Precipitation Bias Correction of WRF-CFSR Model by EOF Method Over Upper Northern Thailand
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Abstract
Climate modeling system is a challenging and difficult task. Because uncertainty of the model processing is caused by many factors that influence the discrepancy of model output in both spatial and time. Therefore, in this study, the objective of this study was to apply methods or techniques for precipitation bias correction method from the WRF-CFSR regional climate model and to evaluate the efficiency of precipitation bias correction methods from the WRF-CFSR regional climate model. This study was selected the Empirical Orthogonal Function (EOF) for the monthly precipitation bias correction method in the upper northern region of Thailand, all 18 stations covering from 1980-2010 (31 years) and use observation grids data (APHRODITE CRU and GPCP) to compare the results with the WRF-CFSR regional climate model data. The result that the EOF correction method can reduce the difference between the precipitation anomaly and mean precipitation to be closer to the difference of the observation data. For validation with the Root Mean Square Error (RMSE) was found that the EOF bias correction method was unable to reduce the precipitation error. However, the validation with correlation coefficient values, the EOF method can maintain the spatial continuity of monthly precipitation. In particular, the correction of the WRF-CFSR regional climate model data and the GPCP grid observation data had r values 0.52 to 0.97 which is the best correction correlation.
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