Geology topics

R. Signell

Publications and source records attributed to R. Signell.

6 recordsLinked to original sources

USGS2011

Building transparent data access for ocean observatories: Coordination of U.S. IOOS DMAC with NSF's OOI Cyberinfrastructure

The NOAA-led U.S. Integrated Ocean Observing System (IOOS) and the National Science Foundation's Ocean Observatories Initiative (OOI) have been collaborating since 2007 on advanced tools and technologies that ensure open access to ocean observations and models. Initial collaboration focused on serving ocean data via cloud computing-a key component of the OOI cyberinfrastructure (CI) architecture. As the OOI transitioned from planning to execution in the Fall of 2009, an OOI/IOOS team developed a customer-based "use case" to align more closely with the emerging objectives of OOI-CI team's first software release scheduled for Summer 2011 and provide a quantitative capacity for stress-testing these tools and protocols. A requirements process was initiated with coastal modelers, focusing on improved workflows to deliver ocean observation data. Accomplishments to date include the documentation and assessment of scientific workflows for two "early adopter" modeling teams from IOOS Regional partners (Rutgers-the State University of New Jersey and University of Hawaii's School of Ocean and Earth Science and Technology) to enable full understanding of data sources and needs; generation of all-inclusive lists of the data sets required and those obtainable through IOOS; a more complete understanding of areas where IOOS can expand data access capabilities to better serve the needs of the modeling community; and development of "data set agents" (software) to facilitate data acquisition from numerous data providers and conversions of the data format to the OOI-CI canonical form. ?? 2011 MTS.

Conference Paper↗

USGS2010

Implementing the National Integrated Ocean Observing System (IOOS): from the federal agency perspective

The national Integrated Ocean Observing System (IOOS??) is responsible for coordinating a network of people, resources, and technology to disseminate continuous data, information, models, products, and services made throughout our coastal waters, Great Lakes, and the oceans. There are many components of the IOOS-including government, academic, and private entities. This article will focus on some of the federal contributions to IOOS and describe the capabilities of several agency partners.

Marine Technology Society Journal↗

USGS2010

Building the IOOS data management subsystem

We discuss progress to date and plans for the Integrated Ocean Observing System (IOOS??) Data Management and Communications (DMAC) subsystem. We begin by presenting a conceptual architecture of IOOS DMAC. We describe work done as part of a 3-year pilot project known as the Data Integration Framework and the subsequent assessment of lessons learned. We present work that has been accomplished as part of the initial version of the IOOS Data Catalog. Finally, we discuss near-term plans for augmenting IOOS DMAC capabilities.

Marine Technology Society Journal↗

USGS2008

Variational analysis of drifter positions and model outputs for the reconstruction of surface currents in the central Adriatic during fall 2002

In this paper we present an application of a variational method for the reconstruction of the velocity field in a coastal flow in the central Adriatic Sea, using in situ data from surface drifters and outputs from the ROMS circulation model. The variational approach, previously developed and tested for mesoscale open ocean flows, has been improved and adapted to account for inhomogeneities on boundary current dynamics over complex bathymetry and coastline and for weak Lagrangian persistence in coastal flows. The velocity reconstruction is performed using nine drifter trajectories over 45 d, and a hierarchy of indirect tests is introduced to evaluate the results as the real ocean state is not known. For internal consistency and impact of the analysis, three diagnostics characterizing the particle prediction and transport, in terms of residence times in various zones and export rates from the boundary current toward the interior, show that the reconstruction is quite effective. A qualitative comparison with sea color data from the MODIS satellite images shows that the reconstruction significantly improves the description of the boundary current with respect to the ROMS model first guess, capturing its main features and its exchanges with the interior when sampled by the drifters. Copyright 2008 by the American Geophysical Union.

Journal of Geophysical Research C: Oceans↗

USGS2008

Surface drift prediction in the Adriatic Sea using hyper-ensemble statistics on atmospheric, ocean and wave models: Uncertainties and probability distribution areas

Despite numerous and regular improvements in underlying models, surface drift prediction in the ocean remains a challenging task because of our yet limited understanding of all processes involved. Hence, deterministic approaches to the problem are often limited by empirical assumptions on underlying physics. Multi-model hyper-ensemble forecasts, which exploit the power of an optimal local combination of available information including ocean, atmospheric and wave models, may show superior forecasting skills when compared to individual models because they allow for local correction and/or bias removal. In this work, we explore in greater detail the potential and limitations of the hyper-ensemble method in the Adriatic Sea, using a comprehensive surface drifter database. The performance of the hyper-ensembles and the individual models are discussed by analyzing associated uncertainties and probability distribution maps. Results suggest that the stochastic method may reduce position errors significantly for 12 to 72??h forecasts and hence compete with pure deterministic approaches. ?? 2007 NATO Undersea Research Centre (NURC).

Journal of Marine Systems↗

USGS1996

Open-ocean boundary conditions from interior data: Local and remote forcing of Massachusetts Bay

Massachusetts and Cape Cod Bays form a semienclosed coastal basin that opens onto the much larger Gulf of Maine. Subtidal circulation in the bay is driven by local winds and remotely driven flows from the gulf. The local-wind forced flow is estimated with a regional shallow water model driven by wind measurements. The model uses a gravity wave radiation condition along the open-ocean boundary. Results compare reasonably well with observed currents near the coast. In some offshore regions, however, modeled flows are an order of magnitude less energetic than the data. Strong flows are observed even during periods of weak local wind forcing. Poor model-data comparisons are attributable, at least in part, to open-ocean boundary conditions that neglect the effects of remote forcing. Velocity measurements from within Massachusetts Bay are used to estimate the remotely forced component of the flow. The data are combined with shallow water dynamics in an inverse-model formulation that follows the theory of Bennett and McIntosh [1982], who considered tides. We extend their analysis to consider the subtidal response to transient forcing. The inverse model adjusts the a priori open-ocean boundary condition, thereby minimizing a combined measure of model-data misfit and boundary condition adjustment. A “consistency criterion” determines the optimal trade-off between the two. The criterion is based on a measure of plausibility for the inverse solution. The “consistent” inverse solution reproduces 56% of the average squared variation in the data. The local-wind-driven flow alone accounts for half of the model skill. The other half is attributable to remotely forced flows from the Gulf of Maine. The unexplained 44% comes from measurement errors and model errors that are not accounted for in the analysis.

Massachusetts↗