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Abstract: Towards filling gaps and supplementing the Earth Radiation Budget record with broadband fluxes derived from Spectral Radiances using Machine Learning (AGU25)

Towards filling gaps and supplementing the Earth Radiation Budget record with broadband fluxes derived from Spectral Radiances using Machine Learning

Maria Zita Hakuba, Jet Propulsion Laboratory, Caltech, Pasadena, United States, Matthew D Lebsock, Jet Propulsion Laboratory, Pasadena, United States, Robert C Wilson, NASA Jet Propulsion Laboratory, Pasadena, CA, United States and Joao Teixeira, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
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