The High Concentration Tails Of The Probability Density Function Of A Dispersing Scalar In The Atmosphere

The distribution function for concentrations of a scalar pollutant dispersing in the turbulent atmosphere has a finite domain that is bounded above and below. Three methods, based on extreme value statistics, are used to obtainestimates for the upper bound and to describe the high concentration tailbehaviour of the distribution; all three methods are applied to concentrationdata obtained from experimental atmospheric releases. Quantile quantile (QQ)plots are used to assess the goodness of fit of the resulting estimates of thedistribution, and also to compare the performance of the three methods. Thepredicted values for the upper bound are orders of magnitude less than thesource concentration, illustrating that molecular diffusion has a large effecton the high concentrations.     

公路和城市街渠机动车大气污染物扩散模式发展综述

随着城市机动车数量的增加，机动车尾气污染已经成为城市污染物的重要来源。研究机动车尾气扩散规律，可为公路建设，车流量控制，街道大气污染的监测、评价与防治提供科学依据。对公路机动车污染物扩散模型的发展进行了回顾，详细论述了高斯模式、数值模式、统计模式等模式的发展历程及其目前存在的问题，并比较了几种典型模式的性能优劣及其各种条件下的适用性。随后对城市街渠峡谷机动车污染物扩散模型进行专述，指出了街渠峡谷模式研究的难点在于街渠流场模拟，介绍了国外最新街渠流场研究方法。最后提出了当前机动车大气污染物扩散模型存在的主要困难，展望了其解决途径和发展的方向。     

Multi-Source Emission Determination Using an Inverse-Dispersion Technique

Inverse-dispersion calculations can be used to infer atmospheric emission rates through a combination of downwind gas concentrations and dispersion model predictions. With multiple concentration sensors downwind of a compound source (whose component positions are known) it is possible to calculate the component emissions. With this in mind, a field experiment was conducted to examine the feasibility of such multi-source inferences, using four synthetic area sources and eight concentration sensors arranged in different configurations. Multi-source problems tend to be mathematically ill-conditioned, as expressed by the condition number κ. In our most successful configuration (average κ = 4.2) the total emissions from all sources were deduced to within 10% on average, while component emissions were deduced to within 50%. In our least successful configuration (average κ = 91) the total emissions were calculated to within only 50%, and component calculations were highly inaccurate. Our study indicates that the most accurate multi-source inferences will occur if each sensor is influenced by only a single source. A “progressive” layout is the next best: one sensor is positioned to “see” only one source, the next sensor is placed to see the first source and another, a third sensor is placed to see the previous two plus a third, and so on. When it is not possible to isolate any sources κ is large and the accuracy of a multi-source inference is doubtful.     

WRF中土壤图及参数表的更新对华北夏季预报的影响研究

土壤质地及其物理性质的参数化对陆面过程模拟具有明显的影响。研究了土壤质地和土壤水文参数表的更新对WRF（Weather Research and Forecasting）模拟性能的影响。使用北京师范大学土壤属性数据集和修正后的土壤水文参数表替换WRF默认数据,对2017年6—8月华北地区开展数值模拟试验和评估验证。结果表明,模拟结果对土壤类型数据集和水文参数表的更新较为敏感,对地面要素预报有正效果。WRF默认土壤数据集中,中国东部以粘壤土为主,而在北京师范大学土壤数据集里则以壤土为主;修正后的土壤水文参数在Noah陆面过程中增强了裸土潜热蒸发能力。数值模拟试验表明,土壤输入数据和土壤水文参数的更新能够增强陆面向大气的潜热同时减弱感热输送,致使大气底层温度降低而湿度增大。利用华北区域748个地面气象观测站的2 m温度和2 m湿度对2017年夏季的模拟结果进行验证,结果显示更新试验对地面要素的预报偏差有较好的修正作用,能够将2 m温、湿度的预报技巧分别提高3.4%和2.9%。      

华北-华东地区高温热浪与土壤湿度的关系研究

利用观测站点的日最高气温、土壤湿度旬观测资料以及土壤湿度再分析资料等,分析了华北-华东地区高温热浪次数的时空变化特征及其与土壤湿度的关系。结果表明:1960s以及1990-2010年为高温热浪次数的高值期,1970s-1980s为低值期。利用旋转经验正交函数分解得到土壤湿度的3个气候分区,分区内前期(3-5月)和同期(6-7月)的土壤湿度与6、7月份高温热浪次数基本呈负相关关系,并且同期相关性更显著。在华北-华东北部与中部,5月下旬土壤湿度与6月高温热浪次数、6月上、中旬平均土壤湿度与6月高温热浪次数、7月平均土壤湿度与7月高温热浪次数的相关性均显著。     

土壤湿度和地表反射率变化对中国北方气候影响的数值研究

本文利用ＯＳＵ两层大气环流模式来考察土壤湿度和地表反射率变化对中国北方气候的影响。在（３０—４６°Ｎ，９０—１２０°Ｅ）的区域上进行了３个试验，结果表明干土壤对我国东部季风区和西部非季风区有不同的影响特征。高反射率造成降水减少。并指出地表过程的作用可能是经常发生在华北的春夏连旱现象的重要原因之一。     

甘肃省东部旱作区土壤水分变化规律的研究

甘肃省东部旱作区的气候条件，降水补给作用及作物生长发育状况的特殊性，导致土壤水分具有独特的时空分布规律，麦田２ｍ土层水分的周年变化呈一峰一谷型，可划分为旱季失墒消耗阶段和雨季蓄墒贮水阶段；其垂直变化呈“Ｓ”型，可划分为水分多变层、过渡层及稳定层。     

Improved Representation of Land-surface Heterogeneity in a Non-hydrostatic Numerical Weather Prediction Model

This study focuses on the relevance of accurate surface parameters, in particular soil moisture, and of parameterizations for heterogeneous land surfaces, for the prediction of sensible and latent heat fluxes by a mesoscale weather forecast model with horizontal grid resolution of 7 km. The analysis is based on model integrations for a 30-day period, which are compared both to flux measurements obtained from the LITFASS-2003 field experiment and to high-resolution-model (1-km grid spacing) results. At first, the relevance of improved parameter sets and input data compared to usual operational practice for an accurate prediction of near-surface fluxes is shown and discussed. It is demonstrated that an observation-based land-surface assimilation scheme leads to an improved soil moisture analysis, which is shown to be essential for the realistic simulation of surface fluxes. Secondly, the implementation of two efficient parameterization strategies for subgrid-scale variability of the surface, the mosaic and the tile approach, is presented. Using these methods, the simulations are in better agreement with measurements than simulations with simple aggregation methods that use effective surface parameters. Integrations with the mosaic approach reproduce high resolution simulations very well and more accurately than simulations with the tile method. Finally, the high resolution simulations are analyzed to justify and discuss the approximations underlying both methods.     

Nonlinear Shallow Water Theories for Coastal Waves

Ocean waves entering the near-shore zone undergo nonlinear and dispersive processes. This paper reviews nonlinear models, focusing on the so-called Serre equations. Techniques to overcome their limitations with respect to the phase speed are presented. Nonlinear behaviours are compared with theoretical results concerning the properties of Stokes waves. In addition, the models are tested against experiments concerning periodic wave transformation over a bar topography and of the shoaling of solitary waves on a beach.     

Quantifying preferential flow in soils: A review of different techniques

Preferential flow (PF) in soil has both environmental and human health implications since it favours contaminant transport to groundwater without interaction with the chemically and biologically reactive upper layer of soil. PF is, however, difficult to measure and quantify. This paper reviews laboratory and field techniques, such as breakthrough curves, dye tracing, and scanning techniques, for evaluating PF in soil at different scales. Advanced technologies, such as scanning techniques, have increased our capability to quantify transport processes within the soil with minimal soil disturbance. Important issues with respect to quantifying PF concern large-scale studies, frozen soil conditions, tracing techniques for particles and gases, a lack of simple mathematical tools for interpreting field data, and the lack of a systematic approach for comparing PF data resulting from different measurement techniques. Also, more research is required to quantify the relative importance of the various PF processes that occur in soil rather than the integrated result of all PF processes in soils.