Remote sensing of snow thaw at the pan-Arctic scale using the SeaWinds scatterometer

  • Michael A. Rawlins
  • , Kyle C. McDonald
  • , Steve Frolking
  • , Richard B. Lammers
  • , Mark Fahnestock
  • , John S. Kimball
  • , Charles J. Vörösmarty

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

Remotely sensed estimates of snow thaw 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 snow 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 observed discharge data, and model snow 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 snow thaw. 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; discrepancies for over half of the analyzed grid cells are less than one week. 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 seasonal snow accumulation, low to moderate tree cover and low topographic complexity. Although our results show inconsistent performance along coastal regions and warmer southerly parts of the study domain, active radar instruments such as SeaWinds offer the potential for monitoring high-latitude snow thaw at spatial scales appropriate for pan-Arctic applications in near real time. Applications include hydrological model verification, analysis of lags between snow thaw and river response, and determination of large-scale snow extent.

Original languageEnglish
Pages (from-to)294-311
Number of pages18
JournalJournal of Hydrology
Volume312
Issue number1-4
DOIs
StatePublished - Oct 10 2005

Funding

The authors gratefully acknowledge Charles Thompson (JPL) and Jason Lee (Caltech) for their assistance with processing the QuikSCAT data. QuikSCAT data were obtained from the JPL Physical Oceanography DAAC through the NASA Ocean Vector Wind Science Team. Alexander Shiklomanov (UNH/AARI) is acknowledged for frequent discussions regarding the river discharge data. We also thank Stanley Glidden (UNH) and Erika Podest (JPL) for their programming assistance. This research was supported by the NSF ARCSS program and NSF grants OPP-9910264, OPP-0230243, OPP-0094532, and NASA grant NAG5-9617. This work was performed at the University of New Hampshire's Water Systems Analysis Group and at the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space Administration.

FundersFunder number
OPP-0230243, OPP-0094532, OPP-9910264
National Aeronautics and Space AdministrationNAG5-9617

    Keywords

    • Pan-Arctic
    • Runoff
    • Scatterometer
    • SeaWinds
    • Snow

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