[1] The distribution of snow and the energy flux components of snowmelt are intrinsic characteristics of the alpine water cycle controlling the location of source waters and the effect of climate on streamflow. Interannual variability of these characteristics is relevant to the effect of climate change on alpine hydrology. Our objective is to characterize the interannual variability in the spatial distribution of snow and energy fluxes of snowmelt in watersheds of a maritime setting, Tokopah Basin (TOK) in California's southern Sierra Nevada, and a continental setting, Green Lake 4 Valley (GLV4) in Colorado's Front Range, using a 12 year database (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) of hydrometeorological observations and satellite-derived snow cover. Snowpacks observed in GLV4 exhibit substantially greater spatial variability than in TOK (0.75 versus 0.28 spatial coefficient of variation). In addition, modeling results indicate that the net turbulent energy flux contribution to snowmelt in GLV4 is, on average, 3 times greater in magnitude (mean 29% versus 10%) and interannual variability (standard deviation 17% versus 6%) than in TOK. These energy flux values exhibit strong seasonality, increasing as the melt season progresses to times later in the year (R 2 ¼ 0.54-0.77). This seasonality of energy flux appears to be associated with snowmelt rates that generally increase with onset date of melt (0.02 cm d À2). This seasonality in snowmelt rate, coupled to differences in hydrogeology, may account for the observed differences in correspondence between the timing of snowmelt and timing of streamflow in these watersheds.

[1] We estimate the spatial distribution of daily melt-season snow water equivalent (SWE) over the Sierra Nevada for March to August, 2000August, -2012, by two methods: reconstruction by combining remotely sensed snow cover images with a spatially distributed snowmelt model and a blended method in which the reconstruction is combined with in situ snow sensor observations. We validate the methods with 17 snow surveys at six locations with spatial sampling and with the operational snow sensor network. We also compare the methods with NOAA's operational Snow Data Assimilation System (SNODAS). Mean biases of the methods compared to the snow surveys are À0.193 m (reconstruction), 0.001 m (blended), and À0.181 m (SNODAS). Corresponding root-mean-square errors are 0.252, 0.205, and 0.254 m. Comparison between blended and snow sensor SWE suggests that the current sensor network inadequately represents SWE in the Sierra Nevada because of the low spatial density of sensors in the lower/higher elevations. Mean correlation with streamflow in 19 Sierra Nevada watersheds is better with reconstructed SWE (r ¼ 0.91) versus blended SWE (r ¼ 0.81), snow sensor SWE (r ¼ 0.85), and SNODAS SWE (r ¼ 0.86). On the other hand, the correlation with blended SWE is generally better than with reconstructed, snow sensor, and SNODAS SWE late in the snowmelt season when snow sensors report zero SWE but snow remains in the higher elevations. Sensitivity tests indicate downwelling longwave radiation, snow albedo, forest density, and turbulent fluxes are potentially important sources of errors/uncertainties in reconstructed SWE, and domainmean blended SWE is relatively insensitive to the number of snow sensors blended.

[1] Linkages between permafrost distribution and lake surface-area changes in cold regions have not been previously examined over a large scale because of the paucity of subsurface permafrost information. Here, a first large-scale examination of these linkages is made over a 5150 km 2 area of Yukon Flats, Alaska, USA, by evaluating the relationship between lake surface-area changes during 1979-2009, derived from Landsat satellite data, and sublacustrine groundwater flow-path connectivity inferred from a pioneering, airborne geophysical survey of permafrost. The results suggest that the shallow (few tens of meters) thaw state of permafrost has more influence than deeper permafrost conditions on the evolving water budgets of lakes on a multidecadal time scale. In the region studied, these key shallow aquifers have high hydraulic conductivity and great spatial variability in thaw state, making groundwater flow and associated lake level evolution particularly sensitive to climate change owing to the close proximity of these aquifers to the atmosphere. Citation: Jepsen, S. M., C. I. Voss, M. A.Walvoord, B. J. Minsley, and J. Rover (2013), Linkages between lake shrinkage/expansion and sublacustrine permafrost distribution determined from remote sensing of interior Alaska, USA, Geophys.

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