Nonlinear and stochastic climate dynamics / edited by Christian L.E. Franzke, University of Hamburg, Germany, and Terence J. O'Kane, Marine and Atmospheric Research, CSIRO, Australia.

It is now widely recognized that the climate system is governed by nonlinear, multi-scale processes, whereby memory effects and stochastic forcing by fast processes, such as weather and convective systems, can induce regime behavior. Motivated by present difficulties in understanding the climate sys...

Full description

Saved in:
Bibliographic Details
Online Access: Full Text (via Cambridge)
Other Authors: Franzke, Christian L. E. (Editor), O'Kane, Terence J. (Editor)
Format: Electronic eBook
Language:English
Published: Cambridge, United Kingdom ; New York, NY, USA : Cambridge University Press, 2017.
Subjects:

MARC

LEADER 00000cam a2200000 i 4500
001 in00000056750
006 m o d
007 cr |||||||||||
008 170112s2017 enka ob 001 0 eng d
005 20230831180946.0
035 |a (OCoLC)ceba968212036 
037 |a ceba9781316339251 
040 |a N$T  |b eng  |e rda  |e pn  |c N$T  |d N$T  |d YDX  |d CSAIL  |d IDEBK  |d UAB  |d OCLCQ  |d CUV  |d VGM  |d OTZ  |d OCLCQ  |d CNCGM  |d TJC  |d U3W  |d OCLCQ  |d INT  |d OCLCQ  |d WYU  |d LVT  |d OCLCQ  |d OCLCA  |d UKAHL  |d OCLCQ  |d LUN  |d K6U  |d OCLCO  |d OCLCQ 
019 |a 1167176571 
020 |a 9781316884201  |q (electronic bk.) 
020 |a 1316884201  |q (electronic bk.) 
020 |a 9781316339251  |q (ebook) 
020 |a 1316339254 
020 |z 9781107118140 
020 |z 110711814X 
029 1 |a AU@  |b 000059703014 
029 1 |a AU@  |b 000062883594 
035 |a (OCoLC)968212036  |z (OCoLC)1167176571 
050 4 |a QC996.5  |b .N66 2017eb 
049 |a GWRE 
245 0 0 |a Nonlinear and stochastic climate dynamics /  |c edited by Christian L.E. Franzke, University of Hamburg, Germany, and Terence J. O'Kane, Marine and Atmospheric Research, CSIRO, Australia. 
264 1 |a Cambridge, United Kingdom ;  |a New York, NY, USA :  |b Cambridge University Press,  |c 2017. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Print version record. 
504 |a Includes bibliographical references and index. 
520 |a It is now widely recognized that the climate system is governed by nonlinear, multi-scale processes, whereby memory effects and stochastic forcing by fast processes, such as weather and convective systems, can induce regime behavior. Motivated by present difficulties in understanding the climate system and to aid the improvement of numerical weather and climate models, this book gathers contributions from mathematics, physics and climate science to highlight the latest developments and current research questions in nonlinear and stochastic climate dynamics. Leading researchers discuss some of the most challenging and exciting areas of research in the mathematical geosciences, such as the theory of tipping points and of extreme events including spatial extremes, climate networks, data assimilation and dynamical systems. This book provides graduate students and researchers with a broad overview of the physical climate system and introduces powerful data analysis and modeling methods for climate scientists and applied mathematicians. 
505 0 0 |g Machine generated contents note:  |g 1.  |t Challenges for Ice Age Dynamics: A Dynamical Systems Perspective /  |r Takahito Mitsui --  |g 2.  |t Tipping Points in the Climate System /  |r Peter Ditlevsen --  |g 3.  |t Atmospheric Teleconnection Patterns /  |r Christian L.E. Franzke --  |g 4.  |t Atmospheric Regimes: The Link between Weather and the Large-Scale Circulation /  |r Susanna Corti --  |g 5.  |t Low-Frequency Regime Transitions and Predictability of Regimes in a Barotropic Model /  |r Terence J. O'Kane --  |g 6.  |t Complex Network Techniques for Climatological Data Analysis /  |r Jonathan F. Donges --  |g 7.  |t On Inference and Validation of Causality Relations in Climate Teleconnections /  |r Didier P. Monselesan --  |g 8.  |t Stochastic Climate Theory /  |r Christian L.E. Franzke --  |g 9.  |t Stochastic Subgrid Modelling for Geophysical and Three-Dimensional Turbulence /  |r Meelis J. Zidikheri --  |g 10.  |t Model Error in Data Assimilation /  |r John Harlim --  |g 11.  |t Long-Term Memory in Climate: Detection, Extreme Events, and Significance of Trends /  |r Josef Ludescher --  |g 12.  |t Fractional Stochastic Models for Heavy Tailed, and Long-Range Dependent, Fluctuations in Physical Systems /  |r Nicholas W. Watkins --  |g 13.  |t Modelling Spatial Extremes Using Max-Stable Processes /  |r Mathieu Ribatet --  |g 14.  |t Extreme Value Analysis in Dynamical Systems: Two Case Studies /  |r Tamas Bodai. 
650 0 |a Statistical weather forecasting. 
650 0 |a Weather forecasting. 
650 0 |a Global warming. 
650 0 |a Climatic changes. 
650 0 |a Atmospheric circulation  |x Mathematical models. 
650 7 |a Atmospheric circulation  |x Mathematical models.  |2 fast  |0 (OCoLC)fst00820401 
650 7 |a Climatic changes.  |2 fast  |0 (OCoLC)fst00864229 
650 7 |a Global warming.  |2 fast  |0 (OCoLC)fst00943506 
650 7 |a Statistical weather forecasting.  |2 fast  |0 (OCoLC)fst01132095 
650 7 |a Weather forecasting.  |2 fast  |0 (OCoLC)fst01173142 
700 1 |a Franzke, Christian L. E.,  |e editor. 
700 1 |a O'Kane, Terence J.,  |e editor. 
776 0 8 |i Print version:  |t Nonlinear and stochastic climate dynamics.  |d Cambridge, United Kingdom ; New York, NY, USA : Cambridge University Press, 2017  |z 9781107118140  |w (DLC) 2016045370  |w (OCoLC)959922710 
856 4 0 |u https://colorado.idm.oclc.org/login?url=https://doi.org/10.1017/9781316339251  |z Full Text (via Cambridge) 
915 |a - 
956 |a Cambridge EBA 
956 |b Cambridge EBA ebooks Complete Collection 
998 |b New collection CUP.ebaebookscomplete 
994 |a 92  |b COD 
999 f f |s e915f7d3-39a0-427d-8821-eae08a4adc48  |i 514f211d-7513-443e-a39c-d76a79efe573 
952 f f |p Can circulate  |a University of Colorado Boulder  |b Online  |c Online  |d Online  |h Library of Congress classification  |i web