An interdisciplinary team of scientists is collaborating to enhance the understanding of the uncertainty in the ocean environment, including the sea bottom, and characterize its impact on tactical system performance. To accomplish these goals quantitatively an end-to-end system approach is necessary. The conceptual basis of this approach and the framework of the end-to-end system, including its components, is the subject of this presentation. Specifically, we present a generic approach to characterize variabilities and uncertainties arising from regional scales and processes, construct uncertainty models for a generic sonar system, and transfer uncertainties from the acoustic environment to the sonar and its signal processing. Illustrative examples are presented to highlight recent progress toward the development of the methodology and components of the system.

Increasingly, more importance is placed on the uncertainty information of data being displayed. This paper focuses on techniques for visualizing 3D scalar data sets with corresponding uncertainty information at each point which is also representedas a scalar value. In Djurcilov (in: D. Ebert, J.M. Favre, R. Peikert (Eds.), Data Visualization 2001, Springer, Berlin, 2001), we presentedtwo general methods (inline DVR approach anda post-processing approach) for carrying out this task. The first methodinvolves incorporating the uncertainty information directly into the volume rendering equation. The second method involves post-processing information of volume rendered images to composite uncertainty information.

We discuss the concepts involved in the evaluation and quantitative verification of ocean forecasts and present two predictive skill experiments to develop and research these concepts, carried out in the North Atlantic and Mediterranean Sea in 2001 and 2002. Ocean forecasting involves complex ocean observing and prediction systems for ocean regions with multi-scale interdisciplinary dynamical processes and strong, intermittent events. Now that ocean forecasting is becoming more common, it is critically important to interpret and evaluate regional forecasts in order to establish their usefulness to the scientific and applied communities. The Assessment of Skill for Coastal Ocean Transients (ASCOT) project is a series of real-time Coastal Predictive Skill (CPSE) and Rapid Environmental Assessment (REA) experiments and simulations focused on quantitative skill evaluation, carried out by the Harvard Ocean Prediction System group in collaboration with the NATO SACLANT Undersea Research Centre. ASCOT-01 was carried out in Massachusetts Bay and the Gulf of Maine in June 2001. ASCOT-02 took place in May 2002 in the Corsican Channel near the island of Elba in the Mediterranean Sea. Results from the ASCOT exercises highlight the dual use of data for skill evaluation and assimilation, real-time adaptive sampling and skill optimization and present both real-time and a posteriori evaluations of predictive skill and predictive capability.

Combining an intensive hydrographic data survey with a numerical primitive equation model by data assimilation, the main features of dominant mesoscale to subbasin-scale variability in the Strait of Sicily (Mediterranean Sea) during the summer of 1996 are estimated, revealed and described, and several hydrographic and dynamical properties of the #ow and variabilities discussed. The feature identi”cation is based on two independent real-time analyses of the variability. One analysis `subjectivelya evaluates and studies physical “eld forecasts and their variations. The other more `objectivelya estimates and forecasts the principal components of the variability. The two independent analyses are found to be in agreement and complementary. The dominant dynamical variations are revealed to be associated with “ve features: the Adventure Bank Vortex, Maltese Channel Crest, Ionian Shelfbreak Vortex, Messina Rise Vortex, and temperature and salinity fronts of the Ionian slope. These features and their variations are found to have links with the meanders of the Atlantic Ionian Stream. For each feature, the characteristic physical scales, and their deviations, are quanti”ed. The predominant circulation patterns, pathways and transformations of the modi”ed Atlantic water, Ionian water and modi”ed Levantine intermediate water, are then identi”ed and discussed. For each of these water masses, the ranges of temperature, salinity, depth, velocity and residence times, and the regional variations of these ranges, are computed. Based on the estimated “elds and variability principal components, several properties of the dynamics in the Strait are discussed. These include: general characteristics of the mesoscale anomalies; bifurcations of the Atlantic Ionian Stream; respective roles of topography, atmospheric forcings and internal dynamics; factors controlling (strengthening or weakening) the vortices identi”ed; interactions of the Messina Rise and Ionian Shelfbreak vortices; and, mesoscale dynamics and relatively complex features along the Ionian slope. For evaluation and validation of the results obtained, in situ data, satellite sea surface temperature images and trajectories of surface drifters are employed, as well as comparisons with previous studies.

Data assimilation is a novel, versatile methodology for estimating oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation. The melding of data and dynamics is a powerful methodology which makes possible efRcient, accurate, and realistic estimations otherwise not feasible. It is providing rapid advances in important aspects of both basic ocean science and applied marine technology and operations. The following sections introduce concepts, describe purposes, present applications to regional dynamics and forecasting, overview formalism and methods, and provide a selected range of examples.