Dynamic reusable workflows for ocean science

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Marine Science and Engineering 4 (2016): 68, doi:10.3390/jmse4040068.Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog searches and data access now make it possible to create catalog-driven workflows that automate—end-to-end—data search, analysis, and visualization of data from multiple distributed sources. Further, these workflows may be shared, reused, and adapted with ease. Here we describe a workflow developed within the US Integrated Ocean Observing System (IOOS) which automates the skill assessment of water temperature forecasts from multiple ocean forecast models, allowing improved forecast products to be delivered for an open water swim event. A series of Jupyter Notebooks are used to capture and document the end-to-end workflow using a collection of Python tools that facilitate working with standardized catalog and data services. The workflow first searches a catalog of metadata using the Open Geospatial Consortium (OGC) Catalog Service for the Web (CSW), then accesses data service endpoints found in the metadata records using the OGC Sensor Observation Service (SOS) for in situ sensor data and OPeNDAP services for remotely-sensed and model data. Skill metrics are computed and time series comparisons of forecast model and observed data are displayed interactively, leveraging the capabilities of modern web browsers. The resulting workflow not only solves a challenging specific problem, but highlights the benefits of dynamic, reusable workflows in general. These workflows adapt as new data enter the data system, facilitate reproducible science, provide templates from which new scientific workflows can be developed, and encourage data providers to use standardized services. As applied to the ocean swim event, the workflow exposed problems with two of the ocean forecast products which led to improved regional forecasts once errors were corrected. While the example is specific, the approach is general, and we hope to see increased use of dynamic notebooks across geoscience domains

Observations and a linear model of water level in an interconnected inlet-bay system

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 122 (2017): 2760–2780, doi:10.1002/2016JC012318.A system of barrier islands and back-barrier bays occurs along southern Long Island, New York, and in many coastal areas worldwide. Characterizing the bay physical response to water level fluctuations is needed to understand flooding during extreme events and evaluate their relation to geomorphological changes. Offshore sea level is one of the main drivers of water level fluctuations in semienclosed back-barrier bays. We analyzed observed water levels (October 2007 to November 2015) and developed analytical models to better understand bay water level along southern Long Island. An increase (∼0.02 m change in 0.17 m amplitude) in the dominant M2 tidal amplitude (containing the largest fraction of the variability) was observed in Great South Bay during mid-2014. The observed changes in both tidal amplitude and bay water level transfer from offshore were related to the dredging of nearby inlets and possibly the changing size of a breach across Fire Island caused by Hurricane Sandy (after December 2012). The bay response was independent of the magnitude of the fluctuations (e.g., storms) at a specific frequency. An analytical model that incorporates bay and inlet dimensions reproduced the observed transfer function in Great South Bay and surrounding areas. The model predicts the transfer function in Moriches and Shinnecock bays where long-term observations were not available. The model is a simplified tool to investigate changes in bay water level and enables the evaluation of future conditions and alternative geomorphological settings.New York State Department of Environmental Conservation Grant Number: (NYS-DEC); U.S. Geological Survey (USGS

Spatial distribution of water level impacting back-barrier bays

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Aretxabaleta, A. L., Ganju, N. K., Defne, Z., & Signell, R. P. Spatial distribution of water level impacting back-barrier bays. Natural Hazards and Earth System Sciences, 19(8), (2019): 1823-1838, doi: 10.5194/nhess-19-1823-2019.Water level in semi-enclosed bays, landward of barrier islands, is mainly driven by offshore sea level fluctuations that are modulated by bay geometry and bathymetry, causing spatial variability in the ensuing response (transfer). Local wind setup can have a complementary role that depends on wind speed, fetch, and relative orientation of the wind direction and the bay. Bay area and inlet geometry and bathymetry primarily regulate the magnitude of the transfer between open ocean and bay. Tides and short-period offshore oscillations are more damped in the bays than longer-lasting offshore fluctuations, such as a storm surge and sea level rise. We compare observed and modeled water levels at stations in a mid-Atlantic bay (Barnegat Bay) with offshore water level proxies. Observed water levels in Barnegat Bay are compared and combined with model results from the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system to evaluate the spatial structure of the water level transfer. Analytical models based on the dimensional characteristics of the bay are used to combine the observed data and the numerical model results in a physically consistent approach. Model water level transfers match observed values at locations inside the bay in the storm frequency band (transfers ranging from 50 %–100 %) and tidal frequencies (10 %–55 %). The contribution of frequency-dependent local setup caused by wind acting along the bay is also considered. The wind setup effect can be comparable in magnitude to the offshore transfer forcing during intense storms. The approach provides transfer estimates for locations inside the bay where observations were not available, resulting in a complete spatial characterization. An extension of the methodology that takes advantage of the ADCIRC tidal database for the east coast of the United States allows for the expansion of the approach to other bay systems. Detailed spatial estimates of water level transfer can inform decisions on inlet management and contribute to the assessment of current and future flooding hazard in back-barrier bays and along mainland shorelines.This work was supported by the US Geological Survey, Coastal and Marine Hazards/Resources Program

Accurate Charge-Dependent Nucleon-Nucleon Potential at Fourth Order of Chiral Perturbation Theory

We present the first nucleon-nucleon potential at next-to-next-to-next-to-leading order (fourth order) of chiral perturbation theory. Charge-dependence is included up to next-to-leading order of the isospin-violation scheme. The accuracy for the reproduction of the NN data below 290 MeV lab. energy is comparable to the one of phenomenological high-precision potentials. Since NN potentials of order three and less are known to be deficient in quantitative terms, the present work shows that the fourth order is necessary and sufficient for a reliable NN potential derived from chiral effective Lagrangians. The new potential provides a promising starting point for exact few-body calculations and microscopic nuclear structure theory (including chiral many-body forces derived on the same footing).Comment: 4 pages Revtex including one figur

Tidal dynamics and dispersion around coastal headlands

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 1989The dynamics of shallow tidal currents and tide-induced dispersion are investigated around coastal headlands that have alongshore length scales that are comparable to or less than the tidal excursion. Depth-averaged shallow water equations forced by oscillatory flow are solved numerically for Gaussian headlands. The tidal flows around these headlands are shown to be characterized by flow separation and. transient eddy formation. Idealized models of flow separation and the transport and damping of vorticity away from the headland explain much of the observed behavior. The characteristics of the separated wake are compared with known results from the study of viscous flow around bluff bodies. The kinematics of particle dispersion in the numerical solutions is described and analyzed.This work was supported by NSF grant OCE-87-11031 and the National Center for Atmospheric Research. Additional funding was provided by the Woods Hole Oceanographic Institution's Ocean Venture Fund, Coastal Research Center, and Education Program

Technical note: Harmonising metocean model data via standard web services within small research groups

Abstract. Work over the last decade has resulted in standardised web services and tools that can significantly improve the efficiency and effectiveness of working with meteorological and ocean model data. While many operational modelling centres have enabled query and access to data via common web services, most small research groups have not. The penetration of this approach into the research community, where IT resources are limited, can be dramatically improved by (1) making it simple for providers to enable web service access to existing output files; (2) using free technologies that are easy to deploy and configure; and (3) providing standardised, service-based tools that work in existing research environments. We present a simple, local brokering approach that lets modellers continue to use their existing files and tools, while serving virtual data sets that can be used with standardised tools. The goal of this paper is to convince modellers that a standardised framework is not only useful but can be implemented with modest effort using free software components. We use NetCDF Markup language for data aggregation and standardisation, the THREDDS Data Server for data delivery, pycsw for data search, NCTOOLBOX (MATLAB®) and Iris (Python) for data access, and Open Geospatial Consortium Web Map Service for data preview. We illustrate the effectiveness of this approach with two use cases involving small research modelling groups at NATO and USGS

Tides of Massachusetts and Cape Cod Bays

The Massachusetts Bays Program made bottom pressure and water velocity observations in Massachusetts and Cape Cod Bays during 1990 and 1991. In the Bays, the sea surface elevation appeared to rise and fall in phase with equal amplitudes at each diurnal or semidiurnal tidal frequency. There is some amplification in Boston and Provincetown harbors. The semidiurnal tides (particularly the M2 constituent) dominate. Massachusetts and Cape Cod Bays are part of the Gulf of Maine/Bay of Fundy system which is resonant near the semidiurnal frequency. This resonance amplifies the importance of the semidiurnal tides so that diurnal and higher harmonic tides become negligible. The sea level tides force currents which move with the same frequencies, but whose amplitudes are affected by the bathymetry. The strongest currents exist in the channel between Race Point and Stellwagen Bank where tidal currents exceed 1 knot. Analysis of current records for their tidal signal is complicated by internal tides which contaminate the records. These internal waves at tidal frequency exist on the stratification in the water column, and disappear during winter well-mixed times. At other times they must be considered as a signifcant source of energy for mixing and resuspension of sediments

Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here by permission of Taylor & Francis for personal use, not for redistribution. The definitive version was published in Journal of Operational Oceanography 10 (2017): 115-126, doi:10.1080/1755876X.2017.1322026.This paper outlines strategies that would advance coastal ocean modeling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the U.S. Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of U.S. based researchers with a cross-section of coastal oceanography and ocean modeling expertise and community representation drawn from Regional and U.S. Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modeling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3-8 year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, U.S. Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal-academic partnerships benefiting IOOS stakeholders and end users.2018-05-2

Tide- and wind-forced currents in Buzzards Bay, Massachusetts

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1987.Microfiche copy available in Archives and Science.Bibliography: leaves 83-86.by Richard Peter Signell.M.S

From the oceans to the cloud: Opportunities and challenges for data, models, computation and workflows.

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Vance, T. C., Wengren, M., Burger, E., Hernandez, D., Kearns, T., Medina-Lopez, E., Merati, N., O'Brien, K., O'Neil, J., Potemrag, J. T., Signell, R. P., & Wilcox, K. From the oceans to the cloud: Opportunities and challenges for data, models, computation and workflows. Frontiers in Marine Science, 6(211), (2019), doi:10.3389/fmars.2019.00211.Advances in ocean observations and models mean increasing flows of data. Integrating observations between disciplines over spatial scales from regional to global presents challenges. Running ocean models and managing the results is computationally demanding. The rise of cloud computing presents an opportunity to rethink traditional approaches. This includes developing shared data processing workflows utilizing common, adaptable software to handle data ingest and storage, and an associated framework to manage and execute downstream modeling. Working in the cloud presents challenges: migration of legacy technologies and processes, cloud-to-cloud interoperability, and the translation of legislative and bureaucratic requirements for “on-premises” systems to the cloud. To respond to the scientific and societal needs of a fit-for-purpose ocean observing system, and to maximize the benefits of more integrated observing, research on utilizing cloud infrastructures for sharing data and models is underway. Cloud platforms and the services/APIs they provide offer new ways for scientists to observe and predict the ocean’s state. High-performance mass storage of observational data, coupled with on-demand computing to run model simulations in close proximity to the data, tools to manage workflows, and a framework to share and collaborate, enables a more flexible and adaptable observation and prediction computing architecture. Model outputs are stored in the cloud and researchers either download subsets for their interest/area or feed them into their own simulations without leaving the cloud. Expanded storage and computing capabilities make it easier to create, analyze, and distribute products derived from long-term datasets. In this paper, we provide an introduction to cloud computing, describe current uses of the cloud for management and analysis of observational data and model results, and describe workflows for running models and streaming observational data. We discuss topics that must be considered when moving to the cloud: costs, security, and organizational limitations on cloud use. Future uses of the cloud via computational sandboxes and the practicalities and considerations of using the cloud to archive data are explored. We also consider the ways in which the human elements of ocean observations are changing – the rise of a generation of researchers whose observations are likely to be made remotely rather than hands on – and how their expectations and needs drive research towards the cloud. In conclusion, visions of a future where cloud computing is ubiquitous are discussed.This is PMEL contribution 4873