8.4
The characterization of snow coverage ablation patterns in the subalpine forest of the Niwot ridge long-term ecological research site
Heather M. McIntyre, Univ. of Colorado, Boulder, CO; and R. G. Barry
Snow covered area (SCA) represents the largest single component 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) detect snow cover at the subpixel resolution but may include incorrect assumptions about the homogeneity of snow cover 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 2010 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 is scheduled for the end of April that will provide the three-dimensional structure of the forest canopy from which forest density can be derived as well as a ‘snow-on' survey of the area. A second LIDAR flight will be conducted in late August to provide a ‘snow-off' survey that can then be subtracted from the ‘snow-on' survey to provide snow depth during the spring survey. A combination of the ground-based snow survey depths and those of the LIDAR flight provide the necessary data to perform a preliminary validation of the MODSCAG model. This study will address the following questions: ‘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?
References:
Barry, R.G. 2008, Mountain Weather and Climate, 3rd Ed., Cambridge University Press, New York, pp. 506.
Cline D, Armstrong R, Davis R, Elder K, Liston G. 2001. NASA Cold Land Processes Field Experiment Plan 2001–2004. NASA Earth Science Enterprise, Land Surface Hydrology Program.
Cline D, Armstrong R, Davis R, Elder K, Liston G. 2002. Updated 2003. CLPX-Ground: ISA Snow Depth Transects and Related Measurements , In situ data edited by Parsons M, Brodzik MJ (eds). National Snow and Ice Data Center: Boulder, CO.
Hall, D.K., Riggs, G.A., and Salomonson, V.V., 1995, Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data. Remote Sensing of the Environment, 54, pp. 127-137.
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.
Session 8, Mountain Hydrometeorology
Tuesday, 31 August 2010, 4:00 PM-5:45 PM, Alpine Ballroom A
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