The analysis of trends in hydroclimatic parameters and assessment of their statistical significance have recently received a great concern to clarify whether or not there is an obvious climate change. In the current study, parametric linear regression and nonparametric Mann– Kendall tests were applied for detecting annual and seasonal trends in the relative humidity (RH) and dew point temperature (Tdew) time series at ten coastal weather stations in Iran during 1966–2005. The serial structure of the data was considered, and the significant serial correlations were eliminated using the trend-free pre-whitening method. The results showed that annual RH increased by 1.03 and 0.28%/decade at the northern and southern coastal regions of the country, respectively, while annual Tdew increased by 0.29 and 0.15°C per decade at the northern and southern regions, respectively. The significant trends were frequent in the Tdew series, but they were observed only at 2 out of the 50 RH series. The results showed that the difference between the results of the parametric and nonparametric tests was small, although the parametric test detected larger significant trends in the RH and Tdew time series. Furthermore, the differences between the results of the trend tests were not related to the normality of the statistical distribution.
