Downscaling of MM5 model output using artificial neural network over western Himalaya

Western Himalaya receives enormous amount of precipitation in the form of snow due to eastward moving synoptic weather system called western disturbance (WD). MM5 a numerical weather prediction (NWP) model, provides precipitation forecast over a grid. Statistical downscaling of NWP output can improve forecast accuracy. In this study artificial neural network (ANN), a non linear method is used to downscale MM5 model forecast to location specific precipitation forecast over western Himalaya. Data of winter months (November to March) from 2003 to 2008 are considered for the study. Data from 2003 to 2007 is used for training and data of winter 2007-2008 is used for validation purpose. In the training process the input-output relationship is extracted and final weight matrix are computed.