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NASA Earth Science Technology for Earth System Digital Twins (ESDT)
  • +4
  • Nikunj Oza,
  • Jacqueline LeMoigne,
  • Marge Cole,
  • Robert Morris,
  • Laura Rogers,
  • Michael Seablom,
  • Benjamin Smith
Nikunj Oza
NASA Ames Research Center

Corresponding Author:nikunj.c.oza@nasa.gov

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Jacqueline LeMoigne
NASA
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Marge Cole
NASA Goddard Space Flight Center
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Robert Morris
NASA Ames Research Center
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Laura Rogers
NASA Langley Research Center
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Michael Seablom
NASA
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Benjamin Smith
NASA Jet Propulsion Laboratory
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Abstract

As part of NASA’s Earth Science Technology Office, the Advanced Information Systems Technology (AIST) Program defines an Earth System Digital Twin (ESDT) as an interactive and integrated multidomain, multiscale, digital replica of the state and temporal evolution of Earth systems that dynamically integrates: Relevant Earth system models and simulations Other relevant models (e.g., related to the world’s infrastructure and human activity); 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 Analytics and artificial intelligence tools. Effective ESDTs will enable users to run hypothetical or “what-if” scenarios to improve the continuous assessment and prediction of Earth system processes, natural phenomena and human activities as well as their many interactions, and to ensure optimal mitigation and response to these phenomena. Toward this goal, the AIST Program is developing individual technologies and a few pilots. Some of the technologies that are being considered include: agile interoperability between measurement acquisition and science investigations; moving from mono-discipline to multi-discipline interconnected models; digital thread developments to provide communication links to all digital twin capabilities and to enable design requirements, records, provenance, and system reconfigurations to be easily coordinated; concepts and technologies for developing “federated ESDTs”; multi-scale simulations, statistics, uncertainty quantification, and causality methodologies; high-end computing and surrogate models to optimize the computational efficiency of “what-if” investigations; and innovative user interfaces and visualization methods capable of visualizing complex systems of systems.