Abstract
The climate model, United Kingdom Meteorological Organization model (UKMO) and multivariate statistics, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed to determine the climate diversity and agroclimatic indicators in future climate change. Monthly weather data from 1968 to 2000 at 36 weather stations in Iran were used to generate climate change scenarios for years 2025 and 2050. The UKMO model predicted a temperature rise of 2.7°C and a rainfall decrease of 12% by 2050. By 2050, length of the growth period is predicted to increase by 16 days, length of the dry period will increase by 22 days because of a delay in the first freezing day and an advance in the last freezing day, and the subsequent increase in temperature and decrease in rainfall. Cluster analysis of weather station data shows that 10 currently defined agroenvironment zones will be reduced to 8 by 2025 and to 7 by 2050. Climate change will decrease geographic differences in temperature and precipitation in Iran, and precipitation will be increasingly a determining indicator in the future.
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