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E-raamat: Particles in the Coastal Ocean: Theory and Applications

, , (Woods Hole Oceanographic Institution, Massachusetts), , , (Dartmouth College, New Hampshire)
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  • Ilmumisaeg: 22-Dec-2014
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781316055410
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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 22-Dec-2014
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781316055410
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This is the first book to summarize the state of the art in modeling and simulation of the transport, evolution, and fate of particles in the coastal ocean. It is an invaluable book for advanced students and researchers in oceanography, geophysics, marine and civil engineering, computational science, and environmental science.

The coastal ocean comprises the semi-enclosed seas on the continental shelf, including estuaries and extending to the shelf break. This region is the focus of many serious concerns, including coastal inundation by tides, storm surges, or sea level change; fisheries and aquaculture management; water quality; harmful algal blooms; planning of facilities (e.g., power stations); port development and maintenance; and oil spills. This book addresses modeling and simulation of the transport, evolution, and fate of particles (physical and biological) in the coastal ocean. It is the first to summarize the state of the art in this field and direct it toward diverse applications, for example in measuring and monitoring sediment motion, oil spills, and larval ecology. This is an invaluable textbook and reference work for advanced students and researchers in oceanography, geophysical fluid dynamics, marine and civil engineering, computational science, and environmental science.

Arvustused

'Particles in the Coastal Ocean deserves a place on the reference bookshelves of every oceanographer, and others such as advanced undergraduate and graduate students, fisheries and pollution researchers, coastal engineers, and fluid modeling simulation experts. This excellent book reveals the gap that existed previously, in both its subject and its quality.' J. J. P. Smith, CMOS Bulletin 'To analyse the particle motion, deterministic, numerical, statistical and full three-dimensional simulations are used. With such a wide scope, the authors have set themselves a challenging task. Nevertheless, the book is a success both in covering a massive amount of material and making it readable the book is an outstanding summary of the methodology, including applications and implications, of particle tracking in the coastal ocean. Considering the length and the number of figures the book is a bargain at £77 (hardback). In my view, it is required reading for anyone interested in coastal fluid dynamics.' Thomas J. Bridges, Contemporary Physics

Muu info

This book summarizes the modeling of the transport, evolution and fate of particles in the coastal ocean for advanced students and researchers.
About the Authors xv
Preface xix
Acknowledgments xxi
List of Acronyms xxiii
Definitions and Notation xxv
Introduction and Scope xxix
Part I Background
1 The Coastal Ocean
3(13)
1.1 Typical Motions and Scales
4(4)
1.2 Particle Simulation
8(8)
1.2.1 Motion
8(2)
1.2.2 Rates
10(2)
1.2.3 Gather, Scatter
12(1)
1.2.4 Simulation
13(1)
1.2.5 Aggregation and Identity
14(2)
2 Drifters and Their Numerical Simulation
16(22)
2.1 Introduction
16(4)
2.2 Drifter Technology
20(5)
2.2.1 Design
20(4)
2.2.2 Communication
24(1)
2.2.3 Quality Control
24(1)
2.3 Particle Tracking
25(4)
2.3.1 Basic Lagrangian Model
25(1)
2.3.2 Practical Issues
26(3)
2.4 Model Validation with Drifters
29(6)
2.4.1 Field Experience
31(4)
2.5 Drifter Applications
35(3)
2.5.1 Drifter Assimilation
37(1)
3 Probability and Statistics - A Primer
38(78)
3.1 Basics - Random Numbers
38(9)
3.1.1 Continuous Distributions: f and F
38(1)
3.1.2 Properties: Survival, Hazard Rate
39(2)
3.1.3 Properties: Mean, Variance, Moments
41(2)
3.1.4 Properties: Median, Mode, Quartile
43(1)
3.1.5 Properties: Other Means
44(1)
3.1.6 Bounding Theorems
44(1)
3.1.7 Discrete Distributions: Pi and Fj
45(2)
3.2 Some Common Distributions
47(17)
3.2.1 Continuous Distributions
47(11)
3.2.2 Discrete Distributions
58(5)
3.2.3 Importance of G, U, B, Pois
63(1)
3.2.4 The Central Limit Theorem
63(1)
3.3 Generating Random Numbers
64(6)
3.3.1 General Methods
64(3)
3.3.2 Some Specific Deviates
67(3)
3.4 Sampling; Finite N
70(12)
3.4.1 Sample Statistics
71(1)
3.4.2 Sample Mean
72(4)
3.4.3 Sample Variance
76(6)
3.4.4 Recap
82(1)
3.5 Covariance
82(17)
3.5.1 Definitions
83(3)
3.5.2 Correlation and Autocorrelation
86(1)
3.5.3 Autocorrelated Time Series
86(6)
3.5.3.1 Separation-Based Covariance and Correlogram
89(2)
3.5.3.2 Correlogram and Impulse Response
91(1)
3.5.4 Autocorrelated Eulerian Fields
92(3)
3.5.5 Generating Covariance
95(3)
3.5.6 Summary - Covariance
98(1)
3.6 Particles in a Box
99(15)
3.6.1 Individual Residence Time
100(1)
3.6.2 Aggregate Properties: Relaxation of Initial Condition
100(2)
3.6.3 Export Rate
102(1)
3.6.4 Long-Run Balance
103(1)
3.6.5 Summary - Steady State
104(1)
3.6.6 Exit Paths
105(2)
3.6.7 Input Paths
107(1)
3.6.8 Autocorrelation
107(1)
3.6.9 Example - Branch Point
108(1)
3.6.10 A Network of Boxes
108(5)
3.6.10.1 Transfer Rate
110(1)
3.6.10.2 Steady State
111(2)
3.6.11 Closing Ideas - Particles in Boxes
113(1)
3.7 Closure
114(1)
3.8 General Sources
115(1)
4 Dispersion by Random Walk
116(55)
4.1 Introduction: Discrete Drunken Walk
117(2)
4.2 Continuous Processes
119(2)
4.2.1 Resolved and Subgrid Motion
119(1)
4.2.2 A Hierarchy
120(1)
4.3 The ARO Model - Uncorrelated Random Walk and Simple Diffusion
121(12)
4.3.1 The Displacement Process
121(1)
4.3.2 Correspondence to Diffusion
122(2)
4.3.3 Multi-Dimensions
124(1)
4.3.4 Inhomogeneous Diffusion
125(1)
4.3.5 Anisotropic Diffusion
126(2)
4.3.6 Shear and Convergence
128(3)
4.3.7 Metrics of Resolution
131(1)
4.3.8 Stepsize and the Need for Autocorrelation
132(1)
4.4 The AR1 Model - Autocorrelated Velocity
133(11)
4.4.1 AR1: Continuous Form and Its Discretization
134(2)
4.4.2 AR1: Discrete Canonical Form
136(3)
4.4.3 AR1: Displacement
139(3)
4.4.4 Some Summary Observations about the AR1 Model
142(2)
4.5 The AR2 Model - Autocorrelated Acceleration
144(12)
4.5.1 Discrete Canonical Forms
144(4)
4.5.2 AR2 Velocity
148(5)
4.5.3 AR2 Displacement and Link to Diffusion
153(3)
4.6 The AR1-s Model - Spinning Walk
156(9)
4.6.1 AR1-s Complex Velocity
157(2)
4.6.2 AR1-s Displacement
159(2)
4.6.3 AR1-s Results
161(1)
4.6.4 Vorticity Sources
162(3)
4.7 Summary - Four Random Walk Models
165(4)
4.7.1 ARO Model
166(1)
4.7.2 AR1 Model
167(1)
4.7.3 AR2 Model
167(2)
4.7.4 AR1 -s Model
169(1)
4.8 Concluding Remarks - Random Motion
169(2)
5 Boundary Conditions, Boundary Layers, Sources
171(23)
5.1 Boundary Layers: Continuum and Discretization
171(2)
5.2 Discretized Boundaries
173(4)
5.2.1 Particle Motion and Change
173(1)
5.2.2 States and Transitions
174(1)
5.2.3 Boundary Types
175(1)
5.2.4 Basic Needs for Boundary Particles
176(1)
5.2.5 Boundary Sources
177(1)
5.3 The Law of the Wall
177(2)
5.4 A Repellant Boundary Layer
179(4)
5.4.1 Boundary Particles
179(1)
5.4.2 The Gaussian Case
180(1)
5.4.3 Pelagic Particles
181(1)
5.4.4 The Steady State
181(2)
5.5 Examples
183(8)
5.5.1 Oiling the Coast
183(3)
5.5.2 Bioaccumulation
186(2)
5.5.3 Wetland Harvesting
188(3)
5.6 Beyond the Boundary - Exogenous Sources
191(1)
5.7 Summary Comments
192(2)
6 Turbulence Closure
194(33)
6.1 Reynolds Stresses and the Gradient Flux Relation
194(3)
6.1.1 The Gradient Flux Relation
196(1)
6.2 Vertical Closure
197(7)
6.2.1 Early Models
197(2)
6.2.2 Turbulent Kinetic Energy
199(3)
6.2.3 Turbulent Length Scale
202(2)
6.3 Vertical Closure Examples
204(17)
6.3.1 Level 2.5 Formulation
204(4)
6.3.1.1 Governing Equations
205(1)
6.3.1.2 Vertical Boundary Conditions
206(2)
6.3.2 Level 2.0 Formulation
208(1)
6.3.3 The Point Model
209(2)
6.3.4 Steady-State Point Model, Level 2 Closure
211(9)
6.3.4.1 Wind Only
212(2)
6.3.4.2 Wind and Gravity
214(1)
6.3.4.3 Rotation and Wind - The Ekman Layer
215(5)
6.3.5 Some Implementations
220(1)
6.4 Horizontal Closure
221(2)
6.5 The Main Points
223(4)
Part II Elements
7 Meshes: Interpolation, Navigation, and Fields
227(44)
7.1 The Horizontal Mesh
227(14)
7.1.1 Triangles
227(1)
7.1.2 Geometry
227(1)
7.1.3 Triangle Basics
228(5)
7.1.4 Depth
233(2)
7.1.5 Spherical-Polar Coordinates
235(1)
7.1.6 Horizontal Interpolation
235(3)
7.1.6.1 Higher Order Interpolation
237(1)
7.1.7 Gradient
238(1)
7.1.8 Location and Navigation
239(2)
7.1.8.1 Global and Local Coordinates
239(1)
7.1.8.2 Is a Particle in an Element?
239(1)
7.1.8.3 Motion within an Element
239(1)
7.1.8.4 When Does a Particle Leave an Element?
240(1)
7.2 Vertical Discretization
241(4)
7.2.1 Separation of Variables
241(1)
7.2.2 Special Functions and Global z-Interpolation
242(1)
7.2.3 Piecewise Local z-Interpolation
242(2)
7.2.4 Vertical Interpolation
244(1)
7.3 3-D Location, Interpolation, Navigation
245(4)
7.3.1 Interpolation on a Single Element
246(1)
7.3.2 Is a Particle in an Element?
247(1)
7.3.3 Motion within an Element
247(1)
7.3.4 When Does a Particle Leave an Element?
248(1)
7.3.5 Summary: An Overlay of Horizontal Meshes
249(1)
7.4 Meshes
249(15)
7.4.1 The Union of Elements
249(1)
7.4.2 Essential Data Structures
250(3)
7.4.3 Example
253(1)
7.4.4 Subsidiary Data Structures
253(4)
7.4.5 The Galerkin Projection
257(2)
7.4.6 Mesh Generators
259(2)
7.4.7 Some Mesh Generation Packages
261(1)
7.4.8 Mesh Diagnostics
262(1)
7.4.9 Graphics
263(1)
7.5 Quadrilateral Elements
264(7)
7.5.1 Local Coordinates and Interpolation
265(2)
7.5.2 Jacobian
267(2)
7.5.3 Locating
269(2)
8 Particles and Fields
271(26)
8.1 Introduction
271(1)
8.2 Scattering among Elements
272(1)
8.3 Scattering within an Element
273(6)
8.3.1 Triangles
274(5)
8.3.1.1 Uniform Distribution on a Triangle
275(1)
8.3.1.2 Linear Distribution on a Triangle
276(1)
8.3.1.3 Examples
276(3)
8.3.2 Quadrilaterals
279(1)
8.4 Projections: The Density of a Set of Particles
279(18)
8.4.1 Simple Fixed Mesh Projections
281(3)
8.4.2 The Least Squares Projection
284(3)
8.4.3 Mass Conservation
287(1)
8.4.4 Example: Particles on a Mesh
287(1)
8.4.5 Convergence - The Small Δx Problem
288(2)
8.4.6 Kernel Methods
290(7)
Part III Applications
9 Noncohesive Sediment - Dense Particles
297(40)
9.1 Introduction
297(1)
9.2 Three States: P, M, B
298(2)
9.3 Sediment Particles
300(1)
9.4 Settling Velocity
301(2)
9.5 Bottom Boundary Layer
303(1)
9.6 Entrainment
303(6)
9.6.1 The Threshold of Motion - The Shields Parameter
304(1)
9.6.2 Entrainment Rate
305(2)
9.6.3 Initial Vertical Position - Entrainment Lift
307(2)
9.7 Vertical Motion: The Rouse Number and ze
309(1)
9.8 Profiles
310(3)
9.9 Flight Simulations
313(5)
9.10 Saltation
318(1)
9.11 Burial
319(3)
9.12 Theoretical Extensions
322(1)
9.13 A Simple Particle Model
322(1)
9.14 2-D
323(12)
9.14.1 Bed-Load - Suspended Load Transport
324(1)
9.14.2 Bed-Load Particle Velocity
325(1)
9.14.3 Suspended Load Particle Velocity
326(1)
9.14.4 Sediment Dispersion Coefficients
327(1)
9.14.5 A Generic Scheme
328(1)
9.14.6 Results
328(7)
9.15 Summary of Notation
335(2)
10 Oil - Chemically Active Particles
337(52)
10.1 Introduction
337(5)
10.1.1 Composition
338(1)
10.1.2 Motion
339(1)
10.1.3 Weathering
340(1)
10.1.4 Subsurface Releases
341(1)
10.2 Oil as Parcels
342(2)
10.2.1 Surface and Subsurface Parcels
343(1)
10.2.2 Generic Model Needs
344(1)
10.3 Surface Parcels
344(10)
10.3.1 Spreading
345(9)
10.4 Weathering Processes
354(12)
10.4.1 Evaporation
354(3)
10.4.2 Emulsification
357(1)
10.4.3 Density and Viscosity
358(1)
10.4.4 A Simple Weathering Model
359(4)
10.4.5 Entrainment
363(3)
10.5 Motion
366(4)
10.5.1 Stokes Drift and Surface Velocity
366(2)
10.5.2 Random Walk Models
368(1)
10.5.3 Droplet Rise Velocity
369(1)
10.5.4 Droplet Size Distribution
370(1)
10.6 Density and Crowding
370(3)
10.6.1 Mass Field
371(1)
10.6.2 Crowding
371(2)
10.7 Submerged Parcels
373(11)
10.7.1 Surface Source - Entrainment
374(1)
10.7.2 Shear Dispersion
375(4)
10.7.3 Subsurface Source - Blowout
379(2)
10.7.4 Dissolution
381(3)
10.8 Field Tests
384(4)
10.8.1 Surface Releases
384(1)
10.8.2 Subsurface Releases
384(1)
10.8.3 The Deepwater Horizon Incident
385(3)
10.9 Impact Assessment
388(1)
11 Individual-Based Models - Biotic Particles
389(66)
11.1 Introduction
389(1)
11.2 Diversity in the Cohort
389(2)
11.3 Individual-Based States
391(1)
11.3.1 Mixing and Aggregation
391(1)
11.3.2 Life Histories
391(1)
11.3.3 Eulerian and Lagrangian Quantities
392(1)
11.3.4 Continuous and Logical States; State Transitions
392(1)
11.4 Vital Rates
392(6)
11.4.1 Growth Rate Distribution - Analytic Example
393(1)
11.4.2 Growth Rate Distribution: Simulation
394(2)
11.4.3 Multiple Equilibria
396(1)
11.4.4 Rate Estimation
396(2)
11.5 Mortality
398(8)
11.5.1 Simulations: Individual-Based Mortality
399(2)
11.5.2 Individual Survivorship Probability: Geometric Distribution
401(2)
11.5.3 Lifetime Distribution
403(1)
11.5.4 Cohort Abundance: Binomial Distribution
404(1)
11.5.5 Cohort Death Rate
405(1)
11.5.6 Example: Growth, Mortality, Motion
406(1)
11.6 Stage Progression
406(12)
11.6.1 Example: Three Stages
408(3)
11.6.2 Stage Completion Rate, Residence Time - Constant α
411(1)
11.6.3 The General Case - Variable α
412(2)
11.6.4 Recap: Stage Completion
414(4)
11.7 Reproduction
418(2)
11.8 Motion - Advection + Random Walk
420(1)
11.9 Motion - Behavior
421(5)
11.9.1 Example Formulations
422(4)
11.10 Benthic Exchange
426(1)
11.11 Plankton IBMs
427(17)
11.11.1 Larval Fish
427(7)
11.11.1.1 Groundfish
428(3)
11.11.1.2 Shellfish
431(2)
11.11.1.3 Recent Summaries - Larval Fish
433(1)
11.11.2 Zooplankton
434(4)
11.11.3 Phytoplankton
438(5)
11.11.3.1 The Gulf of Maine
438(3)
11.11.3.2 Implementation
441(2)
11.11.4 Summary - Plankton IBMs
443(1)
11.12 Population Connectivity
444(3)
11.13 Summary - Individual-Based Modeling
447
Part IV Appendices
A Series, Sums, Limits
455(3)
B Complex Numbers
458(3)
C Wiener Integrals
461(2)
D Rates and Rate Limiters
463(5)
E Diffusion Solutions
468(2)
F Covariance Matrix for Shear and Convergence
470(2)
G Summary - ARn Recursions
472(2)
H Distribution Properties for Linear Triangles
474(5)
Bibliography 479(28)
Index 507
Daniel R. Lynch is MacLean Professor of Engineering at Dartmouth College and Adjunct Scientist at the Woods Hole Oceanographic Institution. He has published extensively on simulation methods in coastal oceanography. He co-founded the Gordon Research Conference in Coastal Ocean Modeling, was executive director of the Regional Association for Research on the Gulf of Maine, and served on the executive committee of the US GLOBEC Northwest Atlantic Program. He developed the Numerical Methods Laboratory at Dartmouth around the theme of interdisciplinary computational engineering and authored the textbook Numerical Solution of Partial Differential Equations for Environmental Scientists and Engineers (2005). He is co-editor of Professions and the Common Good (2006), a contributor to the Civil Engineering Body of Knowledge for the 21st Century (2008), and author of Sustainable Natural Resource Management for Scientists and Engineers (Cambridge University Press, 2009). David A. Greenberg is a research scientist at the Canadian Department of Fisheries and Oceans, Bedford Institute of Oceanography. His research includes model development and application for tidal circulation and resonance, sediment transport, intertidal flooding, sea level rise, tidal power, biological productivity, and aquaculture. Major shelf areas he covers include the Fundy-Maine region, the Newfoundland shelf, the Scotian shelf, and the Canadian Arctic Archipelago. Ata Bilgili is Associate Professor of Coastal and Ocean Engineering at Istanbul Technical University. His research includes the application of particle techniques to wind-dominated coastal systems, the optimization of particle-tracking methods on high-performance computing platforms, particle applications to sediment and water-quality problems, and simulation of intertidal inundation processes. His additional interests include unstructured mesh generation, environmental contingency planning for ports and harbors, and the advancement of maritime-engineering education. Dennis J. McGillicuddy, Jr is a senior scientist in the department of applied ocean physics and engineering at the Woods Hole Oceanographic Institution. His primary research interest is the interface between fluid dynamics and the biology of the sea. He is a recipient of the Office of Naval Research Young Investigator Award (1998), the American Society of Limnology and Oceanography's Lindeman Award (2000) and the University of Miami's Rosenstiel Award (2008). He is author or co-author of more than one hundred refereed publications. Dr McGillicuddy has been very active in the oversight of large interdisciplinary oceanographic programs on both national and international levels, having served on the scientific steering committees of the Joint Global Ocean Flux Study, the Global Ecosystem Dynamics Program, and the Global Ecology and Oceanography of Harmful Algal Blooms. He currently serves as deputy director of the Woods Hole Center for Oceans and Human Health. James P. Manning has been at National Oceanic and Atmospheric Administration's (NOAA) Northeast Fisheries Science Center for more than twenty-five years. He has been responsible for building and deploying low-cost observation systems throughout the Gulf of Maine and the southern New England shelf. His web-served data archive includes more than five million hourly values of moored bottom temperatures and more than a million kilometers of surface-drifter tracks and is used in data assimilation and validation for coastal models. These efforts have assisted in describing the physical oceanographic environments of critical offshore spawning grounds, helping biologists explain the variability in recruitment of larvae and its relationship to physical conditions. He conceived and coordinates the eMOLT program, a partnership with New England fishermen's associations to monitor the sea floor by instrumenting lobster traps. Alfredo L. Aretxabaleta is a physical oceanographer with Integrated Statistics, Inc., of Woods Hole, MA. He is working with the US Geological Survery (USGS) Science Center in Woods Hole on sediment transport problems in the coastal ocean, including cohesion and resuspension processes. He has worked on observation, data assimilation, and real-time forecasting relative to harmful algal blooms and groundfish recruitment in the western Atlantic, and he has worked with Institut de Ciencias del Mar (Barcelona) in the satellite sensing of ocean salinity. He is one of the authors of Project Earth Science: Physical Oceanography (2011).