Performance of three different temperatue temporal downscaling methods

Sufficient measurements of effective parameters with suitable temporal and spatial distributions for all phenomena are needed. However, providing the data and informations are difficult and costly. So, temporal and/or spatial downscaling is of prime importance. By downscaling, one can generate data from available ones. There are diffent downscaling methods in literature but they are not compared with each other yet. In this research, the performance of three different downscaling methods of self similar fractal, piecewise self similar fractal, and periodic regression are compared. Three-hour temperature data of Mashhad synoptic station were considered for 1992-2009 period. Modeling was done for daily data and was downscaled to three-hour perid, the results were compared with measured data. Similar fractal method was superior over the other two methods, based on two criteria of Root Mean Square Error, and Akaike Information Criteria.