paper
2019
Observations & remote sensing
New model or method
Classical ML (trees, GP, linear, kernels) Journal
2019-02-15
008
Feb 2019
Florian Tornow, Carlos Doménech, Juergen Fischer
Journal of Atmospheric and Oceanic Technology
Neural networks with selected geophysical inputs convert EarthCARE clear-sky TOA radiance to flux with 2.7–4.0 W m-2 error, under the 10 W m-2 mission threshold.
On the Use of Geophysical Parameters for the Top-of-Atmosphere Shortwave Clear-Sky Radiance-to-Flux Conversion in EarthCARE
In one sentence. Neural networks with selected geophysical inputs convert EarthCARE clear-sky TOA radiance to flux with 2.7–4.0 W m-2 error, under the 10 W m-2 mission threshold.
Labels
- Topic
- Observations & remote sensing
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Global
- Data
- Satellite, ERA5 / reanalysis
- Status
- Research
- Identifiers
- DOI:10.1175/jtech-d-18-0087.1 OpenAlex:W2912937795
- Added
- 2026-10-22
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