1203 / 2026-03-31 09:08:13

Avoiding the “MJO-mean state trade-off” through the collaborative improvement of moist physical processes

climate modeling, Madden-Julian Oscillation, physical parametrizations

主题1 天气、气候、全球变化、行星大气 > 专题1.2 模式数值算法研究

This study investigates the impact of modified moist physical parameterisations on the global climate model, CIESM, regarding the Madden–Julian oscillation (MJO) simulation. The new moist physical schemes include the Gauss-PDF cloud macrophysical and Single‐ice microphysical schemes, along with the modified ZM convective scheme incorporating convective microphysics and stochastic process. These coordinated adjustments preserve mean-state fidelity while alleviating the MJO propagation deficiencies. The new moist physical schemes reduce the mean precipitation biases over the South Pacific convergence zone, mitigating the double ITCZ problem. They capture the MJO’s key characteristics, including the wavenumber-frequency spectrum, propagation speed, and distance. The Gauss-PDF macrophysics and Single‐ice micro- physics strengthen top-heavy latent heating and effectively export moist static energy (MSE) west of the MJO convection, leading to an enhanced zonal asymmetry in the MSE tendency anomalies. They capture the mid-level evaporative cooling over the western Pacific (~ 150° E), promoting a broader scale of MJO-related zonal circulation anomalies. Appropriate interaction between deep convection and stratiform cloud also plays an important role in altering the MJO propagation. Based on the improvement achieved by the stratiform cloud schemes, the convective microphysics further enhances the top-heavy stratiform heating. Stochastic convection reduces weak precipitation in the dry environment while increasing intense precipitation in the high humidity regime, enhancing the MJO precipitation.