Date of Award

August 2023

Degree Type


Degree Name

Doctor of Philosophy


Atmospheric Science

First Advisor

Sergey Kravtsov

Committee Members

Clark Evans, Jonathan Kahl, Paul Roebber, William Dewar


Air-sea interaction, Climate dynamics, Climate modeling, Coupled models


Most of our knowledge about the causes of 20th-century climate change comes from simulation using numerical models. However, the observed climate variability and the one simulated by the state-of-the-art climate models exhibit substantial discrepancies at the decadal-to-multidecadal time scale and thus it hinders our fundamental understanding of the observed climate change. Evidence is mounting that vigorous intrinsic variability associated with mesoscale oceanic features contributes significantly to large-scale low-frequency climate variability, with fundamental implications for decadal climate low-frequency climate prediction. As of yet, extensive simulation of these decadal effects using high-resolution state-of-the-art coupled climate models has been computationally prohibitive, as it may require mesoscale-resolving atmospheric components. Here we study the effects of mesoscale air-sea coupling on large-scale low-frequency (interannual-to-multidecadal) climate variability using idealized high-resolution coupled climate models.We hypothesized that resolving mesoscale oceanic fronts and eddies in both ocean and atmosphere will lead to the emergence of qualitatively new phenomena rooted, dynamically, in multi-scale ocean-atmosphere interactions. In particular, we propose that the climate system may possess internal climate modes due to multi-scale ocean–atmosphere interactions involving (i) decadal variations in the meridional location and magnitude of the narrow (mesoscale, 100-km wide) sea-surface temperature (SST) fronts associated with the eastward-jet extension of oceanic western boundary currents (such as Gulf Stream); (ii) mesoscale response of the atmospheric planetary boundary layer (APBL) winds and, most importantly, ensuing large-scale (basin-scale-to-global-scale) response of the free atmosphere to these mesoscale SST anomalies; and (iii) subsequent modifications in the large-scale oceanic wind-driven gyres and further changes in the location and/or magnitude of the SST fronts. The unambiguous demonstration of a concerted action of these elements to result in the coherent decadal and longer internal climate variability has yet remained elusive, partly because modeling these dynamics requires at least semi-hemispheric-extent coupled ocean–atmosphere climate models with high horizontal resolution in both fluids; long, multidecadal simulations using these models are challenging to achieve due to their enormous computational expense. The goal of the present work was to test our hypothesis above in a more idealized, numerically efficient model, yet the one containing the requisite dynamics required in the elements (i), (ii), (iii) of the proposed multi-scale coupled decadal climate modes. The model versions we developed and used here are based on the Quasi-Geostrophic Coupled Model (Q-GCM) of Hogg et al. (2003, 2006, 2009, 2014), which was revamped and modified to include a parameterized effect of SST anomalies on APBL wind, a new radiation/heat exchange parameterization meant to invigorate the coupling between the surface and free atmosphere, and, finally, the moisture dynamics and the associated latent heat sources that are likely to be essential in the large-scale atmospheric response to mesoscale SST anomalies; the moist model version was dubbed the MQ-GCM model. Despite these modifications, we have to report that we did not thus far identify, in this model, the parameter regime conducive to the multi-scale coupled ocean–atmosphere modes we were looking for. The two main stumbling blocks we encountered were the inability of the ocean model to produce persistent self-sustained meridional shifts of the midlatitude SST front implied in (i), and the weak forced response of the model’s free atmosphere to variable SST fronts, even in the MQ-GCM model, which affects leg (ii) of the proposed feedback sequence. We used the insights obtained during the project to propose a set of suggestions for future work needed to rectify these issues.