Earth System Science Data (Dec 2012)
Homogenization of Portuguese long-term temperature data series: Lisbon, Coimbra and Porto
Abstract
Three long-term temperature data series measured in Portugal were studied to detect and correct non-climatic homogeneity breaks and are now available for future studies of climate variability. <br><br> Series of monthly minimum (<i>T</i><sub>min</sub>) and maximum (<i>T</i><sub>max</sub>) temperatures measured in the three Portuguese meteorological stations of Lisbon (from 1856 to 2008), Coimbra (from 1865 to 2005) and Porto (from 1888 to 2001) were studied to detect and correct non-climatic breaks. These series, together with monthly series of average temperature (<i>T</i><sub>aver</sub>) and temperature range (DTR) derived from them, were tested in order to detect breaks, using firstly metadata, secondly a visual analysis, and thirdly four widely used homogeneity tests: von Neumann ratio test, Buishand test, standard normal homogeneity test, and Pettitt test. The homogeneity tests were used in absolute (using temperature series themselves) and relative (using sea-surface temperature anomalies series obtained from HadISST2.0.0.0 close to the Portuguese coast or already corrected temperature series as reference series) modes. We considered the <i>T</i><sub>min</sub>, <i>T</i><sub>max</sub> and DTR series as most informative for the detection of breaks due to the fact that <i>T</i><sub>min</sub> and <i>T</i><sub>max</sub> could respond differently to changes in position of a thermometer or other changes in the instrument's environment; <i>T</i><sub>aver</sub> series have been used mainly as control. <br><br> The homogeneity tests showed strong inhomogeneity of the original data series, which could have both internal climatic and non-climatic origins. Breaks that were identified by the last three mentioned homogeneity tests were compared with available metadata containing data such as instrument changes, changes in station location and environment, observation procedures, etc. Significant breaks (significance 95% or more) that coincided with known dates of instrumental changes were corrected using standard procedures. It was also noted that some significant breaks, which could not be connected to known dates of any changes in the park of instruments or stations location and environment, were probably caused by large volcanic eruptions. The corrected series were again tested for homogeneity; the corrected series were considered free of non-climatic breaks when the tests of most of monthly series showed no significant (significance 95% or more) breaks that coincide with dates of known instrument changes. Corrected series are now available within the framework of ERA-CLIM FP7 project for future studies of climate variability (<a href="http://dx.doi.org/10.1594/PANGAEA.785377"target="_blank">doi:10.1594/PANGAEA.785377</a>).