用3D海洋与大气模拟器构建快速准确的气候耦合模型。
SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators
- 采用机器学习代理模型实现大气与海洋的三维耦合模拟。
- 可生成百年尺度模拟，分辨率达1度、6小时/5天，误差接近真实模型。
- 能真实再现厄尔尼诺等气候现象，适合长期气候预测研究。
传统全球气候模型通过分别模拟大气、海洋、海冰、地表等过程，并由耦合器在空间或时间上对齐并交换通量来实现地球系统模拟。受此范式启发，我们提出SamudrACE：一个基于机器学习的耦合全球气候模型模拟器，可在1度水平分辨率、6小时大气和5日海洋分辨率下运行百年级模拟，输出145个二维场，涵盖8个大气层和19个海洋垂直层，以及海冰、地表和大气顶层变量。SamudrACE具有高度稳定性，气候偏差与使用预设边界强迫的组件模型相当，能够真实再现厄尔尼诺等耦合气候现象，而这些在非耦合模式下无法实现。
原文摘要 · Abstract (English)
Traditional numerical global climate models simulate the full Earth system by exchanging boundary conditions between separate simulators of the atmosphere, ocean, sea ice, land surface, and other geophysical processes. This paradigm allows for distributed development of individual components within a common framework, unified by a coupler that handles translation between realms via spatial or temporal alignment and flux exchange. Following a similar approach adapted for machine learning-based emulators, we present SamudrACE: a coupled global climate model emulator which produces centuries-long simulations at 1-degree horizontal, 6-hourly atmospheric, and 5-daily oceanic resolution, with 145 2D fields spanning 8 atmospheric and 19 oceanic vertical levels, plus sea ice, surface, and top-of-atmosphere variables. SamudrACE is highly stable and has low climate biases comparable to those of its components with prescribed boundary forcing, with realistic variability in coupled climate phenomena such as ENSO that is not possible to simulate in uncoupled mode.
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