机构地区:[1]中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室,北京100029
出 处:《气象学报》2007年第1期105-112,共8页Acta Meteorologica Sinica
基 金:国家自然科学基金重点项目"地表通量参数化与大气边界层过程的基础研究"(40233030);自然科学基金面上项目青年科学基金项目"大气湍流能量级串机理及其格子气数值模拟的研究"(40405004)
摘 要:利用2004年11月在白洋淀地区和2005年1月在中国科学院大气物理研究所北京325 m气象塔的47 m高度由超声风温仪和水汽二氧化碳分析仪观测的湍流脉动资料,分析了大气边界层不同下垫面湍流标量场(温度、水汽和二氧化碳)的概率分布及其特征。标量场的概率分布通常不同于高斯分布,而且还会产生偏斜,可以用指数分布描述。因此,标量的偏斜度通常不为0,陡峭度也往往比3大。非0偏斜度的出现可能是由湍流时间序列中的相干结构和间歇性部分造成的。其中,相干结构的存在使概率分布偏斜,但是,它们对偏斜度的贡献相对较小,而与概率分布的长尾现象有关的间歇性则会使偏斜度大大增加。温度、水汽和二氧化碳的平均偏斜度和陡峭度反应了标量场与稳定度、下垫面、天气条件、源汇等因素之间的关系。在不同下垫面,温度和感热通量的偏斜度随稳定度变化比较一致;水汽通量的偏斜度在稳定和不稳定条件下都为正,而水汽本身在不稳定条件下可能出现负的偏斜度;二氧化碳和二氧化碳通量的偏斜度受下垫面影响很大,在不同下垫面,偏斜度与稳定度之间的关系并不一致;而3个标量的陡峭度随稳定度的变化不显著,它们与相应的偏斜度之间存在平方关系。With the three sets of data collected by the ultrasonic anemometers (UAT-Ⅱ) and infrared gas analyzers (Licor 7500) on the towers at the land (land overlying surface)and island (water body overlying surface) in the Baiyangdian region in November 2004, and on a beam at the 47 m level of the Beijing 325 meter meteorological tower of the Institute of Atmospheric Physics, Chinese Academy of Sciences (urban overlying surface), probability distributions of three turbulent scalars (temperature, water vapor and carbon dioxide) over the different characteristic overlying surfaces in the atmospheric boundary layer and their characteristics are analyzed. Probability distributions of temperature, water vapor and carbon dioxide are usually different from Gaussian distribution. In fact, they are skew, steep in middle and long tailed in both ends in most cases, each side of which can be described by exponential distribution. Therefore, the skewness of the three scalars is often not zero and the kurtosis of them is often larger than 3. From the point of view of structures in turbulent time series, non-zero skewness could result from coherent structures and intermittency in scalar time series. Though coherent structures in scalar time series can make probability distributions skew due to their asymmetry, they contribute a little to skewness; while the intermittency related to long tails of probability distributions can increase the skewness a lot. It is in the same way to kurtosis for intermittency. Since scalar fluxes are much more intermittent than scalars themselves, the skewness and kurtosis of scalar fluxes are larger than those of scalars themselves. From the point of view of atmospheric motion, variations of skewness and kurtosis of scalars and their fluxes ar.e complicated due to various mechanical and thermal factors in the atmosphere. On average, the skewness and kurtosis of temperature, water vapor, carbon dioxide and their fluxes describe the relationship of the scalars with stability, overly
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