This book gathers notes from lectures given during a three-week summer school on the fundamentals and the most recent developments of geophysical data assimilation.
This book gathers notes from lectures given during a three-week summer school on the fundamentals and the most recent developments of geophysical data assimilation.
Éric Blayo is a Professor in applied mathematics at the University of Grenoble. He is leading a research team working on the development of mathematical and numerical methods for environmental applications.; Marc Bocquet is a Professor and Senior Researcher at the environment research centre (CEREA), a joint laboratory of École des Ponts ParisTech and EDF R&D. He is working in the field of data assimilation in geosciences.; Emmanuel Cosme obtained his PhD in Earth Sciences at the University of Grenoble in 2002. Thereafter, he worked during 2 years on data assimilation for air quality in Canada, and moved back to Grenoble as an Associate Professor, to specialise in ocean data assimilation.; Leticia F. Cugliandolo: Laboratoire de Physique Theorique et Hautes Energies Universite Pierre et Marie Curie - Paris 6, Paris, France.
Inhaltsangabe
* PART I - KEY LECTURES * 1: Olivier Talagrand: 4D-VAR: four dimensional variational assimilation * 2: Andrew Lorenc: Four-dimensional variational data assimilation * 3: Chris Snyder: Introduction to the Kalman filter * 4: Emmanuel Cosme: Smoothers * 5: Carla Cardinali: Observation influence diagnostic of a data assimilation system * 6: Carla Cardinali: Observation impact on the short range forecast * PART II - SPECIALIZED LECTURES * 7: Loïk Berre: Background error covariances: estimation and specification * 8: Gérald Desroziers: Observation error specifications * 9: Olivier Talagrand: Errors. A posteriori diagnostics * 10: Peter Houtekamer: Error dynamics in ensemble Kalman filter systems: Localization * 11: Peter Houtekamer: Short-range error statistics in an ensemble Kalman filter * 12: Peter Houtekamer: Error dynamics in ensemble Kalman filter systems: System error * 13: Peter Jan Van Leeuwen: Particle filters for the geosciences * 14: Francois-Xavier Le Dimet, Igor Gejadze, and Victor Shutyaev: Second order methods for error propagation in variational data assimilation * 15: Laurent Hascoët: Adjoints by automatic differentiation * 16: Arthur Vidard: Assimilation of images * 17: Laurent Debreu, Emilie Neveu, Ehouarn Simon, and Francois-Xavier Le Dimet: Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation * 18: Marc Bocquet, Lin Wu, Frédéric Chevallier, and Mohammad Reza Koohkan: Selected topics in multiscale data assimilation * 19: Florence Rabier and Mike Fisher: Data assimilation in meteorology * 20: Marc Bocquet: An introduction to inverse modelling and parameter estimation for atmospheric and oceanic sciences * 21: Frédéric Chevallier: Greenhouse gas fluxes inversion * 22: Hendrik Elbern, Elmar Friese, Lars Nieradzik, and Jörg Schwinger: Data assimilation in atmospheric chemistry and air quality * 23: Ichiro Fukumori: Combining models and data in large-scale oceanography: examples from the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) * 24: Javier Zavala-Garay, John Wilkin, and Julia Levin: Data assimilation in coastal oceanography: IS4DVAR in the Regional Ocean Modeling System (ROMS) * 25: Bertrand Bonan, Maëlle Nodet, Olivier Ozenda, and Catherine Ritz: Data assimilation in glaciology
* PART I - KEY LECTURES * 1: Olivier Talagrand: 4D-VAR: four dimensional variational assimilation * 2: Andrew Lorenc: Four-dimensional variational data assimilation * 3: Chris Snyder: Introduction to the Kalman filter * 4: Emmanuel Cosme: Smoothers * 5: Carla Cardinali: Observation influence diagnostic of a data assimilation system * 6: Carla Cardinali: Observation impact on the short range forecast * PART II - SPECIALIZED LECTURES * 7: Loïk Berre: Background error covariances: estimation and specification * 8: Gérald Desroziers: Observation error specifications * 9: Olivier Talagrand: Errors. A posteriori diagnostics * 10: Peter Houtekamer: Error dynamics in ensemble Kalman filter systems: Localization * 11: Peter Houtekamer: Short-range error statistics in an ensemble Kalman filter * 12: Peter Houtekamer: Error dynamics in ensemble Kalman filter systems: System error * 13: Peter Jan Van Leeuwen: Particle filters for the geosciences * 14: Francois-Xavier Le Dimet, Igor Gejadze, and Victor Shutyaev: Second order methods for error propagation in variational data assimilation * 15: Laurent Hascoët: Adjoints by automatic differentiation * 16: Arthur Vidard: Assimilation of images * 17: Laurent Debreu, Emilie Neveu, Ehouarn Simon, and Francois-Xavier Le Dimet: Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation * 18: Marc Bocquet, Lin Wu, Frédéric Chevallier, and Mohammad Reza Koohkan: Selected topics in multiscale data assimilation * 19: Florence Rabier and Mike Fisher: Data assimilation in meteorology * 20: Marc Bocquet: An introduction to inverse modelling and parameter estimation for atmospheric and oceanic sciences * 21: Frédéric Chevallier: Greenhouse gas fluxes inversion * 22: Hendrik Elbern, Elmar Friese, Lars Nieradzik, and Jörg Schwinger: Data assimilation in atmospheric chemistry and air quality * 23: Ichiro Fukumori: Combining models and data in large-scale oceanography: examples from the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) * 24: Javier Zavala-Garay, John Wilkin, and Julia Levin: Data assimilation in coastal oceanography: IS4DVAR in the Regional Ocean Modeling System (ROMS) * 25: Bertrand Bonan, Maëlle Nodet, Olivier Ozenda, and Catherine Ritz: Data assimilation in glaciology
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