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| 气象探测环境等级评估方法及应用 | |
| 引用本文： | 王成刚,魏夏潞,严家德,金莲姬.气象探测环境等级评估方法及应用[J].应用气象学报,2019,30(1):117-128. |
| 作者姓名： | 王成刚 魏夏潞 严家德 金莲姬 |
| 作者单位： | 南京信息工程大学/中国气象局气溶胶与云降水重点开放实验室, 南京 210044 |
| 基金项目： | 国家重点研究发展计划（2016YFC0203304），国家自然科学基金项目（41505136），公益性行业（气象）科研专项（GYHY201106049） |
| 摘 要： | 利用1990，1994，2000，2005，2011，2013年夏季北京地区Landsat卫星资料、2009年数字高程资料计算气象站周边景观指标参数，结果表明:土地利用类型、气象站周边景观指数、建筑物高度及天空可视因子等参数能对气象探测环境的结构配置信息以数字化方式呈现。此外，景观指标参数和气象要素相关分析表明:对气温变化影响较大的景观指标参数主要有城镇面积、水体面积、最大斑块指数、最大斑块占城镇面积比例、蔓延度指数、平均分维数和天空可视因子。对绝对湿度影响较大的景观指标参数为城镇面积、水体面积、最大斑块指数、最大斑块占城镇面积比例、蔓延度指数、聚集度指数和天空可视因子。对小风占比影响较大的景观指标参数仅为水体面积、最大斑块指数和最大斑块占城镇面积比例。基于以上统计结果，提出了一套对探测环境进行评估的方法——景观指标评估法。利用该方法对北京市15个国家级地面气象观测站进行评估，结果表明:周围环境对观测资料影响程度最小的站为怀柔站；环境影响最大的站为丰台站、朝阳站。 |
| 关 键 词： | 国家级地面气象观测站 探测环境 等级评估 |
| 收稿时间： | 2018/9/17 0:00:00 |
| 修稿时间： | 2018/11/14 0:00:00 |
Grade Evaluation of Detection Environment of Meteorological Stations in Beijing |
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| Wang Chenggang,Wei Xialu,Yan Jiade and Jin Lianji.Grade Evaluation of Detection Environment of Meteorological Stations in Beijing[J].Quarterly Journal of Applied Meteorology,2019,30(1):117-128. | |
| Authors: | Wang Chenggang Wei Xialu Yan Jiade and Jin Lianji |
| Institution: | Nanjing University of Information Science & Technology/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing 210044 |
| Abstract: | With the rapid development of urbanization, meteorological station detection environment is constantly changing. A large number of research results show that the impact of detecting environmental changes on meteorological elements is very obvious, and the spatial representativeness of observations has strong diversity characteristics. Therefore, it is necessary to establish a scientific and reasonable assessment method for the spatial representativeness of observation sites. Using Landsat satellite remote sensing data of 6 selected summers of 1990, 1994, 2000, 2005, 2011, 2013 and digital elevation data in 2009, the landscape indicator parameters around national surface weather observatories in Beijing are calculated and statistical analysis are carried out with observations of national surface meteorological stations. Results show that parameters, such as land use types, landscape indexes around station, building height and sky view factor, etc., can digitally denote the configuration information of the meteorological detection environment. The correlation between landscape indicator parameters and meteorological elements is analyzed. In the study of landscape indicator parameters affecting temperature changes, three high-altitude stations (Foyeding Station, Xiayunling Station and Shangdianzi Station) are used as climate background stations to select advantages and disadvantages of existing indicators. The study shows that main factors which affect the difference of temperature are urban area, water area, largest patch index, largest patch of urban area, contagion index, mean fractal dimension and sky view factor. In the study of response of the landscape indicator parameters to the absolute humidity, the correlation between the absolute humidity and the observed landscape indicator parameters which pass the significance test shows that, among the landscape indicator parameters, urban area, water area, largest patch index, largest patch of urban area, contagion index, mean fractal dimension and sky view factor have good relationship with humidity. But only three landscape indicator parameters have good response correlation with small wind frequency, which are water area, largest patch index and largest patch of urban area. Based on statistical results, a set of preliminary methods for evaluating the detection environment are obtained according to the response intensity of landscape indicator parameters to each element. By classifying different stations and obtaining the effective influence range of site data, the landscape indicator assessment which can detect the environmental impact degree may streamline the assessment. This method is used to evaluate 15 national surface meteorological stations in Beijing. The impact of the surrounding environment is lowest in Huairou Station, followed by Fangshan Station, Changping Station, Miyun Station, Pinggu Station and Yanqing Station. There are two stations with the greatest environmental impacts, namely Fengtai Station and Chaoyang Station. |
| Keywords: | national surface meteorological stations detection environment grade evaluation |
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