Year: 2026
Type: article
Abstract: The investigation of oceanic submesoscale phenomena is a vital aspect of comprehending the multiscale fractal structure of the ocean. This study presents a systematic analysis of submesoscale sea surface temperature (SST) variability in the Kuroshio‐Oyashio Extension region, combining high‐resolution along‐track satellite observations (Visible Infrared Imaging Radiometer Suite L2 product) with Massachusetts Institute of Technology General Circulation Model simulations. The spatial variance method effectively captures power‐law scaling and energy density across specific scale ranges (5–300 km), even when applied to fragmented satellite SST data. The analysis reveals a spectral slope in SST spatial variance, consistent with surface quasi‐geostrophic turbulence theory. Furthermore, submesoscale SST variability (5–50 km) exhibits a marked seasonal cycle, peaking in April and reaching a minimum in August. The strongest variance occurs near 42°N, collocated with a pronounced background SST frontal zone in the Oyashio Extension region. To unravel the underlying dynamics, we develop a dynamic diagnostic framework that quantifies the competing generation and dissipation processes controlling submesoscale SST variance. The combined forcing of large‐scale/mesoscale SST fronts and submesoscale turbulent heat transport drives wintertime intensification and an April maximum in submesoscale SST variance, while nonlinear dynamics and horizontal mixing dissipate variance, resulting in an August minimum. The seasonal variation of the frontogenesis function leads the submesoscale SST variance by 1 month, which proves that frontal instability plays an important role in generating submesoscale horizontal SST gradients.
DOI: 10.1029/2025jc023305
Institution: Hohai University
Language: English
Subfield: Oceanography
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: bronze
Awards: G1433578081, G3457123685, G3524624084
OpenAlex ID: W7127083890