000			02945nam a22004575i 4500
001			978-3-642-35088-7
003			DE-He213
005			20140220082859.0
007			cr nn 008mamaa
008			130522s2013 gw | s |||| 0|eng d
020			_a9783642350887 _9978-3-642-35088-7
024	7		_a10.1007/978-3-642-35088-7 _2doi
050		4	_aQC851-999
072		7	_aRB _2bicssc
072		7	_aSCI042000 _2bisacsh
082	0	4	_a551.5 _223
100	1		_aPark, Seon Ki. _eeditor.
245	1	0	_aData Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II) _h[electronic resource] / _cedited by Seon Ki Park, Liang Xu.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013.
300			_aXIX, 730 p. 269 illus., 170 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aA Review on the Theory and Methodologies of Estimation for Dynamical Systems -- Nudging Methods: A Critical Overview -- Markov Chain Monte Carlo Methods: Theory and Applications -- Information Content in Data Assimilation -- A Question of Adequacy of Observations in Variational Data Assimilation -- Quantifying Observation Impact for a Limited Area Atmospheric Forecast Model -- Skewness of the Prior through Position Errors and Its Impact on Data Assimilation -- Background Error Correlation Modeling with Diffusion Operator -- The Adjoint Sensitivity Guidance to Diagnosis and Tuning of Error Covariance Parameters -- Treating Nonlinearities in Data-Space Variational Assimilation -- Linearized Physics for Data Assimilation at ECMWF -- Recent Applications in Representer-Based Variational Data Assimilation. .
520			_aThis book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
650		0	_aGeography.
650		0	_aArtificial intelligence.
650		0	_aK-theory.
650	1	4	_aEarth Sciences.
650	2	4	_aAtmospheric Sciences.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aK-Theory.
700	1		_aXu, Liang. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642350870
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-35088-7
912			_aZDB-2-EES
999			_c97602 _d97602