摘要 : The climate conditions of Iran vary from extremely arid in south parts to very humid in the northern parts. In the past two decades, severe droughts and population growth as well as inappropriate management of water resources have... 展开 The climate conditions of Iran vary from extremely arid in south parts to very humid in the northern parts. In the past two decades, severe droughts and population growth as well as inappropriate management of water resources have intensified Iran's water shortage problems. In this study, we used the Polynomial Regression Analysis (PRA) to investigate the trend of climatic parameters, including minimum and maximum air temperature, total monthly rainfall, average monthly relative humidity, sunshine hours, and average monthly wind speed at Fasa Plain, southern Iran with semi-arid climate during 1967-2019. For each parameter, a significant trend in each month was determined by the model contained a linear effect (t), quadratic effect (t(2)), cubic effect (t(3)), and so on. Results indicated that the temporal trend of minimum and maximum temperature was significantly increasing (maximum values of 0.358 and 0.316 degrees C year(-1) in March and April, respectively) during 1967-2014. While the trend of rainfall has fluctuated and almost significantly decreased (maximum decrement of - 3.367 mm year(-1) in March). Sunshine hours had an increasing trend in recent decades (maximum of 3.220 h year(-1) in December), wind speed had a quite negative trend (maximum reduction of - 0.194 m/s year(-1) in January), and relative humidity had a more decreasing trend (maximum decline of - 1.284% year(-1) in November) in the studied duration. Total changes in the studied meteorological parameters are indicative of more warmth and dryness of the region. Rainfall reduction in March and April is in agreement with warming and drying, during 1967-2014. Then, the validation of the obtained equations was assessed using meteorological data of the study area during 2015-2019. The forecasted results showed the acceptable values of coefficient of determination (R-2) between forecasted and actual data. In general, the results of this study indicate a serious warning about warming and climate change in the studied region. 收起