Sensitivity analysis on the weather research and forecasting model parameters in downscaling a 72-hour rainfall event in Marikina River Basin - Acierto, Ralph Allen Elpa (2012)
Local climate change impact assessment studies are critical in formulating local adaptation strategies for planning and development purposes of a specific locality or in a specific river basin. Impact assessment studies are implemented using downscaling methods to provide higher resolution data needed for impact models like hydrologic models. One of the tools used in downscaling is the limited- area atmospheric model (LAM) called Weather Research and Forecasting (WRF) model. In this study, the WRF model version 3.1.1 was used to downscale a historical 72-hour rainfall event from November 2-5, 2000 in Marikina river basin to investigate the WRF model parametrizations, where event selection is due to data availability constraints. The study was aimed to determine the best physics, dynamics, and nudging parameters for downscaling the historical rainfall event in the study area based on time series analysis of the WRF model parameter sensitivity experiments. The parameter sensitivity experiments are analyzed using observed rainfall from Bosoboso rainfall station and Mt. Oro rainfall station located inside the Marikina River basin. The statistical measures from time series analysis include coefficient of determination (r2), correlation coefficient (r) and RMSE. The coefficient of determination (r2) serves as the main statistical measure used as basis for determining the best parameters in the model. In addition, bias-correction methods and simple 3hourly aggregation are explored in improving the statistical measures and magnitude of the downscaled rainfall time series of the sensitivity experiments.