Relative Humidity and Mean Monthly Temperature Forecasts in Ahwaz Station with ARIMA Model in time Series Analysis
作者单位：Faculty Staff of Agriculture Islamic Azad University Roudehen Branch Roudehen-Iran Student in Water Resources engineering Water Engineering Department Science and Research Branch Islamic Azad University Faculty Staff of Environmental Department Islamic Azad University Roudehen Branch Roudehen-Iran
会议名称：《International Conference on Environment and Industrial Innovation（ICEII 2011）》
会议日期：2011年
学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学]
关 键 词：Mean monthly temperature relative humidity ARIMA Ahwaz
摘 要：In two recent decades, the resultant changes in global climate were one of the main issues propounded among water resources’ experts in the country;and temperature and humidity forecasts can efficiently be applied in decision making and optimum usage of water resources. Temperature and humidity have irrefutable effects on hydrologic cycle, production cycle of agricultural products, water consumptions （specifically agriculture）, human efforts and environment. Utilization of Statistical distribution is one of the main rules that have the capability of forecasting hydrologic events with largeness and distinctive incidence probability. Theory of time series is implemented by two main aims of perception or modeling random mechanisms and prospect of future amounts of series based on its past. Relative humidity and the average monthly temperature of Ahvaz synoptic station is used in present research of 20-year-old statistic. And a proper model is achieved by applying time series analysis software （ITSM） in accordance with ARIMA model and autocorrelation and partial autocorrelation method and by evaluation of all probabilistic models in terms of being static and study of parameters and types of models, in order to forecast average monthly temperature ARIMA （0,0,1）×（0,1,1）12 and forecast monthly relative humidity ARIMA （0,0,1）×（2,1,2）12 based on Box-Jenkins algorithm and after validation and evaluation of model, we determined that selection of given models was very proper and forecast of relative humidity measure and average monthly temperature is implemented in agricultural years of 2009-2010 and 2010-2011 by them.