Abstract
A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04’s poor ability to accurately and reliably measure hydrological signal above 3–9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Bonin JA (2010) Improving the observation of time-variable gravity using GRACE RL04 Data. Dissertation, University of Texas at Austin, Austin
Bruinsma S, Lemoine JM, Biancale R, Valès N (2010) CNES/GRGS 10-day gravity field models (release 2) and their evaluation. Adv Space Res 45(4): 587–601. doi:10.1016/j.asr.2009.10.012
Dahle C, Fletchtner F, Kusche J, Rietbroek R (2008) GFZ EIGEN-GRACE05S weekly gravity field time series. Grace Science Team Meeting, San Francisco
Güntner A, Werth S, Petrovic S, Schmidt R (2008) Calibration analysis of the global hydrological model WGHM with water mass variations from GRACE gravity data. GRACE Science Team Meeting, San Franscisco
Kim JR (2000) Simulation study of a low-low satellite-to-satellite tracking mission. Dissertation, University of Texas at Austin, Austin
Kurtenbach E, Mayer-Gürr T, Eicker A (2009) Deriving daily snapshots of the Earth’s gravity field from GRACE L1B data using Kalman filtering. Geophys Res Lett 36: L17102. doi:10.1029/2009GL039564
Lemoine JM, Bruinsma S, Loyer S, Biancale R, Marty JC, Perosanz F, Balmino G (2007) Temporal gravity field models inferred from GRACE data. Adv Space Res 39: 1620–1629. doi:10.1016/j.asr.2007.03.062
Liu X, Ditmar P, Siemes C, Slobbe DC, Revtova E, Klees R, Riva R, Zhao Q (2010) DEOS mass transport model (DMT-1) based on GRACE satellite data: methodology and validation. Geophys J Int 181(2): 769–788. doi:10.1111/j.1365-246X.2010.04533.x
Mayer-Gürr T, Eicker A, Ilk KH (2009) ITG-Grace03 Gravity Field Model. Universität Bonn Institut für Geodäsie and Geoinformation. http://www.geod.uni-bonn.de/itg-grace03.html (accessed April 11 2009)
Mirador Earth Science Data Search Tool (2010) Goddard Earth Sciences Data and Information Services Center. http://mirador.gsfc.nasa.gov (accessed 21 July 2010)
Niu GY, Yang ZL (2006) Assessing a land surface model’s improvements with GRACE estimates. Geophys Res Lett 33: L07401. doi:10.1029/2005GL025555
Rodell M, Houser PR, Jambor U, Gottschalck J, Mitchell K, Meng CJ, Arsenault K, Cosgrove B, Radakovich K, Bosilovich M, Entin JK, Walker JP, Lohmann D, Toll D (2004) The global land data assimilation system. Bull Am Meteorol Soc 85: 381–394. doi:10.1175/BAMS-85-3-381
Rowlands DD, Luthcke SB, Klosko SM, Lemoine FG, Chinn DS, McCarthy JJ, Cox CM, Andersen OB (2005) Resolving mass flux at high spatial and temporal resolution using GRACE intersatellite measurements. Geophys Res Lett 32: L04310. doi:10.1029/2004GL021908
Save H, Bettadpur S, Tapley BD (2012) Reducing errors in the GRACE gravity solutions using regularization. J Geod. doi:10.1007/s00190-012-0548-5
Strassberg G, Scanlon BR, Rodell M (2007) Comparison of seasonal terrestrial water storage variations from GRACE with groundwater-level measurements from the high plains aquifer (USA). Geophys Res Lett 34: L14402. doi:10.1029/2007GL030139
Swenson S, Famiglietti J, Basara J, Wahr J (2008) Estimating profile soil moisture and groundwater variations using GRACE and Oklahoma Mesonet soil moisture data. Water Resour Res 44: W01413. doi:10.1029/2007WR006057
Swenson S, Wahr J (2002) Methods for inferring regional surface-mass anomalies from gravity recovery and climate experiment (GRACE) measurements of time-variable gravity. J Geophys Res 107(B9): 3. doi:10.1029/2001JB000576
Swenson S, Yeh PJF, Wahr J, Famiglietti J (2006) A comparison of terrestrial water storage variations from GRACE with in situ measurements from Illinois. Geophys Res Lett 33: L16401. doi:10.1029/2006GL026962
Tapley BD, Bettadpur S, Ries JC, Thompson PF, Watkins MW (2004) GRACE measurements of mass variability in the earth system. Science 305: 503–505. doi:10.1126/science.1099192
Wahr J, Swenson S, Velicogna I (2006) Accuracy of GRACE mass estimates. Geophys Res Lett 33: L06401. doi:10.1029/2005GL025305
Wahr J, Swenson S, Zlotnicki V, Velicogna I (2004) Time-variable gravity from GRACE: first results. Geophys Res Lett 31: L11501. doi:10.1029/2004GL019779
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bonin, J.A., Bettadpur, S. & Tapley, B.D. High-frequency signal and noise estimates of CSR GRACE RL04. J Geod 86, 1165–1177 (2012). https://doi.org/10.1007/s00190-012-0572-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00190-012-0572-5