Preprints
https://doi.org/10.5194/npg-2021-5
https://doi.org/10.5194/npg-2021-5

  01 Feb 2021

01 Feb 2021

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

A Study of Capturing AMOC Regime Transition through Observation-Constrained Model Parameters

Zhao Liu1,4, Shaoqing Zhang1,2,3,4, Yang Shen5, Yuping Guan6,7, and Xiong Deng8 Zhao Liu et al.
  • 1Key Laboratory of Physical Oceanography, Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao, 266100, China
  • 2Pilot National Laboratory for Marine Science and Technology (QNLM), Qingdao, 266237, China
  • 3International Laboratory for High-Resolution Earth System Model and Prediction (iHESP), Qingdao, 266000, China
  • 4College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, 266100, China
  • 5College of Science, Liaoning University of Technology, Jinzhou, 121001, China
  • 6State Key Laboratory of Tropical Oceanography, Chinese Academy of Sciences, Guangzhou, 510301, China
  • 7College of Marine Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
  • 8College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China

Abstract. The multiple equilibria are an outstanding characteristic of the Atlantic meridional overturning circulation (AMOC) that has important impacts on the Earth climate system appearing as regime transitions. The AMOC can be simulated in different models but the behavior deviates from the real world due to the existence of model errors. Here, we first combine a general AMOC model with an ensemble Kalman filter to form an ensemble coupled model data assimilation and parameter estimation (CDAPE) system, and derive the general methodology to capture the observed AMOC regime transitions through utilization of observational information. Then we apply this methodology designed within a twin experiment framework with a simple conceptual model that simulates the transition phenomenon of AMOC multiple equilibria, as well as a more physics-based MOC box model to reconstruct the observed AMOC multiple equilibria. The results show that the coupled model parameter estimation with observations can significantly mitigate the model deviations, thus capturing regime transitions of the AMOC. This simple model study serves as a guideline when a coupled general circulation model is used to incorporate observations to reconstruct the AMOC historical states and make multi-decadal climate predictions.

Zhao Liu et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on npg-2021-5', Anonymous Referee #1, 07 Mar 2021
    • AC1: 'Reply on RC1', Zhao Liu, 09 May 2021
  • RC2: 'Comment on npg-2021-5', Anonymous Referee #2, 14 Mar 2021
    • AC2: 'Reply on RC2', Zhao Liu, 09 May 2021

Zhao Liu et al.

Zhao Liu et al.

Viewed

Total article views: 852 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
685 137 30 852 19 12
  • HTML: 685
  • PDF: 137
  • XML: 30
  • Total: 852
  • BibTeX: 19
  • EndNote: 12
Views and downloads (calculated since 01 Feb 2021)
Cumulative views and downloads (calculated since 01 Feb 2021)

Viewed (geographical distribution)

Total article views: 802 (including HTML, PDF, and XML) Thereof 802 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 23 Jul 2021
Download
Short summary
A general methodology is introduced to capture regime transitions of the Atlantic meridional overturning circulation (AMOC). The assimilation models with different parameters simulate different paths for AMOC to switch between equilibrium states. Constraining model parameters with observations can significantly mitigate the model deviations, thus capturing AMOC regime transitions. This simple model study serves as a guideline for improving coupled general circulation models.