Snow covered area (SCA) represents one of the largest components of the cryosphere that fluctuates seasonally. For the mountain west, the distribution and storage of snow is largely within the alpine and subalpine environments known to be sensitive to climate change. The accurate detection of SCA in these environments is critical to accurate climatological and hydrological forecasts and the detection of change in each. Satellite remote sensing can monitor large swaths of SCA but lacks the spatial and temporal resolution required to perfectly quantify its extent. The difficulty of monitoring SCA on the ground in mountainous terrain is compounded by the difficulty of measuring the environmental parameters that influence its distribution (Barry 2008). Satellite remote sensing retrieval data, combined with long-term mountain research stations such as the Niwot Ridge LTER, provide an ideal study site and climate record to address these issues. The disparity between the snow observed on the ground and that which is detected via satellite remote sensing has been adequately addressed in the alpine but resolution of this issue still remains for the subalpine forests. Studies using objective indices such as the Normalized Difference Snow Index (NDSI) combined with the Normalized Difference Vegetation Index (NDVI) (Hall et al. 1995) and the S3 index (Shimamura et al. 2006) provide good estimates (~ 90%) for unforested areas or during midwinter snowpack conditions. Models such as the TMSCAG (Painter et al. 2009a, Rosenthal and Dozier 1996) and more recently the MODSCAG (Painter et al. 2009a) are designed to detect snow cover at the subpixel resolution in the subalpine forests. The MODSCAG model performs well, up to 90% percent accuracy throughout most of the snow season but falters, accuracy reduced up to ~60%, during the snow melt season (Painter 2009b). For this study, snow depth measurements will be collected from three sites near the Niwot ridge LTER C1 site following methods similar to those of Veatch et al. (2009) and the Cold Land Processes Field Experiment (CLPX) (Cline et al. 2001, 2002). Hemispheric photography of the canopy and full snow pit analysis will also be collected throughout the 2011 snowmelt season. Meteorological data parameters will be provided by the established instrumentation networks from the C1 and AMERIFLUX sites. A LIDAR flyover of the site conducted during April-May and August of 2011 provides imagery of the three-dimensional structure of the forest canopy from which forest density can be derived. A comparison of the statistical methods used by Veatch et al. (2009) with the estimates from a physical model based on the observational data sets will also be conducted. Questions addressed by this study include the following: How robust is the assumption that the snow cover is homogenous under the forest canopy? What are the resulting patterns of snow coverage during the snow melt season? How important are these patches' of snow to the overall energy balance of the forest?
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Painter, T.H., K. Rittger, C. McKenzie, P. Slaughter, R. E. Davis, and J. Dozier. 2009a. Retrieval of subpixel snow covered area, grain size, and albedo from MODIS. Remote Sensing of Environment. 113: 868-879.
Painter, T.H., K. E. Rittger, J. Dozier. Assessment of the accuracy of current snow cover mapping algorithms for MODIS (Invited). AGU, Annual Meeting, 2009b, San Francisco, CA. C22A-02.
Rosenthal, W. and Dozier, J., 1996, Automated mapping of montane snow cover at subpixel resolution from the Landsat Thematic Mapper. Water Resources Research, 32, pp. 115-130.
Shimamura, Y., Izumi, T., Matsuyama, H., 2006, Evaluation of a useful method to identify snow-covered areas under vegetation- comparisons among a newly proposed snow index, normalized difference snow index, and visible reflectance. International Journal of Remote Sensing, 27, pp. 4867-4884.
Veatch, W., P.D. Brooks, J.R. Gustafson, and N.P. Molotch. 2009. Quantifying the effects of forest canopy cover on net snow accumulation at a continental, mid-latitude site. Ecohydrol. 2:115-128.