Earth System Digital Twins (ESDT) Technology for NASA Earth Science

For NASA's Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as an interactive and integrated multidomain, multiscale, digital replica of the state and temporal evolution of Earth systems. It dynamically integrates: relevant Earth system models and simulations; other relevant models (e.g., related to the world's infrastructure); continuous and timely (including near real time and direct readout) observations (e.g., space, air, ground, over/underwater, Internet of Things (IoT), socioeconomic); long-time records; as well as analytics and artificial intelligence tools. Effective ESDTs enable users to run hypothetical scenarios to improve the understanding, prediction of and mitigation/response to Earth system processes, natural phenomena and human activities as well as their many interactions.

An ESDT is a type of integrated information system that, for example, enables continuous assessment of impact from naturally occurring and/or human activities on physical and natural environments.

AIST ESDT strategic goals are to:
1. Develop information system frameworks to provide continuous and accurate representations of systems as they change over time;
2. 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;
3. Provide the tools to conduct "what if" investigations that can result in actionable predictions.

The AIST ESDT thrust is developing capabilities toward the development of future digital twins of the Earth or of subcomponents of the Earth. This will enable the development of an overarching framework that will integrate New Observing Strategies (NOS) to enable new observation measurements, i.e., multi-source, coordinated, dynamic and responsive to needs and requests defined by Analytic Collaborative Frameworks (ACF) that enable agile science investigations fusing and analyzing very large amounts of diverse data. NOS and ACF capabilities along with open access to various science, infrastructure and human data, interconnected modeling, data assimilation, simulations, surrogate modeling, high-performance computing and advanced visualization, will define a powerful framework that could be utilized for local, regional or global and/or thematic digital twins.

This presentation will describe a general overview of the AIST ESDT vision including prior work done in the areas of NOS and ACF as well as current and upcoming ESDT projects.