Computational Challenges in the Geosciences [electronic resource] / edited by Clint Dawson, Margot Gerritsen.

Contributor(s): Dawson, Clint [editor.] | Gerritsen, Margot [editor.] | SpringerLink (Online service)
Material type: TextTextSeries: The IMA Volumes in Mathematics and its Applications: 156Publisher: New York, NY : Springer New York : Imprint: Springer, 2013Description: IX, 167 p. 57 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781461474340Subject(s): Mathematics | Meteorology | Geophysics | Mathematical physics | Mathematics | Mathematical Applications in the Physical Sciences | Meteorology | Geophysics/GeodesyAdditional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: QC19.2-20.85Online resources: Click here to access online
Contents:
Physical and Computational Issues in the Numerical Modeling of Ocean Circulation, R.L. Higdon -- Modeling Hazardous, Free-Surface Geophysical Flows with Depth-Averaged Hyperbolic Systems and Adaptive Numerical Methods, D.L. George -- Real-Time Forecasting and Visualization of Hurricane Waves and Storm Surge using SWAN+ADCIRC and FigureGen, J.C. Dietrich, C.N. Dawson, J.M. Proft, M.T. Howard, G. Wells, J.G. Fleming, R.A. Luettich, Jr., J.J. Westerink, Z. Cobell, M. Vitse, H. Lander, B.O. Blanton, C.M. Szpilka, J.H. Atkinson -- Methane in Surbsurface: Mathematical  Modeling and Computational Challenges, M. Peszynska -- Fast Algorithms for Bayesian Inversion, S. Ambikasaran, A. K. Saibaba, E.F. Darve and P.K. Kitanidis -- Modeling Spatial and Structural Uncertainty in the Subsurface , M. Gerritsen and J. Caers.
In: Springer eBooksSummary: Computational Challenges in the Geosciences addresses a cross-section of grand challenge problems arising in geoscience applications, including groundwater and petroleum reservoir simulation, hurricane storm surge, oceanography, volcanic eruptions and landslides, and tsunamis.  Each of these applications gives rise to complex physical and mathematical models spanning multiple space-time scales, which can only be studied through computer simulation.  The data required by the models is often highly uncertain, and the numerical solution of the models requires sophisticated algorithms which are mathematically accurate, computationally efficient and yet must preserve basic physical properties of the models.  This volume summarizes current methodologies and future research challenges in this broad and important field. .
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Physical and Computational Issues in the Numerical Modeling of Ocean Circulation, R.L. Higdon -- Modeling Hazardous, Free-Surface Geophysical Flows with Depth-Averaged Hyperbolic Systems and Adaptive Numerical Methods, D.L. George -- Real-Time Forecasting and Visualization of Hurricane Waves and Storm Surge using SWAN+ADCIRC and FigureGen, J.C. Dietrich, C.N. Dawson, J.M. Proft, M.T. Howard, G. Wells, J.G. Fleming, R.A. Luettich, Jr., J.J. Westerink, Z. Cobell, M. Vitse, H. Lander, B.O. Blanton, C.M. Szpilka, J.H. Atkinson -- Methane in Surbsurface: Mathematical  Modeling and Computational Challenges, M. Peszynska -- Fast Algorithms for Bayesian Inversion, S. Ambikasaran, A. K. Saibaba, E.F. Darve and P.K. Kitanidis -- Modeling Spatial and Structural Uncertainty in the Subsurface , M. Gerritsen and J. Caers.

Computational Challenges in the Geosciences addresses a cross-section of grand challenge problems arising in geoscience applications, including groundwater and petroleum reservoir simulation, hurricane storm surge, oceanography, volcanic eruptions and landslides, and tsunamis.  Each of these applications gives rise to complex physical and mathematical models spanning multiple space-time scales, which can only be studied through computer simulation.  The data required by the models is often highly uncertain, and the numerical solution of the models requires sophisticated algorithms which are mathematically accurate, computationally efficient and yet must preserve basic physical properties of the models.  This volume summarizes current methodologies and future research challenges in this broad and important field. .

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