Note: Cover -- Contents -- Preface -- Chapter 1. Geomagnetism and Paleomagnetism -- 1.1 Geomagnetism -- 1.2 Paleomagnetism -- Chapter 2. Rock Magnetism -- 2.1 Basic Principles of Magnetism -- 2.2 Magnetic Minerals in Rocks -- 2.3 Physical Theory of Rock Magnetism -- Chapter 3. Methods and Techniques -- 3.1 Sampling and Measurement -- 3.2 Statistical Methods -- 3.3 Field Tests for Stability -- 3.4 Laboratory Methods and Applications -- 3.5 Identification of Magnetic Minerals and Grain Sizes -- Chapter 4. Magnetic Field Reversals -- 4.1 Evidence for Field Reversal -- 4.2 The Geomagnetic Polarity Time Scale -- 4.3 Magnetostratigraphy -- 4.4 Polarity Transitions -- 4.5 Analysis of Reversal Sequences -- Chapter 5. Oceanic Paleomagnetism -- 5.1 Marine Magnetic Anomalies -- 5.2 Modeling Marine Magnetic Anomalies -- 5.3 Analyzing Older Magnetic Anomalies -- 5.4 Paleomagnetic Poles for Oceanic Plates -- 5.5 Evolution of Oceanic Plates -- Chapter 6. Continental Paleomagnetism -- 6.1 Analyzing Continental Data -- 6.2 Data Selection and Reliability Criteria -- 6.3 Testing the Geocentric Axial Dipole Model -- 6.4 Apparent Polar Wander -- 6.5 Phanerozoic APWPs for the Major Blocks -- Chapter 7. Paleomagnetism and Plate Tectonics -- 7.1 Plate Motions and Paleomagnetic Poles -- 7.2 Phanerozoic Supercontinents -- 7.3 Displaced Terranes -- 7.4 Rodinia and the Precambrian -- 7.5 Non-Plate Tectonic Hypotheses -- References -- Index -- International Geophysics Series -- Color Plate Section.

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.