Fast and Agile Data Assimilation Framework for MLT and VLEO Instrument Development

This proposed effort aims to develop a fast, modularized, and lightweight data assimilation. This project develops a fast, AI-compatible, and modular data assimilation (DA) framework using WACCM-X (the NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension; the core whole atmosphere general circulation model), ARTS (Atmospheric Radiative Transfer Simulator; the radiative transfer module), and NEDAS (Next-generation Ensemble Data Assimilation System; the DA module) to support mission and instrument development in the Mesosphere and Lower Thermosphere (MLT) and Very Low Earth Orbit (VLEO) environments. Bypassing the inflexible, slowly developing legacy systems that target at operational use, this innovation enables rapid impact assessment of new instruments. The capability directly targets infusion into Terrestrial Resource and Hazard Prediction (TRaHP) operational systems, supporting NASA’s Moon-to-Mars launch/re-entry needs and the accelerated delivery of high-priority space weather data for commercial and national security space operations. (DA) framework specifically designed to support mission and instrument development for the Mesosphere and Lower Thermosphere (MLT, 60-200 km) and Very Low Earth Orbit (VLEO, 200-400 km) environments. Current NASA legacy DA systems are computationally inflexible for evaluating new MLT instrument designs and lack AI compatibility. To overcome these bottlenecks, this project will integrate an agile and AI-friendly suite of open-source modules to enable quick impact assessment cycle of heliosphere weather forecast which will be directly tied to instrument parameters so to effectively speed-up the instrument development cycle. Building on an offline framework initiated under an FY26 IRAD, this project will develop a fully functional online DA framework and demonstrate its capabilities through two use cases: EZIE/THz instrument data assimilation and GNSS-POD derived mass density assimilation. Furthermore, the team will develop a digital-twin data assimilation component to prove the framework's AI compatibility. By creating this highly versatile ecosystem, the project directly supports the Terrestrial Resource and Hazard Prediction (TRaHP) SFA's strategic goal of eroding the artificial boundary between terrestrial Earth Science and Heliophysics space weather. Ultimately, this innovation will enable the rapid prototyping of orbital assets, provide accurate near-real-time environmental forecasts, and ensure Goddard maintains technical leadership as NASA and commercial sectors rapidly expand operations into VLEO.

Fully functional online DA framework integrating WACCM-X, ARTS, and NEDAS; two demonstrated use cases (EZIE/THz instrument DA; GNSS-POD mass density assimilation); digital-twin DA component for AI compatibility; rapid impact assessment of new MLT instruments.

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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