Preprints
https://doi.org/10.5194/npg-2020-27
https://doi.org/10.5194/npg-2020-27

  01 Jul 2020

01 Jul 2020

Review status: a revised version of this preprint is currently under review for the journal NPG.

Optimal Precursors Identification for North Atlantic Oscillation using CESM and CNOP Method

Bin Mu1, Jing Li1, Shijin Yuan1, Xiaodan Luo1, and Guokun Dai2 Bin Mu et al.
  • 1Department of Software Engineering, Tongji University, Shanghai, China
  • 2Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai, China

Abstract. The North Atlantic Oscillation (NAO) is the most prominent atmospheric seesaw phenomenon in the North Hemisphere. It has a profound influence on the westerly wind strength and storm tracks in North Atlantic, which further affect the winter climate in Northern Hemisphere. Therefore, the identification for optimal precursor (OPR) of the NAO event is of research value and practical significance. In this paper, the conditional nonlinear optimal perturbation (CNOP) method, which has been widely used in research on the OPR of climatic event, is adopted to explore which kind of initial perturbation is most likely to trigger the NAO anomaly pattern in the Community Earth System Model (CESM). Since the adjoint model of CESM has yet to be developed, this kind of problem cannot be solved using traditional strategies based on gradient information provided by the adjoint model. We utilize an adjoint-free algorithm to solve CNOP in such a high dimensional numerical model, and OPRs of the NAO can be successfully identified. The results reveal that OPRs obtained by CNOP can cause the basic state to develop into typical dipole mode, and the nonlinear process plays an important role in the last stage of the prediction period. The algorithm adopted in this work can avoid falling into a local optimum and is accelerated with multiple parallel frameworks to enhance performance. The solution scheme can also be generalized to the OPR research of other climate events or other complex numerical models.

Bin Mu et al.

 
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Bin Mu et al.

Bin Mu et al.

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Short summary
The North Atlantic Oscillation (NAO) phenomenon has a significant impact on the global climate. In this paper, we perform the identification of optimal precursors for NAO to investigate the predictability problem of NAO events. We select proper simulation duration and find out the structure of OPRs for two types of NAO events. Besides, the method applied in this work can be generalized to numerical models that do not have an adjoint model, and its efficiency has been further enhanced.