Abstract: Based on the atmospheric analogy principle, the inverse problem that the in formation of historical analogue data is utilized to estimate model errors is pu t forward and a method of Analogue Correction of model Errors (ACE) is developed . The ACE can combine effectively both statistical and dynamical metho d together, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasona bly extract the information of a lot of analogues in historical data in order to reduce model errors and improve forecast skill. urthermore, the ACE may identify specific historical data for the so lution of the inverse problem in terms of the particularity of current forecast. The qualitative analyse show that, the ACE is theoretically equivalent to the previous analogue-ynamical model principle, but need not rebuild the com p licated analogue-eviation model, so has better feasibility and operational for e ground. Moreover, under the ideal situations, when numerical models or historica l analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively.