Southern Ocean latent heat flux variability driven by oceanic meso- and submesoscale motions

Abstract

Latent heat flux is a primary pathway for ocean-atmosphere exchange of heat and moisture, yet the influence of sea surface temperature variability at fine scales ($\leq$ 100 km) on latent heat flux variability, particularly over the Southern Ocean, remains poorly understood. Here we quantify the scale-dependent drivers of latent heat flux (LHF) variability using a year-long, global, fully coupled ocean-atmosphere simulation with kilometer-scale resolution. Annual-mean LHF in eddy-rich regions reaches $\approx$ 215 W m$^{-2}$, approximately three times larger than in eddy-poor regions. Spectral analyses show that ocean mesoscale [$\mathcal{O}$(100 km)] and submesoscale [$\mathcal{O}$(1-10 km)] variability accounts for up to $\approx$ 80% of the total LHF variance in eddy-rich sectors, but as little as 10% in eddy-poor regions, and increases proportionally with eddy kinetic energy and sea surface temperature (SST) variance. We also find that strong submesoscale SST fronts ($\approx$ 5 $^\circ$C over 10 km) force a localized secondary circulation that extends well above the marine boundary layer into the mid-troposphere. Comparison with ERA5 shows that fine ocean scales, responsible for about 17% of the ocean-driven LHF variance in the simulation, are largely unresolved in the reanalysis, leading to a muted atmospheric response lacking any secondary circulation. Despite a strong heterogeneity in LHF variability, the atmospheric dynamics are mostly uniform across the domain, suggesting a non local atmospheric response to ocean forcing. These results highlight the potential for ocean meso- and submesoscales, commonly under-resolved in climate models and reanalysis, to influence Southern Ocean air-sea coupling and atmosphere both locally and remotely.

Figures (22)

• Figure 1: Spectral space partition. Schematic illustrating the spectral space partition that associates each regime with physical scales. The diagonal solid line separates oceanic from atmospheric scales. The dash-dotted vertical line denotes the finest scale ($\sim$80 km) captured by ERA5.
• Figure 2: Southern Ocean spatial heterogeneity and temporal variability in COAS. Annual (a) latent heat flux average, (b) latent heat flux standard deviation, and (c) SST gradient standard deviation, all computed over 11 months in COAS. Boxes are AGUL and CHIL regions with regionally averaged values. Gray shaded area is where sea ice coverage exceeds 50%.
• Figure 3: Regional snapshots of surface fields in COAS. (a,b) Latent heat flux (shading) and SST (white contours, spaced 2 $^\circ$C). (c,d) Downwind SST gradient (shading). Arrows represent 10-m horizontal wind. Left column is the AGUL region, right is CHIL. Snapshot from COAS on 1 April 2020, 2300.
• Figure 4: Probability density distributions in COAS. Distributions in AGUL and CHIL regions of (a) latent heat flux, (b) surface wind stress, (c) 10-m wind speed and (d) ocean surface kinetic energy. Distributions are computed over 11 months in COAS. Dashed vertical lines represent the median of each distribution. The legend shows median, skewness and excess kurtosis.
• Figure 5: Probability density distributions of gradient variables in COAS. Distributions in AGUL and CHIL regions of (a) the amplitude of the latent heat flux gradient, (b) the divergence of the surface wind stress, (c) the downwind SST gradient. Distributions are computed over 11 months in COAS. Dashed vertical lines represent the median of each distribution. The legend shows the median, skewness and excess kurtosis.