HR: 14:25h
AN: C33A-04    [Abstracts]
TI: Detection of Severe Rain on Snow events using passive microwave remote sensing
AU: * Grenfell, T C
EM: tcg@atmos.washington.edu
AF: University of Washington, Department of Atmospheric Sciences MS 351640 University of Washington, Seattle, WA 98195, United States
AU: Putkonen, J
EM: putkonen@u.washington.edu
AF: University of Washington, Department of Earth and Space Sciences University of Washington, Seattle, WA 98195, United States
AB: Severe wintertime rain-on-snow (ROS) events create a strong ice layer or layers in the snow on arctic tundra that act as a barrier to ungulate grazing. These events are linked with large-scale ungulate herd declines via starvation and reduced calf production rate when the animals are unable to penetrate through the resulting ice layer. ROS events also produce considerable perturbation in the mean wintertime soil temperature beneath the snow pack. ROS is a sporadic but well-known and significant phenomenon that is currently very poorly documented. Characterization of the distribution and occurrence of severe rain-on-snow events is based only on anecdotal evidence, indirect observations of carcasses found adjacent to iced snow packs, and irregular detection by a sparse observational weather network. We have analyzed in detail a particular well-identified ROS event that took place on Banks Island in early October 2003 that resulted in the death of 20,000 musk oxen. We make use of multifrequency passive microwave imagery from the special sensing microwave imager satellite sensor suite (SSM/I) in conjunction with a strong-fluctuation-theory (SFT) emissivity model. We show that a combination of time series analysis and cluster analysis based on microwave spectral gradients and polarization ratios provides a means to detect the stages of the ROS event resulting from the modification of the vertical structure of the snow pack, specifically wetting the snow, the accumulation of liquid water at the base of the snow during the rain event, and the subsequent modification of the snowpack after refreezing. SFT model analysis provides quantitative confirmation of our interpretation of the evolution of the microwave properties of the snowpack as a result of the ROS event. In particular, in addition to the grain coarsening due to destructive metamorphism, we detect the presence of the internal water and ice layers, directly identifying the physical properties producing the hazardous conditions. This analysis offers the potential to characterize both the frequency and global distribution of ROS using satellite passive microwave imagery.
DE: 0718 Tundra (9315)
DE: 0734 Icing (aufeis, naled)
DE: 0736 Snow (1827, 1863)
DE: 0758 Remote sensing
DE: 0798 Modeling
SC: Cryosphere [C]
MN: 2007 Fall Meeting