The Optimization of Visibility Monitoring Network in Guangdong

Zhang Zhiyan; Deng Xuejiao; Wang Baomin; Li Fei; Tan Haobo; Deng Tao

doi:10.11898/1001-7313.20150608

Vol.26, NO.6, 2015

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Article Navigation > Journal of Applied Meteorological Science > 2015 > 26(6): 714-724

Zhang Zhiyan, Deng Xuejiao, Wang Baomin, et al. The optimization of visibility monitoring network in Guangdong. J Appl Meteor Sci, 2015, 26(6): 714-724. DOI: 10.11898/1001-7313.20150608.

Citation:

Zhang Zhiyan, Deng Xuejiao, Wang Baomin, et al. The optimization of visibility monitoring network in Guangdong. J Appl Meteor Sci, 2015, 26(6): 714-724. DOI: 10.11898/1001-7313.20150608.

Zhang Zhiyan, Deng Xuejiao, Wang Baomin, et al. The optimization of visibility monitoring network in Guangdong. J Appl Meteor Sci, 2015, 26(6): 714-724. DOI: 10.11898/1001-7313.20150608.

Citation:

Zhang Zhiyan, Deng Xuejiao, Wang Baomin, et al. The optimization of visibility monitoring network in Guangdong. J Appl Meteor Sci, 2015, 26(6): 714-724. DOI: 10.11898/1001-7313.20150608.

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The Optimization of Visibility Monitoring Network in Guangdong

DOI: 10.11898/1001-7313.20150608

1.
Institute of Tropical and Marine Meteorology of CMA, Guangzhou 510080
2.
Department of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275
3.
Ecological Meteorological Center of Guangdong Province, Guangzhou 510080

Received Date: 2015-03-13
Rev Recd Date: 2015-07-23
Publish Date: 2015-11-30

Abstract

Abstract

Visibility is an important indicator to measure the atmospheric transparency conditions, which not only reflects the regional air quality conditions, but also closely relates to human life. Under current visibility conditions, it is crucial to implement an extensive long term stations for visibility monitoring network to track changes in visibility and determine causal mechanism for the visibility impairment in the region. The visibility observation network in Guangdong includes artificial monitoring network and the visibility sensor network. Artificial visibility observation is carried out at 86 meteorological stations every day, instrument observation is carried out at 39 stations, and the spatial distribution of stations is intensive but quite uneven. Therefore, a new method is carried out aiming at the optimization the overall arrangement of visibility monitoring network.
Based on the dataset (daily visibility and relative humidity from the 86 meteorological stations in Guangdong), the method can be applied to optimization of the overall arrangement of the establishing operational visibility sensor network in Guangdong, which will substitute the artificial monitoring network. The figure-of-merit (FOM) and the spheres of influence (SOI) are calculated, and the most desirable location is ranked and identified using the resultant FOM field. The spatial coverage for each of stations is determined by the SOI. The determination of the minimum number of stations required is carried out by deleting lower ranking stations if more than 50% of its effecting area is covered by higher ranking stations. Besides, taking the local terrain, background stations, and other factors into account, it's suggested 51 stations are required.
Above results can be applied in establishing operational visibility sensor network in Guangdong, which will substitute the artificial monitoring network. The related methods are also applicable to the overall arrangement for monitoring network of other variables.
- visibility;
- relative humidity;
- the network of visibility monitoring;
- the figure-of-merit (FOM);
- the spheres of influence (SOI)

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References(20)

Figures and Tables

Fig. 1 The fitting chart of aerosol growth factor in PRD region (from reference[20])

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Fig. 2 The distribution of visibility monitoring stations in Guangdong

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Fig. 3 The spatial distribution of mean visibility from 2009 to 2011 in Guangdong

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Fig. 5 The spatial distribution of monthly average visibility in Guangdong from 2009 to 2011

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Fig. 6 The spatial distribution of FOM in Guangdong (unit:km)

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Fig. 7 The comparison diagram of visibility spatial distribution in Guangdong from 2009-2011 (a) the visibility spatial distribution of the selected 43 stations, (b) the visibility spatial distribution of pristine 86 stations, (c) the difference value

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Fig. 8 The comparison diagram of monthly visibility spatial distribution in Guangdong

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Fig. 9 The distribution of suggested visibility meter stations

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Fig. 10 The comparison of visibility spatial distribution in Guangdong from 2009 to 2011 (a) the visibility spatial distribution of the improved 51 stations, (b) the visibility spatial distribution of pristine 86 stations, (c) the difference value

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Table 1 The FOM value of 86 stations in Guangdong and their representative stations

站点	排序^*	此站点能代表的站点名称 (挑选出SOI值大于0.7的站点)	FOM指数
四会	1	广宁、高要、三水	6.4664
斗门	2	罗定、鹤山、开平、新会、恩平、台山、顺德、中山、珠海、深圳、湛江、阳江、上川岛、徐闻	7.2201
新会	3	高要、南海、东莞、罗定、阳春、新兴、云浮、鹤山、开平、恩平、台山、顺德、中山、斗门、珠海、深圳、湛江、阳江、上川岛	8.8752
湛江	4	鹤山、新会、恩平、台山、中山、斗门、珠海、深圳、廉江、吴川、阳江、电白、上川岛、雷州、徐闻	8.9335
阳江	5	罗定、阳春、鹤山、开平、新会、恩平、台山、顺德、中山、斗门、珠海、深圳、廉江、吴川、湛江、电白、上川岛、雷州、徐闻	9.1442
台山	6	高要、南海、东莞、罗定、阳春、新兴、云浮、鹤山、开平、新会、恩平、顺德、中山、斗门、珠海、深圳、湛江、阳江、上川岛、徐闻	9.4518
珠海	7	鹤山、新会、台山、顺德、中山、斗门、深圳、湛江、阳江、上川岛、徐闻	10.0547
从化	8	清远、广州、增城	10.1886
佛岗	9	英德、连平、新丰、清远、广州、龙门、河源	10.2230
中山	10	高要、南海、东莞、罗定、阳春、新兴、云浮、鹤山、开平、新会、恩平、台山、顺德、斗门、珠海、深圳、湛江、阳江、上川岛、徐闻	10.2513
乐昌	11		10.3661
开平	12	高要、南海、东莞、罗定、阳春、新兴、云浮、鹤山、新会、恩平、台山、顺德、中山、斗门、深圳、阳江、上川岛	10.3798
汕头	13	潮州、饶平、普宁、揭阳、潮阳、澄海、汕尾	10.3979
高要	14	曲江、英德、封开、德庆、怀集、广宁、四会、三水、广州、南海、东莞、罗定、阳春、新兴、云浮、鹤山、开平、新会、恩平、台山、顺德、番禺、中山	10.4827
广宁	15	曲江、英德、怀集、四会、高要、三水、广州	10.5480
增城	16	清远、从化、广州、龙门	10.5652
番禺	17	英德、高要、三水、广州、南海、东莞、博罗、鹤山、顺德	10.6373
顺德	18	英德、郁南、高要、三水、广州、南海、东莞、博罗、阳春、新兴、云浮、鹤山、开平、新会、恩平、台山、番禺、中山、斗门、珠海、深圳、阳江	10.6439
深圳	19	东莞、鹤山、开平、新会、台山、顺德、中山、斗门、珠海、惠东、湛江、阳江、上川岛	10.7005
揭阳	20	揭西、潮州、普宁、汕头、汕尾	10.7347
始兴	21	南雄、曲江	10.7583
广州	22	佛岗、英德、广宁、四会、高要、三水、花都、从化、南海、东莞、河源、增城、博罗、惠阳、丰顺、鹤山、顺德、番禺	10.9177
花都	23	三水、清远、广州	10.9181
南雄	24	仁化、始兴、连平、河源	11.0811
澄海	25	潮州、饶平、汕头	11.0946
东莞	26	高要、三水、广州、南海、新兴、云浮、鹤山、开平、新会、恩平、台山、顺德、番禺、中山、深圳	11.2866
云浮	27	封开、郁南、德庆、高要、三水、南海、东莞、罗定、阳春、新兴、鹤山、开平、新会、恩平、台山、顺德、中山	11.9637
茂名	28		12.0518
曲江	29	连南、连州、英德、始兴、怀集、广宁、高要、三水、河源	12.0922
怀集	30	连州、曲江、英德、封开、广宁、高要、三水	12.1083
新兴	31	德庆、高要、南海、东莞、罗定、阳春、云浮、鹤山、开平、新会、恩平、台山、顺德、中山	12.1481
南海	32	德庆、高要、三水、广州、东莞、新兴、云浮、鹤山、开平、新会、恩平、台山、顺德、番禺、中山	12.2346
连山	33	连南	12.2383
连南	34	连州、连山、阳山、曲江	12.2427
鹤山	35	高要、三水、广州、南海、东莞、罗定、阳春、新兴、云浮、开平、新会、恩平、台山、顺德、番禺、中山、斗门、珠海、深圳、湛江、阳江、上川岛	12.2517
汕尾	36	揭西、丰顺、潮州、普宁、揭阳、汕头、惠来、陆丰	12.2610
清远	37	佛岗、英德、花都、从化、增城	12.2695
英德	38	仁化、阳山、乳源、曲江、佛岗、连平、新丰、怀集、广宁、高要、三水、清远、广州、佛山、河源、顺德、番禺	12.2908
恩平	39	高要、南海、东莞、罗定、阳春、新兴、云浮、鹤山、开平、新会、台山、顺德、中山、斗门、廉江、湛江、阳江、上川岛	12.3029
封开	40	郁南、德庆、怀集、高要、罗定、云浮	12.3046
罗定	41	封开、郁南、高要、新兴、云浮、鹤山、开平、恩平、台山、中山、斗门、廉江、阳江	12.3618
惠来	42	汕尾	12.3855
连州	43	连南、阳山、曲江、怀集	12.3871
三水	44	曲江、英德、德庆、怀集、广宁、四会、高要、花都、广州、南海、东莞、云浮、鹤山、顺德、番禺	12.3932
德庆	45	封开、郁南、高要、三水、南海、新兴、云浮、顺德	12.4721
揭西	46	丰顺、普宁、揭阳、汕尾	12.4876
吴川	47	湛江、阳江、电白	12.6377
郁南	48	封开、德庆、罗定、云浮	12.6483
普宁	49	揭西、揭阳、汕头、汕尾	12.7815
五华	50		12.8729
惠阳	51	广州、河源、博罗	12.9316
上川岛	52	鹤山、开平、新会、恩平、台山、中山、斗门、珠海、深圳、湛江、阳江、雷州、徐闻	13.0361
龙门	53	佛岗、新丰、增城	13.9223
大埔	54		14.6399
新丰	55	仁化、佛岗、英德、连平、龙门、河源	15.1014
潮州	56	丰顺、饶平、揭阳、汕头、潮阳、澄海、汕尾	15.1312
连平	57	仁化、南雄、乳源、佛岗、英德、翁源、新丰	15.1674
乳源	58	仁化、英德、连平	15.2500
陆丰	59	汕尾	15.2665
惠东	60	龙川、深圳	15.4987
兴宁	61	龙川、梅县	15.5267
翁源	62	连平	15.7310
丰顺	63	广州、揭西、潮州、汕尾、	15.7658
廉江	64	罗定、阳春、恩平、遂溪、高州、湛江、阳江、电白、徐闻	15.9780
博罗	65	广州、惠阳、顺德、番禺	16.3604
梅县	66	兴宁	16.3940
潮阳	67	潮州、汕头	16.6128
仁化	68	南雄、乳源、英德、连平、新丰	16.6348
和平	69	龙川	16.8199
河源	70	南雄、曲江、佛岗、英德、新丰、龙川、广州、惠阳	17.1331
遂溪	71	廉江、雷州	17.1537
电白	72	廉江、吴川、湛江、阳江	17.2018
南澳	73		17.3649
平远	74	蕉岭	17.4526
徐闻	75	台山、中山、斗门、珠海、深圳、湛江、阳江、上川岛	18.2115
海丰	76		18.4305
雷州	77	遂溪、湛江、阳江、上川岛	18.5907
龙川	78	和平、兴宁、河源、惠东	19.6493
紫金	79		19.7063
蕉岭	80	平远	19.8054
信宜	81		20.0784
阳山	82	连南、连州、英德	20.5784
饶平	83	潮州、汕头、澄海	22.2270
化州	84		22.3586
阳春	85	高要、新兴、云浮、鹤山、开平、恩平、台山、顺德、中山、廉江、阳江	22.4352
高州	86	廉江	24.9094
注：*按FOM指数从小到大排序。

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