inertial subrange (α ₁) and the von Karman constant of the logarithmic profile (k) are shown to be related by $$\alpha _1 k^{{4 \mathord{\left/ {\vphantom {4 3}} \right. \kern-\nulldelimiterspace} 3}} = \left[ {\frac{{\sum \phi }}{{0.555}}} \right]\left[ {\frac{{nz}}{{\bar U_z }}} \right]^{{2 \mathord{\left/ {\vphantom {2 3}} \right. \kern-\nulldelimiterspace} 3}} \left[ {\frac{{\ln z_2 /z_1 }}{{\bar U_2 - \bar U_1 }}} \right]^2 \simeq 0.136,$$ , where the numerical value results from field measurements recorded in near-ideal conditions. This experimentally-observed Kolmogorov-von Karman ‘K-von K’ product is close to the value designated by a one-dimensional equivalent of the theoretical relation previously given by Roth (1970). More-over, it is in remarkably close agreement with new values of both constants independently proposed in recent years.     

On the magnitude and apparent range of variation of the von Karman constant in the atmospheric surface layer

The half-century history of the experimental evaluation of the von Karman constant in the atmospheric surface layer is reviewed, an evidence indicating that this well-known scaling factor,k, is actually a weak variable that decreases with increasing Reynolds number is discussed. A combined average ofk=0.390 with a standard error of ±0.010 is found from two field studies, a result which indicates that there is only one chance in 40 that the true value of the scaling factor in the population from which the experimental sample was drawn could have been as large as the laboratory value of 0.40. Based on experimental and theoretical results given by others, it is suggested thatk varies from a maximum of 0.41 in light winds over open water and smooth land surfaces, to a minimum near 0.37 in stronger winds over forests and cities. This range is shown to imply that a working value ofk=0.39±1% is appropriate for flows over surfaces characterized by 0.7<z ₀<8.7 cm, a roughness subrange which corresponds to a wide variety of terrain types from sparsely vegetated level plains to mixed croplands with occasional hedges and trees.sponsored in part by the Global Change Post Doctoral Program, Office of Health and Environmental Research, U. S. Department of Energy.Work sponsored by the National Science Foundation under Grant No. ATM-9019682.     

An examination of local similarity theory in the stably stratified boundary layer

A stable boundary layer is investigated in terms of local similarity theory. A study is based on a set of seven runs from the BAO tower (Colorado, U.S.A.). It is shown that a theoretical prediction of constant-with-height similarity functions applies only to ensemble-averaged quantities. Scatter of observational data is analysed.On leave from: Institute of Environmental Engineering, Warsaw Technical University, 00653, Warsaw, Poland.     

不同场景下的交通能见度估算模型的应用

能见度监测是交通出行安全的重要保障,尤其对机场和高速公路的大范围低能见度的监测和预警更为重要。在传统人工目测方法的基础上,以激光透射能见度仪为代表的仪器测量方法更为准确,但存在探测范围小、维护成本高、全覆盖耗资大的局限性。为了克服以上缺陷,使交通能见度的估计更为灵活、高效,本文基于机场气象站点观测数据、机场大雾以及高速公路低能见度图像,构建优化三种不同场景下的能见度估计模型,并探讨了不同模型的适用性。1)基于气象站点观测的能见度估计,运用相关系数矩阵和特征重要性分析筛选出相对湿度、温度、水平风速3个变量,并考虑昼夜分别构建三元三次多项式拟合模型,模型的决定系数(R²)可达0.9以上;2)基于机场大雾图像的能见度估计深度学习模型,利用尺度不变特征变换方法提取图像关键点的特征向量,输入全连接神经网络(fully connected neural network)模型,加快训练过程并提高模型的可解释性;3)基于高速公路图像的能见度估计的反演模型,根据暗通道先验理论和能见度测量基本方程,计算大气光亮度和透射率,并根据图像距离信息得到单目图像的能见度,该方法无须预置目标物和...     

Assessments of the global anthropogenic greenhouse and sulfate signal using different types of simplified climate models

Summary The problem of global climate change forced by anthropogenic emissions of greenhouse gases (GHG) and sulfur components (SU) has to be addressed by different methods, including the consideration of concurrent forcing mechanisms and the analysis of observations. This is due to the shortcoming and uncertainties of all methods, even in case of the most sophisticated ones. In respect to the global mean surface air temperature, we compare the results from multiple observational statistical models such as multiple regression (MRM) and neural networks (NNM) with those of energy balance (EBM) and general circulation models (GCM) where, in the latter case, we refer to the recent IPCC Report. Our statistical assessments, based on the 1866–1994 period, lead to a GHG signal of 0.8–1.3 K and a combined GHG-SU signal of 0.5–0.8 K detectable in observations. This is close to GCM simulations and clearly larger than the volcanic, solar and ENSO (El Niño/southern oscillation) signals also considered.With 2 Figures     

Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models

The Finnish Meteorological Institute has calculated statistics for the new reference period of 1981–2010. During this project, the grid size has been reduced from 10 to 1 km, the evaluation of the interpolation has been improved, and comparisons between different methods has been performed. The climate variables of interest were monthly mean temperature and mean precipitation, for which the spatial variability was explained using auxiliary information: mean elevation, sea percentage, and lake percentage. We compared three methods for spatial prediction: kriging with external drift (KED), generalized additive models (GAM), and GAM combined with residual kriging (GK). Every interpolation file now has attached statistical key figures describing the bias and the normality of the prediction error. According to the cross-validation results, GAM was the best method for predicting mean temperatures, with only very small differences relative to the other methods. For mean precipitation, KED produced the most accurate predictions, followed by GK. In both cases, there was notable seasonal variation in the statistical skill scores. For the new reference period and future interpolations, KED was chosen as the primary method due to its robustness and accuracy.     

A comparison of local and non-local turbulence closure methods for the case of a cold air outbreak

Numerical experiments have shown that large-eddy-simulation models (LES) are able to reproduce the common features of convective boundary layers (CBL) quite well. Models which cannot resolve the convective motions due to their grid structure (1D-models or models with coarse horizontal and/or vertical resolution) have to take into account the effects of large eddies within their subgrid diffusion terms. Turbulent fluxes are frequently parameterized through first-order-closure methods (K-theory). Recently, non-local closure schemes have also been developed. In this paper we compare 1D-and 2D-models using different local and non-local first-order closure methods. The analysis is carried out for the case of an idealized cold air outbreak (CAO). One of the non-local closures is based on the so-called transilient turbulence theory. The reference states are given by a bulk-model and a 2D-model which resolves the large eddies explicitly. A comparison of the results is presented for characteristic quantities such as evolution of boundary-layer height and surface heat flux as well as mean wind and temperature profiles. It is found that simple local first-order closure does not give good agreement with the reference models. The results of the transilient turbulence model shows that a non-local closure is able to parameterize the effects of the large eddies. Comparable results are produced by a local closure where eddy diffusivities are parameterized by dimensionless gradient-functions.     

Methodological and empirical flaws in the design and application of simple climate-economy models

One of the main arguments brought forward in favour of the continued use of simple climate-economy models is their transparency, which should enable researchers to easily interpret the simulation results and adapt the model to their specific research interests. We investigate the degree to which this claim is supported in the case of the DICE model but most of our findings are relevant for other welfare-optimizing climate-economy models as well. Specifically, this paper reviews the handling of time discounting in social welfare functions, the combination of different social welfare functions in an analysis, the calibration of uncertain climate parameters, the representation of uncertainty about future climate change, and the evolution of carbon abatement costs over time. We find that each of these aspects has been treated inconsistently in the past, and that these inconsistencies can strongly affect the results of several previous studies. We discuss the methodological questions raised by some of these problems and make specific recommendations how to avoid the problems identified here in future analyses.     

单站气象要素资料在本地大--暴雨预报中的应用

作为常规经验预报手段的单站气象要素资料及预报工具图,在现代天气预报流程中往往被忽视了。其实在定点预报中,单站气象要素资料有着不可替代的作用。在此提出用微机自动处理资料并生成相应预报工具图表的方法,并且对压、温、湿日变化在大—暴雨预报中的作用进行研究。     

Northern African climate at the end of the twenty-first century: an integrated application of regional and global climate models

A method for simulating future climate on regional space scales is developed and applied to northern Africa. Simulation with a regional model allows for the horizontal resolution needed to resolve the region’s strong meridional gradients and the optimization of parameterizations and land-surface model. The control simulation is constrained by reanalysis data, and realistically represents the present day climate. Atmosphere–ocean general circulation model (AOGCM) output provides SST and lateral boundary condition anomalies for 2081–2100 under a business-as-usual emissions scenario, and the atmospheric CO₂ concentration is increased to 757 ppmv. A nine-member ensemble of future climate projections is generated by using output from nine AOGCMs. The consistency of precipitation projections for the end of the twenty-first century is much greater for the regional model ensemble than among the AOGCMs. More than 77% of ensemble members produce the same sign rainfall anomaly over much of northern Africa. For West Africa, the regional model projects wetter conditions in spring, but a mid-summer drought develops during June and July, and the heat stoke risk increases across the Sahel. Wetter conditions resume in late summer, and the likelihood of flooding increases. The regional model generally projects wetter conditions over eastern Central Africa in June and drying during August through September. Severe drought impacts parts of East Africa in late summer. Conditions become wetter in October, but the enhanced rainfall does not compensate for the summertime deficit. The risk of heat stroke increases over this region, although the threat is not projected to be as great as in the Sahel.     

On the potential application of land surface models for drought monitoring in China

The potential of using land surface models (LSMs) to monitor near-real-time drought has not been fully assessed in China yet. In this study, we analyze the performance of such a system with a land surface model (LSM) named the Australian Community Atmosphere Biosphere Land Exchange model (CABLE). The meteorological forcing datasets based on reanalysis products and corrected by observational data have been extended to near-real time for semi-operational trial. CABLE-simulated soil moisture (SM) anomalies are used to characterize drought spatial and temporal evolutions. One outstanding feature in our analysis is that with the same meteorological data, we have calculated a range of drought indices including Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI). We have assessed the similarity among these indices against observed SM over a number of regions in China. While precipitation is the dominant factor in the drought development, relationships between precipitation, evaporation, and soil moisture anomalies vary significantly under different climate regimes, resulting in different characteristics of droughts in China. The LSM-based trial system is further evaluated for the 1997/1998 drought in northern China and 2009/2010 drought in southwestern China. The system can capture the severities and temporal and spatial evolutions of these drought events well. The advantage of using a LSM-based drought monitoring system is further demonstrated by its potential to monitor other consequences of drought impacts in a more physically consistent manner.     

Proof of the monotonicity of grid size and its application in grid-size selection for mesoscale models

Terrain characteristics can be accurately represented in spectrum space. Terrain spectra can quantitatively reflect the effect of topographic dynamic forcing on the atmosphere. In wavelength space, topographic spectral energy decreases with decreasing wavelength, in spite of several departures. This relationship is approximated by an exponential function. A power law relationship between the terrain height spectra and wavelength is fitted by the least-squares method, and the fitting slope is associated with grid-size selection for mesoscale models. The monotonicity of grid size is investigated, and it is strictly proved that grid size increases with increasing fitting exponent, indicating that the universal grid size is determined by the minimum fitting exponent. An example of landslide-prone areas in western Sichuan is given, and the universal grid spacing of 4.1 km is shown to be a requirement to resolve 90% of terrain height variance for mesoscale models, without resorting to the parameterization of subgrid-scale terrain variance. Comparison among results of different simulations shows that the simulations estimate the observed precipitation well when using a resolution of 4.1 km or finer. Although the main flow patterns are similar, finer grids produce more complex patterns that show divergence zones, convergence zones and vortices.Horizontal grid size significantly affects the vertical structure of the convective boundary layer. Stronger vertical wind components are simulated for finer grid resolutions. In particular, noticeable sinking airflows over mountains are captured for those model configurations.     

一次局地短时强降水的成因和预报误差分析

利用常规气象观测资料、NCEP/NCAR再分析资料和多普勒天气雷达资料,对2016年8月6—8日潍坊一次强对流天气的成因和预报误差进行了分析,结果表明：1）500 hPa冷涡底部低槽、850 hPa低涡切变线和地面倒槽是主要影响天气系统, 数值预报对此次天气过程的影响系统预报偏差大,而预报员对数值预报依赖程度高是此次预报失误的主要原因;2）850 hPa以下强的水汽辐合是强降水发生的重要条件,低层辐合和高层辐散配置导致的强垂直上升运动是暴雨产生的动力机制,位势不稳定因中高层的冷空气入侵下沉得以加强;3）列车效应和强回波维持少动是造成短时强降水的重要回波特征,逆风区的发展和移动对于判断强降水的落区有指示作用,多普勒雷达反演风场中的中尺度辐合线是导致局地强降水发生的直接原因;4）风廓线雷达水平风场可以连续地反映降水过程中风场垂直结构及其变化,降水发生前探测高度明显升高,中高层冷空气侵入时间与强降水的时段相对应。     

华南局地锋生及对流系统发展的模拟分析研究

2009年3月28日一条东西向的锋面出现在华南25°N附近。伴随着锋面的活动,对流降水回波午后开始在广西的梧州附近发展,并在随后几小时向东移动,组织发展成为中尺度对流系统(MCS),为广东中西部及珠三角地区带来了雷暴、暴雨、冰雹等灾害天气。应用地面自动站、雷达回波、卫星云图以及NCEP-FNL再分析资料和WRF模式的模拟结果,对锋面暴雨形成的天气特征进行了诊断分析,考察了中尺度对流系统的发展演变过程及其与局地锋生的相互关系。结果表明,锋面对流系统形成发展于一个东西向水平尺度约200km的地面中尺度辐合线附近,对流起始发展于具有较大对流有效位能(CAPE)和较小对流抑制位能(CIN)的区域。伴随着对流的发展,锋面强度增强。锋生函数的计算发现,非绝热项和倾斜项分别在由对流引起的次级环流的上升运动支和下沉运动支起锋生作用,是引发中尺度锋生的主要影响因子。而相对来说,水平辐合项和形变项的作用却比较小。这与大尺度的锋生过程不同,中尺度锋生更主要的是由热力直接触发的非地转环流所驱动。涡度场的演变分析还发现,沿着850hPa锋区大的正涡度区与500hPa的强上升运动区对应良好,对流系统发展与中尺度锋生之间存在着类似于第二条件不稳定机制的相互作用,对流增强了锋生过程,锋面则对中尺度对流系统的发展起组织作用。中尺度锋生对对流组织发展的作用作为此类灾害天气形成的原因值得关注。     

Towards an operational aqueous phase chemistry mechanism for regional chemistry-transport models: CAPRAM-RED and its application to the COSMO-MUSCAT model

Mechanism reductions of the detailed aqueous phase chemistry mechanism CAPRAM 3.0i are performed. Manual methods and automatic techniques are both applied in order to provide a less computationally intensive mechanism which is operational in regional chemistry transport models (CTMs). The finally reduced mechanism contains less than 200 reactions (4 times smaller than the detailed CAPRAM 3.0i) and describes the main characteristics of inorganic and organic aqueous phase processes occurring in tropospheric warm clouds. Most of the chemical reduction potential is realized in the CAPRAM 3.0i organic chemistry. The number of aqueous phase species decreases from 380 in the full mechanism to 130 in the final reduced version. The calculated percentage deviations between the full and reduced mechanism are on average below 5% for the most important organic and inorganic target compounds such as oxidants, inorganic and organic acids, carbonyls and alcohols. Comparisons of the required CPU times between the full and reduced mechanisms show reductions of approximately 40%. 2-D test simulations with the CTM MUSCAT were performed using prescribed meteorological conditions in order to examine the applicability of the reduced mechanism at regional scale. Simulations with the reduced CAPRAM 3.0i mechanism and a much less complex mechanism with only limited inorganic chemistry (INORG) were compared to evaluate the effects of more detailed chemistry. The model results show large differences in the level of oxidants and the inorganic and organic mass processing. Prospectively, the reduced mechanism represents the basis for studying aerosol cloud processing effects at regional scale with future CTMs and will allow more adequate interpretation of field data.     

Analysis of rainfall seasonality from observations and climate models

Two new indicators of rainfall seasonality based on information entropy, the relative entropy (RE) and the dimensionless seasonality index (DSI), together with the mean annual rainfall, are evaluated on a global scale for recently updated precipitation gridded datasets and for historical simulations from coupled atmosphere–ocean general circulation models. The RE provides a measure of the number of wet months and, for precipitation regimes featuring a distinct wet and dry season, it is directly related to the duration of the wet season. The DSI combines the rainfall intensity with its degree of seasonality and it is an indicator of the extent of the global monsoon region. We show that the RE and the DSI are fairly independent of the time resolution of the precipitation data, thereby allowing objective metrics for model intercomparison and ranking. Regions with different precipitation regimes are classified and characterized in terms of RE and DSI. Comparison of different land observational datasets reveals substantial difference in their local representation of seasonality. It is shown that two-dimensional maps of RE provide an easy way to compare rainfall seasonality from various datasets and to determine areas of interest. Models participating to the Coupled Model Intercomparison Project platform, Phase 5, consistently overestimate the RE over tropical Latin America and underestimate it in West Africa, western Mexico and East Asia. It is demonstrated that positive RE biases in a general circulation model are associated with excessively peaked monthly precipitation fractions, too large during the wet months and too small in the months preceding and following the wet season; negative biases are instead due, in most cases, to an excess of rainfall during the premonsoonal months.     

Testing the method for surface air temperature refinement based on a complex of models of the atmospheric boundary layer and local heat and water budgets

A method is considered for space-time refinement of surface air temperature obtained from the atmospheric general circulation model (GCM) of the Hydrometeorological Center of Russia over a limited area by means of use of a complex of the atmospheric boundary layer models and surface heat and water budget model. The latter describes all major processes of heat and water exchange at the underlying surface and within the soil and vegetation using 14 external parameters for different types of landscapes and soils. The side and upper boundary conditions for the local model are provided from the GCM model. Different statistical estimates of the modeling results show possibility and reliability of the refinement for time changes of the quantity under calculation as well as for development of averaged fields reflecting small-scale inhomogeneities of the landscape.