Accession Number:

ADA623041

Title:

Do Assimilated Drifter Velocities Improve Lagrangian Predictability in an Operational Ocean Model?

Descriptive Note:

Journal article

Corporate Author:

NAVAL RESEARCH LAB STENNIS DETACHMENT STENNIS SPACE CENTER MS

Report Date:

2015-05-01

Pagination or Media Count:

13.0

Abstract:

The Lagrangian predictability of general circulation models is limited by the need for high-resolution data streams to constrain small-scale dynamical features. Here velocity observations from Lagrangian drifters deployed in the Gulf of Mexico during the summer 2012 Grand Lagrangian Deployment GLAD experiment are assimilated into the Naval Coastal Ocean Model NCOM 4D variational DVAR analysis system to examine their impact on Lagrangian predictability. NCOM-4DVAR is a weak-constraint assimilation system using the indirect representer method. Velocities derived from drifter trajectories, as well as satellite and in situ observations, are assimilated. Lagrangian forecast skill is assessed using separation distance and angular differences between simulated and observed trajectory positions. Results show that assimilating drifter velocities substantially improves the model forecast shape and position of a Loop Current ring. These gains in mesoscale Eulerian forecast skill also improve Lagrangian forecasts, reducing the growth rate of separation distances between observed and simulated drifters by approximately 7.3 km dayexp -1 on average, when compared with forecasts that assimilate only temperature and salinity observations. Trajectory angular differences are also reduced.

Subject Categories:

  • Meteorology
  • Physical and Dynamic Oceanography

Distribution Statement:

APPROVED FOR PUBLIC RELEASE