Grade Evaluation of Detection Environment of Meteorological Stations in Beijing

Wang Chenggang; Wei Xialu; Yan Jiade; Jin Lianji

doi:10.11898/1001-7313.20190111

Vol.30, NO.1, 2019

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Article Navigation > Journal of Applied Meteorological Science > 2019 > 30(1): 117-128

Wang Chenggang, Wei Xialu, Yan Jiade, et al. Grade evaluation of detection environment of meteorological stations in Beijing. J Appl Meteor Sci, 2019, 30(1): 117-128. DOI: 10.11898/1001-7313.20190111.

Citation:

Wang Chenggang, Wei Xialu, Yan Jiade, et al. Grade evaluation of detection environment of meteorological stations in Beijing. J Appl Meteor Sci, 2019, 30(1): 117-128. DOI: 10.11898/1001-7313.20190111.

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Grade Evaluation of Detection Environment of Meteorological Stations in Beijing

DOI: 10.11898/1001-7313.20190111

Nanjing University of Information Science & Technology/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing 210044

Received Date: 2018-09-17
Rev Recd Date: 2018-11-14
Publish Date: 2019-01-31

Abstract

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.
- national surface meteorological stations;
- detection environment;
- grade evaluation

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References(40)

Figures and Tables

Fig. 1 Distribution of land use types in 5 km buffer zone of Tongzhou Station in 1990 and 2013

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Fig. 2 Relation between temperature difference and six observation landscape indicator parameters at Tongzhou Station

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Fig. 3 The fitting of building height, sky view factor to temperature in clear sky on 3 Jul, 3 Aug and 22 Aug in 2009

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Table 1 Landscape indicator parameters at Tongzhou Station (5 km buffer)

指标	1990年	1994年	2000年	2005年	2011年	2013年
城镇面积/%	24.79	29.29	47.47	54.50	63.60	70.80
林地面积/%		0.04	0.04	0.06	0.04
裸地面积/%	43.53	40.41	1.77	0.02	3.30	4.90
农田面积/%	21.86	17.24	44.83	29.60	6.23	5.44
绿地面积/%		4.69	4.01	14.35	24.40	16.65
水体面积/%	9.81	8.33	1.88	1.62	2.42	2.21
斑块数	967	1976	449	859	754	616
最大斑块指数	12.02	13.64	38.11	45.85	59.17	63.61
平均分维数	1.0597	1.059	1.052	1.0561	1.0553	1.0525
蔓延度指数	37.81	45.40	64.19	60.80	62.20	62.00
景观丰度指数	4	6	6	6	6	5
聚集度指数/%	88.68	84.04	93.46	91.33	92.11	93.47
平均邻近指数	260.25	339.45	416.60	478.90	632.35	1066.72

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Table 2 Correlations between landscape indicator parameters and temperature difference at 15 stations

气象站	最大斑块指数	平均分维数	蔓延度指数	水体面积	城镇面积	最大斑块占城镇面积比例
海淀站		-0.92	0.83
顺义站		-0.84
延庆站
密云站
朝阳站
北京市观象台	0.83				0.98	0.84
石景山站	0.94		0.94		0.98	0.95
丰台站	0.90				0.90	0.90
大兴站
房山站
昌平站			0.86	-0.97	0.92
门头沟站	0.92		0.91		0.91	0.93
平谷站				-0.85
通州站	0.90	-0.87	0.87	-0.86	0.94	0.88

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Table 3 Correlations of landscape indicator parameters to humidity at 15 stations

缓冲区	最大斑块指数	蔓延度指数	聚集度	水体面积	城镇面积	最大斑块占城镇面积比例
海淀站				0.94
顺义站
延庆站	-0.89
密云站		-0.89	-0.97
朝阳站
北京市观象台		-0.81
石景山站		-0.83	-0.82
丰台站
大兴站	-0.88	-0.82			-0.85	-0.88
房山站
昌平站	-0.90		-0.84	0.86	-0.92	-0.87
门头沟站	-0.91		-0.87		-0.91	-0.91
平谷站
通州站	-0.86	-0.87	-0.96	0.90	-0.84	-0.86

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Table 4 Correlations of landscape indicator parameters to the ratio of low wind at 15 stations

缓冲区	最大斑块指数	蔓延度指数	景观丰度	水体面积	城镇面积	最大斑块占城镇面积比例
海淀站
顺义站
延庆站	0.82				0.76	0.82
密云站	0.80
朝阳站
北京市观象台	0.80				0.79	0.82
石景山站	0.77				0.72	0.77
丰台站				0.87
大兴站
房山站	0.79				0.76	0.79
昌平站	0.74			-0.72
门头沟站	0.73	0.75	0.78		0.81	0.73
平谷站
通州站		-0.85	-0.70	0.86
怀柔站	0.71		0.77		0.71	0.73

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Table 5 The response intensity of landscape indicator parameters affecting temperature, humidity and small wind frequency

参数	气温	绝对湿度	小风占比
城镇面积	6	4	6
水体面积	3	3
最大斑块指数	5	5	8
最大斑块占城镇面积比例	5	4	6
蔓延度指数	5	5
平均分维数	3
聚集度		5
天空可视因子	5	5

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Table 6 The environment impact on observations of 15 stations in Beijing by four assessment methods

气象站	景观指标评估法	人口数量划分法	卫星图像评估法	卫星资料评估法
怀柔站	很小	小	小	很小
房山站	小	大	很大	小
昌平站	小	很大	很大	很大
密云站	小	中	小	中
平谷站	小	中	大	中
延庆站	中	中	中	中
石景山站	中	大	很小	小
门头沟站	中	中	中	大
顺义站	大	大	很大	中
北京市观象台	大	小	很大	大
海淀站	大	很大	很大	大
通州站	大	很大	大	很大
大兴站	大	很大	小	很大
朝阳站	很大	很大	小	大
丰台站	很大	很大	很大	很大

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