Bagher Ghermezcheshmeh; Aliakbar Rasuli; Majid Rezaei Banafsheh; Alireza Massah Bovani; Alimohammad Khorshiddust
Abstract
Increasing Green House Gases (GHG) may change the climate in different areas. Investigation of parameters are difficult due to induced changes in climate parameters, such as precipitation and temperature. For predicting global climate change, different climate scenarios are defined, using AOGCM models. ...
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Increasing Green House Gases (GHG) may change the climate in different areas. Investigation of parameters are difficult due to induced changes in climate parameters, such as precipitation and temperature. For predicting global climate change, different climate scenarios are defined, using AOGCM models. AOGCMs are able to simulate global atmospheric circulation patterns. However, the spatial resolutions of such models are coarse; for example HadCM3 has spatial resolutions of 3.75 and 2.5 in longitude and latitude, respectively. Therefore, to study climate change in a given area, the outputs of the used AOGCMs must be downscaled properly. For this reason, statistical and dynamical methods have been developed. Statistical methods establish a relationship between AOGCM outputs and climate parameters such as precipitation and temperature. For example, many statistical methods use multiple regressions to predict future climate parameters. However, the accuracy of downscaling procedure varies depending on the geographical position of the studied station in relative to the nearby AOGCM grids. In this research, the accuracy of SDSM was tested in different synoptic stations of northwest Iran. This area has a complex topography and climate due to intrusion of different rain bearing weather systems to the region. First of all, daily climate data (precipitation, maximum and minimum temperature) were collected and their time series created. HadCM3 data for the girds over the studied area was obtained and SDSM model was applied for each climate parameters of all synoptic stations in the region. Then, the difference between the SDSM outputs and observed parameters were evaluated for all the stations and the performance of the downscaled outputs were evaluated by comparing the mean and variance of the model outputs and those of the NCEP/NCAR for the present climate. The morpho-climatic parameters were derived for each station and their relations with the magnitude of the model error were evaluated. Results showed that the error in precipitation has significant relation with the distance to the grid center, whereas the error in maximum temperature is related to the difference between the elevation of a given station and the mean elevation of the HadCM3 grids. For example, in Urmia station, the error is the highest of 104 mm while in Saqez the error is the lowest of 9.4 mm. Also, the maximum temperature accuracy in stations with elevation near to mean elevation of the grid is higher. Pars Abad station with 32 m elevation and with high elevation difference with the grid mean elevation, showed 1.14 ºC of error and Tabriz station with less elevation difference to grid mean elevation, showed 0.0.08 ºC of error.
