Search USGS⌕ Search
Home/Archive/USGS

USGS · 70177894

Dynamic reusable workflows for ocean science

Richard P. Signell·Filipe Fernandez·Kyle Wilcox
View original source ↗Export metadata ↓

Abstract

Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog search and data access make it now 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 enters 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 the geoscience domains.

Explore related subjects

Journal of Marine Science and EngineeringArticle

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Richard P. Signell, Filipe Fernandez, Kyle Wilcox. 2016-10-25. Dynamic reusable workflows for ocean science. https://doi.org/10.3390/jmse4040068

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

The USGS Rotating X-ray Computed Tomography (RXCT) Coral-Core Archive: Scope, access, and standardization

We announce the U.S. Geological Survey (USGS) Rotating X-ray Computed Tomography (RXCT) Coral-Core Archive, a digital resource derived from ~400 coral reef cores curated at the USGS Pacific and St. Petersburg Coastal and Marine Science Centers. The archive de-livers calibrated 3-D image volumes that enable reproducible values of skeletal density, linear extension, and calcification from decadal-to-centennials scale records of coral growth and bioerosion. Cross-study comparability within the archive is supported by a unified RXCT workflow that minimizes imaging artifacts. This includes rejecting im-age-intensity–density regressions with r² < 0.95, back-calculating standard densities to verify a ±10% target precision, and confirming that band-averaged density values fall within published species- and site-specific ranges. Given global coral-reef decline and the rarity of physical archives, we release data under FAIR (Findable, Accessible, Interopera-ble, Reusable) principles. Calibrated imagery and scan metadata are distributed through CoralCache/CoralCT for analysis (DeCarlo et al., 2025), while core locations and collection metadata are published through the USGS Geologic Core and Sample Database (DOI: 10.5066/F7319TR3) with links to CT slice imagery in a USGS ScienceBase repository (DOI: 10.5066/P139Y9H4). This archive provides a powerful dataset for evaluating environ-mental controls on coral growth, establishing restoration baselines, and improving coastal-hazard assessments in the face of global coral-reef declines.

American Somoa, Guam, Florida, Hawaii, U.S. Virgin↗
USGS2024

Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D

Numerical simulation of sediment transport and subsequent morphological evolution rely on accurate parameterizations of sediment characteristics. However, these data are often not available or are spatially and/or temporally limited. This study approaches the problem of limited sediment grain-size data with a series of simulations assessing model sensitivity to sediment parameters and initial bed composition configurations in Delft3D, leading to improved modeling practices. A previously validated Delft3D sediment transport and morphology model for Dauphin Island, Alabama, USA, is used as the benchmark case. A method for the generation of representative sediment grain sizes and their spatially varying distributions is presented via end-member analysis of in situ surficial sediment samples. Derived sediment classes and their spatial distributions are applied to two sensitivity case simulations with increasing bed composition complexity. First, multiple sediment classes are applied in a single fully mixed layer, regardless of sediment type. Second, multiple sediment classes are applied in a thin, fully mixed transport layer with underlayers containing only the non-cohesive sediment classes below. Simulations were carried out in a probabilistic, Delft3D MorMerge configuration to capture long-term morphology change for 10 years. We found there is sensitivity to the inclusion of additional sediment classes and sediment distribution made evident in bed level and morphology change. Inclusion of highly mobile fine sediments altered model results in each sensitivity case. The model was also found to be sensitive to initial bed composition in terms of bed level and morphology change, with notable differences between sensitivity cases on decadal timescales, indicating an armoring effect in the second sensitivity case, which used the transport and underlayer bed configuration. The results of this study offer guidance for numerical modelers concerned with sediment behavior in coastal and estuarine environments.

Alabama↗
USGS2024

Photogrammetry of the deep seafloor from archived unmanned submersible exploration dives

Large amounts of video images have been collected for decades by scientific and governmental organizations in deep (>1000 m) water using manned and unmanned submersibles and towed cameras. The collected images were analyzed individually or were mosaiced in small areas with great effort. Here, we provide a workflow for utilizing modern photogrammetry to construct virtual geological outcrops hundreds or thousands of meters in length from these archived video images. The photogrammetry further allows quantitative measurements of these outcrops, which were previously unavailable. Although photogrammetry had been carried out in recent years in the deep sea, it had been limited to small areas with pre-defined overlapping dive paths. Here, we propose a workflow for constructing virtual outcrops from archived exploration dives, which addresses the complicating factors posed by single non-linear and variable-speed vehicle paths. These factors include poor navigation, variable lighting, differential color attenuation due to variable distance from the seafloor, and variable camera orientation with respect to the vehicle. In particular, the lack of accurate navigation necessitates reliance on image quality and the establishment of pseudo-ground-control points to build the photogrammetry model. Our workflow offers an inexpensive method for analyzing deep-sea geological environments from existing video images, particularly when coupled with rock samples.

Journal of Marine Science and Engineering↗