Guest post by Peter Domonkos, one of the leading figures in the homogenization of climate data and developer of the homogenization method ACMANT, which is probably the most accurate method currently available.
A recent investigation done in the Centre of Climate Change of University Rovira i Virgili (Spain) showed that the ratio of the practical use of HOME-recommended monthly homogenisation methods is very low, namely it is only 8.4% in the studies published or accepted for publication in 6 leading climatic journals in the first half of 2013.
The six journals examined are the Bulletin of the American Meteorological Society, Climate of the Past, Climatic Change, International Journal of Climatology, Journal of Climate and Theoretical and Applied Climatology. 74 studies were found in which one or more statistical homogenisation methods were applied for monthly temperature or precipitation datasets, the total number of homogenisation exercises in them is 119. A large variety of homogenisation methods was applied: 34 different methods have been used, even without making distinction among different methods labelled by the same name (as it is the case with the procedures of SNHT and RHTest). HOME-recommended methods were applied only in 10 cases (8.4%) and the use of objective or semi-objective multiple break methods was even much rare, 3.4% only.
In the international blind test experiments of HOME, the participating multiple break methods produced the highest efficiency in terms of the residual RMSE and trend bias of homogenised time series. (Note that only methods that detect and correct directly the structures of multiple breaks are considered multiple break methods.) The success of multiple break methods was predictable, since their mathematical structures are more appropriate for treating the multiple break problem than the hierarchic organisation of single break detection and correction.
Thus the closing study of HOME (in Climate of the Past) recommended all of the participating multiple break methods (MASH, PRODIGE, ACMANT, Craddock-test) to use in practice. One hierarchic method (USHCN) approached the efficiency of the multiple break methods and showed some other good features, therefore it is also included in the HOME-recommended methods. The difference between the well-performing and poorer methods turned out to be large therefore no other homogenisation method was recommended by HOME.
A short time has passed since the end of HOME, so we might hope that the positive impact of HOME will be manifested later. However, the authors of the present report were surprised by the fact that the HOME-recommendations are never cited or discussed in the studies of 2013. So the question arises if we are in the right way in achieving advance in time series homogenisation or not.
The whole report includes the analysis of the possible causes of the delay in the expected advance and does recommendations for the future. It has been published in the 13th annual meeting of the European Meteorological Society (Reading, Sept. 2013).
University Rovira i Virgili
Centre for Climate Change (C3)
UPDATE by VV: It may be that this post was published too early. That we were a little impatient. At the EUMETNET Data Management Workshop 2013, a large number of climatologists used modern methods for homogenization, especially HOMER was applied a lot.