NDLI: Probability Estimates of Extreme Temperature Events: Stochastic Modelling Approach vs. Extreme Value Distributions

Content Provider	Springer Nature Link
Author	Kyselý, Jan
Copyright Year	2002
Abstract	The paper deals with the probability estimates of temperature extremes (annual temperature maxima and heat waves) in the Czech Republic. Two statistical methods of probability estimations are compared; one based on the stochastic modelling of time series of the daily maximum temperature (TMAX) using the first-order autoregressive (AR(1)) model, the other consisting in fitting the extreme value distribution to the sample of annual temperature peaks.The AR(1) model is able to reproduce the main characteristics of heat waves, though the estimated probabilities should be treated as upper limits because of deficiencies in simulating the temperature variability inherent to the AR(1) model. Theoretical extreme value distributions do not yield good results when applied to maximum annual lengths of heat waves and periods of tropical days (TMAX ≥ 30°C), but it is the best method for estimating the probability and recurrence time of annual one-day temperature extremes. However, there are some difficulties in the application: the use of the two-parameter Gumbel distribution and the three-parameter generalized extreme value (GEV) distribution may lead to different results, particularly for long return periods. The resulting values also depend on the chosen procedure of parameter estimation. Based on our findings, the shape parameter testing for the GEV distribution and the L moments technique for parameter estimation may be recommended.The application of the appropriate statistical tools indicates that the heat wave and particularly the long period of consecutive tropical days in 1994 were probably a more rare event than the record-breaking temperatures in July 1983 exceeding 40°C. An improvement of the probability estimate of the 1994 heat wave may be expected from a more sophisticated model of the temperature series.
Starting Page	93
Ending Page	112
Page Count	20
File Format	PDF
ISSN	00393169
Journal	Studia Geophysica et Geodaetica
Volume Number	46
Issue Number	1
e-ISSN	15731626
Language	English
Publisher	Kluwer Academic Publishers-Plenum Publishers
Publisher Date	2002-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Structural Geology Geophysics/Geodesy Meteorology/Climatology
Content Type	Text
Resource Type	Article
Subject	Geochemistry and Petrology Geophysics

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