AbstractThe new cloud condensation nuclei (CCN) number concentration (N_CCN) prediction method that combines multiple linear regression and non‐negative matrix factorization, hereafter the MLR_NMF method, to the aerosol number size distribution data is evaluated and applied to the Korea‐United States air quality (KORUS‐AQ) airborne measurement data. The mean fractional bias (MFB) and the mean fractional error (MFE) were used as performance metrics. The performance metrics of the MLR_NMF method for the test data set at several supersaturations (S) (0.4%, 0.6%, 0.8%, and 1.0%) met the performance goal values (MFB and MFE being less than or equal to ±30% and +50%, respectively), and thus, it implies that the MLR_NMF method is appropriate at various S. Applying the MLR_NMF method to KORUS‐AQ airborne measurement data, it was demonstrated that aerosols in Seoul, Korean Peninsula, East Sea, and South Sea had similar hygroscopicity to each other, and aerosols over the Yellow Sea and the East China Sea showed similar hygroscopicity values during the KORUS‐AQ field campaign. Based on the MLR_NMF method, two parameterizations of CCN spectra for a full S range representing various regions in and around the Korean Peninsula in springtime were formulated (Twomey relationship and logarithmic fitting curve). Additionally, it was found that N_CCN decreased exponentially with altitude, and the scale height was approximately 1,700 m in the Seoul metropolitan area. The MLR_NMF method can be used to create a global distribution map of N_CCN or CCN spectra in many regions around the world.