Application of random walk model to fit temperature in 46 gamma world cities from 1901 to 1998
Shaomin Yan, Guang Wu
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DOI: 10.4236/ns.2010.212174   PDF    HTML     5,765 Downloads   10,859 Views   Citations

Abstract

Very recently, we have applied the random walk model to fit the global temperature anomaly, CRUTEM3. With encouraging results, we apply the random walk model to fit the temperature walk that is the conversion of recorded tem-perature and real recorded temperature in 46 gamma world cities from 1901 to 1998 in this study. The results show that the random walk model can fit both temperature walk and real recorded temperature although the fitted results from other climate models are unavailable for comparison in these 46 cities. Therefore, the random walk model can fit not only the global temperature anomaly, but also the real recorded temperatures in various cities around the world.

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Yan, S. and Wu, G. (2010) Application of random walk model to fit temperature in 46 gamma world cities from 1901 to 1998. Natural Science, 2, 1425-1431. doi: 10.4236/ns.2010.212174.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Yan, S. and Wu, G. (2009) What these trends suggest? American Journal of Applied Sciences, 6, 1116-1121.
[2] Yan, S. and Wu, G. (2009) Trends in global warming and evolution of polymerase basic protein 2 family from in-fluenza A virus. Journal of Biomedical Sciences and En-gineering, 2, 458-464.
[3] Yan, S. and Wu, G. (2009) Trends in global warming and evolution of matrix protein 2 family from influenza A virus. Interdisciplinary Sciences: Computational Life Sciences, 1, 272-279.
[4] Yan, S.M., Zuo, W.P., Zhu, Q.X., Huang, Y.Y., Pan, L.X. and Wu, G. (2010) Trends in global warming and evolu-tion of neuraminidases from influenza A viruses since 1918. Guangxi Sciences, 17, 80-84.
[5] Yan, S. and Wu, G. (2010) Trends in global warming and evolution of nucleoproteins from influenza A viruses since 1918. Transboundary and Emerging Diseases.
[6] Feller, W. (1968) An introduction to probability theory and its applications. 3rd Edition, Wiley, New York.
[7] Yan, S. and Wu, G. (2010) Modeling of global tempera-ture change from 1850 to 2009 using random walk. Guangxi Sciences, 17, 148-150.
[8] Gordon, A.H. (1991) Global warming as a manifestation of a random walk. Journal of Climate, 4, 589-597.
[9] Wikimedia Foundation, Inc. (2010) Global city. http://en.wikipedia.org/wiki/Global_city
[10] New, M., Hulme, M. and Jones, P. (2000) Representing twentieth-century space-time climate variability. Part II: Development of 1901-96 monthly grids of terrestrial surface climate. Journal of Climate, 13, 2217-2238.
[11] Willison, S. (2010) Get lat lon. http://www.getlatlon.com/
[12] SPSS Inc., SigmaPlot for Windows Version 8.02. (1986-2001).
[13] Borovkov, A. and Borovkov, K. (2008) Asymptotic analysis of random walks: heavy-tailed distributions, Cambridge University Press, Cambridge.
[14] Tekhasski, A. (2010) Random walk model suggests that the global warming could be mainly attributed to random mechanism. http://www.amazon.com/tag/science/forum/ ref=cm_cd_pg_pg7?_encoding=UTF8&cdForum=FxZ58KVEERYS5E&cdPage=7&cdSort=oldest&cdThread=Tx3TXP04WUSD4R1&displayType=tagsDetail
[15] Neil, J. (2009) Simply complexity: A clear guide to com-plexity theory. Reprint edition, Oneworld Publications, Oxford.
[16] Williams, P.D. (2005) Modelling climate change: the role of unresolved processes. Philosophical Transactions of the Royal Society A, 363, 2931-2946.

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