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Satellite and Atmospheric Data Fusion for Improved Characterization of Thermodynamic Profiles
- Truvace record
- TRV-2026-2539raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Controlled or validated comparison
- Sources
- 1 sourcePeer-reviewed
- sha256
- 398d66c6c043…check it
Abstract This paper presents Total Atmospheric Characterization–Thermodynamics (TAC-Thermo), a global artificial intelligence (AI) data fusion system to improve satellite-retrieved thermodynamic profiles with a focus on data-sparse regions. TAC-Thermo uses available satellite retrievals and numerical weather prediction model output to upscale satellite-retrieved temperature and moisture profiles that can capture thermodynamic features (up to ∼12 km) on sigma vertical coordinate levels (i.e., 1.0–0.2). TAC-Thermo…
The gain
In a validation against radiosonde soundings, the TAC-Thermo AI system had smaller dewpoint temperature errors than NUCAPS and the GFS at every sigma level, and filled in sounding data where radiosondes are absent.
What this doesn’t fix
The gridded product was examined for only a 24-hour period, and its temperature errors were close to, not clearly below, the best NUCAPS and GFS values.
Sources
1 on file- Artificial Intelligence for the Earth Systemsdoi:10.1175/aies-d-25-0092.1
Cite this record
v1Truvace Impact Record TRV-2026-2539, v1: “Satellite and Atmospheric Data Fusion for Improved Characterization of Thermodynamic Profiles.” Truvace, 2026-11-12. /record/TRV-2026-2539 (accessed on the day you copy it). sha256 398d66c6c0433009…
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1 versionEvery change made to this record since it was first published, and why. Nothing has changed since it went up.
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