English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Quality assessment of GRACE observations over the oceans by means of satellite altimetry.

Authors
/persons/resource/dobslaw

Dobslaw,  Henryk
Deutsches GeoForschungsZentrum;

/persons/resource/mthomas

Thomas,  Maik
Deutsches GeoForschungsZentrum;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in GFZpublic
Supplementary Material (public)
There is no public supplementary material available
Citation

Dobslaw, H., Thomas, M. (2008): Quality assessment of GRACE observations over the oceans by means of satellite altimetry., (EOS, Transactions American Geophysical Union, 89(23), Suppl., Abstract G31A-03), 2008 Western Pacific Geophysics Meeting (Cairns, Australia 2008).


https://gfzpublic.gfz-potsdam.de/pubman/item/item_237094
Abstract
Sea-level variability as observed by satellite altimetry reflects the integral effect of various dynamic processes in the oceans including the response to atmospheric loading, density changes in the water column as well as re- distribution of ocean mass. Since the first two effects are reasonably estimated and removed from the data, altimetric observations of the remaining mass induced height changes can be used to validate direct measurements of ocean mass variations as obtained with the satellite gravimetry mission GRACE. In order to assess the accuracy of various GRACE products, recently released gravity field solutions from, e.g., GFZ Potsdam, CSR Austin, JPL Pasadena and the Universities of Bonn and Delft will be contrasted both against sterically corrected Jason 1 observations and mass anomalies simulated with the numerical ocean model OMCT. Focussing on the time period 2003 until 2007, regional distribution, intensity, and shape of mass variabilities as well as corresponding barotropic current anomalies are used to assess the accuracy and reliability of the latest GRACE results over the oceans separately for individual monthly solutions. The cross- comparisons will additionally allow for first order error estimates of the data sets involved, which are necessary to know for using these data in any type of inversion experiment.