Prediction of slowdown of the Atlantic Meridional Overturning Circulation in coupled model simulations

被引:0
|
作者
Yamazaki, Kuniko [1 ]
Jackson, Laura C. [1 ]
Sexton, David M. H. [1 ]
机构
[1] Met Off Hadley Ctr, FitzRoy Rd, Exeter EX1 3PB, England
关键词
Atlantic Meridional Overturning Circulation (AMOC); AMOC slowdown; Perturbed parameter ensemble (PPE); Global climate model (GCM) development; Statistical methods; Amazon River; CLIMATE; VARIABILITY; JULES; UNCERTAINTY; MECHANISMS;
D O I
10.1007/s00382-024-07159-5
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
In coupled perturbed parameter ensemble (PPE) experiments or for development of a single coupled global climate model (GCM) in general, models can exhibit a slowdown in the Atlantic Meridional Overturning Circulation (AMOC) that can result in unrealistically reduced transport of heat and other tracers. Here we propose a method that researchers running PPE experiments can apply to their own PPE to diagnose what controls the AMOC strength in their model and make predictions thereof. As an example, using data from a 25-member coupled PPE experiment performed with HadGEM3-GC3.05, we found four predictors based on surface heat and freshwater fluxes in four critical regions from the initial decade of the spinup phase that could accurately predict the AMOC transport in the later stage of the experiment. The method, to our knowledge, is novel in that it separates the effects of the drivers of AMOC change from the effects of the changed AMOC. The identified drivers are shown to be physically credible in that the PPE members exhibiting AMOC weakening possess some combination of the following characteristics: warmer ocean in the North Atlantic Subpolar Gyre, fresher Arctic and Tropical North Atlantic Oceans and larger runoff from the Amazon and Orinoco Rivers. These characteristics were further traced to regional responses in atmosphere-only experiments. This study suggests promising potential for early stopping rules for parameter perturbations that could end up with an unrealistically weak AMOC, saving valuable computational resources. Some of the four drivers are likely to be relevant to other climate models so this study is of interest to model developers who do not have a PPE.
引用
收藏
页码:5197 / 5217
页数:21
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