Abstract
Gravity measurements within the Gravity Recovery and Climate Experiment (GRACE) provide a direct measure of monthly changes in mass over the Earth’s land masses. As such changes in mass mainly correspond to water storage changes, these measurements allow to close the continental water balance on large spatial scales and on a monthly time scale within the respective error bounds. When quantifying uncertainties, positive and negative peaks are detected in GRACE aggregated monthly time series (from different data providers) that do not correspond to hydrological or hydro-meteorological signals. These peaks must be interpreted as outliers, which carry the danger of signal degradation. In this paper an algorithm is developed to identify outliers and replace them with hydrologically plausible values. The algorithm is based on a statistical approach in which hydrological and hydro-meteorological signals are used to control the algorithm. The procedure of outlier detection is verified by evaluating catchment based aggregated GRACE monthly signals with ground truth from hydrology and hydro-meteorological signals. The results show improvement in the correlation of GRACE versus hydrometeorological and hydrological signals in most catchments. Also, the noise level is significantly reduced over 255 largest catchments.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baarda W., 1968. A Testing Procedure for Use in Geodetic Networks. Netherlands Geodetic Commission Publ. Geodesy, 2(5) (http://www.ncg.knaw.nl/Publicaties/Geodesy/pdf/09Baarda.pdf).
Barnett V. and Lewis T., 1994. Outliers in Statistical Data. John Wiley & Sons, New York.
Bettadpur S., 2007. Gravity Recovery and Climate Experiment. Level-2 Gravity Field Product User Handbook. GRACE 327-734, CSR-GR-03-01, Center for Space Research, The University of Texas at Austin, Austin, TX (http://www.csr.utexas.edu/grace/publications/handbook/L2-UserHandbook_v1.0.pdf).
Hobbins M.T., Ramirez J.A., Brown T.C. and Claessens L.H.J.M., 2001. The complementary relationship in estimation of regional evapotranspiration: The complementary Relationship Areal Evapotranspiration and Advection-Aridity models. Water Resour. Res., 37, 1367–1387, DOI: 10.1029/2000WR900358.
ITG-GRACE, 2010. Unconstrained monthly solutions (http://www.igg.uni-bonn.de/apmg/index.php?id=itg-grace2010).
Kern M., Preimesberger T., Allesch M., Pail R., Bouman J. and Koop R., 2005. Outlier detection algorithms and their performance in GOCE gravity field processing. J. Geodesy, 78, 509–519, DOI: 10.1007/s00190-004-0419-9.
Swenson S. and Wahr J., 2006. Post-processing removal of correlated errors in GRACE data. Geophys. Res. Lett., 33, L08402, DOI: 10.1029/2005GL025285.
Syed T.H., Famiglietti J.S., Chen J., Rodell M., Seneviratne S.I. and Viterbo P., 2005. Total basin discharge for the Amazon and Mississipi River basins from GRACE and a land-atmosphere water balance. Geophys. Res. Lett., 32, L24404, DOI: 10.1029/2005GL024851.
Tapley B.D., Bettadpur S., Ries J.C., Thompson P.F. and Watkins M.M., 2004, The Gravity Recovery and Climate Expriment: Mission overview and early results. Geophys. Res. Lett., 31, L09607, DOI: 10.1029/2004GL019920.
Wahr J., Molenaar M. and Bryan F., 1998. The time-varibility of the Earth’s gravity field: Hydrological and oceanic effects and their possible detection using GRACE. J. Geophys. Res., 103, 30205–30230, DOI: 10.1029/98JB02844.
Wahr J., Swenson S. and Velicogna I., 2006. Accuracy of GRACE mass estimates. Geophys. Res. Lett., L06401, DOI: 10.1029/2005GL025305.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Tourian, M.J., Riegger, J., Sneeuw, N. et al. Outlier identification and correction for GRACE aggregated data. Stud Geophys Geod 55, 627–640 (2011). https://doi.org/10.1007/s11200-009-9007-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11200-009-9007-z