Submitted as: development and technical paper
18 Jun 2021
Submitted as: development and technical paper | 18 Jun 2021
Status: a revised version of this preprint is currently under review for the journal GMD.

A Moist Quasi-Geostrophic Coupled Model: MQ-GCM2.0

Sergey Kravtsov1,2,3, Ilijana Mastilovic1, Andrew McC. Hogg4, William Dewar5,6, and Jeffrey Blundell7 Sergey Kravtsov et al.
  • 1Department of Mathematical Sciences, University of Wisconsin-Milwaukee, P. O. Box 413, Milwaukee, WI 53201, USA
  • 2Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, 117218, Russia
  • 3Institute of Applied Physics, Russian Academy of Sciences, Nizhniy Novgorod, 603155, Russia
  • 4Research School of Earth Sciences, and ARC Centre of Excellence in Climate Extremes, Australian National University, Canberra, Australia
  • 5Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL 32304, USA
  • 6Laboratoire de Glaciologie et Geophysique de l'Environnement, CNRS, Grenoble, France
  • 7Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, Southampton SO14 3ZH, United Kingdom

Abstract. This paper contains a description of recent changes to the formulation and numerical implementation of the Quasi-Geostrophic Coupled Model (Q-GCM), which constitute a major update of the previous version of the model (Hogg et al., 2014). The Q-GCM model has been designed to provide an efficient numerical tool to study the dynamics of multi-scale mid-latitude air–sea interactions and their climatic impacts. The present additions/alterations were motivated by an inquiry into the dynamics of mesoscale ocean–atmosphere coupling and, in particular, by an apparent lack of Q-GCM atmosphere’s sensitivity to mesoscale sea-surface temperature (SST) anomalies, even at high (mesoscale) atmospheric resolutions, contrary to ample theoretical and observational evidence otherwise. Major modifications aimed at alleviating this problem include an improved radiative-convective scheme resulting in a more realistic model mean state and associated model parameters, a new formulation of entrainment in the atmosphere, which prompts more efficient communication between the atmospheric mixed layer and free troposphere, as well as an addition of temperature-dependent wind component in the atmospheric mixed layer and the resulting mesoscale feedbacks. The most drastic change is, however, the inclusion of moist dynamics in the model, which may be key to midlatitude ocean–atmosphere coupling. Accordingly, this version of the model is to be referred to as the MQ-GCM model. Overall, the MQ-GCM model is shown to exhibit a rich spectrum of behaviours reminiscent of many of the observed properties of the Earth’s climate system. It remains to be seen whether the added processes are able to affect in fundamental ways the simulated dynamics of the mid-latitude ocean–atmosphere system’s coupled decadal variability.

Sergey Kravtsov 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 gmd-2021-160', Anonymous Referee #1, 18 Jul 2021
    • AC1: 'Reply on RC1', Sergey Kravtsov, 12 Jun 2022
  • CEC1: 'Comment on gmd-2021-160', Juan Antonio Añel, 14 Aug 2021
    • CC1: 'Reply on CEC1', Ilijana Mastilovic, 26 Aug 2021
  • RC2: 'Comment on gmd-2021-160', Anonymous Referee #2, 06 Jun 2022
    • AC2: 'Reply on RC2', Sergey Kravtsov, 12 Jun 2022

Sergey Kravtsov et al.

Sergey Kravtsov et al.


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Short summary
Climate is a complex system whose behavior is shaped by multitudes of processes operating on widely different spatial and times scales. In hierarchical modelling, one goes back and forth between highly idealized process models and state-of-the-art models coupling the entire range of climate subsystems to identify specific phenomena and understand their dynamics. The present contribution highlights an intermediate climate model focussing on midlatitude ocean–atmosphere interactions.