: This project, which now has the working name OSCAR (Ocean Surface Currents Analysis Real-Time), develops a processing system and data center to provide operational ocean surface velocity fields from satellite altimeter and vector wind data. The regional focus is the tropical Pacific, where the value of this data is demonstrated for a variety of uses, specifically large-scale climate diagnostics and prediction as well as fisheries management and recruitment and monitoring debris drift, larvae drift, oil spills, fronts, and eddies. The end product will be to leave in place a turnkey system running at the National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite, Data, and Information Service (NESDIS), with an established user clientele and easy internet data access. The method to derive surface currents with satellite altimeter and scatterometer data is the outcome of several years of NASA-sponsored research. This project transitions the capability to operational oceanographic applications. The near-term objective is to provide data that is updated on a weekly basis, and to carry out a thorough validation analysis. The data have been very useful in monitoring the El Nino in 2002 and its fading in early 2003, and in evaluating forecasting models.

A major accomplishment of the recently completed Tropical Ocean‐Global Atmosphere (TOGA) Program was the development of an ocean observing system to support seasonal‐to‐interannual climate studies. This paper reviews the scientific motivations for the development of that observing system, the technological advances that made it possible, and the scientific advances that resulted from the availability of a significantly expanded observational database. A primary phenomenological focus of TOGA was interannual variability of the coupled ocean‐atmosphere system associated with El Niño and the Southern Oscillation (ENSO).Prior to the start of TOGA, our understanding of the physical processes responsible for the ENSO cycle was limited, our ability to monitor variability in the tropical oceans was primitive, and the capability to predict ENSO was nonexistent. TOGA therefore initiated and/or supported efforts to provide real‐time measurements of the following key oceanographic variables: surface winds, sea surface temperature, subsurface temperature, sea level and ocean velocity. Specific in situ observational programs developed to provide these data sets included the Tropical Atmosphere‐Ocean (TAO) array of moored buoys in the Pacific, a surface drifting buoy program, an island and coastal tide gauge network, and a volunteer observing ship network of expendable bathythermograph measurements. Complementing these in situ efforts were satellite missions which provided near‐global coverage of surface winds, sea surface temperature, and sea level. These new TOGA data sets led to fundamental progress in our understanding of the physical processes responsible for ENSO and to the development of coupled ocean‐atmosphere models for ENSO prediction.

A major accomplishment of the recently completed Tropical Ocean-Global Atmosphere (TOGA) Program was the development of an ocean observing system to support seasonal-to-interannual climate studies. This paper reviews the scientific motivations for the development of that observing system, the technological advances that made it possible, and the scientific advances that resulted from. the availability of a significantly expanded observational database. A primary phenomenological focus of TOGA was interannual variability of the coupled ocean-atmosphere system associated with El Nino and the Southern Oscillation (ENSO). Prior to the start of TOGA, our understanding of the physical processes responsible for the ENSO cycle was limited, our ability to monitor variability in the tropical oceans was primitive, and the capability to predict ENSO was nonexistent. TOGA therefore initiated and/or supported efforts to provide real-time measurements of the following key oceanographic variables: surface winds, sea surface temperature, subsurface temperature, sea level and ocean velocity. Specific in situ observational; programs developed to provide these data sets included the Tropical Atmosphere-Ocean (TAO) array of moored buoys, in the Pacific, a surface drifting buoy program, an island and coastal tide gauge network, and a volunteer observing ship network of expendable bathythermograph measurements. Complementing these in situ efforts were satellite missions which provided near-global coverage of surface winds, sea surface temperature, and sea level. These new TOGA data sets led to fundamental progress in our understanding of the physical processes responsible for ENSO and to the development of coupled ocean-atmosphere models for ENSO prediction.

A pattern recognition method and a spatial integration filtering method have been developed to analyze satellite altimeter sea surface elevation anomaly (SSEA) data for the tropical Pacific Ocean. The pattern recognition method treats SSEA as an independent variable of the ocean, and SSEA map, its two-dimensional distribution image, as similar to a normal satellite image. The results of the pattern recognition processing of the SSEA maps quantitatively reveal the information of the movement of SSEA patterns. The spatial integration filtering method is used as low-pass filtering to detect the equatorial Kelvin waves from Geosat SSEA time series data. The wave patterns and the frequency spectra are derived from SSEA data. This article describes these two methods, including an overview of the algorithms used and the results derived. Further applications of the methods are then suggested.

The European Space Agency's (ESA) remote‐sensing satellite, ERS‐1, launched in 1991, is the first in a series of satellite altimeters that should provide uninterrupted global coverage of sea level throughout the 1990s. We have analyzed these new data, together with Geosat data from the 1980s, to derive time series of sea level throughout the tropical Pacific. While altimeter observations are unique in their ability to provide sea‐level descriptions that are both large‐scale and detailed, these data suffer from a variety of errors. Currently, the biggest source of error for ERS‐1 is uncertainty in the satellite orbit at wavelengths corresponding to one revolution around the Earth. Conversion of ERS‐1 data into sea‐level deviations requires that this error be removed by some form of long‐arc adjustment.

We will analyze the TOPEX/POSEIDON data using techniques developed for Geosat, although the more accurate TOPEX/POSEIDON data will enable a wider range of problems to be addressed. Our proposed investigations will have five distinct areas: (1) a description of global sea level variability; (2) tropical ocean dynamics; (3) coupled models for El Nino prediction; (4) structure of the lithosphere; and (5) global tide model improvement.

The Geosat satellite altimeter mission ended January 5 after nearly 5 years of highly successful operation. Geosat data collection had already been dramatically curtailed since October 1989, when the remaining operable tape recorder failed. The mission was terminated when the altimeter output power dropped below acceptable limits.Following NASA's abbreviated Seasat altimeter mission in 1978, Geosat was conceived by the U.S. Navy as a means of obtaining high‐resolution maps of mean sea level for geodesy. The satellite was designed and constructed by the Johns Hopkins University Applied Physics Laboratory, Laurel, Md., and launched in March 1985.

The 1986–1987 El Nino was the first to be monitored by a satellite altimeter, and maps of sea level anomaly during the event reveal a rich and previously unknown structure. By chance, timing of the U.S. Navy GEOSAT altimeter mission was ideal for capturing this El Nino in its entirety. GEOSAT was launched in March 1985 and had gathered 1 full year of global data when an El Nino was predicted [Cane et al, 1986]. Dramatic atmospheric and oceanic changes were observed during the height of the event in 1986–1987, and by early 1988, conditions returned to normal. Throughout this 3‐year period, GEOSAT provided virtually uninterrupted coverage of the tropical Pacific, and prospects for several more years of observations are excellent. In this brief report we present results demonstrating the enormous potential of satellite altimetry for application to large‐scale ocean dynamics and climate research.

A forthcoming special issue of the Journal of Geophysical Research will be devoted to results from the GEOSAT altimeter mission. Contributions are solicited on all aspects of the data, including sea level, ocean dynamics, tides, marine geodesy, wind speed, wave height, data management, model assimilation, algorithm development, altimeter calibration, orbit determination, and geopotential improvement. GEOSAT is a U.S. Navy satellite built and operated by the Applied Physics Laboratory of Johns Hopkins University. The GEOSAT data set has been prepared by NOAA National Ocean Service and is distributed through the National Oceanographic Data Center. The archive presently includes geophysical data records for 2 years (Cheney et al., GEOSAT Altimeter Geophysical Data Record User Handbook, NOAA Technical Memorandum NOS NGS‐46, 32 pp., July 1987); new data are added each month. An additional 18‐month wind‐wave data set is also available (Dobson et al., GEOSAT Altimeter Wind and Wave Data Record User Handbook, Johns Hopkins Applied Physics Laboratory Report SIR88U, 29 p p. March 1988).

GEOSAT altimeter data collected after November 8, 1986, will be made available to the general research community by the National Oceanic and Atmospheric Administration (NOAA) beginning in early 1987. Although GEOSAT has been operating since April 1985, observations from the first 18 months are classified. In October 1986 the satellite was maneuvered into a 17‐day exact repeat orbit whose ground track coincides with the previous Seasat altimeter tracks, allowing new GEOSAT data to be unclassified. Under agreement reached with the U.S. Navy and the Johns Hopkins University Applied Physics Laboratory (Laurel, Md.), NOAA will assume responsibility for generating the unclassified data sets from this Exact Repeat Mission (ERM). Doppler tracking data will first be evaluated by the Naval Astronautics Group (NAG) to ensure that the GEOSAT ground track has deviated by no more than 1 km (cross track) from the exactrepeat orbit. On‐board thrusters will be fired when necessary (approximately monthly) to maintain colinearity. Raw data in, the form of sensor data records (SDRs) will then be transmitted to a NOAA processing facility in Rockville, Md., where they will be converted to finished geophysical data records (GDRs). SDR‐to‐GDR production consists of merging the altimeter data with an ephemeris provided by NAG and adding correctionfields for tides, troposphere (wet and dry components), and ionosphere. Completed GDRs will be sent to NOAA National Environmental Satellite Data and Information Service (NESDIS) in Washington, D.C., where they will be made avilable to the public. (GEOSAT data will initially be distributed to U.S. institutions only; foreign institutions are advised to seek access through formal embassy channels.)

In April 1985 the U.S. Navy satellite GEOSAT began generating a remarkable data set that may change the way in which physical oceanographers view the global oceans. GEOSAT (Figure 1) carries a radar altimeter that provides a continuous record of sea level along the satellite ground track. Such records enable determination of sea level variability and have application in many areas of ocean dynamics. Experience with GEOS 3 (Geodynamics Experimental Ocean Satellite 3) and Seasat in the 1970s demonstrated the enormous potential of altimetry for oceanography. Seasat, for example, gathered sufficient altimeter data in its last 25 days alone to yield a global description of the mesoscale eddy field [Cheney et al., 1983], wave number spectra of sea level variability [Fu, 1983], and a global model of the M2 tide [Mazzega, 1985].

Satellite-borne altimeters have had a profound impact on geodesy, geophysics, and physical oceanography. To first order approximation, profiles of sea surface height are equivalent to the geoid and are highly correlated with seafloor topography for wavelengths less than 1000 km. Using all available Geos-3 and Seasat altimeter data, mean sea surfaces and geoid gradient maps have been computed for the Bering Sea and the South Pacific. When enhanced using hill-shading techniques, these images reveal in graphic detail the surface expression of seamounts, ridges, trenches, and fracture zones. Such maps are invaluable in oceanic regions where bathymetric data are sparse. Superimposed on the static geoid topography is dynamic topography due to ocean circulation. Temporal variability of dynamic height due to oceanic eddies can be determined from time series of repeated altimeter profiles. Maps of sea height variability and eddy kinetic energy derived from Geos-3 and Seasat altimetry in some cases represent improvements over those derived from standard oceanographic observations. Measurement of absolute dynamic height imposes stringent requirements on geoid and orbit accuracies, although existing models and data have been used to derive surprisingly realistic global circulation solutions. Further improvement will only be made when advances are made in geoid modeling and precision orbit determination. In contrast, it appears that use of altimeter data to correct satellite orbits will enable observation of basin-scale sea level variations of the type associated with climatic phenomena.

A unique data set consisting of expendable bathythermograph (XBT) observations from repeated Gulf Stream crossings was used to provide ground-truth for GEOS-3 altimeter measurements of temporal sea height variability. The XBT data were obtained by NAVOCEANO using ocean liners travelling between New York and Bermuda as observation platforms. Approximately 120 crossings, each consisting of 50-60 XBTs, were made between October 1969 and November 1974. Dynamic heights were calculated using XBT profiles and temperature/salinity relationships from historical data. Results were then compared to sea height variability measured from the differences in altimeter profiles between pairs of collinear GEOS-3 passes. The comparison shows that the satellite measurements are in good agreement with the conventional shipboard observations. Additionally, it is shown that dynamic height variability correlates very highly with temperature variability at depths between 100 and 450 meters. This relationship indicates that in the Gulf Stream region, the sea surface topography in conjunction with historical data could be used to infer subsurface thermal structure.