Improving ENSO Simulation through Optimization of Atmospheric Parameterizations in the ICON XPP Earth System Model

The El Niño/Southern Oscillation (ENSO) is a dominant mode of interannual climate variability, profoundly influencing global weather and climate systems. However, accurately simulating ENSO in climate models remains a major scientific challenge due to the complex coupled ocean-atmosphere interactions involved. Utilizing the ENSO Metrics Package, which evaluates tropical climatology, ENSO performance, and feedback biases, twenty-one atmospheric parameters related to cloud physics, microphysics, and turbulence schemes were tuned for ENSO simulations in the next-generation Max-Planck-Institute for Meteorology Earth System model, ICON XPP. Initial parameter perturbations were performed in AMIP simulations to estimate model sensitivities to each parameter. The optimal parameter combination for ENSO simulations was estimated based on the Nelder-Mead optimization scheme using the linear superposition of the parameter sensitivities. This approach effectively reduced the ENSO metrics cost function by 40% in the optimized run within AMIP experiments, including very good simulations of the Bjerknes and atmospheric net heat flux feedbacks. However, applying the optimized parameter sets to fully coupled ocean-atmosphere simulations resulted in very different parameter sensitivities and much less improved ENSO simulations. This discrepancy in the coupled model is largely related to very strong mean state changes in the Sea Surface Temperatures (SST) in the tropical. Direct tuning of parameters in coupled ICON XPP simulations will be explored in subsequent studies.