A statistical downscaling method based on SOM which named SOM-SD is used over North China. It’s applicatibility by downscaling daily precipitation is evaluated. Indices are selected which represent the statistics of daily precipitation with regard to both precipitation amount (Prtot, SDII) and frequency (nr001), as well as extreme event (P95T, CWD, CDD). The large-scale predictors were extracted from the daily NCEP reanalysis data, while the predictand was high resolution gridded daily observed precipitation. A downscaling method based on SOM named SOM-SD was presented and evaluated. In evaluating, the frequency difference of wet-dry nodes is defined. And it is confirmed that there was a significant positive correlation between frequency difference and precipitation. The SOM-SD method displayed a high skill in reproducting the climatologic statistical properties of the observed precipitation. The value of BS is between 0 and 1.5×10-4. Sscore is between 0.8 and 1. The bias ranges are -7.4% and -11.6% for Prtot and SDII, -3.1days for nr001, +3.4% for P95T, -1.1 days for CWD and +3.5 days for CDD. Therefore, SOM-SD method works reasonably well.