US Integrated Ocean Observing System Research Articles

Integrating Biodiversity and Environmental Observations in Support of National Marine Sanctuary and Large Marine Ecosystem Assessments

Species and habitats are the subjects of legislation that mandates reporting of information on ecosystem conditions. Improvements in sensors, sampling platforms, information systems, and collaborations among experts and information users now enables more effective and up-to-date information to meet regional and national needs. Specifically, advances in environmental DNA (eDNA)-based assessments of biodiversity, community science data, various underwater imaging devices, and environmental, behavioral, and physiology observations from animal telemetry provide new opportunities to address multiple requirements for reporting status and trends, including insights into life in the deep ocean. Passive and active acoustic sensors help monitor marine life, boat traffic, and noise pollution. Satellites provide repeated, frequent, and long-term records of many relevant variables from global to local scales and, when combined with numerical computer simulations, allow planning for future scenarios. Metadata standards facilitate the transfer of data from machine to machine, thus streamlining assessments and forecasting and providing knowledge directly to the public. The Marine Biodiversity Observation Network (MBON) facilitates this exchange of information on life in the sea. The collaborative efforts of the Central and Northern California Ocean Observing System (CeNCOOS) of the US Integrated Ocean Observing System and its partners provide an example of a regional MBON process for information delivery. This includes linking policy and management needs, prioritizing observing data from various platforms and methods, streamlining data handling practices, and delivery of information for management such as for the Monterey Bay National Marine Sanctuary and the California Current Large Marine Ecosystem, with iterative process adaptation.

The Ocean Enterprise – understanding and quantifying business activity in support of observing, measuring and forecasting the ocean

ABSTRACTSustained ocean observations, measurements and models provide a wide range of societal benefits underpinning the safety, operational and compliance needs of beneficiaries that operate around, on and under the ocean (In the context of this paper, the term ‘ocean’ is defined as encompassing the global ocean, enclosed seas and the US Great Lakes.) They also provide an essential input to ocean scientific research and the effective protection of the marine environment. Delivering the means to collect and use ocean data and information on a sustained basis constitutes a significant business undertaking. The companies that enable sustained ocean observation, measurement and forecasting, and deliver its benefits as commercial services, combine to create a unique and growing industry cluster; the Ocean Enterprise. Ocean Enterprise businesses underpin the ability to provide societal benefit from sustained ocean observations, measurements and models, as well as delivering significant economic and employment benefits in their own right. In this paper, we describe a systematic evaluation of the scale, scope and characteristics of the Ocean Enterprise in the United States. We explore the ways in which this industry cluster interacts with the US Integrated Ocean Observing System and how the United States Ocean Enterprise compares to that of the United Kingdom.

From heterogeneous marine sensors to sensor web: (near) real-time open data access adopting OGC sensor web enablement standards

Sensor engineering is continuously evolving as devices become cheaper, smaller, more intelligent, and more efficient. Today, oceanographic sensors aim at monitoring marine processes by means of physical, chemical, and biological variables, and use different data formats, units, parameters, resolutions, data quality standards, and protocols. Therefore, integration and interoperability at European level represent a challenge.To cope with this challenge, the Sensor Web Enablement (SWE) standards, developed by the Open Geospatial Consortium (OGC), are a good solution, as they ensure interoperability and long-term archiving of data series with complete information for all devices.The interoperability allows integrating information from different sources or pre-existing architectures, such as those developed in the SANY project (http://www.opengeospatial.org/ogc/regions/SANY) or by the US Integrated Ocean Observing System (https://github.com/ioos).In this paper, we illustrate the real-time data management system, developed by the Italian National Oceanographic Data Centre (NODC) at the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, OGS in Trieste – Italy, designed to share data acquired by a large number of heterogeneous observing platforms. This system adopts Observations and Measurements (O&M) and Sensor Model Language (SensorML) as data and metadata formats, as well as the Sensor Observation Service (SOS) released by the 52°North as server and Web client for open data access.The work done shows that the choice to manage real-time data using OGC Sensor Web Enablement (SWE) standards can be considered a valid solution with pros and cons. Nevertheless, in the future, the SWE community will grow, and with it, the number of applications to manage SWE standards to simplify their adoption.

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

ABSTRACTThis paper outlines strategies that would advance coastal ocean modelling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the US Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of US-based researchers with a cross-section of coastal oceanography and ocean modelling expertise and community representation drawn from Regional and US 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, modelling 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, US 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.

Dynamic Reusable Workflows for Ocean Science

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.

English

In 2007, the US west coast shellfish industry began to feel the effects of unprecedented levels of larval mortality in commercial hatcheries producing the Pacific oyster Crassostrea gigas. Subsequently, researchers at Whiskey Creek Shellfish Hatchery, working with academic and government scientists, showed a high correlation between aragonite saturation state (Ωarag) of inflowing seawater and survival of larval groups, clearly linking increased CO2 to hatchery failures. This work led the Pacific Coast Shellfish Growers Association (PCSGA) to instrument shellfish hatcheries and coastal waters, establishing a monitoring network in collaboration with university researchers and the US Integrated Ocean Observing System. Analytical developments, such as the ability to monitor Ωarag in real time, have greatly improved the industry’s understanding of carbonate chemistry and its variability and informed the development of commercial-scale water treatment systems. These treatment systems have generally proven effective, resulting in billions of additional oyster larvae supplied to Pacific Northwest oyster growers. However, significant challenges remain, and a multifaceted approach, including selective breeding of oyster stocks, expansion of hatchery capacity, continued monitoring of coastal water chemistry, and improved understanding of biological responses will all be essential to the survival of the US west coast shellfish industry. Full text: 0865_CoastalAcidImpactsShellfish.pdf

Knowledge discovery in large model datasets in the marine environment: the THREDDS Data Server example

In order to monitor, describe and understand the marine environment, many research institutions are involved in the acquisition and distribution of ocean data, both from observations and models. Scientists from these institutions are spending too much time looking for, accessing, and reformatting data: they need better tools and procedures to make the science they do more efficient. The U.S. Integrated Ocean Observing System (US-IOOS) is working on making large amounts of distributed data usable in an easy and efficient way. It is essentially a network of scientists, technicians and technologies designed to acquire, collect and disseminate observational and modelled data resulting from coastal and oceanic marine regions investigations to researchers, stakeholders and policy makers. In order to be successful, this effort requires standard data protocols, web services and standards-based tools. Starting from the US-IOOS approach, which is being adopted throughout much of the oceanographic and meteorological sectors, we describe here the CNR-ISMAR Venice experience in the direction of setting up a national Italian IOOS framework using the THREDDS (THematic Real-time Environmental Distributed Data Services) Data Server (TDS), a middleware designed to fill the gap between data providers and data users. The TDS provides services that allow data users to find the data sets pertaining to their scientific needs, to access, to visualize and to use them in an easy way, without downloading files to the local workspace. In order to achieve this, it is necessary that the data providers make their data available in a standard form that the TDS understands, and with sufficient metadata to allow the data to be read and searched in a standard way. The core idea is then to utilize a Common Data Model (CDM), a unified conceptual model that describes different datatypes within each dataset. More specifically, Unidata (<a href="http://www.unidata.ucar.edu" target="_blank">www.unidata.ucar.edu</a>) has developed CDM specifications for many of the different kinds of data used by the scientific community, such as grids, profiles, time series, swath data. These datatypes are aligned the NetCDF Climate and Forecast (CF) Metadata Conventions and with Climate Science Modelling Language (CSML); CF-compliant NetCDF files and GRIB files can be read directly with no modification, while non compliant files can be modified to meet appropriate metadata requirements. Once standardized in the CDM, the TDS makes datasets available through a series of web services such as OPeNDAP or Open Geospatial Consortium Web Coverage Service (WCS), allowing the data users to easily obtain small subsets from large datasets, and to quickly visualize their content by using tools such as GODIVA2 or Integrated Data Viewer (IDV). In addition, an ISO metadata service is available through the TDS that can be harvested by catalogue broker services (e.g. GI-cat) to enable distributed search across federated data servers. Example of TDS datasets can be accessed at the CNR-ISMAR Venice site <a href="http://tds.ve.ismar.cnr.it:8080/thredds/catalog.html" target="_blank">http://tds.ve.ismar.cnr.it:8080/thredds/catalog.html</a>.

Knowledge discovery in large model datasets in the marine environment: the THREDDS Data Server example

In order to monitor, describe and understand the marine environment, many research institutions are involved in the acquisition and distribution of ocean data, both from observations and models. Scientists from these institutions are spending too much time looking for, accessing, and reformatting data: they need better tools and procedures to make the science they do more efficient. The U.S. Integrated Ocean Observing System (US-IOOS) is working on making large amounts of distributed data usable in an easy and efficient way. It is essentially a network of scientists, technicians and technologies designed to acquire, collect and disseminate observational and modelled data resulting from coastal and oceanic marine regions investigations to researchers, stakeholders and policy makers. In order to be successful, this effort requires standard data protocols, web services and standards-based tools. Starting from the US-IOOS approach, which is being adopted throughout much of the oceanographic and meteorological sectors, we describe here the CNR-ISMAR Venice experience in the direction of setting up a national Italian IOOS framework using the THREDDS (THematic Real-time Environmental Distributed Data Services) Data Server (TDS), a middleware designed to fill the gap between data providers and data users. The TDS provides services that allow data users to find the data sets pertaining to their scientific needs, to access, to visualize and to use them in an easy way, without downloading files to the local workspace. In order to achieve this, it is necessary that the data providers make their data available in a standard form that the TDS understands, and with sufficient metadata to allow the data to be read and searched in a standard way. The core idea is then to utilize a Common Data Model (CDM), a unified conceptual model that describes different datatypes within each dataset. More specifically, Unidata (www.unidata.ucar.edu) has developed CDM specifications for many of the different kinds of data used by the scientific community, such as grids, profiles, time series, swath data. These datatypes are aligned the NetCDF Climate and Forecast (CF) Metadata Conventions and with Climate Science Modelling Language (CSML); CF-compliant NetCDF files and GRIB files can be read directly with no modification, while non compliant files can be modified to meet appropriate metadata requirements. Once standardized in the CDM, the TDS makes datasets available through a series of web services such as OPeNDAP or Open Geospatial Consortium Web Coverage Service (WCS), allowing the data users to easily obtain small subsets from large datasets, and to quickly visualize their content by using tools such as GODIVA2 or Integrated Data Viewer (IDV). In addition, an ISO metadata service is available through the TDS that can be harvested by catalogue broker services (e.g. GI-cat) to enable distributed search across federated data servers. Example of TDS datasets can be accessed at the CNR-ISMAR Venice site http://tds.ve.ismar.cnr.it:8080/thredds/catalog.html.