skip to main content


Search for: All records

Creators/Authors contains: "Berta, Maristella"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. The diurnal cycling of submesoscale circulations in vorticity, divergence, and strain is investigated using drifter data collected as part of the Lagrangian Submesoscale Experiment (LASER) experiment, which took place in the northern Gulf of Mexico during winter 2016, and ROMS simulations at different resolutions and degree of realism. The first observational evidence of a submesoscale diurnal cycle is presented. The cycling is detected in the LASER data during periods of weak winds, whereas the signal is obscured during strong wind events. Results from ROMS in the most realistic setup and in sensitivity runs with idealized wind patterns demonstrate that wind bursts disrupt the submesoscale diurnal cycle, independently of the time of day at which they happen. The observed and simulated submesoscale diurnal cycle supports the existence of a shift of approximately 1–3 h between the occurrence of divergence and vorticity maxima, broadly in agreement with theoretical predictions. The amplitude of the modeled signal, on the other hand, always underestimates the observed one, suggesting that even a horizontal resolution of 500 m is insufficient to capture the strength of the observed variability in submesoscale circulations. The paper also presents an evaluation of how well the diurnal cycle can be detected as function of the number of Lagrangian particles. If more than 2000 particle triplets are considered, the diurnal cycle is well captured, but for a number of triplets comparable to that of the LASER analysis, the reconstructed diurnal cycling displays high levels of noise both in the model and in the observations.

     
    more » « less