Please wait a minute...
Chin. Phys. B, 2011, Vol. 20(7): 079201    DOI: 10.1088/1674-1056/20/7/079201
GEOPHYSICS, ASTRONOMY, AND ASTROPHYSICS Prev   Next  

Circulation system complex networks and teleconnections

Gong Zhi-Qiang(龚志强)a), Wang Xiao-Juan(王晓娟) b)†, Zhi Rong(支蓉) a), and Feng Ai-Xia(冯爱霞)c)
a Laboratory for Climate Monitoring and Diagnosing, National Climate Center, China Meteorological Administration, Beijing 100081, China; b College of Physics and Electronic Engineering, Changshu Institute of Technology, Changshu 215500, China; c Department of Physics, Yangzhou University, Yangzhou 225009, China
Abstract  In terms of the characteristic topology parameters of climate complex networks, the spatial connection structural complexity of the circulation system and the influence of four teleconnection patterns are quantitatively described. Results of node degrees for the Northern Hemisphere (NH) mid-high latitude (30°N—90°N) circulation system (NHS) networks with and without the Arctic Oscillations (AO), the North Atlantic Oscillations (NAO) and the Pacific—North American pattern (PNA) demonstrate that the teleconnections greatly shorten the mean shortest path length of the networks, thus being advantageous to the rapid transfer of local fluctuation information over the network and to the stability of the NHS. The impact of the AO on the NHS connection structure is most important and the impact of the NAO is the next important. The PNA is a relatively independent teleconnection, and its role in the NHS is mainly manifested in the connection between the NHS and the tropical circulation system (TRS). As to the Southern Hemisphere mid-high latitude (30°S—90°S) circulation system (SHS), the impact of the Antarctic Arctic Oscillations (AAO) on the structural stability of the system is most important. In addition, there might be a stable correlation dipole (AACD) in the SHS, which also has important influence on the structure of the SHS networks.
Keywords:  complex network      structural feature      circulation system      node degree  
Received:  24 August 2010      Revised:  14 February 2011      Accepted manuscript online: 
PACS:  92.60.Wc (Weather analysis and prediction)  

Cite this article: 

Gong Zhi-Qiang(龚志强), Wang Xiao-Juan(王晓娟), Zhi Rong(支蓉), and Feng Ai-Xia(冯爱霞) Circulation system complex networks and teleconnections 2011 Chin. Phys. B 20 079201

[1] Tsonis A A, Swanson K L and Roebber P J 2006 Bull. Amer. Meteor. Soc. 87 585
[2] Tsonis A A and Swanson K L 2008 Phys. Rev. Lett. 100 228502
[3] Tsonis A A and Kyle L S 2008 J. Climate 21 2990
[4] Shi Y N 1984 Journal of Nanjing University 20 796 (in Chinese)
[5] Yang P C and Zhou X J 2005 Acta Meteor. Sin. 63 556 (in Chinese)
[6] Feng G L, Dong W J, Gong Z Q and Hou W 2006 Nonlinear Spatotemporal Distribution Theory and Methods for Observational Data (Beijing: China Meteorological Press) p. 227 (in Chinese)
[7] Li J P and Chou J F 1996 Acta Meteor. Sin. 54 312 (in Chinese)
[8] Li J P and Chou J F 1997 Sci. China Ser. B 27 89 (in Chinese)
[9] Watts D J and Strogatz S H 1998 Nature 393 440
[10] Barabasi A L and Albert R 1999 Science 286 509
[11] Jeong H, Tombor B and Albert R 2000 Nature 407 651
[12] Garlaschelli D, Caldarelli G and Pietronero L 2003 Nature 423 165
[13] Gong Z Q, Zhou L, Zhi R and Feng G L 2008 Acta Phys. Sin. 57 5351 (in Chinese)
[14] Wang X J, Gong Z Q, Zhou L and Zhi R 2009 Acta Phys. Sin. 58 6651 (in Chinese)
[15] Yamasaki K, Gozolchiani A and Havlin S 2008 Phys. Rev. Lett. 100 228501
[16] Gong Z Q, Zou M W, Gao X Q and Dong W J 2005 Acta Phys. Sin. 54 3947 (in Chinese)
[17] Feng G L and Dong W J 2003 Chin. Phys. 12 1076
[18] Gong Z Q, Wang X J, Zhi R and Feng G L 2009 Acta Pyhs. Sin. 58 4342 (in Chinese)
[19] Zhi R, Gong Z Q, Zhen Z H and Zhou L 2009 Acta Phys. Sin. 58 2113 (in Chinese)
[20] Kistler R, Kalnay E and Kanamitsu M 2001 Bull. Amer. Meteor. Soc. 82 247
[21] Walker G T and Bliss E V 1932 Mem. Roy. Meteor. Soc. 4 58
[22] Wallace J M and Gutzler D S 1981 Mon. Wea. Rev. 109 784
[23] Fan K and Wang H J 2004 Geophys. Res. Lett. 31 L10201
[24] Gong D Y and Wang S W 1998 Chin. Sci. Bull. 43 296 (in Chinese)
[25] Gong D Y and Wang S W 1999 Geophys. Res. Lett. 26 459
[26] Yuan X and Martinson D G 2001 Geophys. Res. Lett. 28 3609
[27] Li C Y 2000 An Introduction to Climate Dynamics (Beijing: China Meteorological Press) p. 230 (in Chinese)
[28] Thompson D and Wallace J M 1998 Geophys. Res. Lett. 25 1297
[29] Carlson B D 1988 IEEE Trans. Aerosp. Electron. Syst. 24 397
[1] Analysis of cut vertex in the control of complex networks
Jie Zhou(周洁), Cheng Yuan(袁诚), Zu-Yu Qian(钱祖燏), Bing-Hong Wang(汪秉宏), and Sen Nie(聂森). Chin. Phys. B, 2023, 32(2): 028902.
[2] Vertex centrality of complex networks based on joint nonnegative matrix factorization and graph embedding
Pengli Lu(卢鹏丽) and Wei Chen(陈玮). Chin. Phys. B, 2023, 32(1): 018903.
[3] Effect of observation time on source identification of diffusion in complex networks
Chaoyi Shi(史朝义), Qi Zhang(张琦), and Tianguang Chu(楚天广). Chin. Phys. B, 2022, 31(7): 070203.
[4] An extended improved global structure model for influential node identification in complex networks
Jing-Cheng Zhu(朱敬成) and Lun-Wen Wang(王伦文). Chin. Phys. B, 2022, 31(6): 068904.
[5] Characteristics of vapor based on complex networks in China
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). Chin. Phys. B, 2022, 31(4): 049201.
[6] Explosive synchronization: From synthetic to real-world networks
Atiyeh Bayani, Sajad Jafari, and Hamed Azarnoush. Chin. Phys. B, 2022, 31(2): 020504.
[7] Robust H state estimation for a class of complex networks with dynamic event-triggered scheme against hybrid attacks
Yahan Deng(邓雅瀚), Zhongkai Mo(莫中凯), and Hongqian Lu(陆宏谦). Chin. Phys. B, 2022, 31(2): 020503.
[8] Finite-time synchronization of uncertain fractional-order multi-weighted complex networks with external disturbances via adaptive quantized control
Hongwei Zhang(张红伟), Ran Cheng(程然), and Dawei Ding(丁大为). Chin. Phys. B, 2022, 31(10): 100504.
[9] Explosive synchronization in a mobile network in the presence of a positive feedback mechanism
Dong-Jie Qian(钱冬杰). Chin. Phys. B, 2022, 31(1): 010503.
[10] LCH: A local clustering H-index centrality measure for identifying and ranking influential nodes in complex networks
Gui-Qiong Xu(徐桂琼), Lei Meng(孟蕾), Deng-Qin Tu(涂登琴), and Ping-Le Yang(杨平乐). Chin. Phys. B, 2021, 30(8): 088901.
[11] Complex network perspective on modelling chaotic systems via machine learning
Tong-Feng Weng(翁同峰), Xin-Xin Cao(曹欣欣), and Hui-Jie Yang(杨会杰). Chin. Phys. B, 2021, 30(6): 060506.
[12] Dynamical robustness of networks based on betweenness against multi-node attack
Zi-Wei Yuan(袁紫薇), Chang-Chun Lv(吕长春), Shu-Bin Si(司书宾), and Dong-Li Duan(段东立). Chin. Phys. B, 2021, 30(5): 050501.
[13] Exploring individuals' effective preventive measures against epidemics through reinforcement learning
Ya-Peng Cui(崔亚鹏), Shun-Jiang Ni (倪顺江), and Shi-Fei Shen(申世飞). Chin. Phys. B, 2021, 30(4): 048901.
[14] Improving robustness of complex networks by a new capacity allocation strategy
Jun Liu(刘军). Chin. Phys. B, 2021, 30(1): 016401.
[15] Manufacturing enterprise collaboration network: An empirical research and evolutionary model
Ji-Wei Hu(胡辑伟), Song Gao(高松), Jun-Wei Yan(严俊伟), Ping Lou(娄平), Yong Yin(尹勇). Chin. Phys. B, 2020, 29(8): 088901.
No Suggested Reading articles found!