Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation

被引:20
作者
Metref, Sammy [1 ]
Cosme, Emmanuel [1 ]
Le Sommer, Julien [1 ]
Poel, Nora [1 ,2 ]
Brankart, Jean-Michel [1 ]
Verron, Jacques [1 ,3 ]
Gomez Navarro, Laura [1 ,4 ]
机构
[1] Univ Grenoble Alpes, CNRS, IRD, IGE, F-38000 Grenoble, France
[2] Univ Potsdam, Inst Comp Sci, D-14469 Potsdam, Germany
[3] Ocean Next, F-38000 Grenoble, France
[4] UIB, CSIC, Mediterranean Inst Adv Studies, IMEDEA, Esporles 07190, Spain
关键词
SWOT; correlated errors; OSSE; projection; detrending; ensemble kalman filter; OCEAN; EFFICIENT; SEASONALITY; SYSTEM; WATER;
D O I
10.3390/rs11111336
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Surface Water and Ocean Topography (SWOT) mission is a next generation satellite mission expected to provide a 2 km-resolution observation of the sea surface height (SSH) on a two-dimensional swath. Processing SWOT data will be challenging because of the large amount of data, the mismatch between a high spatial resolution and a low temporal resolution, and the observation errors. The present paper focuses on the reduction of the spatially structured errors of SWOT SSH data. It investigates a new error reduction method and assesses its performance in an observing system simulation experiment. The proposed error-reduction method first projects the SWOT SSH onto a subspace spanned by the SWOT spatially structured errors. This projection is removed from the SWOT SSH to obtain a detrended SSH. The detrended SSH is then processed within an ensemble data assimilation analysis to retrieve a full SSH field. In the latter step, the detrending is applied to both the SWOT data and an ensemble of model-simulated SSH fields. Numerical experiments are performed with synthetic SWOT observations and an ensemble from a North Atlantic, 1/60 degrees simulation of the ocean circulation (NATL60). The data assimilation analysis is carried out with an ensemble Kalman filter. The results are assessed with root mean square errors, power spectrum density, and spatial coherence. They show that a significant part of the large scale SWOT errors is reduced. The filter analysis also reduces the small scale errors and allows for an accurate recovery of the energy of the signal down to 25 km scales. In addition, using the SWOT nadir data to adjust the SSH detrending further reduces the errors.
引用
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页数:21
相关论文
共 36 条
[1]   Up to What Extent Can We Characterize Ocean Eddies Using Present-Day Gridded Altimetric Products? [J].
Amores, Angel ;
Jorda, Gabriel ;
Arsouze, Thomas ;
Le Sommer, Julien .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2018, 123 (10) :7220-7236
[2]  
[Anonymous], 2012, OCEAN SCI, DOI DOI 10.5194/os-8-633-2012
[3]  
[Anonymous], 2003, ATMOSPHERIC MODELING
[4]  
Asch M., 2016, Data Assimilation
[5]  
Bennett A.F., 1992, INVERSE METHODS PHYS
[6]   Sequential data assimilation techniques in oceanography [J].
Bertino, L ;
Evensen, G ;
Wackernagel, H .
INTERNATIONAL STATISTICAL REVIEW, 2003, 71 (02) :223-241
[7]   Efficient Parameterization of the Observation Error Covariance Matrix for Square Root or Ensemble Kalman Filters: Application to Ocean Altimetry [J].
Brankart, Jean-Michel ;
Ubelmann, Clement ;
Testut, Charles-Emmanuel ;
Cosme, Emmanuel ;
Brasseur, Pierre ;
Verron, Jacques .
MONTHLY WEATHER REVIEW, 2009, 137 (06) :1908-1927
[8]   Seasonality of submesoscale flows in the ocean surface boundary layer [J].
Buckingham, Christian E. ;
Garabato, Alberto C. Naveira ;
Thompson, Andrew F. ;
Brannigan, Liam ;
Lazar, Ayah ;
Marshall, David P. ;
Nurser, A. J. George ;
Damerell, Gillian ;
Heywood, Karen J. ;
Belcher, Stephen E. .
GEOPHYSICAL RESEARCH LETTERS, 2016, 43 (05) :2118-2126
[9]   Data assimilation in the geosciences: An overview of methods, issues, and perspectives [J].
Carrassi, Alberto ;
Bocquet, Marc ;
Bertino, Laurent ;
Evensen, Geir .
WILEY INTERDISCIPLINARY REVIEWS-CLIMATE CHANGE, 2018, 9 (05)
[10]   Prospects for future satellite estimation of small-scale variability of ocean surface velocity and vorticity [J].
Chelton, Dudley B. ;
Schlax, Michael G. ;
Samelson, Roger M. ;
Farrar, J. Thomas ;
Molemaker, M. Jeroen ;
McWilliams, James C. ;
Gula, Jonathan .
PROGRESS IN OCEANOGRAPHY, 2019, 173 :256-350