Tropical Pacific near‐surface currents estimated from altimeter, wind, and drifter data

Lagerloef, Gary; Mitchum, Gary T.; Lukas, Roger; Niiler, Pearn P.

doi:10.1029/1999jc900197

Cited by 295 publications

(281 citation statements)

References 33 publications

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“…Over the years, the OSCAR project has evolved from a tropical study [Lagerloef et al, 1999] to a global near-real-time product. The physics in OSCAR are based on three factors: geostrophy, Ekman dynamics, and thermal wind.…”

Section: How Are These Motions Measured?mentioning

confidence: 99%

Ocean surface currents from satellite data

Dohan

2017

JGR Oceans

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The atmosphere drives entire ocean motions, and yet the exchange of momentum between the atmosphere and ocean occurs in the thin layer where they meet, involving the smallest scales of turbulence. The Ocean Surface Current Analyses Real‐time (OSCAR) project attempts to better understand this exchange using satellite observations with simplified physics to calculate global ocean currents. The goal is to continually improve the physics in OSCAR and more accurately model the currents. The theoretical study will help coupled ocean‐atmosphere modeling efforts whereas the societal benefits of measuring ocean currents are broad, e.g., fish larval dispersion, heat transport, commercial shipping, and search and rescue.

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Section: How Are These Motions Measured?mentioning

confidence: 99%

Ocean surface currents from satellite data

Dohan

2017

JGR Oceans

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“…Turiel et al: The MF structure of SST trace streamlines 449 absolute topography maps using the geostrophic assumption. In the equatorial band the quasi geostrophic approximation is applied (Lagerloef et al, 1999).…”

Section: Description Of the Datamentioning

confidence: 99%

The multifractal structure of satellite sea surface temperature maps can be used to obtain global maps of streamlines

et al. 2009

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Abstract. Nowadays Earth observation satellites provide information about many relevant variables of the ocean-climate system, such as temperature, moisture, aerosols, etc. However, to retrieve the velocity field, which is the most relevant dynamical variable, is still a technological challenge, specially in the case of oceans. New processing techniques, emerged from the theory of turbulent flows, have come to assist us in this task. In this paper, we show that multifractal techniques applied to new Sea Surface Temperature satellite products opens the way to build maps of ocean currents with unprecedented accuracy. With the application of singularity analysis, we show that global ocean circulation patterns can be retrieved in a daily basis. We compare these results with high-quality altimetry-derived geostrophic velocities, finding a quite good correspondence of the observed patterns both qualitatively and quantitatively; and this is done for the first time on a global basis, even for less active areas. The implications of this findings from the perspective both of theory and of operational applications are discussed.

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“…The operators K ηT and K ηS in Equation (13) (Lagerloef et al, 1999). A detailed description of the multivariate balance operator can be found in Weaver et al (2005).…”

Section: Data Assimilation Methodsmentioning

confidence: 99%

Ensemble estimation of background‐error variances in a three‐dimensional variational data assimilation system for the global ocean

Daget

Weaver

Balmaseda

2009

Quart J Royal Meteoro Soc

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This paper studies the sensitivity of global ocean analyses to two flow-dependent formulations of the background-error standard deviations (σ b ) for temperature and salinity in a three-dimensional variational data assimilation (3D-Var) system. The first formulation is based on an empirical parameterization of σ b in terms of the vertical gradients of the background temperature and salinity fields, while the second formulation involves a more sophisticated approach that derives σ b from the spread of an ensemble of background states. The ensembles are created by explicitly perturbing both the surface fluxes (wind stress, fresh water and heat) used to force the model and the observations (temperature and salinity profiles) used in the assimilation process. The two formulations are compared in two cycled 3D-Var experiments for the period 1993-2000. In both experiments, the observation-error standard deviations (σ o ) are geographically dependent and estimated from a model-data comparison prior to assimilation. An additional 3D-Var experiment that employs the parametrized σ b but a simpler σ o formulation, and a control experiment involving no data assimilation, were also conducted and used for comparison.All 3D-Var experiments produce a significant reduction in the mean and standard deviation of the temperature and salinity innovations compared to those of the control experiment. The largest differences between the two σ b formulations occur in the upper 150 m, where the parametrized σ b are notably larger than the ensemble σ b . In this region, the innovation statistics are slightly better for the parametrized σ b . Statistical consistency checks indicate that both schemes underestimate σ b , the underestimation being stronger with the ensemble formulation. The error growth between cycles, however, is much reduced with the ensemble σ b , suggesting that the analyses produced with the ensemble σ b are in better balance than those produced with the parametrized σ b . This claim is supported by independent data comparisons involving model fields not directly constrained by the assimilated temperature and salinity profiles. In particular, sea-surface height (SSH) anomalies in the northwest Atlantic and zonal velocities in the equatorial Pacific are clearly better with the ensemble σ b than with the parametrized σ b . Results also show that while some aspects of those variables are improved with data assimilation (SSH anomalies and currents in the central and eastern Pacific), other aspects are degraded (SSH anomalies in the northwest Atlantic, currents in the western Pacific). Areas for improving the ensemble method and for making better use of the ensemble information are discussed.

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Tropical Pacific near‐surface currents estimated from altimeter, wind, and drifter data

Cited by 295 publications

References 33 publications

Ocean surface currents from satellite data

Ocean surface currents from satellite data

The multifractal structure of satellite sea surface temperature maps can be used to obtain global maps of streamlines

Ensemble estimation of background‐error variances in a three‐dimensional variational data assimilation system for the global ocean

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