- Community Spotlight, Success Stories, Uncategorized
- Satellite Science & Environmental Intelligence
Evaluating the Use of Earth Observations Digital Twin Technologies
Earth Observations Digital Twin technologies are data analytics, artificial intelligence, and advanced modeling technologies that provide an estimate of the true state of the Earth. An Earth Systems Digital Twin is observations-based and grid-flexible with multiple components and high-resolution data over space and time to capture all available observations and feed a variety of direct observations to users. Adding or removing data is flexible, cost-efficient, and agile with fast processing. NOAA’s National Environmental Satellite, Data, and Information Service (NESDIS) is exploring the use of this technology.
Through their joint venture program, they contracted three companies to each developed a prototype to explore this technology. CSS employee owners (formerly Riverside staff) were responsible for evaluating these prototypes. Our staff evaluated the code for each Earth Observations Digital Twin prototype and explored using them for enhancing the ability to process, monitor, quality-control, consolidate, fuse, and assimilate environment observations and streamline the satellite data ground processing. Our staff provided feedback and recommendations to NESDIS regarding the validity and integrity of using an Earth Observations Digital Twin, and whether or not they could be used for potential future applications.
Learn more about how NESDIS is exploring the use of Earth Observations Digital Twin.
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Advancing Severe Weather Predictions with Artificial Intelligence
As artificial intelligence (AI) and machine learning (ML) technologies evolve in Earth sciences, CSS employee owners (formerly Riverside staff) are growing our expertise in this field. CSS employee owners are advancing technologies for our client, NOAA’s Center for Satellite Applications and Research (STAR). Our staff have developed a framework, exploiting modern AI/ML techniques, to rapidly…
Developing a Database for Ecosystem Service Models
CSS scientists have been major developers and contributors to the online U.S. Environmental Protection Agency’s EcoService Models Library (ESML) database since its inception in 2012. The ESML database contains detailed but concise descriptions of ecosystem service models to facilitate the selection of models by ecosystem scientists for a variety of management and research applications. The…
Contributing to Wind Energy Area Designations
The Bureau of Ocean Energy Management (BOEM) recently announced two Wind Energy Areas (WEAs) in the Gulf of Mexico. The WEAs are located off the coasts of Galveston, Texas, and Lake Charles, Louisiana and have the potential to power nearly three million homes. BOEM collaborated with the National Oceanic and Atmospheric Administration (NOAA) to identify…