000			03271nam a22004695i 4500
001			u377686
003			SIRSI
005			20160812084515.0
007			cr nn 008mamaa
008			100427s2010 ne | s |||| 0|eng d
020			_a9789048137022 _9978-90-481-3702-2
040			_cMX-MeUAM
100	1		_aNavarra, Antonio. _eauthor.
245	1	2	_aA Guide to Empirical Orthogonal Functions for Climate Data Analysis _h[recurso electrónico] / _cby Antonio Navarra, Valeria Simoncini.
264		1	_aDordrecht : _bSpringer Netherlands, _c2010.
300			_aVI, 151 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aElements of Linear Algebra -- Basic Statistical Concepts -- Empirical Orthogonal Functions -- Generalizations: Rotated, Complex, Extended and Combined EOF -- Cross-Covariance and the Singular Value Decomposition -- The Canonical Correlation Analysis -- Multiple Linear Regression Methods.
520			_aClimatology and meteorology have basically been a descriptive science until it became possible to use numerical models, but it is crucial to the success of the strategy that the model must be a good representation of the real climate system of the Earth. Models are required to reproduce not only the mean properties of climate, but also its variability and the strong spatial relations between climate variability in geographically diverse regions. Quantitative techniques were developed to explore the climate variability and its relations between different geographical locations. Methods were borrowed from descriptive statistics, where they were developed to analyze variance of related observations-variable pairs, or to identify unknown relations between variables. A Guide to Empirical Orthogonal Functions for Climate Data Analysis uses a different approach, trying to introduce the reader to a practical application of the methods, including data sets from climate simulations and MATLAB codes for the algorithms. All pictures and examples used in the book may be reproduced by using the data sets and the routines available in the book . Though the main thrust of the book is for climatological examples, the treatment is sufficiently general that the discussion is also useful for students and practitioners in other fields.
650		0	_aGeography.
650		0	_aMathematical geography.
650		0	_aMeteorology.
650		0	_aComputer science.
650		0	_aClimatic changes.
650	1	4	_aEarth Sciences.
650	2	4	_aMeteorology/Climatology.
650	2	4	_aMathematical Applications in Earth Sciences.
650	2	4	_aComputational Science and Engineering.
650	2	4	_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
650	2	4	_aClimate Change.
700	1		_aSimoncini, Valeria. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9789048137015
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-90-481-3702-2
596			_a19
942			_cLIBRO_ELEC
999			_c205566 _d205566