Selecting The Best Meteorological Forcing Dataset For Each River Basin

One of the most important goal of Global Soil Wetness Project (GSWP) is to produce state-of-the-art global data sets of land surface fluxes, state variables and related hydrological quantities for 10-year period (1986-1995). Due to the time schedule and huge amount of data sets, GSWP simulation had started without enough validation and quality check of the provided forcing data. Considering the goal of GSWP, baseline simulation should be run by the "best" dataset. Off course, there is no "perfect" global dataset. Information on the bias and accuracy in the forcing dataset will be helpful for the data analysis. In the previous study, forcing data sets of GSWP-2 are analyzed and compared with surface measurement in terms of monthly mean value and day-to-day variation within one month. And the rank of the accuracy of each dataset was shown for each continent. By the way, the accuracy of the data varies from place to place within the same continent. In this study, same kind of analyses were applied for each river basin. And the best combination of dataset will be produced for each river basin. Also, we try to remove the biases detected in the data analyses for enabling the quantitative use of hydrological application.