Abstract
An infrastructure for earth science data is emerging across the globe based on common data models and web services. As we evolve from custom file formats and web sites to standards-based web services and tools, data is becoming easier to distribute, find and retrieve, leaving more time for science. We describe recent advances that make it easier for ocean model providers to share their data, and for users to search, access, analyze and visualize ocean data using MATLAB® and Python®. These include a technique for modelers to create aggregated, Climate and Forecast (CF) metadata convention datasets from collections of non-standard Network Common Data Form (NetCDF) output files, the capability to remotely access data from CF-1.6-compliant NetCDF files using the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS), a metadata standard for unstructured grid model output (UGRID), and tools that utilize both CF and UGRID standards to allow interoperable data search, browse and access. We use examples from the U.S. Integrated Ocean Observing System (IOOS®) Coastal and Ocean Modeling Testbed, a project in which modelers using both structured and unstructured grid model output needed to share their results, to compare their results with other models, and to compare models with observed data. The same techniques used here for ocean modeling output can be applied to atmospheric and climate model output, remote sensing data, digital terrain and bathymetric data.
Highlights
Ocean modelers typically require many different types of input data for forcing, assimilation and boundary conditions, and routinely produce GB or larger amounts of output data
Future work to build on this infrastructure was recommended, including improved techniques for searching datasets, better support for unstructured grids and observational data, server-side subsetting for unstructured grids, more tools for common analysis tasks, and tools for scientific analysis and visualization environments in addition to Matlab
The Network Common Data Form (NetCDF)-Java library is capable of reading NetCDF, HDF5, GRIB and GRIB2 data files into a common data model, which allows a uniform representation of the data regardless of input format
Summary
Ocean modelers typically require many different types of input data for forcing, assimilation and boundary conditions, and routinely produce GB or larger amounts of output data. Users were able to access these standardized data streams using a variety of tools, from simple map-based browsing, to more sophisticated 3D visualization, to full scientific exploration on their desktop computers With this success, future work to build on this infrastructure was recommended, including improved techniques for searching datasets, better support for unstructured grids and observational data, server-side subsetting for unstructured grids, more tools for common analysis tasks, and tools for scientific analysis and visualization environments in addition to Matlab. Many of these were developed in the COMT and other IOOS activities, while other components were developed external to IOOS in the international geoscience community These include new standards for unstructured grid model output and for observational data (e.g., time series, profiles, trajectories), new services and access tools for consuming these standardized data, more analysis tools for Matlab users, and new tools for Python users. Data Model feature types (by the use of CF-1.6 and UGRID-0.9 conventions), it can be distributed uniformly by appropriate services and consumed by standards-based clients, providing data interoperability for the user
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