Gravity Anomalies and Estimated Topography Derived from Satellite AltimetryAlternate Views: Get Data, FAQ, ISO Rubric, DOI Rubric, CSW, HTML, Components, XML
Gravity Anomalies and Estimated Topography Derived from Satellite Altimetry
In many areas of the global ocean, the depth of the seafloor is not well known because survey lines by ships are hundreds of kilometers apart. Satellites carrying radar altimeters have measured the shape of the ocean along tracks only 3-4 km apart, and from these data we can make very accuratore (+/-3mGal) and high resolution (15km) maps of the marine gravity field. The gravity field mimics the seafloor topography in the 15-160 km wavelength band if sediment cover on the ocean floor is thin. Long-wavelength (greater than 160 km) topography is isostatically compensated and is not correlated with the gravity field. In addition, the satellite gravity field and the available depth measurements were used to determine the correlation between gravity and the seafloor topography. By applying this correlation to the gravity field we predict seafloor topography in the 15-160 km wavelength band. This topography is combined with a long-wavelength component estimated directly from ship depth measurements. The result reveals many new features and is within +/- 100m of actual depths in many cases. The Predicted Seafloor Topography derived from the depths estimated from Satellite Altimetry in combination with measured trackline bathymetry is an inferred data set and is not true bathymetry. It is, however, the best estimate of seafloor topography available resulting from satellite gravity data and actual ship depth measurements. These data are intended for scientific research and should not be used for navigational purposes. Additional software is required in order to manipulate the data or produce your own graphic images. Poster and CD-ROM products are available for both gravity anomaly and estimated seafloor topography of several regions. Please refer to URL http://www.ngdc.noaa.gov/mgg/announcements/announce_predict.html for more information, and to download sample images.

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