Premium
Comparison of techniques for detection of discontinuities in temperature series
Author(s) -
DucréRobitaille JeanFrançois,
Vincent Lucie A.,
Boulet Gilles
Publication year - 2003
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.924
Subject(s) - classification of discontinuities , homogeneity (statistics) , series (stratigraphy) , homogeneous , homogenization (climate) , computer science , mathematics , machine learning , geology , mathematical analysis , biodiversity , paleontology , ecology , combinatorics , biology
Several techniques for the detection of discontinuities in temperature series are evaluated. Eight homogenization techniques were compared using simulated datasets reproducing a vast range of possible situations. The simulated data represent homogeneous series and series having one or more steps. Although the majority of the techniques considered in this study perform very well, two methods seem to work slightly better than the others: the standard normal homogeneity test without trend, and the multiple linear regression technique. Both methods are distinctive because of their sensitivity concerning homogeneous series and their ability to detect one or several steps properly within an inhomogeneous series. Copyright © 2003 Environment Canada. Published by John Wiley & Sons, Ltd.