Premium
An automatized homogenization procedure via pairwise comparisons with application to Argentinean temperature series
Author(s) -
Hannart Alexis,
Mestre Olivier,
Naveau Philippe
Publication year - 2014
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.3925
Subject(s) - pairwise comparison , homogenization (climate) , computer science , probabilistic logic , series (stratigraphy) , cluster analysis , data mining , pattern recognition (psychology) , artificial intelligence , algorithm , geology , biodiversity , ecology , paleontology , biology
ABSTRACT We describe a fully automatized homogenization procedure and illustrate it on Argentinean weather station temperature series. The procedure relies on multiple pairwise comparisons between a candidate station and its surrounding stations. The main advantage of this approach is to get around the difficulty of defining a reliable reference series; its main drawback is to often require visual attribution and grouping of shifts resulting in too high a cost in human time for implementation on large datasets. Here, we fully automatize these two steps by using a probabilistic metric of similarity between shifts which is leveraged within two optimized clustering schemes. Simulation results show performance improvements versus both visual inspection and the automatized procedure of Menne MJ, Williams CN, Jr. 2009. Homogenization of temperature series via pairwise comparisons. J. Clim . 22: 1700–1717. Implementation on Argentinean temperature series results in the identification and removal of numerous inhomogeneities; corrected series reveal stronger and spatially smoother warming trends.