Abstract's details
Analysis of Geomed2 Combined Geoid Models
Event: 2018 Ocean Surface Topography Science Team Meeting
Session: The Geoid, Mean Sea Surfaces and Mean Dynamic Topography
Presentation type: Type Oral
Contribution: PDF file
Abstract:
The GEOMED 2 project computed a high-accuracy and high-resolution marine geoid model based on the availability of improved models for gravity, thanks to GRACE and GOCE in particular, for land topography and bathymetry, and the compilation of a cleaned-up and de-biased gravity database of the Mediterranean area based on BGI and SHOM data. Land and marine gravity data, the latest combined GOCE/GRACE based Global Geopotential Models and a combination of MISTRALS, EMODnet and SRTM/bathymetry terrain models were used in the gravimetric geoid computation. Computation of a gravimetric marine geoid of the Mediterranean is challenging due to:
• The poor coverage of the marine gravity data for certain areas;
• The inhomogeneous quality of the marine gravity data (bias, precision);
• The data reduction is not as efficient as achieved over land.
Marine gravity data is not available for large parts of the Mediterranean and consequently the gravimetric geoid solution is significantly less accurate there. Gravity inferred from altimetry data, or a mean sea surface corrected for mean dynamic topography (i.e., an ‘oceanographic’ geoid model), can be used to fill the gaps. However, ocean dynamic signal may contaminate the derived gravity or geoid, which is why a pure gravimetric solution is preferred in an ideal world.
The effect on the geoid solution of using several altimeter-based datasets, such as DTU10, DTU15 and UCSD V24 gravity, using simple gap filling, weighted combinations with the gravimetric data, and combination through collocation, will be evaluated and quantified. The combined models are compared with the gravimetric geoid solution as well as with marine geoids constructed with MSS and MDT, a so-called ‘oceanographic’ geoid. Significant differences are visible, from small to medium scales, between all solution types; the reasons for the differences are not clear presently.
• The poor coverage of the marine gravity data for certain areas;
• The inhomogeneous quality of the marine gravity data (bias, precision);
• The data reduction is not as efficient as achieved over land.
Marine gravity data is not available for large parts of the Mediterranean and consequently the gravimetric geoid solution is significantly less accurate there. Gravity inferred from altimetry data, or a mean sea surface corrected for mean dynamic topography (i.e., an ‘oceanographic’ geoid model), can be used to fill the gaps. However, ocean dynamic signal may contaminate the derived gravity or geoid, which is why a pure gravimetric solution is preferred in an ideal world.
The effect on the geoid solution of using several altimeter-based datasets, such as DTU10, DTU15 and UCSD V24 gravity, using simple gap filling, weighted combinations with the gravimetric data, and combination through collocation, will be evaluated and quantified. The combined models are compared with the gravimetric geoid solution as well as with marine geoids constructed with MSS and MDT, a so-called ‘oceanographic’ geoid. Significant differences are visible, from small to medium scales, between all solution types; the reasons for the differences are not clear presently.