Solid Earth Science ESDR System
Yehuda Bock - PI, Scripps Institution of Oceanography
Building on NASA's investments in the measurement of crustal deformation from continuous GPS, the Solid Earth Science ESDR System (SESES) we will provide mature, long term Earth System Data Records (ESDRs) that support NASA's Earth Surface and Interiors (ESI) focus area, and meet the ESI science goals for understanding earthquakes and the processes that drive tectonic motion and crustal deformation. This project is responsive and directly relevant to the Group on Earth Observation's (GEO) Global Earth Observation System of Systems (GEOSS) strategic targets for building an integrated system of systems, specifically in the areas of Data Management,Science and Technology, and User Engagement, with the focus in the Disaster Resilience GEOSS Societal Benefits Area,
By leveraging work under several earlier and ongoing NASA projects, SESES will:
- Continue to provide multi-decade calibrated and validated GPS-derived deformation time series and deformation vectors, based on daily GPS data that include GPS networks in western North America. The time series are a unique product in terms of number of stations and duration (20 years), and have been modeled and catalogued for coseismic, postseismic and transient deformation, as well as instrumental offsets.
- Provide the following new multi-decade GPS-derived ESDRs:
- Expand current ESDR generation from the Western US to include global GPS sites.
- Troposphere delay time series for calibrating atmospheric delay errors in Interferometric Synthetic Aperture Radar (InSAR) that are one of the limiting InSAR error sources.
- Precipitable Water Vapor (PWV) time series for use in Probable Maximum Precipitation studies, historical weather event analysis, and studies of long-term water vapor trends.
- Fusion of GPS and seismic measurements at collocated stations to estimate three-dimensional high-rate displacement time series with mm precision, during significant historic seismic events (e.g., 2003 Mw 8.3 Tokachi-oki earthquake in Japan; 2010 Mw 7.2 El Mayor-Cucapah earthquake in northern Baja California; 2011 Mw 9.0 Tohoku-oki earthquake in Japan) and new events during the project duration.
Datasets to be used in constructing the ESDR include Global Positioning System data from multiple regional and global networks; seismic data (from broadband seismometer and accelerometers) collected at or near (1-2 km) of a GPS station; surface pressure and temperature data from onsite sensors, nearby weather stations, and weather models.
All ESDRs will be accessible through NASA’s Crustal Dynamics Data and Information System (CDDIS), and will also be archived at the project s database at University of California San Diego Scripps Orbit and Permanent Array Center, where they would be accessible through the project's GPS Explorer web portal. SESES IT system has been designed using modern IT tools and principles in order to be extensible to any geographic location, scale, natural hazard, and combination of geophysical sensor and related data.
The team will continue to provide value and support to ongoing NASA Earth data system evolution by participating in Data System Working Group on Technology Infusion. The project's product quality and accessibility will continue to be scrutinized by a community-based advisory committee.
No new algorithm development is required. All algorithms used in this project will represent NASA technology investments through NASA's Advanced Information Systems Technology (AIST) Program, Early Stage Innovations (ESI) and Advancing Collaborative Connections for Earth System Science (ACCESS) programs. Calibration and validation of the GPS measured deformation time series is done through a combined solution of two independently derived GPS position time series. In addition quality control tools based on Principal Component Analysis, developed under an AIST-08 project will be applied to the time series. Calibration and validation of the GPS troposphere and precipitable water series will be likewise done by comparing the independently derived parameters.
Last Updated: Nov 14, 2018 at 4:20 PM EST