Geosat Altimeter Data Research Articles

Mapping the Southwest Indian Ridge with Geosat

Satellite altimetry continues to have an extraordinary impact on the Earth sciences. It is sure to be considered the most important new observing tool for marine geophysics and geology to emerge in recent times. Spacecraft that have used and are currently using radar altimeters to map sea‐surface topography, and thereby marine gravity, include Geos‐3, Seasat, Geosat, ERS‐1, and Topex/Poseidon. To date, however, only Geosat altimeter data have possessed both the accuracy and density of coverage necessary to clearly resolve tectonic details in the marine gravity field on a global basis.

Global marine gravity grid and poster developed

Over the last 6 months, a dramatic increase in satellite altimetry coverage of the oceans has led to great improvements in the resolution of the marine gravity field. The 35‐day repeat orbit of the ERS‐1 altimeter has doubled spatial coverage globally, and recently declassified Geosat altimeter data have provided extremely dense coverage south of 30'S. Early results from these new data (see Eos, March 24, 1992) were presented at the AGU 1992 Fall Meeting in San Francisco. To provide better access to these large and diverse data sets, a global gravity grid has been constructed using satellite altimeter profiles from ERS‐1, Geosat, and Seasat.

A Comparison of Gulf Stream Sea Surface Height Fields Derived from Geosat Altimeter Data and Those Derived from Sea Surface Temperature Data

Abstract Two types of satellite data, Geosat altimeter data and sea surface temperature data (SST), are compared and evaluated for their usefulness in assimilation into a numerical model of the Gulf Stream region. Synoptic sea surface height (SSH) fields are derived from the SST data in the following way: first three-dimensional temperature and salinity analysis fields are obtained through the Optimum Thermal Interpolation System (OTIS), and then SSH fields are calculated using a primitive equation, free-surface, numerical model running in a diagnostic mode. The aforementioned SSH fields are compared with SSH fields obtained from the Geosat altimeter data. Use of Geosat data requires an estimate of the cream SSH field relative to the earth geoid. Three different methods to obtain the mean SSH field are demonstrated. The first method uses altimetry and SST data, the second uses a diagnostic calculation with climatological data; and the third uses prognostic numerical calculations. The three estimates compa...

A comparison of GEOSAT altimeter inferred currents and measured flow at 5400 m depth in the Argentine Basin

Abstract A comparison is made between an 11 month duration current meter record obtained near the bottom at 40°27′S, 49°25′W in the mid-Argentine Basin in water depth 5400 m, and near-surface flow inferred from GEOSAT altimeter data. The GEOSAT has a repeat path time of 17 days, and inferred near-surface flow features with periods of 34 days or less should not be detectable. Thus the current meter record was filtered with a 34 day low pass filter. Since only fluctuating flows can be inferred with the GEOSAT altimeter data, the deep recorded mean current was added to the satellite-inferred flow for comparison purposes. The deep flow and the altimeter-inferred near-surface flow agree remarkably well, suggesting that for time scales ⩾34 days the flow was nearly barotropic in this region of the South Atlantic.

Analysis of a general circulation model: 2. Distribution of kinetic energy in the South Atlantic and Kuroshio/Oyashio systems

The energy of the model transient eddies at 37.5 m is compared with Geosat altimeter observations, for the South Atlantic Ocean and for the Kuroshio system. The model shows areas of transient motions overlapping the ones obtained from Geosat altimeter data. For the South Atlantic Ocean, the modeled eddy kinetic energy is smaller than the one observed with Geosat, by a factor of 3 for area average on the whole South Atlantic region, and by a factor of 4 for its western boundary. On the Agulhas system, transient eddy activity develops in the region where the Agulhas current retroflects. In the western South Atlantic, the modeled eddy activity is concentrated on the Confluence front; observed variability along a more extended region following the topography is not resolved in the model. For the Kuroshio region, the energy level of the modeled transient motions is comparable with Geosat observations, but the model eddy activity is more concentrated in the Kuroshio Current and not in the Kuroshio extension. The observations show the opposite. For the South Atlantic Ocean, a comparison is also done between model eddy kinetic energy (defined as including standing and transient eddy contributions) with values obtained from surface drifters. The analysis shows differences in the western boundary, and good agreement across the South Atlantic Ocean between 35°S and 45°S. In this formulation, the model mean energy level is smaller than the observed with drifters from the First GARP Global Experiment; differences might be due to an overestimation in the values obtained with the drifters.

The determination of a one year mean sea surface height track from Geosat altimeter data and ocean variability implications

One year (November 1986 to October 1987) of Geosat altimeter data with improved orbits produced at The Ohio State University has been used to define sea surface heights for 22 ERM and one year averaged Geosat track. All sea surface heights were referenced to the single reference track through the application of geoid gradient corrections. The root mean square (RMS) gradient correction was on the order of ±1 cm although it could reach 20 cm with data points in trench areas. 10 values used to form the mean were considered. Although this study was initially driven by a need for a good reference sea surface for geodetic applications the formation of the reference track yields information on the variability of the ocean surface in the first year of the Geosat ERM. The RMS point variability was ± 12.6 cm with only a very small number of values exceeding 50 cm when a depth editing criteria was used. Global plots of the sea surface variability clearly reveal the major ocean currents and their variations in position in the year. Examination of the 1° × 1° averaged sea surface height variations show average and maximum variability values as follows: Gulf Stream (29 and 50 cm); Kurshio Current (24 and 49 cm); Agulhas Current (24 and 52 cm) and the Gulf of Mexico (18 and 31 cm). These magnitudes may be dependent on the radial orbit correction procedure. To investigate this effect sea slope variations were also computed. These results also showed clear current structures but also high frequency gravity field information despite efforts to average out such information. The data described in the paper is available from the authors for numerous other studies, some of which are suggested in the paper.

The global structure of the annual and semiannual sea surface height variability from Geosat altimeter data

The global structure of the annual and semiannual sea surface height variability is constructed from the first 2 years of the Geosat Exact Repeat Mission (ERM) altimeter data. The GEM‐T2 orbits available for the first 2 years of the ERM have an accuracy of 40 cm RMS. Residual orbit error is modeled as one cycle per orbital revolution and is removed from collinear differences of arcs made of data from one full orbital revolution of the satellite. The error in the Schwiderski M2 tidal model must be estimated due to the fact that the tidal variability aliases to 1.15 cycles per year (cpy), and this frequency is not separable from 1 cpy with the 2 years of data. An estimate of the M2 tidal error is made based on the particular temporal and spatial aliasing of the tide. With this error removed, a least squares fit of sine and cosine waves with annual and semiannual frequencies is made to the time series at every point along the ground track of the satellite. This produces sine and cosine coefficients at the ground track points which are interpolated to a regularly spaced ½° grid over the globe. From the sine and cosine maps, amplitude and phase may be obtained. Interpolation of the sine and cosine coefficients using different spatial scales is done to better observe the large‐scale phase changes and to remove small‐scale noise. Results show the phase relationships between major current systems, large‐scale variations near the equator in the Intertropical Convergence Zone (ITCZ), a 180° phase difference between the northern and southern hemispheres for the annual variability, large‐scale westward propagating waves, and other large‐scale gyre features.

An improved special sensor microwave imager water vapor correction for Geosat altimeter data

A wet tropospheric correction for the Geosat altimeter data is derived from the special sensor microwave imager (SSM/I) water vapor products by sub‐objective mapping. The correction presents wavenumber spectral characteristics close to those of the original SSM/I data in the 200‐ to 2000‐km wave band, and is filtered in the short wavelength domain. In both respects, it behaves significantly better than corrections derived from 4‐day averages of the SSM/I data interpolated quadratically under the Geosat track. As an example, the along‐track rms mesoscale variability is lowered by 3 cm for some tracks in the northeast Atlantic Ocean when this correction is applied rather than the correction of Wentz [1990]. This suggests that it indeed improves the altimeter data.

An agulhas ring in the South Atlantic ocean and its interaction with the Benguela upwelling frontal system

An Agulhas ring was detected using XBT probes on a cruise between Cape Town and Vema Seamount in the south-east Atlantic Ocean in April 1989. CTD and nutrient data, collected on a second cruise in May 1989, GEOSAT altimeter data for February–April 1989 and cloud-free NOAA-11 satellite imagery from June 1989 were used to characterize the ring. The ring was elliptical (330 km E-W and 165 km N-S, relative to the 16°C isotherm at 200 m depth), evident to at least 1200 m, and centred on 30.5°S, 9.2°E in May, about 700 km west of the Orange River. Its drift velocity was 6.4 ± 1 cm s −1 to the NW. Maximum anticyclonic geostrophic surface currents near its edge were 55 cm s −1 relative to 1150 db. The available potential energy was estimated to be 38.8 × 10 15 J and the kinetic energy 2.3 × 10 15 J using a two layer model of the ring. A cool filament extending 450 km offshore from the Benguela upwelling front was identified in the hydrography and the NOAA-11 imagery. Entrainment velocities (maximum of 75 cm s −1) of mature upwelled water from the Benguela frontal region were inferred from feature tracking.

Global sea level change from satellite altimetry

We examine the feasibility of using satellite altimeter data to measure the long‐term change of global sea level (estimated from tide gauge data to be a rise of approximately 0.2 cm yr−1). Two and one‐half years of collinear Geosat altimeter data (1986–1989) are used together with a 17‐day set of Seasat altimetry (July–August 1978) having nearly the same ground track. A consistent set of precise orbits was used throughout, and residual orbit error was removed as a sinusoidal fit to approximately 3‐day arcs of sea level collinear differences. The globally averaged Geosat data show sea level falling at 1.2 ± 0.3 cm yr−1 over the first 2 years, even after removal of tide errors and instrument biases not accounted for in the Geosat geophysical data records. This unrealistic result is found to be due largely to long‐term error in the ionospheric model for the single‐frequency Geosat altimeter. The Geosat‐Seasat comparison, based on data 10 years apart, shows an apparent sea level rise of 1.0 cm yr−1. Assuming this result is also unrealistic, a possible explanation is a biased scale to the Doppler‐determined Geosat orbit which, unlike Seasat, did not have the benefit of laser tracking. It is also possible that the Geosat altimeter (without external in‐orbit calibration) had a bias of the order of 10 cm. We conclude that for satellite altimetry to make a fundamental contribution to monitoring global mean sea level change, both the altimeter (including its media corrections) and the orbit model which provides a geocentric reference for the ocean surface will need continuing and careful calibration with absolute standards.

Assimilation of altimeter data in a global third‐generation wave model

We investigated the effect of the assimilation of altimeter satellite data in the third‐generation ocean wave model WAM. We used a sequential method, where analyzed significant wave height fields are created by optimum interpolation, and the analyzed values are then used to construct the analyzed wave spectrum. The method provides also an estimate of the surface stress showing the possibility of using the analysis of the wave spectrum to derive an analyzed surface stress field. In a first set of numerical experiments, the data, provided by the Seasat altimeter, have been assimilated in the WAM model for 1½ days. The comparison between model results and satellite data during the continuation of the run shows a positive and persistent impact of the assimilation. In a second set of numerical experiments, Geosat altimeter data were assimilated for 10 days and the resulting analysis was compared with buoy data. Although the assimilation improves the model results, it is not capable of compensating the differences between model and buoys. Some failures are clearly derived from the absence in the satellite data of the high‐wave events that were reported by the buoys. Other failures may be the consequence of an excessive swell attenuation in the WAM model, which compromises the effect of a previous correction. In fact, the comparison of WAM model results with altimeter data suggests that there is a tendency of the model to overevaluate initially the wind sea, and successively to overestimate the decay of the wave energy, when the waves leave the area of the storm.

Continuous assimilation in an open domain of the northeast Atlantic: 1. Methodology and application to AthenA‐88

A scheme to perform suboptimal intermittent assimilation in an open‐ocean, quasi‐geostrophic model is presented and applied to the assimilation of altimeter data in a domain of the northeast Atlantic west of Ireland. Both simulated and real altimeter data are used. Three‐dimensional (3‐D) synoptic observation fields and error variance fields are derived from synoptic dynamic topography anomaly estimates, using an empirical orthogonal mode (EOF) vertical extension technique. The 3‐D estimates are suboptimally combined with the time‐dependent part of the forecast fields. Suboptimality here means that the combination does not directly use spatial correlations of errors; however, the 3‐D synoptic observation estimates used in the combination do contain error spatial statistical information. The resulting fields added to a mean model climatology are used as initial conditions for the model, which is integrated until a new dynamic topography anomaly estimate is available. Locally, the combination is optimal in the sense that it is based on the observational error variances, which reflect the measurement noise and the space‐time distribution of data, and that it minimizes the error variance of the results. A similar combination scheme using past as well as future observations is used to update the boundaries during model integration. Simulated surface topography anomaly maps, typical of the northeast Atlantic, are assimilated every 20 days for a 300‐day period, with different noise characteristics typical of altimetric sampling errors, in a three‐level version of the model. The assimilation fields, especially the vorticity at deeper levels, converge toward the reference fields. The convergence is obtained after O(100 days), regardless of the observational noise levels tested (up to −2 dB). Using a relevant observational error model seems to matter, in particular, the error level should not be underestimated. In the case of an 80‐day gap in the data inflow, the model predictability limits the reliability of the forecast beyond 20 days. The scheme makes the model converge back as soon as new observations are entered, with limited convergence loss due to the gap. The case of an unknown model climatology is also studied. Finally, the scheme is applied to Geosat altimeter data, added to the Robinson, Bauer and Schroeder annual climatology, in the AthenA‐88 cruise area, which is contained in the model box. The assimilation results compare favorably with hydrographical data from the cruise and help the synoptic interpretation of the observed phenomena.

Wind-wave relationship for bay of Bengal from GEOSAT data

Stellite Remote Sensing is an emerging technique for observation of oceans. The important oceanic parameters, wave heights and wind speeds derived fron GEOSAT Altimeter data, are analysed in the present paper. Relation between wind speed and height of ‘sea waves’ are obtained for southwest monsoon, northeast monsoon and nonmonsoon seasons, and regression equations are arrived at for each case. Good correlation and high accuracy are observed for all the seasons. This assures the usage of remotely sensed data for oceanic studies.

Estimation of the Sea-State Bias in Radar Altimeter Geosat Data from Examination of Frontal Systems

The sea-state bias is the deviation of the sea surface height as seen by a satellite altimeter due to differential scattering by the crest and troughs of waves and to oversimplification of the radar waveform algorithms that calculate this height. Here the sea-state bias is estimated by automatically analyzing with a least-squares technique the along-track deviation of sea surface in the case of fronts of significant wave height (SWH). Twenty-two thousand profiles of 1500-km length of Geosat altimeter data are analyzed. Since a very strict selection was applied, only nine clear front situations are found. Among these five correspond to atmospheric frontal situations as suggested by the altimetric wind profiles. The sea-state bias is of 3.6% ±0.6% of SWH (2σ error). The four other fronts are interpreted as swell fronts: they present smaller biases of the order of 1.0%±1.6% of SWH. These results are in agreement with experimental studies and justify the calculation of sea-state bias as a function of sea maturity.

Quality of ocean variability results from satellite altimetry

Abstract One year of Geosat altimeter data is used for a comparison among three different processing techniques for the determination of mesoscale ocean currents. The observations, like sea surface variability and sea surface anomaly time series, yield a valuable contribution to all kinds of oceanographic studies. The article presents an a‐priori estimate of the feasible spatial and temporal resolutions of the observations by validating the different processing techniques and comparing the results. It shows an excellent correlation between the different sea surface anomaly field solutions. For the Agulhas Retroflection area it was found that the standard deviation of the obtained relative sea level may amount to up to 4 cm and that the average correlation is better than 0.90 (±0.04). The overall quality of the results obtained was shown to depend on the mesoscale signal strength and therefore differs for each region. This nonisotropic behavior of the correlation between the sea surface anomaly fields is s...

Frontal structure and transport of the Antarctic Circumpolar Current in the south Indian Ocean sector, 40–80°E

Based on recent conductivity-temperature-depth (CTD) data at the Kerguelen-Amsterdam passage plus historical expendable bathy thermograph (XBT) and hydrographie data from the Crozet Basin, the frontal structure and volume transport of the Antarctic Circumpolar Current (ACC) in the south Indian Ocean sector are described. Recent findings on sea-level variability from GEOSAT altimeter data are reviewed as well as barotropic transport variability from bottom pressure measurements at Kerguelen and Amsterdam Islands. The ACC here is mostly concentrated in a narrow frontal zone of 2–3° of latitude, without any noticeable multi-band structure, as a result of the confluence of the Subantarctic and Subtropical Fronts. The Polar Front in this sector is not associated with any prominent current core. This regional particularity of the ACC was further supported by GEOSAT altimetry data. About 80% of the ACC transport (106Sv; 1 Sv=10 6 m 3s −1) passes north of Kerguelen, concentrated along the northern flank of the Kerguelen Plateau; only 30 Sv passes south of Kerguelen. The bottom-pressure-derived barotropic transport variability at Kerguelen-Amsterdam passage was estimated to lie between 10 and 30 Sv, consistent with findings at Drake Passage. It is suggested that the study area constitutes a prominent ACC observatory during the WOCE (World Ocean Circulation Experiment).

Global‐scale sea surface variability from combined altimetric and tide gauge measurements

By correcting Geosat altimetric data for a set of line frequencies, and then doing a heavy average in space and time, a set of global maps of sea surface variability is produced over time intervals ranging from three months to two years. These maps are demonstrated to be consistent with the global network of tide gauges and sets of maps incorporating those data into the altimetric estimates are also produced. Tide gauge records too fragmentary for computation of a two‐year mean are employed by time differencing them. An estimate of the global difference of sea level change over one year, on very large space scales, shows the effects of the 1987 El Niño. The spherical harmonic coefficients employed in the computations are then used to estimate the full three‐dimensional frequency/wavenumber spectrum of surface circulation variability.

Wave studies with the radar altimeter

Abstract In this paper we review the physical understanding and the algorithms necessary to extract wave information from the radar altimeter return from the sea surface. This allows us to assess the progress made since the launch of Seasat, to identify areas where further work is necessary in order to develop our understanding of the basic mechanisms of radar interaction with the sea surface, and to suggest how new wave parameters might be obtained from the radar return. Following on from this were view the wave studies that have been carried out using Seasat and Geosat altimeter data and present some new results, on the joint probability distribution of significant waveheight and wind speed, which we have obtained recently from Seasat data.

Anticyclonic current rings in the eastern tropical Pacific Ocean

Observations from satellite‐tracked drifting buoys, expendable bathythermograph and conductivity‐temperature‐depth data, and Geosat altimeter data are used to describe anticyclonic eddies that occur in small numbers off the Pacific coast of Central America. These eddies are similar in many respects to the well‐known warm‐core rings that are observed north of the Gulf Stream off the Atlantic coast of North America, except that they occur in an environment that also is warm, and they contain considerably greater kinetic energy. It is hypothesized that they are formed as a result of conservation of potential vorticity when the North Equatorial Countercurrent (NECC) turns northward upon approaching the eastern boundary during its autumnal maximum. The rings so formed have a strongly nonlinear character which causes them to propagate westward between 9°N and 14°N with a speed in excess of that of long Rossby waves. Due to a relatively small available potential energy content, these rings have a dissipation time scale of about 6 months and perhaps end by collision with and reabsorbtion into the NECC. The rings account for the observed enhancement of surface kinetic energy, and probably for the seaward transport of waters enriched in copper.

Impact of the Geosat altimeter wet tropospheric range correction in the Greenland‐Iceland‐Norwegian Sea

Atmospheric water vapor data derived from the special sensor microwave imager (SSM/I) are used to make time‐coincident wet tropospheric range corrections to Geosat altimeter data in the Greenland‐Iceland‐Norwegian (GIN) Sea. The SSM/I sensor is onboard a polar orbiting Defense Meteorological Satellite Program platform and provides water vapor data at 25‐km spatial resolution and an accuracy of 0.24 g cm−2. Water vapor height corrections were calculated and analyzed along all Geosat tracks crossing the area of interest in July and September 1987 and January and March 1988. Results indicate that the horizontal spatial variations in the altimeter height corrections can sometimes equal or exceed the magnitude (10–20 cm/100 km) of true GIN Sea sea surface height gradients, especially in the summer and autumn seasons. SSM/I and Geosat data must be closely matched in time, due to the potential rapid movement of atmospheric systems through this region (35–40 km h−1). The water vapor data must be timely enough to adequately describe atmospheric conditions at the time of the altimeter pass, or significantly false signals may be introduced into the sea surface height data. Substantial differences in water vapor gradients were observed in SSM/I data sets 12 hours apart. Because of this, it is suggested that future satellite altimeter platforms include a nadir‐viewing radiometer to provide time‐coincident atmospheric water vapor data.