Investigation and evaluation of methods for homogenization of hydroclimatic data

E. Steirou, Investigation and evaluation of methods for homogenization of hydroclimatic data, Diploma thesis, 156 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2011.



This study focuses on the inhomogeneities of temperature time series covering the last 100 years, as well as on the methods used for their adjustment, and has three components. Based on a systematic study of scientific literature, observed inhomogeneities in historical and modern time series and their adjustment methods were recorded, classified and evaluated. It was found that these methods are mainly statistical, not well justified by experiments and are rarely supported by metadata. In many of the cases studied the proposed corrections are not even statistically significant. From the global database GHCN-Monthly Version 2, all stations containing both raw and adjusted data and satisfying certain criteria of continuity were examined. In the United States of America, because of the big number of available stations, stations were chosen after a suitable sampling. In total 181 stations were analyzed globally. For these stations the differences between the adjusted and non-adjusted linear 100-year trends were calculated. It was found that in the two thirds of the cases, the homogenization procedure increased positive or decreased the negative temperature trends differences. The most common homogenization method ‘SNHT for single shifts’ was applied to synthetic time series with selected statistical characteristics, occasionally with offsets. The method was satisfactory when applied to independent data with normal distribution, but not in data with long-term persistence. The above results cast some doubts in the use of homogenization procedures and tend to indicate that the global temperature increase during the last century is between 0.4°C and 0.7°C, where these two values are the estimates derived from raw and adjusted data, respectively.

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