A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and non-environmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS's inputs (generally due to disagreement between forecasts) are propagated through the DSS's output by using the unscented transform. In this way, the system is not only able to provide a traffic light map (run/not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations

Validation and Operational Implementation of the Navy Coastal Ocean Model Four Dimensional Variational Data Assimilation System (NCOM 4DVAR) In the Okinawa Trough

The Navy Coastal Ocean Model Four-Dimensional Variational Assimilation (NCOM 4DVAR) system is an analysis software package that is designed to supplement the current capability of the operational analysis/prediction system known as the Relocatable Navy Coupled Ocean Model (Relo NCOM) system. The present assimilation component of Relo NCOM employs the Navy Coupled Ocean Data Assimilation Three-Dimensional Variational Assimilation (NCODA 3DVAR) system to process and assimilate observations. The NCOM 4DVAR, on the other hand, uses a representer based 4DVAR method and has been found to improve the forecast-skill for several regional applications. This chapter presents the results of validation experiments performed in the Okinawa Trough. The analysis and resulting forecast skill of the two assimilation methods within Relo NCOM (NCOM 4DVAR and NCODA 3DVAR) are compared, and the operational implementation of NCOM 4DVAR is examined to verify that it satisfies operational constraints. The metrics used to validate the NCOM 4DVAR system include: computational efficiency, scalability, robustness, and the prediction accuracy of temperature, sea surface height, and sonic layer depth through NCOM 4DVAR and NCODA 3DVAR analyses. Forecast skill metrics are computed using surface observations of temperature, salinity and sea surface height, and profile observations from gliders and AXBTs (aerial expendable bathythermograph). Overall, the validation reveals that NCOM 4DVAR has lower root mean square errors for both analyses and forecasts than the operational NCODA 3DVAR system

Evaluation of Global Ocean Data Assimilation Experiment Products on South Florida Nested Simulations with the Hybrid Coordinate Ocean Model

The South Florida Hybrid Coordinate Ocean Model (SoFLA-HYCOM) encompasses a variety of coastal regions (the broad Southwest Florida shelf, the narrow Atlantic Keys shelf, the shallow Florida Bay, and Biscayne Bay) and deep regions (the Straits of Florida), including Marine Protected Areas (the Florida Keys Marine Sanctuary and the Dry Tortugas Ecological Reserve). The presence of the strong Loop Current/Florida Current system and associated eddies connects the local and basin-wide dynamics. A multi-nested approach has been developed to ensure resolution of coastal-scale processes and proper interaction with the large scale flows. The simulations are free running and effects of data assimilation are introduced through boundary conditions derived from Global Ocean Data Assimilation Experiment products. The study evaluates the effects of boundary conditions on the successful hindcasting of circulation patterns by a nested model, applied on a dynamically and topographically complex shelf area. Independent (not assimilated) observations are employed for a quantitative validation of the numerical results. The discussion of the prevailing dynamics that are revealed in both modeled and observed patterns suggests the importance of topography resolution and local forcing on the inner shelf to middle shelf areas, while large scale processes are found to dominate the outer shelf flows. The results indicate that the successful hindcasting of circulation patterns in a coastal area that is characterized by complex topography and proximity to a large scale current system requires a dynamical downscaling approach, with simulations that are nested in a hierarchy of data assimilative outer models