Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/1/1998
Publication Date: N/A
Citation: Interpretive Summary: The total amount of solar energy reflected from the earth's surface from the visible through the shortwave infrared, known as albedo, is of interest for surface energy balance studies (energy balance affects water resources) and weather and climate studies. Albedo is to be acquired globally by the next generation of satellites to be launched in 1999. The procedure presented in this paper separates albedo as measured under a specific atmospheric condition, called apparent albedo, from albedo that is independent of atmospheric conditions, called inherent albedo. Inherent albedo is more useful as it can be used to calculate apparent albedo for different atmospheric conditions and is more representative of the surface. A new procedure for obtaining inherent albedo is proposed that uses a neural network. Use of albedo as calculated from satellite data has been shown to result in improved weather forecasts, especially for drought and heavy precipitation.
Technical Abstract: Land surface albedo is a critical parameter affecting climate and is required by global and regional climatic modeling and surface energy balance monitoring. Surface albedo retrieved from satellite observations at one atmospheric condition may not be suitable for application to other atmospheric conditions. In this paper the authors separate the apparent surface albedo from the inherent surface albedo, which is independent of atmospheric conditions. The results show that spectral inherent albedos are different from spectral apparent albedos in many cases. Total shortwave apparent albedos under both clear and cloudy conditions are also significantly different from their inherent total shortwave albedos. The conversion coefficients of the surface inherent narrow band albedos derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multiangle Imaging SpectroRadiometer) instruments to the surface broadband inherent albedo are reported. A new approach of predicting broadband inherent albedos from MODIS or MISR top-of-atmosphere (TOA) narrowband albedos using a neural network is proposed. The simulations show that surface total shortwave and near-infrared inherent albedos can be predicted accurately from TOA narrowband albedos without atmospheric information, whereas visible inherent albedos cannot.