【作者】 陈端伟；

【导师】 束炯；

【作者基本信息】 华东师范大学 ， 环境科学， 2005， 硕士

【摘要】 分析和预报污染物在大气中的扩散过程必须要考虑大气自身的运动特点,只有掌握了大气的运动规律才能很好地研究污染物扩散以及污染源对周边环境的影响。目前,国内外多数学者普遍采用传统的高斯模式来研究污染物在大气中的扩散问题,而高斯模式是基于对大气流动、下垫面条件和污染物扩散等几点假设的前提下建立的,因而,在应用过程中存在一定的局限性,随着计算技术的飞速发展,应用数学模型,通过计算机模拟来分析大气污染的过程已成为研究大气污染的最有效手段之一。 在空气污染物输送和扩散规律的研究中,风场的时空变化规律是起支配作用的重要因素,因此提高风场的精度和客观分析能力,才能更好的分析和预报污染物在大气中的扩散情况。目前计算风场的方法主要有诊断方法和预报方法。 预报方法得到的风场能比较客观地反映实际的大气情况,对观测资料的依赖性小,但是其模式复杂,具有计算时间长的缺点,特别是在处理复杂地形情况时,往往要求有较高的空间分辨率,这就使其缺点变得尤为严重。相比之下,诊断方法虽然需要观测资料较多,对观测资料依赖性较强,但从另一个角度来看,这种方法注重实际的观测资料,不仅具有较强的真实性,而且模式简单,计算时间短,因此诊断方法比较常利用。但是诊断方法要得到高精度的风场,也需要高质量的初始猜想场,因此可以考虑利用预报方法得出的粗糙格点分辨率的风场,作为它的初始猜想场,经过诊断方法客观分析,提高风场的精度,以此达到更好的模拟空气中污染物的扩散规律,提高预报空气质量精度的目的。 本文系统地研究了风场诊断方法计算风场的过程。利用粗糙分辨率的预报模型MM5的风场输出耦合到高分辨率诊断模型CALMET里,模拟出高精度的风场,为空气质量模型提供精确的气象场。更多还原

【Abstract】 In the process of analyzing and predicting the dispersion of pollutants in the atmosphere, it is necessary to consider the features of atmospheric movement. Mastery of the rules of atmospheric movement makes successful study of the dispersion of pollutants and the impacts of pollution sources on the ambient environment. An conventional model called Gaussian dispersion model, which is based on the assumptions of atmospheric movement, surface conditions and dispersion of pollutants, is adopted to study the dispersion of pollutants in the atmosphere. However, it has some limits during application. With the rapid development of computation, mathematic models and numerical simulations are applied to analyze the processes of air pollution, which has become one of the most effective methods in this field.The spatial and temporal variations of wind fields play a dominant role in the research of transportation and dispersion of air pollutants. Thus, it is necessary to improve the accuracy of wind fields and enhance the analytic ability. Up to now, diagnosis and prognosis are two main methods of simulating wind fields.Wind fields produced by prognostic methods objectively reflect the real atmosphere and depend less on observations. However, on the other hand, this kind of models is complex, has a long runtime and especially when terrain is complicated, high spatial resolutions are usually required. By contrast, although diagnostic methods deal with more observations and rely more on them, this kind of methods is simpler and more real and has a shorter runtime. This is why diagnostic methods are commonly used. In order to produce high quality wind fields, high quality initial conditions are needed. Hence, it is considerable to use low resolution wind fields produced by prognostic methods as initial conditions and enhance the quality of wind fields using diagnostic methods, which makes simulations of the dispersion of pollutants more effective and predictions of air quality more accurate.In this paper one of the diagnostic methods is studied to simulate wind fields, using the wind fields from a low resolution prognostic model called MM5 as inputs of CALMET, which is a high resolution diagnostic model. The results of this study indicate that utilizing the coarsest prognostic meteorological model output in a diagnostic model provides an attractive option for generating accurate meteorological inputs for air quality modeling.更多还原