Homogeneity Assessment of Annual and Seasonal Maximum and Minimum Temperatures Time Series (Case study of Khazar Region)

One of the important arguments in variability and climate change assessment is the accuracy of climatic time series analysis. Therefore time series to be used should be homogeneous. Annual and seasonal maximum and minimum temperatures of 5 synoptic stations that contain long time series have been assessed in this study. For so doing, we utilized direct and indirect methods. We used metadata through indirect method and absolute and relative standard normal homogeneity test through direct routine. Results showed inhomogeneity which was identified by statistical methods corresponding to metadata. Relative standard normal homogeneity test is more suitable than absolute standard normal homogeneity test in this concern. Assessment of homogeneity between annual and seasonal minimum and maximum temperatures indicates that the parameter of minimum temperature has more inhomogeneity in the data. Comparison of homogeneity results between temperature of warm and cold season reveals that the temperature is more stable during relocation and other changes in cold season than in warm season. Relocation of many stations was not proved to be the cause of inhomogeneity in annual and seasonal maximum temperatures