Evaluation of Uncertainties in Downscaling Precipitation Due to Climate Change Scenarios

There are considerable uncertainties in precipitation downscaling especially in considering climate change scenario effects. Evaluation of these uncertainties plays an important role in Integrated Water Resources Management (IWRM). Global Climate Models (GCMs) are the primary tools for climate change. There is considerable uncertainty in GCM simulations of climate change associated with: (i) uncertainty in future green house gas emissions and cycles that are usually simulated `off-line' (ii) uncertainty in the GCM response to model structure, parameterization, and spatial resolution. In this paper, the effects of using different climate change scenarios for precipitation downscaling are evaluated. Uncertainties in the downscaling model are also dependent on the input data and available observations for model calibration. For assessment of this aspect of uncertainties in precipitation downscaling, different periods of available data are used for model calibration. After developing 100 sets of ensemble data of downscaled precipitation for one hundred years, the probability distributions of downscaled values are determined and compared with the observed values. The results show that there are considerable uncertainties associated with the climate change scenarios and the input data of the model.