TY - GEN

T1 - An initial investigation of the GOCE error variance-covariance matrices in the context of the GOCE user toolbox project

A1 - Bingham,Rory J.

A1 - Tscherning,Christian

A1 - Knudsen,Per

AU - Bingham,Rory J.

AU - Tscherning,Christian

AU - Knudsen,Per

PB - European Space Agency, ESA

PY - 2011

Y1 - 2011

N2 - The availability of the full error variance-covariance matrices for the GOCE gravity field models is an important feature of the GOCE mission. Potentially, it will allow users to evaluate the accuracy of a geoid or mean dynamic topography (MDT) derived from the gravity field model at any particular location, design optimal filters to remove errors from the surfaces, and rigorously assimilate a geoid/MDT into ocean models, or otherwise combine the GOCE gravity field with other data. Here we present an initial investigation into the error characteristics of the GOCE gravity field models as they are realised in the calculated geoid anomalies. We examine how the error variances depend on location and spatial scale, and how they differ between models. The inhomogeneous and anisotropic nature of the error covariances are explored, and an example of how this information may be used in ocean data assimilation is provided. Finally, we consider some of the practical issues relating to the handling of the huge files containing the error variance-covariance information.

AB - The availability of the full error variance-covariance matrices for the GOCE gravity field models is an important feature of the GOCE mission. Potentially, it will allow users to evaluate the accuracy of a geoid or mean dynamic topography (MDT) derived from the gravity field model at any particular location, design optimal filters to remove errors from the surfaces, and rigorously assimilate a geoid/MDT into ocean models, or otherwise combine the GOCE gravity field with other data. Here we present an initial investigation into the error characteristics of the GOCE gravity field models as they are realised in the calculated geoid anomalies. We examine how the error variances depend on location and spatial scale, and how they differ between models. The inhomogeneous and anisotropic nature of the error covariances are explored, and an example of how this information may be used in ocean data assimilation is provided. Finally, we consider some of the practical issues relating to the handling of the huge files containing the error variance-covariance information.

SN - 978-92-9092-260-5

BT - Proceedings of 4th International GOCE User Workshop

T2 - Proceedings of 4th International GOCE User Workshop

ER -