Application of a testbed for validating remote sensor data and retrieval algorithms

Author: Alan E. Lipton, Jean-Luc Moncet, John F. Galantowicz, H. Hu, Richard Lynch, S.-A. Boukabara, David Hogan, Robert d'Entremont and Yuguang He
Date: 
October 14, 2004
Type: 
Presentation
Venue: 
Preprints, SPIE conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization: An End-to-End System Perspective, 4–6 Aug, 2004., Denver, CO.
Citation: 

Lipton, A., J.-L. Moncet, J. Galantowicz, H. Hu, R. Lynch, S.-A.Boukabara, D. Hogan, R. d’Entremont, Y. He, 2004: Application of a testbed for validating remote sensor data and retrieval algorithms. Preprints, SPIE conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization: An End-to-End System Perspective, 4–6 Aug., Denver, CO.

The AER algorithm testbed has been applied to instruments measuring in spectra from the ultraviolet to the microwave. The sensor simulation component starts with environmental data from numerical weather prediction models, surface property and terrain databases, and imagers, and simulates the detailed sensor spatial and spectral sampling processes, radiative transfer, polarization, and detector characteristics. This simulation is integrated with algorithm execution, to provide end-to-end capability. The tools allow for simulation of specific sensor errors, and tracing of their impact through the algorithm process to the quality of the retrieved environmental products. A critical component of the testbed is its radiative transfer models, which employ state-of-the-science programs for line-by-line optical properties, for radiative transfer in scattering atmospheres, and for a variety of surfaces. Fast and accurate computational methods are incorporated, such as Optimal Spectral Sampling (OSS). Application examples are shown, including characterization of AMSU sensor data errors and retrieval performance evaluation, in which retrievals from the microwave sounder data and infrared image data contribute to the interpretation of remote sensing phenomena in cloudy environments.