LEADER 04516nam 22006495 450 001 9910349319603321 005 20250609111754.0 010 $a3-030-22247-0 024 7 $a10.1007/978-3-030-22247-5 035 $a(CKB)4100000009374654 035 $a(DE-He213)978-3-030-22247-5 035 $a(MiAaPQ)EBC5904627 035 $a(PPN)242823483 035 $a(MiAaPQ)EBC5918166 035 $a(EXLCZ)994100000009374654 100 $a20190924d2019 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aTropical Intraseasonal Variability and the Stochastic Skeleton Method /$fby Andrew J. Majda, Samuel N. Stechmann, Shengqian Chen, H. Reed Ogrosky, Sulian Thual 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (IX, 123 p. 46 illus., 33 illus. in color.) 225 1 $aSpringerBriefs in Mathematics of Planet Earth, Weather, Climate, Oceans,$x2509-7326 311 0 $a3-030-22246-2 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- The deterministic skeleton model and observed features of the MJO -- A Stochastic Skeleton Model for the MJO -- Tropical?extratropical Interactions and the MJO Skeleton Model -- New indices for observations of tropical variability based on the skeleton model and a model for the Walker circulation -- Refined Vertical Structure in the Stochastic Skeleton Model for the MJO -- Current and Future Research Perspectives. 330 $aIn this text, modern applied mathematics and physical insight are used to construct the simplest and first nonlinear dynamical model for the Madden-Julian oscillation (MJO), i.e. the stochastic skeleton model. This model captures the fundamental features of the MJO and offers a theoretical prediction of its structure, leading to new detailed methods to identify it in observational data. The text contributes to understanding and predicting intraseasonal variability, which remains a challenging task in contemporary climate, atmospheric, and oceanic science. In the tropics, the Madden-Julian oscillation (MJO) is the dominant component of intraseasonal variability. One of the strengths of this text is demonstrating how a blend of modern applied mathematical tools, including linear and nonlinear partial differential equations (PDEs), simple stochastic modeling, and numerical algorithms, have been used in conjunction with physical insight to create the model. These tools are also applied in developing several extensions of the model in order to capture additional features of the MJO, including its refined vertical structure and its interactions with the extratropics. This book is of interest to graduate students, postdocs, and senior researchers in pure and applied mathematics, physics, engineering, and climate, atmospheric, and oceanic science interested in turbulent dynamical systems as well as other complex systems. 410 0$aSpringerBriefs in Mathematics of Planet Earth, Weather, Climate, Oceans,$x2509-7326 606 $aMathematics 606 $aProbabilities 606 $aClimatology 606 $aMathematics of Planet Earth$3https://scigraph.springernature.com/ontologies/product-market-codes/M36000 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 606 $aClimate, general$3https://scigraph.springernature.com/ontologies/product-market-codes/300000 615 0$aMathematics. 615 0$aProbabilities. 615 0$aClimatology. 615 14$aMathematics of Planet Earth. 615 24$aProbability Theory and Stochastic Processes. 615 24$aClimate, general. 676 $a519 676 $a519 700 $aMajda$b Andrew J$4aut$4http://id.loc.gov/vocabulary/relators/aut$0477021 702 $aStechmann$b Samuel N$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aChen$b Shengqian$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aOgrosky$b H. Reed$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aThual$b Sulian$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349319603321 996 $aTropical Intraseasonal Variability and the Stochastic Skeleton Method$92499077 997 $aUNINA