Ocean acoustic tomography

About: Ocean acoustic tomography is a research topic. Over the lifetime, 346 publications have been published within this topic receiving 4537 citations.

Ocean Acoustic Tomography

Abstract: The problem of ocean acoustic tomography is to infer from precise measurements of travel time, or other properties of acoustic propagation, the state of the ocean traversed by a sound field. Tomography takes advantage of two facts: that travel time and other measurable acoustic parameters are functions of temperature, water velocity, and other parameters of oceanographic interest, and can be interpreted to provide information about the intervening ocean using inverse methods; and that the ocean is virtually transparent to low-frequency sound, so that signals can be transmitted over distances of many thousands of kilometres. It is therefore possible to prepare a practical system of transmitters and receivers to interpret the behaviour of the oceans. This book gives a comprehensive presentation of the underlying oceanography and mathematics necessary to understand and develop such a system. It covers the forward and inverse tomography problem, as well as numerous models for data interpretation. Also included is an epilogue outlining the history of tomographic techniques. It should prove a valuable resource to oceanographers and climatologists, as well as applied mathematicians and engineers interested in applications of fluid mechanics tools.

Application of stochastic inverse theory to ionospheric tomography

Abstract: Tomographic processing of path integral electron density records is emerging as a viable tool for ionospheric research. Tomographic processors fall into at least two major classes: those applying the Radon transform and those employing linear algebraic matrix inversion. In this paper we apply one of the latter, the “weighted, damped, least squares” technique of stochastic inversion, to two simulated but realistic data sets. This method, which repeatedly has been applied successfully to ocean acoustic tomography, is particularly suited to solving inverse problems in geophysics because it provides an orderly mechanism for judicious use of a priori or external information to complement sparse or nonuniform path integral data. The limited range of angles through which the ionosphere may be viewed on satellite-to-ground paths represents such a nonuniformity in ionospheric tomography. The method also provides means for estimating uncertainty in the image field, uncertainty which itself is nonuniform.

Modern approaches to data assimilation in ocean modeling

Abstract: Preface. Introduction. The oceanographic data assimilation problem: overview, motivation and purposes (P. Malanotte-Rizzoli, E. Tziperman). Models and Data. Recent developments in prognostic ocean modeling (W.R. Holland, A. Capotondi). Oceanographic data for parameter estimation (N.G. Hogg). A case study of the effect of errors in satellite altimetry on data assimilation (L.L. Fu, I. Fukumori). Ocean acoustic tomography: integral data and ocean models (B.D. Cornuelle, P.F. Worcester). Global Applications. Combining data and the global Primitive Equation Ocean General Circulation model using the adjoint method (Z. Sirkes, E. Tziperman, W.C. Thacker). Data assimilation methods for ocean tides (G. Egbert, A.F. Bennett). Global ocean data assimilation system (A. Rosati, R. Gudgel, R. Miyakoda). Tropical Ocean Applications. Tropical data assimilation: theoretical aspects (R.N. Miller, M.A. Cane). Data assimilation in support of tropical ocean circulation studies (A.J. Busalacchi). Data assimilation as a component of a coupled forecast system (A. Leetmaa, M. Ji). Regional Applications. A methodology for the construction of a hierarchy of Kalman filter/smoothers for nonlinear primitive equation models (P. Malanotte-Rizzoli, I. Fukumori, R.E. Young). Data assimilation in a North Pacific Ocean monitoring and prediction system (M.R. Carnes et al.). Toward an operational nowcast/forecast system for the U.S. East Coast (F. Aikman et al.). Real-time regional forecasting (A.R. Robinson et al.). Interdisciplinary Applications. An interdisciplinary ocean prediction system: assimilation strategies and structured data models (C.J. Lozano et al.).