Remote Sensing of Pan-Arctic Snowpack Thaw Using the SeaWinds Scatterometer

Remotely sensed estimates of snowpack 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 determined from approximately 25 km resolution daily radar backscatter data with observed daily river discharge time series and model simulated snowpack water content data for 52 basins (5000--10,000 km2) 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, the obs erved discharge data, and model snowpack water from the pan-Arctic Water Balance Model (PWBM). Radar-derived thaw shows general agreement with discharge increases (mean absolute difference, MAD = 21 days, r = 0.45), with better agreement (16 days) in basins with moderate--high runoff due to snowmelt. Even better agreement is noted when comparing the scatterometer-derived primary thaw timing with model simulated snow water increase (MAD = 14 days, r = 0.75). 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 compared scatterometer-derived date of the primary (maximum) thaw with the timing of simulated snow water increases from the PWBM. Good agreement is found across much of the pan-Arctic; almost half (49.4%) of the analyzed grid cells have an associated MAD of ≤ 7 days. MADs are 11.7 days for the Arctic basin in Eurasian and 15.1 days across North America. Mean biases are low; 2.1 and -3.1 days for Eurasia and North America respectively. Stronger backscatter response (high signal--low noise) is noted with higher snow cover, low to moderate tree cover and low topographic complexity. The greatest differences between the remotely sensed thaw timing and model snowmelt initiation are primarily due to the identification of two (or more) major thaw events during spring. This analysis suggests that active radar instruments such as the SeaWinds scatterometer offer the potential for monitoring high-latitude snowpack thaw at spati al scales appropriate for pan-Arctic applications in near real time. Potential applications include hydrological model verification, analysis of lags between snowmelt and river response, and determination of large-scale snow extent