عنوان مقاله [English]
Homogeneity analysis is one of the important challenges of trend detection in the climate data series. However, the ability of homogeneity tests in detecting heterogeneity differs depending to the parameters or types of changes. Rasht Synoptic Station has long-term climate data which according to the recorded metadata and documents has undergone several location changes. In this study, homogeneous tests including cumulative deviations, Worsley, Normal Standard, Pettit and Bishand were used to test the homogeneity of daily average temperature, air pressure and rainfall data of Rasht station during the period from 1961 to 2018. The results showed that none of the tests were able to reveal any jump in precipitation data. In temperature and pressure parameters, Both Bishand and Pettit tests had more success in discovering the sharpest heterogeneities in accordance to changes in the metadata. However, simultaneous use of multiple test results will lead to more reliable results for identifying heterogeneity. Also, although these tests give a definite date as a jump date, it should be noted that the given dates represent the range of heterogeneity occurring in the least-estimated two years around the real time of the jump. Awareness of the time period of the change of metadata can be useful in choosing the appropriate test. If it is known that potential changes have occurred around the midpoints of the series, Pettit and Bisahnd methods provide a more accurate estimate of the time of the jump occurrence.