AbstractAutomated methods are important for the identification of mesoscale eddies in the large volume of oceanic data provided by altimetric measurements and numerical simulations. This paper presents an optimized algorithm for detecting and tracking eddies from two-dimensional velocity fields. This eddy identification uses a hybrid methodology based on physical parameters and geometrical properties of the velocity field, and it can be applied to various fields having different spatial resolutions without a specific fine-tuning of the parameters. The efficiency and the robustness of the angular momentum eddy detection and tracking algorithm (AMEDA) was tested with three different types of input data: the 1/8° Archiving, Validation, and Interpretation of Satellite Oceanographic Data (AVISO) geostrophic velocity fields available for the Mediterranean Sea; the output of the idealized Regional Ocean Modeling System numerical model; and the surface velocity field obtained from particle imagery on a rotating tank experiment. All these datasets describe the dynamical evolution of mesoscale eddies generated by the instability of a coastal current. The main advantages of AMEDA are as follows: the algorithm is robust to the grid resolution, it uses a minimal number of tunable parameters, the dynamical features of the detected eddies are quantified, and the tracking procedure identifies the merging and splitting events. The proposed method provides a complete dynamical evolution of the detected eddies during their lifetime. This allows for identifying precisely the formation areas of long-lived eddies, the region where eddy splitting or merging occurs frequently, and the interaction between eddies and oceanic currents.
Journal of Atmospheric and Oceanic Technology – American Meteorological Society
Published: Apr 11, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera