Multi‐Objective Ensemble‐Processing Strategies to Optimize the Simulation of the Western North Pacific Subtropical High in Boreal Summer

Abstract

Abstract The western North Pacific Subtropical High (WNPSH) in boreal summer is a major atmospheric player affecting East Asian climate, but its simulation in state‐of‐the‐art climate models is still largely biased. Here we use a multi‐objective optimization strategy, the Pareto optimality, to incorporate multiple physical constraints in processing multi‐model simulations provided by the Coupled Model Intercomparison Project Phase 6. We aim to improve the simulation of WNPSH by this practice. Sea surface temperatures from three tropical oceanic basins are found highly related to WNPSH, and thus used as constraints. We also present an ameliorated strategy, which takes a subset of the raw Pareto optimality by imposing conditions of smallest errors. Results show that the overestimate of WNPSH is effectively corrected. The two multi‐objective optimization schemes both perform better than the traditional approach, revealing the importance of implementing physically based links in processing multi‐model ensemble simulations.

Keywords

• CMIP6
• multi‐objective optimization
• Pareto optimality
• the western North Pacific Subtropical High
• ensemble simulations