Identification of inhomogeneities in precipitation time series using SUR models and the Ellipse test

Ana Cristina M. Costa 1 and Amílcar Soares 2
1 Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa
Campus de Campolide, 1070-312 Lisboa, Portugal
Tel.: + 351 213 870 413; Fax: + 351 213 872 140
ccosta@isegi.unl.pt
2 Instituto Superior Técnico, Universidade Técnica de Lisboa
Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Tel.: + 351 218 417 444; Fax: + 351 218 417 389
ncmrp@alfa.ist.utl.pt

Abstract
The homogenization and analysis of long-term meteorological data sets are currently of unprecedented interest to the scientific community. If the monitoring station network is dense enough, many techniques use data  from nearby stations (‘reference’ stations) in order to account for regional climate changes and to isolate the effects of irregularities in a ‘candidate’ station. We propose an extension of the method of cumulative residuals (Ellipse test) that takes into account the contemporaneous relationship between several candidate series from the same climatic area. The proposed technique uses the residuals from a Seemingly unrelated regression equations (SUR) model. This procedure (SUR+Ellipse test) was applied to a testing variable, with annual resolution, derived from the daily precipitation data from 27 stations located in the southern region of Portugal. Three well established statistical tests were also applied: the Standard normal homogeneity test (SNHT) for a single break, the Buishand range test and  the Pettit test. The promising results from this case study indicate the proposed methodology as a valuable tool for homogeneity testing of climate time series if the station network is dense enough.

Keywords: homogeneity testing, ellipse test, seemingly unrelated regression equations, precipitation

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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