Data assimilation considerations for improved ocean predictability during the Gulf of Mexico Grand Lagrangian Deployment (GLAD)

Jacobs, Gregg A.; Bartels, Brent; Bogucki, Darek; Beron-Vera, F. J.; Chen, Shuyi S.; Coelho, Emanuel; Curcic, Milan; Griffa, Annalisa; Gough, Matt K.; Haus, Brian K.; Haza, Angelique C.; Helber, Robert W.; Hogan, Patrick; Huntley, Helga S.; Iskandarani, Mohamed; Judt, Falko; Kirwan, A. D.; Laxague, Nathan J. M.; Valle‐Levinson, Arnoldo; Lipphardt, B. L.; Mariano, Arthur J.; Ngodock, Hans; Novelli, Guillaume; Olascoaga, M. J.; Özgökmen, Tamay M.; Poje, Andrew C.; Reniers, Ad; Rowley, Clark; Ryan, Edward H.; Smith, Scott; Spence, Peter L.; Thoppil, Prasad G.; Wei, Meng

doi:10.1016/j.ocemod.2014.09.003

Cited by 58 publications

(57 citation statements)

References 57 publications

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“…A comparison between our experiments and a higherresolution (3 km) reanalysis (named RT3km_v2 in Jacobs et al 2014b) shows that the variance of the difference of surface velocities is approximately 0.03 m s 21 and is subsumed into the larger observational error. Observation errors include both estimated instrument error and representative error.…”

Section: Model and Data Assimilation Systemmentioning

confidence: 75%

“…When assimilated, the disparity in space and time scales of the altimeter measurements lead to biases in the mesoscale forecasts that are very difficult to quantify (Jacobs et al 2014a). Temperature, salinity, and sea surface height (SSH, measured along-track by satellite altimeters) observations are typically assimilated in operational ocean models.…”

Section: Introductionmentioning

confidence: 99%

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

Muscarella

Carrier

Ngodock

et al. 2015

Monthly Weather Review

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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 (4DVAR) 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 day 21 on average, when compared with forecasts that assimilate only temperature and salinity observations. Trajectory angular differences are also reduced.FIG. 9. (a) Mean separation distance (km) after 24 h between the GLAD and simulated drifters for each assimilation cycle. The average is taken only over the drifters removed in the data-denial experiment (cf. Fig. 4). (b) The minimum distance of each unassimilated drifter to the nearest assimilated drifter, averaged over all the unassimilated drifters at each hourly time step.

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Section: Model and Data Assimilation Systemmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

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

Muscarella

Carrier

Ngodock

et al. 2015

Monthly Weather Review

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“…The multiscale surface flow analyzed here is produced by a data-assimilative Navy Coastal Ocean Model (NCOM) of the Gulf of Mexico at 1-km horizontal resolution (23). This flow has been shown to reproduce relative dispersion statistics (24) observed during the Grand Lagrangian Experiment (GLAD) in the northern Gulf of Mexico (25), a period during which submesoscale motions were argued (26) to be active.…”

Section: Significancementioning

confidence: 99%

Coherent Lagrangian swirls among submesoscale motions

Beron-Vera

Hadjighasem

Xia

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

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The emergence of coherent Lagrangian swirls (CLSs) among submesoscale motions in the ocean is illustrated. This is done by applying recent nonlinear dynamics tools for Lagrangian coherence detection on a surface flow realization produced by a dataassimilative submesoscale-permitting ocean general circulation model simulation of the Gulf of Mexico. Both mesoscale and submesoscale CLSs are extracted. These extractions prove the relevance of coherent Lagrangian eddies detected in satellitealtimetry-based geostrophic flow data for the arguably more realistic ageostrophic multiscale flow.Lagrangian coherence | mesoscale eddies | submesoscale eddies | satellite altimetry | high-resolution ocean models A dvances in nonlinear dynamical systems theory over the past few years (1-5) have enabled the discovery of unexpectedly resilient mesoscale material eddies in ocean velocity fields derived from satellite-sensed sea-surface height (SSH) fields (6). Ranging between 50 km and 250 km in diameter, these supercoherent Lagrangian eddies show no breakup or disintegration over a period of several months, in some cases up to 2 y (3, 7-10). Detected in a fashion fully independent from the observer, such Lagrangian eddies are bounded by uniformly stretching fluid (i.e., material) loops that stationarize the material-line-averaged tangential strain functional (3, 4). As a result, these material boundaries or elliptic Lagrangian coherent structures (11) will nearly exactly reassume their initial arc length at the end of the coherence assessment interval. Coupled with area preservation in the incompressible case, the preservation of boundary length renders these special Lagrangian eddies coherent to a previously undocumented and unexpected degree.The presence of one such supercoherent Lagrangian eddy in the Gulf of Mexico has recently been confirmed by independent measurements of satellite-derived chlorophyll and satellitetracked drifter paths (12). On the other hand, while satellitebased measurements are widely used for monitoring mesoscale variability in the ocean (13), they are incapable of resolving submesoscales, ranging from 100 m to a few tens of kilometers (14). There is, therefore, reason to believe (15, 16) that unresolved submesoscale motions, if sufficiently energetic, will erode the boundaries of supercoherent Lagrangian eddies inferred from satellite data. For this reason, the ubiquitous presence of submesoscale turbulence in the ocean (17, 18) has casted some doubt on the practical relevance of supercoherent mesoscale eddies inferred from satellite altimetry.The goal of this paper is to demonstrate that, even in the presence of active submesoscale motions, mesoscale swirling structures will exist, even though their boundaries will show increased filamentation relative to the supercoherent boundaries inferred from satellite altimetry. Such material interfaces will constrain mixing in the presence of multiscale ocean motions, ranging from largely geostrophic (balanced, equilibrated) mesoscale motions to likely ageostrophi...

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“…Other drifter deployments included an initial larger‐scale survey and two multiscale, nodal deployments; the T deployment that targeted cross‐shelf transport near the northern tip of the DeSoto Canyon with drifter nodes deployed along a triangular‐shaped pattern, and the L deployment sampling a strong cyclone in deeper water (Figure , middle). The choice of sampling pattern was guided by numerical simulations using data‐assimilative models [ Jacobs et al ., ; Özgökmen et al ., ]. Drifters were launched from the R/V Walton Smith and two small boats allowing the deployment of 90 drifters in a span of 5 h. This deployment pattern of a large scale survey and different deployments of tight clusters allowed simultaneous sampling at multiple separation scales, initially on the order of 100 m to 10's of km, which then permitted sampling of different dynamical features.…”

Section: Datamentioning

confidence: 99%

Statistical properties of the surface velocity field in the northern Gulf of Mexico sampled by GLAD drifters

et al. 2016

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The Grand LAgrangian Deployment (GLAD) used multiscale sampling and GPS technology to observe time series of drifter positions with initial drifter separation of O(100 m) to O(10 km), and nominal 5 min sampling, during the summer and fall of 2012 in the northern Gulf of Mexico. Histograms of the velocity field and its statistical parameters are non‐Gaussian; most are multimodal. The dominant periods for the surface velocity field are 1–2 days due to inertial oscillations, tides, and the sea breeze; 5–6 days due to wind forcing and submesoscale eddies; 9–10 days and two weeks or longer periods due to wind forcing and mesoscale variability, including the period of eddy rotation. The temporal e‐folding scales of a fitted drifter velocity autocorrelation function are bimodal with time scales, 0.25–0.50 days and 0.9–1.4 days, and are the same order as the temporal e‐folding scales of observed winds from nearby moored National Data Buoy Center stations. The Lagrangian integral time scales increase from coastal values of 8 h to offshore values of approximately 2 days with peak values of 3–4 days. The velocity variance is large, O(1) m2/normals2, the surface velocity statistics are more anisotropic, and increased dispersion is observed at flow bifurcations. Horizontal diffusivity estimates are O(103) m2/s in coastal regions with weaker flow to O(105) m2/s in flow bifurcations, a strong jet, and during the passage of Hurricane Isaac. The Gulf of Mexico surface velocity statistics sampled by the GLAD drifters are a strong function of the feature sampled, topography, and wind forcing.

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Data assimilation considerations for improved ocean predictability during the Gulf of Mexico Grand Lagrangian Deployment (GLAD)

Cited by 58 publications

References 57 publications

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

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

Coherent Lagrangian swirls among submesoscale motions

Statistical properties of the surface velocity field in the northern Gulf of Mexico sampled by GLAD drifters

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