HR: 14:10h
AN: B33D-03    [Abstracts]
TI: Evaluation of Operational Albedo Algorithms For AVHRR, MODIS and VIIRS: Case Studies in Southern Africa
AU: * Privette, J L
EM: jeff.privette@nasa.gov
AF: NASA's Goddard Space Flight Center, Code 923 NASA's GSFC, Greenbelt, MD 20771 United States
AU: Schaaf, C B
EM: schaaf@bu.edu
AF: Boston University, Dept. of Geography 675 Commonwealth Ave, Boston, MA 02215 United States
AU: Saleous, N
EM: nazmi@kratmos.gsfc.nasa.gov
AF: Raytheon STX, Code 922 NASA's GSFC, Greenbelt, MD 20771 United States
AU: Liang, S
EM: sliang@geog.umd.edu
AF: University of Maryland, Geography Department LeFrak Hall, College Park, MD 20742 United States
AB: Shortwave broadband albedo is the fundamental surface variable that partitions solar irradiance into energy available to the land biophysical system and energy reflected back into the atmosphere. Albedo varies with land cover, vegetation phenological stage, surface wetness, solar angle, and atmospheric condition, among other variables. For these reasons, a consistent and normalized albedo time series is needed to accurately model weather, climate and ecological trends. Although an empirically-derived coarse-scale albedo from the 20-year NOAA AVHRR record (Sellers et al., 1996) is available, an operational moderate resolution global product first became available from NASA's MODIS sensor. The validated MODIS product now provides the benchmark upon which to compare albedo generated through 1) reprocessing of the historic AVHRR record and 2) operational processing of data from the future National Polar-Orbiting Environmental Satellite System's (NPOESS) Visible/Infrared Imager Radiometer Suite (VIIRS). Unfortunately, different instrument characteristics (e.g., spectral bands, spatial resolution), processing approaches (e.g., latency requirements, ancillary data availability) and even product definitions (black sky albedo, white sky albedo, actual or blue sky albedo) complicate the development of the desired multi-mission (AVHRR to MODIS to VIIRS) albedo time series -- a so-called Climate Data Record. This presentation will describe the different albedo algorithms used with AVHRR, MODIS and VIIRS, and compare their results against field measurements collected over two semi-arid sites in southern Africa. We also describe the MODIS-derived VIIRS proxy data we developed to predict NPOESS albedo characteristics. We conclude with a strategy to develop a seamless Climate Data Record from 1982- to 2020.
UR: http://modarch.gsfc.nasa.gov/MODIS/LAND/VAL/terra/privette/
DE: 3322 Land/atmosphere interactions
DE: 3359 Radiative processes
DE: 1610 Atmosphere (0315, 0325)
DE: 1640 Remote sensing
DE: 0315 Biosphere/atmosphere interactions
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting