Assimilation of GRACE-derived oceanic mass distributions with a global ocean circulation model

To study the sub-seasonal distribution and generation of ocean mass anomalies, Gravity Recovery and Climate Experiment (GRACE) observations of daily and monthly resolution are assimilated into a global ocean circulation model with an ensemble-based Kalman-Filter technique. The satellite gravimetry observations are processed to become time-variable fields of ocean mass distribution. Error budgets for the observations and the ocean model’s initial state are estimated which contain the full covariance information. The consistency of the presented approach is demonstrated by increased agreement between GRACE observations and the ocean model. Furthermore, the simulations are compared with independent observations from 54 bottom pressure recorders. The assimilation improves the agreement to high-latitude recorders by up to 2 hPa. The improvements are caused by assimilation-induced changes in the atmospheric wind forcing, i.e., quantities not directly observed by GRACE. Finally, the use of the developed Kalman-Filter approach as a destriping filter to remove artificial noise contaminating the GRACE observations is presented.

[1]  O. Francis,et al.  Modelling the global ocean tides: modern insights from FES2004 , 2006 .

[2]  S. Swenson,et al.  Post‐processing removal of correlated errors in GRACE data , 2006 .

[3]  J. Kusche,et al.  Significance of secular trends of mass variations determined from GRACE solutions , 2009 .

[4]  Jens Schröter,et al.  The Global Ocean Mass Budget in 1993-2003 Estimated from Sea Level Change , 2007 .

[5]  S. Bettadpur,et al.  Ensemble prediction and intercomparison analysis of GRACE time‐variable gravity field models , 2014 .

[6]  Lars Nerger,et al.  Software for ensemble-based data assimilation systems - Implementation strategies and scalability , 2013, Comput. Geosci..

[7]  M. Wenzel,et al.  Assimilation of Earth rotation parameters into a global ocean model: length of day excitation , 2011 .

[8]  Robert Dill,et al.  Hydrological model LSDM for operational Earth rotation and gravity field variations , 2008 .

[9]  Uncertainty in ocean mass trends from GRACE , 2010 .

[10]  Don P. Chambers,et al.  Evaluation of Release-05 GRACE time-variable gravity coefficients over the ocean , 2012 .

[11]  Jens Schröter,et al.  Data Assimilation with the Ensemble Kalman Filter and the SEIK Filter applied to a Finite Element Model of the North Atlantic , 2004 .

[12]  Jan Saynisch,et al.  Ensemble Kalman filtering of Earth rotation observations with a global ocean model , 2012 .

[13]  D. Pham.  Stochastic Methods for Sequential Data Assimilation in Strongly Nonlinear Systems , 2001 .

[14]  D. Stammer,et al.  Relation between sea level and bottom pressure and the vertical dependence of oceanic variability , 2007 .

[15]  H. Storch,et al.  Statistical Analysis in Climate Research , 2000 .

[16]  R. Greatbatch.  A note on the representation of steric sea level in models that conserve volume rather than mass , 1994 .

[17]  Dinh Tuan Pham,et al.  Filtres de Kaiman singuliers volutifs pour l'assimilation de donnes en ocanographie , 1998 .

[18]  J. Kusche.  Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models , 2007 .

[19]  Assimilation of Earth rotation parameters into a global ocean model: excitation of polar motion , 2011 .

[20]  Jürgen Kusche,et al.  Evaluation of GRACE filter tools from a hydrological perspective , 2009 .

[21]  I. Sasgen,et al.  Combined GRACE and InSAR estimate of West Antarctic ice mass loss , 2010 .

[22]  A. Cazenave,et al.  Time-variable gravity from space and present-day mass redistribution in theEarth system , 2010 .

[23]  D. Stammer,et al.  Impact of assimilating bottom pressure anomalies from GRACE on ocean circulation estimates , 2012 .

[24]  M. Rothacher,et al.  System Earth via Geodetic-Geophysical Space Techniques , 2010 .

[25]  Torsten Mayer-Gürr,et al.  Improved daily GRACE gravity field solutions using a Kalman smoother , 2012 .

[26]  Jürgen Sündermann,et al.  Consideration of ocean tides in an OGCM and impacts on subseasonal to decadal polar motion excitation , 2001 .

[27]  Rory J. Bingham,et al.  The relationship between sea‐level and bottom pressure variability in an eddy permitting ocean model , 2008 .

[28]  J. Willis,et al.  Assessing the globally averaged sea level budget on seasonal to interannual timescales , 2008 .

[29]  A high resolution satellite‐only GRACE‐based mean dynamic topography of the South Atlantic Ocean , 2007 .

[30]  Olaf Boebel,et al.  Validation of GRACE Gravity Fields by In-Situ Data of Ocean Bottom Pressure , 2010 .

[31]  Patrick Heimbach,et al.  A Comparison of Atmospheric Reanalysis Surface Products over the Ocean and Implications for Uncertainties in Air–Sea Boundary Forcing , 2013 .

[32]  R. Ponte,et al.  Estimating high frequency ocean bottom pressure variability , 2011 .

[33]  E. Schrama,et al.  Revisiting Greenland ice sheet mass loss observed by GRACE , 2011 .

[34]  D. Chambers,et al.  Evaluation of high‐frequency oceanographic signal in GRACE data: Implications for de‐aliasing , 2011 .

[35]  Maik Thomas,et al.  Simulation and observation of global ocean mass anomalies , 2007 .

[36]  Paul Berrisford,et al.  Towards a climate data assimilation system: status update of ERA-interim , 2008 .

[37]  M. Hecht,et al.  The oxidation‐reduction potential of aqueous soil solutions at the Mars Phoenix landing site , 2011 .

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

[39]  H. Dobslaw,et al.  Short‐term transport variability of the Antarctic Circumpolar Current from satellite gravity observations , 2012 .

[40]  R. Ponte,et al.  High frequency barotropic ocean variability observed by GRACE and satellite altimetry , 2012 .

[41]  Kevin E. Trenberth,et al.  Atmospheric Moisture Transports from Ocean to Land and Global Energy Flows in Reanalyses , 2011 .

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

[43]  R. Ponte,et al.  Estimating weights for the use of time-dependent gravity recovery and climate experiment data in constraining ocean models , 2008 .