Abstract

http://ssrn.com/abstract=1859847
 
 

References (59)



 


 



Space‐Time Modelling of Trends in Temperature Series


Peter F. Craigmile


Ohio State University - Department of Statistics

Peter Guttorp


University of Washington - Department of Statistics

July 2011

Journal of Time Series Analysis, Vol. 32, Issue 4, pp. 378-395, 2011

Abstract:     
Classical assessments of temperature trends are based on the analysis of a small number of time series. Considering trend to be only smooth changes of the mean value of a stochastic process through time is limiting, because it does not provide a mechanism to study changes of the mean that could also occur over space. Thus, in studies of climate there is a substantial interest in being able to jointly characterize temperature trends over time and space. In this article we build wavelet‐based space‐time hierarchical Bayesian models that can be used to simultaneously model trend, seasonality, and error, allowing for the possibility that the error process may exhibit space‐time long‐range dependence. We demonstrate how these statistical models can be used to assess the significance of trend over time and space. We motivate and apply our methods to the analysis of space‐time temperature trends, based on data collected in the last five decades from central Sweden.

Number of Pages in PDF File: 18

Keywords: Bayesian hierarchical models, Daubechies wavelets, long memory dependence, prediction, seasonality, wavelet decompositions

Accepted Paper Series


Date posted: June 8, 2011  

Suggested Citation

Craigmile, Peter F. and Guttorp, Peter, Space‐Time Modelling of Trends in Temperature Series (July 2011). Journal of Time Series Analysis, Vol. 32, Issue 4, pp. 378-395, 2011. Available at SSRN: http://ssrn.com/abstract=1859847 or http://dx.doi.org/10.1111/j.1467-9892.2011.00733.x

Contact Information

Peter F. Craigmile (Contact Author)
Ohio State University - Department of Statistics ( email )
2100 Neil Avenue
404 Cockins Hall
Columbus, OH 43210
United States
Peter Guttorp
University of Washington - Department of Statistics ( email )
Seattle, WA
United States
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