Sea surface height variations in the Atlantic Ocean: A comparison of TOPEX altimeter data with results from an ocean data assimilation system

Behringer, David

doi:10.1029/94jc01637

Cited by 15 publications

(6 citation statements)

References 10 publications

(5 reference statements)

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“…This article will focus on the comparison of the T/P data with the model simulations of sea surface height (from run II unless specified otherwise) covering the same period (October 1992-October 1994, with the same analysis techniques applied to both the data and model simulations. Such comparisons of T/P data have been made to models of lower resolutions (e.g., Chao and Fu 1995;Behringer 1994;Stammer et al 1996). The present study presents results that are complementary to the previous ones as well as providing a new perspective from a global model of the highest resolution performed to date.…”

Section: B Modeling the Global Ocean Circulationsupporting

confidence: 63%

Global Ocean Circulation from Satellite Altimetry and High-Resolution Computer Simulation

Fu¹,

Smith²

1996

Bull. Amer. Meteor. Soc.

133

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The sea surface elevation relative to the geoid, a dynamic boundary condition for the three-dimensional oceanic pressure field, is being determined over the global ocean every 10 days by a precision radar altimeter aboard the TOPEX/POSEIDON satellite. This is the most accurate altimeter data stream to date for the study of the ocean general circulation and its variability. The authors compare results from 2 years (October 1992-October 1994) of the satellite observations to computer simulations for the same period using a state-of-the-art ocean general circulation model driven by realistic winds from an atmospheric weather-prediction model. The average horizontal resolution of the model is 1/5° (varying from 30 km at the equator to 6 km at the polar latitudes), the highest for a global simulation performed to date. Comparisons of the mean circulation, the mesoscale variability, the amplitude, and phase of the annual cycle, as well as intraseasonal and interannual changes show that the simulations and observations agree fairly well over a broad range of temporal and spatial scales. However, the sea level variance produced by the model is generally less than the observation by a factor of 2, primarily in the eddy-rich regions. Comparison of wavenumber spectra indicates that even higher spatial resolution is needed to fully resolve the mesoscale eddies. The absolute dynamic topography determined from either the data or the model has an error on the order of 10 cm at wavelengths larger than 2000 km. Geoid errors are the limiting factor for the utility of the altimeter data at smaller scales. Heat flux forcing is a key factor in determining the simulated annual cycle of the ocean. Improved agreement with the observation is achieved when the model is driven by heat flux forcing instead of being nudged to sea surface temperature climatology. The temporal evolution of the intraseasonal fluctuations at mid-and high latitudes as well as the interannual variability of the tropical oceans, both are primarily wind driven, is simulated fairly well by the model.

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Section: B Modeling the Global Ocean Circulationsupporting

confidence: 63%

Global Ocean Circulation from Satellite Altimetry and High-Resolution Computer Simulation

Fu¹,

Smith²

1996

Bull. Amer. Meteor. Soc.

133

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“…In particular we want to determine the relative importance of each mode of variability and their probable causes. Although the annual signal in the Atlantic Ocean derived from the satellite altimetry data has already been studied before [e.g., Behringer , 1994; Ferry et al , 2000], these studies mainly dealt with the large‐scale character of the sea level variability. In this work we want to zoom in on our particular region.…”

Section: Introductionmentioning

confidence: 99%

Annual and interannual variability of sea level in the northern North Atlantic Ocean

Volkov

Aken

2003

J. Geophys. Res.

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(300 cycles) were processed. The annual and interannual signals were examined, and their contribution to the total variance is estimated. Both signals appeared to be responsible for a greatest portion of variability outside the North Atlantic Current (NAC) and its branches. The annual signal manifested consistency with seasonal changes in the heat storage, possibly enhanced by seasonal variations of advection. A considerable interannual change was monitored in the vast areas of the northern North Atlantic Ocean as well as along the NAC. The interannual change in SLA was found to be consistent with the North Atlantic Oscillation (NAO) index when it changed from its positive to its negative phase in 1996. The significant negative correlation coefficient between the annually averaged SLA and NAO index time series was estimated in all dynamically calm areas outside the NAC. Hydrographic data obtained during several cruises for the time interval studied were also investigated and coupled with the variations of SLA and NAO index. The analysis showed a good agreement between the altimeter-derived SLA and dynamic height anomalies suggesting that the sea level changes in the northern North Atlantic have a baroclinic nature.

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“…Equatorial Current (NEC) by more than 10% and underestimate that of the South Equatorial Current (SEC) by more than 25%. Comparisons of geopotential height variations from the analyses to satellite altimeter measurements have been made for the tropical Pacific by Maul et al [1997] and for the entire Atlantic Ocean by Behringer [1994]. The former found rms differences of 4-6 cm in the midtropical Pacific with data from Geosat, and the latter found rms differences of only 2-4 cm in the North Atlantic using the more accurate TOPEX data.…”

Section: Introductionmentioning

confidence: 99%

“…[1987] argued that accurate temperature fields are the most important consideration in the initialization of OGCMs for climate prediction. The primary objective of the NCEP analysis system is to provide the best possible predictions of sea surface temperature (SST) fields to help make predictions of the E1 Nifio-Southern Oscillation (ENSO) variations in the tropical Pacific, but the analysis system has been extended to the Atlantic Ocean [Behringer, 1994] and applied to other climate issues [Smith and Chelliah, 1995]. The NCEP analyses are produced on both a "nowcast" timescale [Hayes et al, 1989] and some "reanalyses" that provide consistent decadelong descriptions of the physical state of the ocean.…”

Section: Introductionmentioning

confidence: 99%

Evaluation and diagnosis of surface currents in the National Centers for Environmental Prediction's ocean analyses

Acero-Schertzer¹,

Hansen²,

Swenson³

1997

J. Geophys. Res.

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Abstract. Ensemble average currents from the 15 m depth level of the National Centers for Environmental Prediction's (NCEP) analyses of the tropical Pacific Ocean are evaluated against surface mixed layer current observations obtained from an extensive set of satellite-tracked drifting buoys. These averages display many climatological characteristics of the region but are not intended to serve as a climatology because the data from the analyses are trimmed to match the time-space distribution of the observations. Substantial discrepancies between the analyses and the observations are revealed. First, the near-equatorial meridional currents and divergence have approximately twice the magnitude in the analyses as in the observations. This discrepancy is largely independent of whether temperature profile data are assimilated or not and is attributed to the parameterization of vertical viscosity. Second, the zonal flow in both the North Equatorial Countercurrent (NECC) and the South Equatorial Current (SEC) is much stronger in the analyses than in the observations, especially in the western Pacific. This discrepancy is associated with assimilation of temperature profile data. It arises because salinity is an active variable in the underlying analysis model but is not controlled by boundary fluxes or other observations. Under the uncontrolled influence of advection and strong horizontal diffusion the salinity distribution becomes nearly homogeneous. Consequently, the analyses do not account for observed temperature-salinity correlations when density is computed following assimilation of temperature profile data. This leads to erroneous pressure gradients that drive excessively strong geostrophic currents and force large accelerations near the western boundary. Our results indicate that it is important to consider the consequences on the density structure of neglecting salinity during the assimilation of temperature data. We recommend that surface salinity observations from drifting buoys and volunteer observing ships be initiated to improve the ocean analyses.

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Sea surface height variations in the Atlantic Ocean: A comparison of TOPEX altimeter data with results from an ocean data assimilation system

Cited by 15 publications

References 10 publications

Global Ocean Circulation from Satellite Altimetry and High-Resolution Computer Simulation

Global Ocean Circulation from Satellite Altimetry and High-Resolution Computer Simulation

Annual and interannual variability of sea level in the northern North Atlantic Ocean

Evaluation and diagnosis of surface currents in the National Centers for Environmental Prediction's ocean analyses

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