To be able to discuss eight papers, this post does not contain as much background information as usual and is aimed at people already knowledgeable about homogenization of climate networks.
- Mónika Lakatos and Tamás Szentimrey: Editorial.
- The editorial explains the background of this special issue: the importance of homogenisation and the COST Action HOME. Mónika and Tamás thank you very much for your efforts to organise this special issue. I think every reader will agree that it has become a valuable journal issue.
- Ralf Lindau and Victor Venema: On the multiple breakpoint problem and the number of significant breaks in homogenization of climate records.
- My article with Ralf Lindau is already discussed in a previous post on the multiple breakpoint problem.
- José A. Guijarro: Climatological series shift test comparison on running windows.
- Longer time series typically contain more than one inhomogeneity, but statistical tests are mostly designed to detect one break. One way to resolve this conflict is by applying these tests on short moving windows. José compares six statistical detection methods (t-test, Standard Normal Homogeneity Test (SNHT), two-phase regression (TPR), Wilcoxon-Mann-Whithney test, Durbin-Watson test and SRMD: squared relative mean difference), which are applied on running windows with a length between 1 and 5 years (12 to 60 values (months) on either side of the potential break). The smart trick of the article is that all methods are calibrated to a false alarm rate of 1% for better comparison. In this way, he can show that the t-test, SNHT and SRMD are best for this problem and almost identical. To get good detection rates, the window needs to be at least 2*3 years. As this harbours the risk of having two breaks in one window, José has decided to change his homogenization method CLIMATOL to using the semi-hierarchical scheme of SNHT instead of using windows. The methods are tested on data with just one break; it would have been interesting to also simulate the more realistic case with multiple independent breaks.
- Olivier Mestre, Peter Domonkos, Franck Picard, Ingeborg Auer, Stéphane Robin, Emilie Lebarbier, Reinhard Böhm, Enric Aguilar, Jose Guijarro, Gregor Vertachnik, Matija Klan-car, Brigitte Dubuisson, and Petr Stepanek: HOMER: a homogenization software – methods and applications.
- HOMER is a new homogenization method and is developed using the best methods tested on the HOME benchmark. Thus theoretically, this should be the best method currently available. Still, sometimes interactions between parts of an algorithm can lead to unexpected results. It would be great if someone would test HOMER on the HOME benchmark dataset, so that we can compare its performance with the other algorithms.