Regional four-dimensional hydrological mass variations from GRACE, atmospheric flux convergence, and river gauge data

[1] The spatiotemporal behavior of the Earth’s gravity field is traditionally modeled as a series expansion in terms of spherical harmonics with a number of time-dependent coefficients. In this contribution we study regional effects, namely, hydrological mass variations observed by the Gravity Recovery And Climate Experiment (GRACE) satellite mission since 2002. As compared to the global spherical harmonics, scaling and wavelet functions are quasi-compactly supported, i.e., highly localizing with respect to space and time. Consequently, they establish a system of base functions well suited for regional modeling. We determine a spatiotemporal regional gravity model from GRACE using the spherical wavelet technique for the spatial part and a one-dimensional B spline expansion for the temporal variations; that is, we end up with a four-dimensional multiresolution representation (MRR) of the geopotential over selected regional areas and time intervals. For an exemplary area consisting of three large river basins in South America we compute mass variations expressed in terms of equivalent water heights. We demonstrate that a B spline expansion for modeling the temporal behavior is more appropriate than the classical Fourier series approach. In order to corroborate the results, our storage estimates are balanced with the net effect of river discharge from gauges (outflow) and the difference of precipitation and evaporation (inflow) from the convergence of vertically integrated water vapor fluxes. Furthermore, our results are compared with monthly mass grids from GRACE spherical harmonic solution data products. We conclude that the MRR means a robust tool to maximize the observational accuracy for GRACE, it considers the spatiotemporal resolution of the observations due to resolution-dependent highest levels, and it is applicable elsewhere globally to model hydrological or other phenomena of mass change.

[1]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[2]  C. K. Shum,et al.  Signals of extreme weather conditions in Central Europe in GRACE 4-D hydrological mass variations , 2008 .

[3]  Michael Schmidt,et al.  Ellipsoidal Wavelet Representation of the Gravity Field , 2008 .

[4]  A. Arguez.  Supplement to State of the Climate in 2006 , 2007 .

[5]  A. Arguez,et al.  State of the Climate in 2006 , 2007 .

[6]  Torsten Mayer-Gürr,et al.  Regional gravity modeling in terms of spherical base functions , 2006 .

[7]  D. Chambers.  Evaluation of new GRACE time‐variable gravity data over the ocean , 2006 .

[8]  Karsten Shein,et al.  State of the Climate in 2005 , 2006 .

[9]  C. Wagner,et al.  Degradation of Geopotential Recovery from Short Repeat-Cycle Orbits: Application to GRACE Monthly Fields , 2006 .

[10]  Christopher Jekeli,et al.  Precise estimation of in situ geopotential differences from GRACE low‐low satellite‐to‐satellite tracking and accelerometer data , 2006 .

[11]  Michael Schmidt.  Multi-resolution representation of the gravity field from satellite data based on wavelet expansions with time-dependent coefficients , 2006 .

[12]  C. K. Shum,et al.  Regional high‐resolution spatiotemporal gravity modeling from GRACE data using spherical wavelets , 2006 .

[13]  C. Shum,et al.  Improved estimation of terrestrial water storage changes from GRACE , 2005 .

[14]  Michael Schmidt,et al.  Wavelet modelling in support of IRI , 2005 .

[15]  U. Meyer,et al.  An Earth gravity field model complete to degree and order 150 from GRACE: EIGEN-GRACE02S , 2005 .

[16]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

[17]  A. Waple,et al.  State of the Climate in 2003 , 2004 .

[18]  M. Watkins,et al.  The gravity recovery and climate experiment: Mission overview and early results , 2004 .

[19]  D. Bromwich,et al.  Large‐scale hydro‐climatology of the terrestrial Arctic drainage system , 2002 .

[20]  D. Bromwich,et al.  The Atmospheric Hydrologic Cycle over the Arctic Basin from Reanalyses. Part I: Comparison with Observations and Previous Studies* , 2000 .

[21]  Philip Crotwell.  Constructive Approximation on the Sphere , 2000 .

[22]  F. Bryan,et al.  Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE , 1998 .

[23]  Willi Freeden,et al.  Constructive Approximation on the Sphere: With Applications to Geomathematics , 1998 .

[24]  D. Bromwich,et al.  Spatial and Temporal Variability of Antarctic Precipitation from Atmospheric Methods , 1998 .

[25]  David Salesin,et al.  Wavelets for computer graphics: a primer. 2 , 1995, IEEE Computer Graphics and Applications.

[26]  Taikan Oki,et al.  Global atmospheric water balance and runoff from large river basins , 1995 .

[27]  David Salesin,et al.  Wavelets for computer graphics: a primer.1 , 1995, IEEE Computer Graphics and Applications.

[28]  Karl-Rudolf Koch,et al.  Parameter estimation and hypothesis testing in linear models , 1988 .

[29]  W. Farrell.  Deformation of the Earth by surface loads , 1972 .