The role of dynamics in total ozone deviations from their long-term mean over the Northern Hemisphere

Total ozone anomalies (deviation from the long-term mean) are created by anomalous circulation patterns. The dynamically produced ozone anomalies can be estimated from known circulation parameters in the layer between the tropopause and the middle stratosphere by means of statistics. Satellite observations of ozone anomalies can be compared with those expected from dynamics. Residual negative anomalies may be due to chemical ozone destruction. The statistics are derived from a 14 year data set of TOMS (Total Ozone Mapping Spectrometer January 1979-Dec. 1992) and corresponding 300 hPa geopotential (for the tropopause height) together with 30 hPa temperature (for stratospheric waves) at 60°N. The correlation coefficient for the linear multiple regression between total ozone (dependent variable) and the dynamical parameters (independent variables) is 0.88 for the zonal deviations in the winter of the Northern Hemisphere. Zonal means are also significantly dependent on circulation parameters, besides showing the known negative trend function of total ozone observed by TOMS. The significant linear trend for 60°N is 3 DU/year in the winter months taking into account the dependence on the dynamics between the tropopause region and the mid-stratosphere. The highest correlation coefficient for the monthly mean total ozone anomalies is reached in November with 0.94.     

东疆黑戈壁近地大气边界层气象要素季节变化规律

利用东疆红柳河黑戈壁下垫面陆气相互作用观测站2017年近地大气边界层梯度探测资料和红柳河气象站天气现象观测数据,分析该地区典型晴天条件下的近地层风速、温度和比湿的四季廓线特征。结果表明:四季近地层风廓线变化规律明显。典型晴天条件下,在0.5～4 m高度内风速随高度的增加而变大的速度较快,在4～32 m范围内,白天风速随高度增大较缓慢,但夜间出现快速增大;存在明显的夜间逆温,逆温层主要集中在4～32 m,冬季逆温强于夏季,晨间0.5～32 m间的温度差可达4.6℃,且红柳河四季的气温日较差均较大,秋季可达到15.7℃;夜间比湿高于白天,秋、冬季夜间逆湿层出现在10～32 m,其比湿差为0.15 g/kg左右,夏季无逆湿现象。     

大气遥感最小二乘反演法最优方程的建立和效果研究

以“使反演误差均方达最小”为准则,用不同的回归方法寻求最优通道组合,建立大气温湿遥感最小二乘反演法最优方程,以避免因自变量过多产生计算病态而造成的回归系数不稳定。通过实例比较最优子集法、前进法、后退法、逐步回归法以及文中提出的单F逐步回归法和定M逐步回归法等各种方法所得方程的回归效果。单F和定M逐步回归法不仅计算简单、意义明确,而且实际效果较好,接近于最优子集法的结果。     

The development of stochastic space transformation and diagrammatic perturbation techniques in subsurface hydrology

This paper develops concepts and methods to study stochastic hydrologic models. Problems regarding the application of the existing stochastic approaches in the study of groundwater flow are acknowledged, and an attempt is made to develop efficient means for their solution. These problems include: the spatial multi-dimensionality of the differential equation models governing transport-type phenomena; physically unrealistic assumptions and approximations and the inadequacy of the ordinary perturbation techniques. Multi-dimensionality creates serious mathematical and technical difficulties in the stochastic analysis of groundwater flow, due to the need for large mesh sizes and the poorly conditioned matrices arising from numerical approximations. An alternative to the purely computational approach is to simplify the complex partial differential equations analytically. This can be achieved efficiently by means of a space transformation approach, which transforms the original multi-dimensional problem to a much simpler unidimensional space. The space transformation method is applied to stochastic partial differential equations whose coefficients are random functions of space and/or time. Such equations constitute an integral part of groundwater flow and solute transport. Ordinary perturbation methods for studying stochastic flow equations are in many cases physically inadequate and may lead to questionable approximations of the actual flow. To address these problems, a perturbation analysis based on Feynman-diagram expansions is proposed in this paper. This approach incorporates important information on spatial variability and fulfills essential physical requirements, both important advantages over ordinary hydrologic perturbation techniques. Moreover, the diagram-expansion approach reduces the original stochastic flow problem to a closed set of equations for the mean and the covariance function.     

NOAA－AVHRR图像大气影响校正方法研究及软件研制第一部分 原理和模型

大气影响是遥感定量化应用的主要障碍之一。本文首先分析了大气对遥感图像产生的各种影响并对影响程度进行了一般的阐述，然后在原理和方法上对典型的大气影响校正算法进行了总结。通过分析我们认为，为了校正遥感图像所受到的大气影响，定量地获取当时当地的大气条件是完成这一工作的必要条件，而且是非常重要的条件之一。为此，我们提出了利用ＮＯＡＡ星载垂直探测器资料即ＴＯＶＳ资料，结合使用气溶胶模型，通过大气辐射传输模型，建立地面辐射量与卫星测量值之间的关系，并完成了对ＮＯＡＡ－ＡＶＨＲＲ图像的大气影响校正。在此基础上对我们的模型和算法进行了详细论述。这一模型是一套适用于发展业务软件的校正模型，软件发展完善后将为ＮＯＡＡ－ＡＶＨＲＲ数据的定量化应用打下基础。     

NOAA—AVHRR图像大气影响校正方法研究及软件研制第二部分：软件研制

本文重点介绍平面平行大气多次散射方程的求解及Ｔｏｖｓ资料与图像的配准等问题。对于散射方程的求解本文吸取了众多的研究成果，但由于我们已知的是大气顶的辐射，而未知的是地表反射率，因此直接利用正演方法将存在问题。为此，本文引进地面总波谱辐射与直接波谱辐射的比值作为中间变量，并提出了一种有效的解决办法。本文将重点介绍程序设计，并对一些结果进行了讨论，指出了进一步的工作。经过一年多的试运行，证明该软件运行可靠，时效较高，已达到常规运行的要求。     

夏季华南降水与水汽输送气流及大气加热场的关系

利用ＣＥＭＷＦ／ＷＭＯ逐日资料分析了１９８２年夏季大尺度水汽输送气流，大气加热场与华南降水的关系。结果表明，来自印度洋，孟加拉湾和西太平洋的两支水汽输送气流都具有３０－６０天振荡特征，并共同影响华南地区的降水；夏季风建立后，华南强降水过程与其上空的加热场有良好的对应关系；视热源与水汽汇的加强（减弱）对应华南地区多（少）雨期。     

气溶胶粒子对城市夜间边界层温度影响的模式研究

用一维非定常模式模拟大气气溶胶粒子对城市夜间边界层大气温度场的影响。结果表明：气溶胶粒子对近地层大气地增温作用，对１５０ｍ以上大气起降温作用，并削弱近地逆温层的强度。