IMPROVING THE PARAMETERIZATION OF ERRORS STATISTICS FOR DATA ASSIMILATION IN A HYCOM BAY OF BISCAY REGIONAL CONFIGURATION P. BRASSEUR, G. BROQUET, J.M. BRANKART, F. CASTRUCCIO, C. LAUVERNET

First Page		Document Content
Date: 2009-05-23 19:00:12 Systems theory Estimation theory Bayesian statistics Linear filters Robot control Data assimilation Kalman filter Normal distribution Vehicle Identification Number Statistics Control theory Cybernetics		IMPROVING THE PARAMETERIZATION OF ERRORS STATISTICS FOR DATA ASSIMILATION IN A HYCOM BAY OF BISCAY REGIONAL CONFIGURATION P. BRASSEUR, G. BROQUET, J.M. BRANKART, F. CASTRUCCIO, C. LAUVERNET Add to Reading List Source URL: hycom.org Download Document from Source Website File Size: 3,36 MB Share Document on Facebook

	Constraining regional-scale CO2 fluxes using a coupled meteorological–carbon ensemble Kalman filter Hans W. Chen, Fuqing Zhang, Thomas Lauvaux, Richard B. Alley, and Kenneth J. Davis DocID: 1vaGB - View Document
	Tina Memo NoInternal. Tutorial: The Likelihood Interpretation of the Kalman Filter. N.A.Thacker, A.J.Lacey. DocID: 1v1Tg - View Document
	High-rank Ensemble Transform Kalman Filter (HETKF) Bo Huang and Xuguang Wang Multi-scale data Assimilation and Predictability (MAP) Laboratory School of Meteorology, University of Oklahoma, Norman, OK DocID: 1uOhU - View Document
	A Stabilized Dual Kalman Filter for Adaptive Tracking of Brain-Computer Interface Decoding Parameters DocID: 1uL66 - View Document
	Progress toward estimating surface carbon dioxide fluxes at the regional scale using an augmented Ensemble Kalman Filter 1,2 Hans W. Chen DocID: 1uJvA - View Document