HR: 1340h
AN: C23A-0942    [Abstracts]
TI: Improved Snow Cover Retrievals from Satellite Passive Microwave Data over the Tibet Plateau: The need for atmospheric corrections over high elevations
AU: * Savoie, M H
EM: savoie@nsidc.org
AF: NSIDC/CIRES University of Colorado at Boulder, 449 UCB, Boulder, CO 80309, United States
AU: Wang, J
EM: james.r.wang@nasa.gov
AF: NASA Goddard Space Flight Center, Mail Code 975 Bldg 33, Room A416, Greenbelt, MD 20771, United States
AU: Brodzik, M J
EM: brodzik@nsidc.org
AF: NSIDC/CIRES University of Colorado at Boulder, 449 UCB, Boulder, CO 80309, United States
AU: Armstrong, R L
EM: rlax@nsidc.org
AF: NSIDC/CIRES University of Colorado at Boulder, 449 UCB, Boulder, CO 80309, United States
AB: During the past four decades much important information on continental to hemispheric scale snow extent and variability has been provided by satellite remote sensing using both optical and microwave data. The Tibet Plateau is the only large geographic region in the Northern Hemisphere where the microwave retrievals tend to consistently disagree with snow cover climatologies derived from optical data. Initial speculation as to the cause of this significant overestimate by microwave retrievals has included the following: 1) soil type 2) frozen soil 3) widespread presence of frozen lakes. Our analysis has eliminated these explanations and we present an alternative explanation based on the influence of the atmosphere on the microwave retrievals. Numerous microwave snow cover algorithms have been developed with approaches ranging from the theoretical to the purely empirical. However, in most all cases, when these algorithms are actually applied, they are tuned or calibrated to return snow extents that match well with the optical satellite data over a particular study area. Therefore, although the algorithms might have been initially developed using brightness temperatures measured at ground level or from aircraft, they have been adjusted to provide the most accurate results possible when applying brightness temperatures measured from satellite. This simply means that these algorithms have implicitly accounted for the presence of an atmosphere because the surface or scene brightness temperature values applied in the algorithms have actually passed through the atmosphere along their path to reach the satellite sensor. Therefore, given that an algorithm is tuned to return favorable results across a relatively standard atmospheric thickness between the ground surface and the satellite, a potential problem arises when the same algorithm is applied to an extremely high elevation target where the atmosphere thickness is greatly reduced, such as on the Tibet Plateau. Using radiosonde data from both the more typical lower elevations and the exceptional Tibet Plateau, combined with a radiative transfer model, we derive the coefficients required to make the necessary corrections to retrievals over land surfaces at high elevations.
DE: 0700 CRYOSPHERE (4540)
DE: 0736 Snow (1827, 1863)
DE: 0758 Remote sensing
DE: 9320 Asia
SC: Cryosphere [C]
MN: 2007 Fall Meeting