آناليز شاخص هاي اگروكليماتيك ايران در شرايط تغيير اقليم

Analysis of agroclimatic indices of Iran under future climate change scenarios

Agroclimatic indices could be affected by climate change and evaluation of these indices under different climate scenarios provides a framework for further impact studies. Principal component analysis (PCA) and cluster analysis are proper methods for regional analysis of agroclimatic data and classification of climatic regions based on their similarities. Using 55 agroclimatic variables similarity of 36 meteorological stations around the country were studied under the present and future (2025 and 2050 as target years) climatic conditions. Results of PCA showed that 5 principal components including 1) temperature data, 2) precipitation data and winter minimum temperature, 3) winter maximum temperature, 4) winter precipitation and maximum temperature of spring, summer and autumn and 5) growth degree days during spring and winter and summer precipitation accounts for 97% of total observed variance. Results of cluster analysis showed that under the current climate, the studied stations were grouped in 10 clusters. However, number of clusters was reduced to 8 and 7 for the years 2025 and 2050, respectively. Based on the results it was concluded that under future climatic conditions agroclimatic diversity of Iran will be reduced considerably.