| GEOPHYSICS, ASTRONOMY, AND ASTROPHYSICS |
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Characteristics of vapor based on complex networks in China |
| Ai-Xia Feng(冯爱霞)1, Qi-Guang Wang(王启光)2,†, Shi-Xuan Zhang(张世轩)3, Takeshi Enomoto(榎本刚)4, Zhi-Qiang Gong(龚志强)5, Ying-Ying Hu(胡莹莹)6, and Guo-Lin Feng(封国林)5 |
1 Data Service Office, National Meteorological Information Center CMA, Beijing 100081, China;
2 China Meteorological Administration Training Center, China Meteorological Administration, Beijing 100081, China;
3 Pacific Northwest National Laboratory, Richland WA 99352, USA;
4 Disaster Prevention Research Institute, Kyoto University, Uji, Kyoto 611-0011, Japan;
5 Laboratory for Climate Studies, National Climate Center CMA, Beijing 100081, China;
6 Chinese Academy of Meteorological Sciences, Beijing 100081, China |
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Abstract The uneven spatial distribution of stations providing precipitable water vapor (PWV) observations in China hinders the effective use of these data in assimilation, nowcasting, and prediction. In this study, we proposed a complex network framework for exploring the topological structure and the collective behavior of PWV in the mainland of China. We used the Pearson correlation coefficient and transfer entropy to measure the linear and nonlinear relationships of PWV amongst different stations and to set up the undirected and directed complex networks, respectively. Our findings revealed the statistical and geographical distribution of the variables influencing PWV networks and identified the vapor information source and sink stations. Specifically, the findings showed that the statistical and spatial distributions of the undirected and directed complex vapor networks in terms of degree and distance were similar to each other (the common interaction mode for vapor stations and their locations). The betweenness results displayed different features. The largest betweenness ratio for directed networks tended to be larger than that of the undirected networks, implying that the transfer of directed PWV networks was more efficient than that of the undirected networks. The findings of this study are heuristic and will be useful for constructing the best strategy for the PWV data in applications such as vapor observational networks design and precipitation prediction.
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Received: 04 October 2021
Revised: 08 December 2021
Accepted manuscript online: 16 December 2021
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PACS:
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92.60.Jq
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(Water in the atmosphere)
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| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 41775081, 41975100, 41901016, and 41875100), the Innovation Project of the China Meteorological Administration (Grant No. CXFZ2021Z034), and the National Key Research and Development Program of China (Grant No. 2018YFC1507702). |
Corresponding Authors:
Qi-Guang Wang
E-mail: photon316@163.com
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Cite this article:
Ai-Xia Feng(冯爱霞), Qi-Guang Wang(王启光), Shi-Xuan Zhang(张世轩), Takeshi Enomoto(榎本刚), Zhi-Qiang Gong(龚志强), Ying-Ying Hu(胡莹莹), and Guo-Lin Feng(封国林) Characteristics of vapor based on complex networks in China 2022 Chin. Phys. B 31 049201
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[1] Kiehl J T and Trenberth K E 1997 Bull. Am. Meteorol. Soc. 78 197
[2] Vey S, Dietrich R, Fritsche M, Rülke A, Steigenberger P and Rothacher M 2009 J. Geophys. Res. Atmos. 114 D10
[3] Bevis M, Businger S, Chiswell S, Herring T A and Ware R H 1994 J. Appl. Meteor. 33 379
[4] Watts D J and Strogatz S H 1998 Nature 393 440
[5] Albert R and Barabasi A L 2002 Rev. Mod. Phys. 74 47
[6] Newman M E J 2003 SIAM Rev. 45 167
[7] Tsonis A A and Roebber P J 2004 Phys. A 333 497
[8] Tsonis A A, Swanson K L and Roebber P J 2006 Bull. Am. Meteorol. Soc. 87 585
[9] Tsonis A A, Swanson K L and Kravtsov S 2007 Geophys. Res. Lett. 34
[10] Tsonis A A, Swanson K L and Wang G L 2008a J. Clim. 21 2990
[11] Tsonis A A, Swanson K L and Wang G L 2008b Phys. A 387 5287
[12] Gozolchiani A, Yamasaki K, Gazit O and Havlin 2008 Europhys. Lett. 83 28005
[13] Tsonis A A and Swanson K L 2008 Phys. Rev. Lett. 100 228502
[14] Wang G L and Tsonis A A 2008 Geophys. Res. Lett. 35 L17702
[15] Wang G L and Tsonis A A 2009 Chin. Phys. B 18 5091
[16] Wang G L, Swanson K L and Tsonis A A 2009 Geophys. Res. Lett. 36 L07708
[17] Yamasaki K, Gozolchiani A and Havlin S 2008 Phys. Rev. Lett. 100 228501
[18] Donges J F, Zou Y, Marwan N and Kurths J 2009 Eur. Phys. J. Spec. Top. 174 157
[19] Donges J F, Zou Y, Marwan N and Kurths J 2009 Europhys. Lett. 87 48007
[20] Donges J F, Schultz H C H, Marwan N, Zou Y and Kurths J 2011 Eur. Phys. J. B 84 635
[21] Feng A X, Gong Z Q, Wang Q G and Feng G L 2012 Theor. Appl. Climatol. 109 635
[22] Boers N, Donner R V, Bookhagen B and Kurths J 2015 Clim. Dyn. 45 619
[23] Lu Z H, Yuan N M and Fu Z T 2016 Sci. Rep. 6 26779
[24] Sun X, Yu Y B, Yang Y T, Dong J Y, Christian B and Chen X E 2020 Chin. Phys. B 29 108901
[25] Malik N, Bookhagen B, Marwan N and Kurths J 2012 Clim. Dyn. 39 971
[26] Boers N, Bookhagen B, Marwan N, Kurths J and Marengo J A 2013 Geophys. Res. Lett. 40 4386
[27] Boers N, Bookhagen B, Barbosa H M J, Marwan N, Kurths J and Marengo J A 2014 Nat. Commun. 5 5199
[28] Vastano J A and Swinney H L 1988 Phys. Rev. Lett. 60 1773
[29] Schreiber T 2000 Phys. Rev. Lett. 85 461
[30] Abarbanel H D I, Masuda N, Rabinovich M I and Tumer E 2001 Phys. Lett. A 281 368
[31] Bhattacharya J, Hlavackova-Schindler K, Palus M and Vejmelka M 2007 Phys. Rep. 441 1
[32] Wilks D S 1995 Statistical Methods in the Atmospheric Science (New York:Academic Press) pp. 45-54 |
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