NASA NTRS · 20190028555
MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records
Abstract
Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.
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Fu, Dejian, Bowman, K. W., Miyazaki, K., Kulawik, S. S., Worden, J. R., Worden, H. M., Livesey, N. J., Payne, V. H., Luo, M., Natraj, V., Yu, S., Veefkind, P., Aben, I., Landgraf, J., Flynn, L. E., Yong, H., Liu, X., Strow, L. L., Irion, F., Fishbein, E.. 2016-03-22. MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records. https://ntrs.nasa.gov/citations/20190028555
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