Abstract: A single identification algorithm usually cannot accurately identify the flood-causing rainstorm weather system. To solve the problem this paper studies the flood-causing rainstorm weather process in the upper reaches of the Han River in the autumn flood season since 2000. Combining the curvature value tracking algorithm, domain search method and other mainstream objective identification algorithms, we design an objective identification algorithm that can simultaneously identify multiple weather systems, and builds a digital model that can be used for computer identification based on the flood-causing rainstorm weather conceptual model. By doing so, we realize the objective identification of the flood-causing rainstorm weather conceptual model. A historical case study of the flood-causing rainstorm processes of 15 major flood events in the upper reaches of the Hanjiang River was carried out. The results show that the algorithm is relatively accurate in the objective identification of the location, intensity, moving path and other aspects of large-scale weather systems, and the hit rate is more than 90%. When conducting the objective identification test of the flood-causing rainstorm weather concept model, the hit rate is more than 70%. The objective recognition algorithm of weather conceptual model can be applied to the MICAPS grid data. It can not only quickly identify the flood-causing rainstorm weather pattern in the upper reaches of the Hanjiang River in the autumn flood season, but also can be applied to flood forecasting operations in other basins.