Statistical Downscaling of AGCM60km Precipitation based on Spatial Correlation of AGCM20km Output

Abstract

A statistical downscaling method based on regressing precipitation data is introduced and applied to 60-km resolution Atmospheric General Circulation Model (AGCM60km) output for daily precipitation. The method utilizes a regression domain with a 3×3 60-km grid, and the downscaling target is 3×3 20-km grids in the center of the regression domain. By shifting the regression domain one grid by one grid in 60-km resolution, the same form of regression model, but different regression coefficients for each 20-km grid, can be applied to all the downscaling target areas. Based on application tests for the Asian Monsoon region, the statistical downscaling algorithm shows extremely effective results with a certain pattern of regression error. The monthly based downscaled results from AGCM60km output shows a rather good match to the monthly mean precipitation amount of AGCM20km. The downscaled results also show a plausible mimic to the AGCM20km output in the frequency of daily precipitation amounts; however, the results showed noticeable limitations in simulating low rainfall amounts (e.g., less than 5 mm d^–1), especially on land.