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Article
Article Type:
Research Article

Change-Point Analysis of Polar Zone Radiosonde Temperature Data

V. K. Jandhyala Department of Mathematics, Washington State University, Pullman, Washington

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P. Liu Philips Healthcare, Seattle, Washington

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S. B. Fotopoulos Department of Finance and Management Sciences, Washington State University, Pullman, Washington

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I. B. MacNeill Department of Statistical and Actuarial Sciences, Western University, London, Ontario, Canada

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Print Publication:
01 Mar 2014
DOI:
https://doi.org/10.1175/JAMC-D-13-084.1
Page(s):
694–714
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Abstract

A comprehensive change-point analysis of annual radiosonde temperature measurements collected at the surface, troposphere, tropopause, and lower-stratosphere levels at both the South and North Polar zones has been done. The data from each zone are modeled as a multivariate Gaussian series with a possible change point in both the mean vector as well as the covariance matrix. Prior to carrying out an analysis of the data, a methodology for computing the large sample distribution of the maximum likelihood estimator of the change point is first developed. The Bayesian approach for change-point estimation under conjugate priors is also developed. A simulation study is carried out to compare the maximum likelihood estimator and various Bayesian estimates. Then, a comprehensive change-point analysis under a multivariate framework is carried out on the temperature data for the period 1958–2008. Change detection is based on the likelihood ratio procedure, and change-point estimation is based on the maximum likelihood principle and other Bayesian procedures. The analysis showed strong evidence of change in the correlation between tropopause and lower-stratosphere layers at the South Polar zone subsequent to 1981. The analysis also showed evidence of a cooling effect at the tropopause and lower-stratosphere layers, as well as a warming effect at the surface and troposphere layers at both the South and North Polar zones.

Corresponding author address: V. K. Jandhyala, Dept. of Mathematics, Washington State University, Pullman, WA 99164-3113. E-mail: jandhyala@wsu.edu

Abstract

A comprehensive change-point analysis of annual radiosonde temperature measurements collected at the surface, troposphere, tropopause, and lower-stratosphere levels at both the South and North Polar zones has been done. The data from each zone are modeled as a multivariate Gaussian series with a possible change point in both the mean vector as well as the covariance matrix. Prior to carrying out an analysis of the data, a methodology for computing the large sample distribution of the maximum likelihood estimator of the change point is first developed. The Bayesian approach for change-point estimation under conjugate priors is also developed. A simulation study is carried out to compare the maximum likelihood estimator and various Bayesian estimates. Then, a comprehensive change-point analysis under a multivariate framework is carried out on the temperature data for the period 1958–2008. Change detection is based on the likelihood ratio procedure, and change-point estimation is based on the maximum likelihood principle and other Bayesian procedures. The analysis showed strong evidence of change in the correlation between tropopause and lower-stratosphere layers at the South Polar zone subsequent to 1981. The analysis also showed evidence of a cooling effect at the tropopause and lower-stratosphere layers, as well as a warming effect at the surface and troposphere layers at both the South and North Polar zones.

Corresponding author address: V. K. Jandhyala, Dept. of Mathematics, Washington State University, Pullman, WA 99164-3113. E-mail: jandhyala@wsu.edu
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