ML models predict optical turbulence from ERA5 data with better summer accuracy and solar radiation as the top feature, but performance varies by season and location.
Using an artificial neural network approa ch to estimate surface-layer optical turbulence at mauna loa, hawaii
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
physics.optics 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Learning from Translation: Seasonal Errors and Feature Importance of the ERA5 Turbulence Predictions
ML models predict optical turbulence from ERA5 data with better summer accuracy and solar radiation as the top feature, but performance varies by season and location.