应用AMDAR数据探寻高空颠簸区的方法研究

发布时间：2018-01-16 06:14

本文关键词：应用AMDAR数据探寻高空颠簸区的方法研究　出处：《中国民用航空飞行学院》2016年硕士论文　论文类型：学位论文

【摘要】：目前颠簸区的统计资料主要来自飞行员报告,报告数量少、主观性强,忽视航线以外区域,导致颠簸区统计效果不佳,实用性差。本文首先利用AMDAR(飞机气象数据下传)资料来获取颠簸案例,进而选取了4个颠簸预报指数,基于NCEP再分析数据,对采集的颠簸案例进行模拟预报,通过对预报效果的定量评价,得到最优颠簸预报指数,然后,绘制最优颠簸预报指数分布图,实现分布图的统计,最终得到颠簸高发区。具体如下。对AMDAR资料进行时空特征统计与质量分析,得出：AMDAR是具有高时空密度、高质量的数据资料,实用性极强。通过获取AMDAR资料中DEVG(等效垂直阵风)资料,实现对颠簸案例的采集。选取4个颠簸预报指数,利用NCEP再分析数据集分别对采集的颠簸案例进行模拟预报。选取PODy(发生颠簸正确诊断率)、PODn(未发生颠簸正确诊断率)、POD(整体预报正确率)以及TS (True Skill)评分4个评价指标,对颠簸指数模拟预报的效果进行定量评价,得出,Moscat概率预报因子具有更好的预报效果。基于最优颠簸预报指数Moscat概率预报因子,绘制特定时空条件下的最优颠簸指数分布图,引入灰度图方法,实现颠簸指数分布图的初步筛选,进而采用频数统计的方法,对筛选后的图像作最终处理,最终得到特定区域特定高度层上不同季节下的颠簸高发区具体分布情况。
[Abstract]:At present, the statistical data of the bumpy area mainly come from the pilot report, the number of reports is small, the subjectivity is strong, and the area outside the route is ignored, which leads to the poor statistical effect of the bumpy area. This paper first uses AMDAR data to obtain turbulence cases, and then selects four turbulence forecasting indices, based on NCEP reanalysis data. Through the quantitative evaluation of the forecast effect, the optimal turbulence forecast index is obtained. Then, the distribution map of the optimal turbulence forecast index is drawn to realize the statistics of the distribution map. Finally, we get the bumpy high incidence area. The details are as follows. The space-time characteristic statistics and quality analysis of AMDAR data show that the AMDAR data have high space-time density and high quality data. By obtaining the equivalent vertical gust data from AMDAR data, the acquisition of bumpy cases is realized. Four turbulence prediction indices are selected. The NCEP reanalysis data set is used to simulate and forecast the bumpy cases, and PODyy (correct diagnostic rate for the occurrence of turbulence) is selected. POD (overall prediction accuracy rate) and TS true kill (TS) evaluation index were used to evaluate quantitatively the effect of simulation prediction of turbulence index. The Moscat probability forecast factor has better forecast effect. Based on the Moscat probability forecast factor of the optimal turbulence forecast index, the optimal distribution map of the turbulence index is drawn under the special time and space conditions. The grayscale image method is introduced to realize the preliminary screening of the bumping index distribution map, and then the final processing of the filtered image is made by the method of frequency statistics. Finally, the specific distribution of the bumping high area in different seasons on the specific height layer is obtained.
【学位授予单位】：中国民用航空飞行学院
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V321.2

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