Detection and correction of inhomogeneities in Greek climate temperature series

Abstract

Long term time series of climate observations measured at meteorological stations provide one of the most accurate records of climate in the past. Nevertheless, there are a number of factors that affect measurements of climatic parameters which may cause abrupt or more gradual shifts and trends in the corresponding time series. Thus in order to draw sound conclusions about the climate, homogenized data series are required. Because of the large number of different monthly homogenization methods a coordinated European initiative was launched namely the COST Action HOME ES0601: Advances in Homogenization Methods of Climate Series: an integrated approach (HOME). Its main objective was to review and improve common homogenization methods and to assess their impact on climate time series. In this paper the homogenization method HOMER resulted by the COST Action ES0601, was applied to 52 monthly temperature series of synoptic stations for the period 1960–2004, belonging to the operational weather network of the Hellenic National Meteorological Service (HNMS). Eight stations passed the homogeneity test successfully without any break point or outlier, for two stations only outliers were reported, but not any break points and the remaining 42 stations presented one or more breaks. Approximately 32% of the breaks could be explained by the stations' history. Station relocations as well as changes in observation practices caused most of the temperature anomalies. The adjustments in yearly temperature series were in the range from −1.2 to 2.0 °C. Seasonal and annual anomalies of raw and homogenized series were calculated using as reference the 30-year period 1961–1990. Also, seasonal and annual mean temperature trends before and after homogenization were analysed and their statistical significance calculated. A reduction of trend magnitude was found to be noticeable in all seasons. The most pronounced trend differences were found in summer followed by winter.