HR: 17:35h
AN: C42C-07    [PDF]
TI: Remote Sensing of pan-Arctic Snowpack Thaw Using the Seawinds Scatterometer
AU: * Rawlins, M A
EM: michael.rawlins@unh.edu
AF: Water Systems Analysis Group, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824 United States
AU: McDonald, K C
EM: kyle.mcdonald@jpl.nasa.gov
AF: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 United States
AU: Frolking, S
EM: steve.frolking@unh.edu
AF: Water Systems Analysis Group, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824 United States
AU: Lammers, R B
EM: richard.lammers@unh.edu
AF: Water Systems Analysis Group, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824 United States
AU: Fahnestock, M
EM: mf@eos.sr.unh.edu
AF: Water Systems Analysis Group, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824 United States
AU: Kimball, J S
EM: johnk@ntsg.umt.edu
AF: School of Forestry/NTSG, University of Montana, Missuola, MT 59812 United States
AU: Vorosmarty, C J
EM: charles.vorosmarty@unh.edu
AF: Water Systems Analysis Group, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824 United States
AB: Springtime snowmelt is a major hydrological event across the pan-Arctic. Melt is typically simulated using time series climate data which, given a sparse network of Arctic meteorological stations, may not accurately capture detailed between-station spatial and temporal variability. Remotely-sensed estimates of snowpack freeze/thaw state offer the potential of more complete spatial coverage across remote, undersampled areas such as the terrestrial Arctic drainage basin. We compared the timing of spring thaw de termined from approximately 25\,km resolution daily radar backscatter data with observed daily river discharge time series for 52 basins (5000--10,000 km$^2$) across Canada and Alaska for the spring of 2000. Algorithms for identifying critical thaw transitions were applied to daily backscatter time series from the Seawinds scatterometer aboard NASA QuikSCAT. Radar-derived thaw shows general agreement with discharge increases in basins with moderate--high ($> \sim$\,120mm) runoff due to snowmelt. Average absolute difference in those basins was 16.2 days. Good correspondence is found across higher latitude basins in western Canada and Alaska, while the largest discrepancies appear at the driest watersheds with lower snow and daily discharge amounts. Extending this analysis to the entire pan-Arctic drainage basin, we compare scatterometer-derived date of the final spring thaw event with snow cover disappearance from composited satellite visible-band snow cover data. Good agreement is found across much of the pan-Arctic, with distinct zones of larger discrepancies across mainly southern parts of the basin. The largest disagreement occurs across south-central Asia and is likely due to high tree cover and topographic complexity. Stronger backscatter response in the signal-to-noise ratio is seen with higher snow cover, low--moderate tree cover and low topographic complexity. This analysis suggests that active radar instruments such as the Seawinds scatterometer offer the potential for monitoring high-latitude snowpack thaw and may lead to a better understanding of the timing and linkages between snowmelt and hydrologic response.
DE: 1833 Hydroclimatology
DE: 1860 Runoff and streamflow
DE: 1863 Snow and ice (1827)
SC: Cryosphere [C]
MN: 2003 Fall Meeting