High Performance Multidisciplinary Open Standard Data Services to Serve Terrestrial Environmental Modeling
The primary objective of this proposal is to advance the availability of Land Processes Distributed Active Archive Center (LP-DAAC) Moderate Resolution Imaging Spectroradiometer (MODIS) derived products and the Langley Research Center (LARC) Clouds and the Earth's Radiant Energy System (CERES) data sets to land-surface modelers. Model development and associated scientific assessments that are part of the U.S. Geological Survey National Water Census (NWC) and National Climate Change and Wildlife Science Center’s (NCCWSC) network of academic Climate Science Centers (CSC) will be applied to demonstrate the data service outcomes of this work.
The U.S. Geological Survey’s (USGS) Center for Integrated Data Analytics (CIDA), a software development team specializing in scalable services for multidisciplinary data sharing and access needs, will lead this effort. CIDA data managers and software developers will work with the LP-DAAC and LARC to implement and vet robust services for their data sets and with USGS science and model development teams to demonstrate the services utility.
These web service interfaces will be implemented in two widely used USGS models. The Soil Water Balance Model that calculates a spatially distributed soil water balance and Software for Assissted Habitat Modeling where the services will be used directly to build and run species distribution models for landscape management decision making. Additional scientific applications around impacts of climate and land use on the hydrologic cycle and ecosystems are being identified and will be presented in the final proposal.
CIDA staff have working relationships with the Unidata Program Center team responsible for NetCDF-Java and the THREDDS Data Server, and the Open Source Geospatial team responsible for GeoTools and GeoServer. These two open-source teams are community hubs for implementation of production-grade web servers that can provide numerous source data formats in a variety of output formats through standard web service interfaces.
NASA datasets will be represented using these, and possibly other server implementations. Any software modifications necessary to map NASA data into the applicable common data model will be implemented and committed back to an open-source project. In this way, updates to the open-source projects will be compatible with NASA data going forward.
The CIDA’s Geo Data Portal (GDP) allows environmental modelers to access simple server-side processing that extracts meaningful summaries of very large data. The GDP is implemented to allow remote access to any data available via a suite of international data and service standards. As part of this proposal, Geo Data Portal
processing capabilities will be deployed close to the MODIS and CERES data to help provide easy access and value added products to data consumers.
This proposal will include a range of functionality from data discovery to access and processing mature open source projects from both climate and geospatial science domains. The same patterns are being used assist the USGS NCCWSC and NWC (among other initiatives) to access data from, share data with, and disseminate data to partners. We propose to bring the MODIS and CERES data products into this data partnership.
Significance to solicitation:
This proposal is directly applicable to the ACCESS program goals. Multimission, Multiinstrument goals will be achieved through the application of both CERES and MODIS data products. The primary technical goal of the proposal is the application of tools and technologies that improve discovery, access, and ease of use of data products. A major emphasis of this proposal is on access to data and data products for modelling various processes in the hydrology and ecology domains. The outcomes of this proposal will allow environmental data consumers to access data from systems in USGS, NOAA, NASA, and others using the same tools.
David Blodgett - PI, U.S. Geological Survey
Page Last Updated: May 5, 2019 at 11:07 PM EDT