Extreme Analysis of an Annual Rainfall Dataset

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Abstract:

Annual rainfall values in Fortaleza in Brazil from 1849 to 1979 are modeled with extreme values theory. Generalized Extreme Value (GEV) distribution with and without trend are estimated by using maximum likelihood method for these rainfall values. Moreover, return levels, which is inferred from estimation result of GEV, associated with various return periods are analyzed.

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Periodical:

Advanced Materials Research (Volumes 610-613)

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2756-2760

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December 2012

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Albeverio S et al (2005) Extreme Events in Nature and Society, Springer

Google Scholar

[2] Faranda D et al (2011) Numerical Convergence of the Block-Maxima Approach to the Genera-lized Extreme Value Distribution, J Stat Phys 145: 1156–1180

DOI: 10.1007/s10955-011-0234-7

Google Scholar

[3] Coles S (2001) An Introduction to Statistical Modeling of Extreme Values, Springer, London

Google Scholar

[4] Katz RW (2010) Statistics of extremes in climate change, Climatic Change 100: 71-76

DOI: 10.1007/s10584-010-9834-5

Google Scholar

[5] Furrer, ME et al (2010) Statistical modeling of hot spells and heat waves, Climate Research 43: 191-205

DOI: 10.3354/cr00924

Google Scholar

[6] Rydén J (2011) Statistical Analysis of Temperature Extremes in Long-time Series from Uppsala, Theor Appl Climatol 105: 193-197

DOI: 10.1007/s00704-010-0389-1

Google Scholar

[7] Rychlik I and Rydén J (2006) Probability and Risk analysis – an Introduction for Engineers, Springer, Heideberg

Google Scholar

[8] Tarleton LF,.Katz RW (1994) Statistical Explanation for Trends in Extreme Summary Tempera-tures at Phoenix, Arizona, Journal of Climate 8: 1704-1708

DOI: 10.1175/1520-0442(1995)008<1704:seftie>2.0.co;2

Google Scholar

[9] Nadarajah S (2005) Extremes of Daily Rainfall in West Central Florida, Climatic Change 69: 325-342

DOI: 10.1007/s10584-005-1812-y

Google Scholar

[10] The R Project for Statistical Computing. http://www.r-project.org/

Google Scholar

[11] Extremes Toolkit. http://www.assessment.ucar.edu/toolkit/

Google Scholar

[12] Time Series Data Library. http://robjhyndman.com/TSDL/

Google Scholar