Earth System Digital Twin for Wildfire

Earth System Digital Twin for Wildfire is sponsored by NASA. This project, funded by a NASA grant, develops an innovative artificial intelligence system designed to forecast wildfire progression and evaluate its impact on air quality.

Earth System Digital Twins - NASA Earth Science and Technology Office Earth System Digital Twin Towards understanding the evolution and interactions of Earth’s most complicated systems The Advanced Information Systems Technology (AIST) program leads NASA’s Earth System Digital Twins (ESDT) efforts, developing novel technologies for integrating diverse Earth and human activity models, continuous observations and information system capabilities to provide unified, comprehensive representations and predictions that can be utilized for monitoring as well as for developing actionable information and supporting decision making.

Using insights generated from its Novel Observing Strategies (NOS) and Analytic Collaborative Frameworks (ACF) efforts, AIST pioneers ESDTs that could be used to help researchers better understand the fundamental Earth systems that impact everything from wildfires to climate change.

Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an ESDT are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models and Impact Assessment capabilities.

The Digital Replica is fed by continuous and targeted diverse observations, powered by Data Assimilation and Fusion, and provides an accurate representation of the current state of the system. Forecasting is facilitated by advanced computational capabilities, Machine Learning (ML) and Surrogate Modeling, and provides real-time or near-real-time prediction of future states of the system.

Finally, Impact Assessment uses the Digital Replica and forecasting capabilities with ML, causality, uncertainty quantification and advanced computation and visualization capabilities for running large amounts of simulated predictions quickly and at various spatial and temporal scales, opening the door to investigating “what-if” scenarios.

These will allow to understand better the impact of one system on another one, and better predict Earth Science events, e.g., severe weather events. This third component provides hypothetical future states of the system.

The latest AIST project solicitation requested technologies dedicated to furthering AIST’s three strategic ESDT goals, which are: To develop information system frameworks that provide continuous and accurate representations of systems as they change over time.

To mirror various Earth Science systems and utilize the combination of Data Analytics, Artificial Intelligence, Digital Thread and state-of-the-art models to help predict the Earth’s response to various phenomena. To provide the tools to conduct “what-if” investigations that can result in actionable predictions.

These goals will allow future Earth System Digital Twins to better represent, predict, and investigate complex Earth system phenomena. In total, AIST selected thirteen projects to further develop its ESDT efforts according to these strategic principles. These projects will explore technologies for better ESDT infrastructure, ML-surrogate modeling for ESDT applications, ACF for ESDT applications, and fully-functioning ESDT prototypes.

A complete list of selected AIST-21 projects can be found here. In addition to funding specific projects related to NASA’s Earth System Digital Twins objectives, AIST supports a number of workshops dedicated to facilitating productive conversations about ESDT technologies. Information about the latest workshops can be found here.

2023 – Standards for Interoperable Digital Twins Workshop September 18, 2023 / 11:00 am – 2:00 pm (ET) 2 / Virtual + Presentations from the 2023 Workshop 2022 – Earth Systems Digital Twin (ESDT) Workshop (Co-Organized with Earth Science Information Partners, ESIP) October 26-28, 2022 / Virtual + Get the Workshop Report (pdf)