Comparative study of climatic regions of Golestan province under different climate change scenarios

Climate which is defined as the average weather, has been changed in recent years due to increased greenhouse gasses emission and imbalance of radiation in atmosphere.Climate change is one of the major challenges with affect different aspects of human life on the earth.For recognition of climates a set of rules are employed which are called climatic classification.For performing classification the observed at-stationdata should be interpolated using different methods.Golestan province located in northeast of Iran with diverse climates is chosen for current study. As it is animportantagricultural production region, its climatic classification is ofmainconcern. The aim of this study is to investigate the effects of climate change on climatic zones .
The study area is located in southeastern part of Caspian Sea, between 36˚ 24' to 38˚ N and 53˚ 51' to 56˚ 14' E. The required data of temperature and rainfall for baseline period 1982-2011 were generated using LARS-WG model these generated data along with historical observed dataset were used for calculation of DeMartone classification index. Besides, the index was workedout using the data for baseline and outputs of HADCM3 climate model for three future periods of 2011-2030, 2046-2065 and 2080-2100 under three emission scenario of A2, A1B and B1. The rainfall and temperature data were interpolated using Kriging and Geographically Weighted Regression methods, respectively. The climatic zones were compared based on their coverage percentage in province.
The outputs of LARS weather generator indicated the increase of mean air temperature in Golestan province for about 4.3°C by 2100. Among different emission scenarios, the A2 scenario at the period of 2070 to 2100 shows the maximum increase in temperature . The average monthly rainfall showed decreasing trend in some months and increasing trend in some others but in general, the total annual rainfall will increase. The evaluation of different interpolation methods revealed that the Kriging method is performing more accurately than IDW and Spline methods atinterpolation of rainfall data.
The outputs of LARS weather generator showed an increasing trend in both temperature and rainfall, but the increase would be more significant in case of temperature which in turn, would shift the climatic zones of province. In overall, the province would experience more arid conditions in future periods as a result of climate change. In this manner, the A2 scenario projects morearid conditions for Golestan provinceby the end of this century.