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values. Continued development of new regional schemes which account for microwave emmission<br />
from forests should improve large-scale SWE estimates. Poor agreements among all SWE products<br />
—particularly across parts of western Eur<strong>as</strong>ia—are noted in are<strong>as</strong> with low discharge variability.<br />
Pre-screening to eliminate b<strong>as</strong>ins with low flow or insufficient variability would likely improve <strong>the</strong><br />
SWE vs. Q agreements.<br />
Results of <strong>the</strong> covari<strong>an</strong>ce <strong>an</strong>alysis using alternate temporal integrations to derive pre-melt SWE<br />
(or Q) suggest that our choice of a fixed interval for spring, ie. April–June, is not <strong>the</strong> primary cause<br />
of <strong>the</strong> relatively low R 2 s. Fur<strong>the</strong>rmore, we conclude that much of <strong>the</strong> inter<strong>an</strong>nual variability in river<br />
discharge must be influenced by factors o<strong>the</strong>r th<strong>an</strong> b<strong>as</strong>in SWE storage variations. The unexplained<br />
variability is likely due to a combination of effects from physical processes (sublimation, infiltration)<br />
<strong>an</strong>d errors in spatial SWE. Relatively good agreement between simulated <strong>an</strong>d observed spring Q<br />
suggests that hydrological models c<strong>an</strong> be useful in underst<strong>an</strong>ding <strong>the</strong> SWE-to-Q linkages. Our<br />
results provide a benchmark of <strong>the</strong> relationship between <strong>the</strong> solid precipitation input <strong>an</strong>d spring<br />
discharge flux, <strong>an</strong>d demonstrate that hydrological models driven with re<strong>an</strong>alysis data c<strong>an</strong> provide<br />
SWE estimates sufficient for use in validation of remote-sensing <strong>an</strong>d GCM SWE fields. Additional<br />
studies using daily discharge data to better qu<strong>an</strong>tify snowmelt runoff will fur<strong>the</strong>r facilitate SWE<br />
product evaluations <strong>an</strong>d <strong>the</strong> underst<strong>an</strong>ding of linkages in arctic hydrological system.<br />
ACKNOWLEDGEMENTS<br />
The authors th<strong>an</strong>k Richard Lammers, Ernst Linder, <strong>an</strong>d Dominik Wisser (University of New<br />
Hampshire) for frequent useful discussions, <strong>an</strong>d Kyle McDonald (Jet Propulsion Laboratory) for <strong>the</strong><br />
thaw timing data. We also th<strong>an</strong>k Chris Milly (NOAA/GFDL) for providing <strong>the</strong> LaD SWE estimates,<br />
<strong>an</strong>d Ross Brown (Environnement C<strong>an</strong>ada) for <strong>the</strong> CCIN data. This study w<strong>as</strong> supported by <strong>the</strong><br />
NSF ARCSS program <strong>an</strong>d NSF gr<strong>an</strong>ts OPP-9910264, OPP-0230243, OPP-0094532, <strong>an</strong>d NASA gr<strong>an</strong>t<br />
NAG5-9617.<br />
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