Abstract
We present a machine learning-based measure-correlate-predict approach that predicts a multi-year time-series of optical turbulence strength (Cn2) with high accuracy (r = 0.78 at 16 locations) based on a single year of in-situ Cn2 measurements and reanalysis data.
| Original language | English |
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| Number of pages | 3 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | Propagation Through and Characterization of Atmospheric and Oceanic Phenomena, pcAOP 2024 - Part of Optica Imaging Congress - Toulouse, France Duration: 15 Jul 2024 → 19 Jul 2024 https://www.optica.org/events/congress/imaging_and_applied_optics_congress/program/propagation_through_and_characterization_of_atmosp/ |
Conference
| Conference | Propagation Through and Characterization of Atmospheric and Oceanic Phenomena, pcAOP 2024 - Part of Optica Imaging Congress |
|---|---|
| Country/Territory | France |
| City | Toulouse |
| Period | 15/07/24 → 19/07/24 |
| Internet address |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
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