000 02513nam a22003498i 4500
001 CR9781316543818
003 UkCbUP
005 20200124160157.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 150728s2019||||enk o ||1 0|eng|d
020 _a9781316543818 (ebook)
020 _z9781107142886 (hardback)
020 _z9781316600245 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aQA403.5
_b.C76 2019
082 0 0 _a515/.24330155
_223
100 1 _aCrockett, R. G. M.
_q(Robin G. M.),
_eauthor.
245 1 2 _aA primer on Fourier analysis for the geosciences /
_cRobin Crockett.
264 1 _aCambridge :
_bCambridge University Press,
_c2019.
300 _a1 online resource (xiv, 176 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aTitle from publisher's bibliographic system (viewed on 04 Feb 2019).
505 0 _aWhat is Fourier analysis? -- Covariance-based approaches -- Fourier series -- Fourier transforms -- Using the FFT to identify periodic features in time-series -- Constraints on the FFT -- Stationarity and spectrograms -- Noise in time-series -- Periodograms and significance.
520 _aTime-series analysis is used to identify and quantify periodic features in datasets and has many applications across the geosciences, from analysing weather data, to solid-Earth geophysical modelling. This intuitive introduction provides a practical 'how-to' guide to basic Fourier theory, with a particular focus on Earth system applications. The book starts with a discussion of statistical correlation, before introducing Fourier series and building to the fast Fourier transform (FFT) and related periodogram techniques. The theory is illustrated with numerous worked examples using R datasets, from Milankovitch orbital-forcing cycles to tidal harmonics and exoplanet orbital periods. These examples highlight the key concepts and encourage readers to investigate more advanced time-series techniques. The book concludes with a consideration of statistical effect size and significance. This useful book is ideal for graduate students and researchers in the Earth system sciences who are looking for an accessible introduction to time-series analysis.
650 0 _aFourier analysis.
650 0 _aEarth sciences
_xMathematics.
776 0 8 _iPrint version:
_z9781107142886
856 4 0 _uhttps://doi.org/10.1017/9781316543818
999 _c514506
_d514504