A Three-Dimensional Variational Data Assimilation Scheme for the Regional Ocean Modeling System

The International Journal of Robotics Research

Chao

et al. 2010

168

133

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV. While traversing the path connecting these locations, the vehicle collects data and provides near-real time, in situ measurements back to the model to increase the skill of future predictions. Our focus is on algorithms to determine relevant points of scientific interest for a vehicle to visit within a dynamically evolving oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design sampling missions and present simulated scenarios and results from field deployments for AUV feature tracking in the Southern California coastal ocean.

Section: Regional Ocean Modeling Systemmentioning

confidence: 99%

Planning and Implementing Trajectories for Autonomous Underwater Vehicles to Track Evolving Ocean Processes Based on Predictions from a Regional Ocean Model

The International Journal of Robotics Research

Chao

et al. 2010

168

133

“…The three nested ROMS domains are coupled online and run simultaneously, exchanging boundary conditions at every time step of the coarser resolution domain. ROMS provides hindcasts, nowcasts, and hourly forecasts (up to 72 h) for the SCB (Li, Chao, McWilliams, & Ide, 2008;Vu, 2008). The operational model assimilates temperature and salinity data from autonomous vehicles, sea surface temperature from satellites, and surface currents from the high-frequency radar network.…”

Section: Roms: Southern California Bightmentioning

confidence: 99%

Persistent ocean monitoring with underwater gliders: Towards accurate reconstruction of dynamic ocean processes

Schwager

2011 IEEE International Conference on Robotics and Automation

et al. 2011

Ocean processes are dynamic and complex and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show improvements in both data resolution and path reliability compared to previously executed sampling paths used in the respective regions. C 2011 Wiley Periodicals, Inc.

Bulletin of the American Meteorological Society

“…Freshwater input is computed from a modified hydrological model of Wang et al (2004) using a digital elevation model and the air temperature and precipitation data from the PWS-WRF. For all three domains, a three-dimensional variational data assimilation (3DVA R) met hodolog y (Li et al 2008) was used to enable nowcast (analysis) and forecast. This ROMS 3DVAR forecasting system has been used successfully in several other field experiments, including t he 2 0 03 Autonomou s Ocean Sampling Network (w w w.mbari.org / aosn) experiment in Monterey Bay (Chao et al 2009).…”

Section: Sound Predictions 2009mentioning

confidence: 99%

An Ocean Observing and Prediction Experiment in Prince William Sound, Alaska

Schoch¹,

Chao

Colas

et al. 2011

Self Cite

The observing and forecasting conditions of coastal oceans in Alaska is technically challenging because of the mountainous terrain, the notoriously stormy seas, and a complex hydrological system of freshwater from rivers and glaciers. The Alaska Ocean Observing System and their partners developed a demonstration project over a 5-yr period in Prince William Sound. This location was chosen because of historical efforts to monitor ocean circulation following the Exxon Valdez oil spill of 1989. The primary goal is to develop a quasi-operational system that delivers weather and ocean information in near–real time to diverse user communities. This observing system now consists of a spatial array of atmospheric and oceanic sensors and a new generation of computer models to numerically simulate and forecast weather, waves, and ocean circulation. The project culminated in a 2009 field experiment that evaluated the performance of the model forecasts. Three ships, 44 surface drifters, an underwater glider, and an autonomous underwater vehicle, as well as two shore-based surface current radar systems, augmented the routine atmospheric and oceanographic measurements from weather stations and oceanographic buoys. Observations from terrestrial and moored weather stations were compared with atmospheric circulation forecasts, and wave gauges provided data that were used to evaluate the forecasts of significant wave heights and periods. The radar current mappers and drifter buoys validated the surface ocean circulation forecasts. Improved observations and forecasts of coastal oceans will benefit oil spill responders, commercial shippers that convey large amounts of freight to and from Alaska, and U.S. Coast Guard search-and-rescue operations.