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  • Cambridge :Cambridge University Press,  (1)
  • 1
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    Keywords: Ocean currents - Mathematical models. ; Electronic books.
    Description / Table of Contents: Written by international experts in their field, this book is a review of Lagrangian observation, analysis and assimilation methods in physical and biological oceanography. It will be of great interest to researchers and graduate students looking for information on transport and dispersion in physical systems, biological modeling, and data assimilation.
    Type of Medium: Online Resource
    Pages: 1 online resource (525 pages)
    Edition: 1st ed.
    ISBN: 9780511273353
    DDC: 551.4620151
    Language: English
    Note: Cover -- Half-title -- Title -- Copyright -- Contents -- Contributors -- Preface -- 1 Evolution of Lagrangian methods in oceanography -- 1.1 Introduction -- 1.2 History of floats -- 1.2.1 The SOFAR float -- 1.2.2 The mini-MODE float -- 1.2.3 The POLYMODE float -- 1.2.4 The autonomous listening station (ALS) -- 1.2.5 The RAFOS float -- 1.2.6 The ALACE float -- 1.2.7 The ALFOS and MARVOR floats -- 1.2.8 Isopycnal operation -- 1.2.9 The compressee -- 1.2.10 The COOL float -- 1.2.11 Bottom-following floats -- 1.2.12 Convecting floats -- 1.3 Acoustic navigation -- 1.4 Float-based in-situ observations -- 1.4.1 Vertical velocity -- 1.4.2 Relative motion -- 1.4.3 Vertical movements in fronts -- 1.4.4 Static stability or f/h -- 1.4.5 Estimating salinity -- 1.4.6 Oxygen -- 1.4.7 The barotropic component -- 1.5 Some lessons learned -- 1.6 Future trends -- Acknowledgments -- References -- 2 Measuring surface currents with Surface Velocity Program drifters: the instrument, its data, and some recent results -- 2.1 Introduction -- 2.2 The SVP drifter -- 2.2.1 Design -- 2.2.2 Deployment -- 2.2.3 Data transmission -- 2.2.4 Drifter lifetime -- 2.3 Drifter dataquality control, interpolation and coverage -- 2.3.1 Quality control -- 2.3.2 Interpolation -- 2.3.3 Data coverage -- 2.4 Velocity observations -- 2.4.1 Slip, with and without a drogue -- 2.4.2 Ekman drift -- 2.5 Other observations -- Sea surface temperature (SST) -- Barometric pressure -- Wind -- Ocean color -- Salinity -- Subsurface temperature -- 2.6 Recent drifter-based studies: an overview -- 2.7 The future -- Acknowledgments -- References -- 3 Favorite trajectories -- 3.1 Mesoscale eddies in the Red Sea outflow region -- References -- 3.2 Conservation of potential vorticity in the Gulf Stream-Deep Western Boundary Current crossover region -- References. , 3.3 Are there closed surface pathways in the tropical Atlantic? -- 3.4 Near-surface dispersion of particles in the South China Sea -- References -- 3.5 The Naval Postgraduate School RAFOS Study -- References -- 3.6 Favorite drifter trajectories deployed from the western shelf of Florida and the coastal waters of the Florida Keys -- Acknowledgments -- References -- 3.7 On the Intermediate Circulation in the Iceland Basin -- References -- 3.8 Where is the diffusivity? -- References -- 3.9 Opposing trajectories in the Mediterranean! -- 3.10 Tracking the sub-polar gyre -- References -- 4 Particle motion in a sea of eddies -- Abstract -- 4.1 Introduction -- 4.2 The two-component view of mesoscale turbulence -- 4.3 Equations of motion -- 4.4 Mesoscale vortices as transport barriers -- 4.5 Estimate of Lagrangian statistics -- 4.6 Velocity statistics -- 4.7 Particle dispersion -- 4.8 Parameterization of particle dispersion -- 4.9 Mesoscale vortices and the marine ecosystem -- 4.10 Perspectives -- Acknowledgments -- References -- 5 Inertial particle dynamics on the rotating Earth -- 5.1 Introduction -- 5.2 The nondimensional equations of Inertial dynamics on a sphere -- 5.3 Hamiltonian form of the Inertial dynamics on a sphere: westward drift -- 5.4 Hamiltonian formulation on the β-plane and the zonal drift there -- 5. Concluding remarks -- Acknowledgments -- References -- 6 Predictability of Lagrangian motion in the upper ocean -- 6.1 Introduction -- 6.2 Problem statement -- 6.3 Multi-particle LSM -- 6.4 Prediction algorithms -- 6.4.1 Kalman filter -- 6.4.2 Regression -- 6.5 Monte Carlo experiments with LSM -- 6.5.1 EKF -- 6.5.2 Comparison of RA with EKF using LSM -- 6.6 Ocean circulation model simulations and in-situ data -- 6.6.1 Simulations with Miami isopycnic coordinate ocean model. , 6.6.2 In-situ drifter data: applications to Adriatic Sea and Pacific Ocean clusters -- Adriatic Sea clusters -- Pacific Ocean clusters -- 6.6.3 Comparison of EKF and RA using Pacific Ocean clusters -- 6.7 Optimal sampling -- 6.8 Summary and discussion -- Acknowledgments -- References -- 7 Lagrangian data assimilation in ocean general circulation models -- 7.1 Introduction -- 7.2 General formulation for Lagrangian data assimilation -- 7.3 Methodology -- 7.3.1 Correction of Eulerian velocity field from float position data -- 7.3.2 Dynamical compatibility between corrected velocity and layer thickness -- 7.3.3 Vertical projection of corrections in multi-layer models -- 7.3.4 Twin experiment approach and error analysis -- 7.4 Results -- 7.4.1 Impact of velocity field correction in single-layer QG -- 7.4.2 Sensitivity experiments -- 7.4.3 Impact of layer thickness correction in single-layer MICOM -- 7.4.4 Comparison with pseudo-Lagrangian assimilation methods -- 7.4.5 Impact of vertical projection in multi-layer MICOM -- 7.5 Conclusions -- Acknowledgments -- References -- 8 Dynamic consistency and Lagrangian data in oceanography: mapping, assimilation, and optimization schemes -- 8.1 Introduction -- 8.2 Background and history -- 8.2.1 Assimilation of ''pseudo-Lagrangian'' velocity -- 8.2.2 Assimilation of drifter positions -- 8.3 Analysis methods based on conservation laws -- 8.3.1 Conservation of temperature -- 8.3.2 Analysis based on vorticity conservation -- 8.4 Optimal trajectory between two positions -- 8.4.1 Optimization formulation with standard constraints -- 8.4.2 Constraints based on background statistics -- 8.5 Sequential data assimilation using the Kalman filter -- 8.5.1 Extended Kalman filter algorithm -- 8.5.2 Combining KF with the optimal contour -- 8.6 Lagrangian model dynamics and Kalman filter. , 8.7 An augmented state approach for Lagrangian positions -- 8.8 Concluding remarks -- Appendix A: Calculus of variation -- References -- 9 Observing turbulence regimes and Lagrangian dispersal properties in the oceans -- 9.1 Introduction -- 9.2 Lagrangian velocity spectra, velocity correlation function and diffusivity -- 9.3 Variability of time and space scales: two different regimes of dispersion -- 9.4 Hierarchy of Markovian LSM -- 9.5 Data analysis -- 9.6 Turbulence regimes and dispersal properties -- 9.7 Summary and concluding remarks -- Acknowledgments -- References -- 10 Lagrangian biophysical dynamics -- 10.1 Introduction -- 10.2 Describing the dynamics of marine populations -- 10.2.1 The average fish: mean field models -- 10.2.2 Structured population models -- 10.2.3 Mortality as a function of condition -- 10.3 Lagrangian implementation of structured models -- 10.3.1 Coupling the model to the rest of the ecosystem -- 10.3.2 Bioenergetics across trophic levels -- 10.3.3 The energetics of pelagic fish and the average ocean -- 10.4 Trajectories of marine life -- 10.4.1 Types of movement in the ocean -- 10.4.2 Eastern boundary currents and upwelling -- 10.4.3 Western boundary currents -- 10.4.4 Lagrangian dynamics at the mesoscale -- 10.4.5 Trajectories and behavior -- 10.4.6 Biological enhancement and aggregation dynamics -- 10.4.7 Schooling dynamics -- 10.4.8 Trajectories of organisms and recruitment -- 10.4.9 Some examples of Lagrangian problems in the coastal ocean -- 10.5 Modeling trajectories of marine organisms -- 10.5.1 Building a simulation model -- 10.5.2 Oceanographic connectivity in the Greater Caribbean: an example -- 10.5.3 Retention on topography: a final look -- 10.5.4 Simplified models for longer-term population dynamics -- 10.6 Conclusions -- Acknowledgments -- References -- 11 Plankton: Lagrangian inhabitants of the sea. , 11.1 Introduction -- 11.1.1 A historical view of plankton -- 11.1.2 The planktonic life mode -- 11.2 Lagrangian studies of plankton -- 11.2.1 Fate of individual larvae -- Direct observations of larval dispersal -- Mark/recapture techniques and geochemical signatures -- 11.2.2 Tracers -- Fluorescent dyes -- SF6 -- 11.2.3 Surface drifters -- Applications of surface drifters by biologists -- Upwelling zones -- Estuarine and river plumes -- Instrumented surface drifters -- Larval transport -- 11.2.4 Subsurface Platforms -- 11.3 Future directions -- Acknowledgments -- References -- 12 A Lagrangian stochastic model for the dynamics of a stage structured population. Application to a copepod population -- 12.1 Introduction -- 12.2 Basic assumptions of the modeling approach -- 12.3 Life history of an individual -- 12.3.1 Development and mortality processes -- 12.3.2 Reproduction process -- 12.3.3 Formalization of choice processes -- 12.3.4 Infinitesimal and finite time scale of noise -- 12.4 Dynamics of the overall population -- 12.4.1 Linear model -- 12.4.2 Feedback of the population size on the recruitment -- 12.4.3 Effects of the uncertainty levels -- 12.4.4 Eulerian formulation -- 12.5 Application to a copepod population -- 12.5.1 Malthusian growth -- 12.5.2 Limits to exponential growth -- 12.6 Concluding remarks -- Acknowledgments -- References -- 13 Lagrangian analysis and prediction of coastal and ocean dynamics (LAPCOD) -- 13.1 Introduction -- 13.2 The mean flow and flow variability -- 13.3 Methods for estimating mean flow and its variability from Lagrangian data -- 13.4 On the influence of topography on ocean motion -- 13.5 Dispersion and mixing -- 13.6 Biological Applications -- 13.7 Lagrangian stochastic models -- 13.8 Numerical simulations of ocean circulation and Lagrangian trajectories -- 13.9 Lagrangian data assimilation and prediction. , 13.10 Lagrangian-based dynamics.
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