A multiparameter linear regression model (MLR) of aragonite saturation state (ΩARG) as a function of temperature, pressure and O2 concentration in the upper 1,000 m of the Sea of Japan (East Sea) was derived with an uncertainty of ±0.020 (1σ). The ΩARG data (n = 1,482) used to derive the basin-wide ΩARG prediction model were collected during a field survey in 1999 and were corrected for anthropogenic CO2. Some biases were resolved by addition of a pressure and O2 concentration interaction term to the proposed model. Correlation between the two predictor terms, caused by addition of this term, was minimized by centering the data for the three variables (thus subtracting the mean from each individual data point). Validation of the model against data sets obtained in 1992 and 2007 yielded correlation coefficients of 0.995 ± 0.013 for 1992 (n = 64, p ≪ 0.001) and 0.995 ± 0.009 for 2007 (n = 137, p ≪ 0.001) and root mean square errors of ±0.064 for 1992 and ±0.050 for 2007. The strong correlation between measurements and predictions suggests that the model can be used to estimate the distribution of ΩARG in the Sea of Japan (East Sea) (including dynamic coastal waters) on varying time scales when basic hydrographic data on temperature, pressure and O2 concentration are available. Application of the model to past measurements for the Sea of Japan (East Sea) indicated that interdecadal variability (2σ from the mean) in ΩARG corrected for anthropogenic CO2 was generally high (0.1–0.7) in the upper water layer (<200 m depth), and decreased (0.05–0.2) with depth for waters deeper than 500 m. The interdecadal variability is largely controlled by variations in the degree of water column ventilation. Superimposed on this natural variability, the input of CO2 derived from fossil fuels has markedly acidified the upper water layers during the anthropocene and thereby moved the aragonite saturation horizon upward by 50–250 m. The impact of CO2 derived from fossil fuels on upper ocean acidification will increase in the future. The present study indicates that, in combination with other easily measurable parameters, a multifunctional model can be a powerful tool for predicting the temporal evolution of ΩARG in the ocean, including coastal waters that are highly likely to be susceptible to ocean acidification in the future.