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A winning proposal for the Innovative Research Program, 2005: Realization of Snow/Vegetation Interactions Using Field SpectroscopyInvestigators: Noah Molotch (Visiting Fellow) and Thomas Painter (NSIDC) Objective: Our objective is to quantify the impact of vegetation on snow metamorphism (i.e. snow grain size and liquid water content). The broader impact is an improved understanding of hydrologic response to land cover change. A feedback loop between vegetation and snow exists in which the distribution of snow and the timing of snowmelt largely control vegetation health during the growing season while vegetation intercepts snowfall and dramatically alters snow / atmosphere energy exchange and therefore the mass balance of the snow cover. Previous works have not been able to directly link vegetation-altered energy flux to alterations in snow cover ablation because quantitative measurements of snowpack microstructure are extremely time consuming. The proposed research will use field spectroscopy coupled with contact illumination to rapidly measure the vertical and horizontal stratigraphic distribution of grain size and liquid water content (Figure 1a) in snow trenches excavated surrounding coniferous vegetation (Figure 1b). The rapid acquisition of snow grain size and liquid water content measurements afforded using field optical spectroscopy will allow us to quantify the spatio-temporal variation in snow metamorphism surrounding vegetation. The proposed research is unique in that it will be the first attempt to bridge the gap between vegetation-induced alterations to snowpack / atmosphere energy exchange and snowpack mass balance. Research Theme: Advanced Observing and Modeling Systems. Background and Importance Studies of snow / vegetation interactions have primarily been performed in high-latitude regions (60 – 70°). In such regions snowmelt rates are negatively correlated with snow water equivalent; shallower areas melt faster than deeper areas. Due to snow interception by trees snow depth often decreases from crown-edge to tree trunks (Figure 1b) (Faria et al., 2000). Thus, snowpack metamorphic rates and grain size may increase with proximity to tree trunks. Much less is known about these interactions at continental lower latitude (30 – 40°) sites, where lower solar zenith angles (i.e. higher incident solar radiation) and lower atmospheric emissivities (i.e. lower incident longwave radiation) may cause snowmelt energy to decrease with increasing canopy density. Understanding the effect of vegetation on snow metamorphic rates is necessary to mathematically represent the physics of snowmelt under forest canopies. Such an understanding is a vital step to explicitly representing snow / vegetation interactions in distributed hydrologic models. Characterizing the influence of vegetation on snow metamorphism is difficult using standard procedures (i.e. a hand-lens) because it is extremely time consuming and lacks repeatability. To reduce the field time required to obtain measurements of snow characteristics we propose to use an Analytical Spectral Devices FR field spectroradiometer (ASD-FR) coupled with an ASD High Intensity Contact Probe (Figure 1a). The ASD-FR samples reflectance, radiance, and irradiance in the wavelength range 350-2500 nm at 3-10 nm spectral resolution. While the coupling of the ASD-FR with the contact probe has been used to infer mineralogy for studies of swelling soils, it has not been used to determine stratigraphic information of snow.  Figure 1. (a) Snow grain size stratigraphy measured at 2 cm sampling interval using the ASD-FR, Red Mountain Pass, CO. (b) Excavated snow trench extending radially from a coniferous tree trunk, Wolf Creek Pass, CO. - note the increase in snow depth with distance from the tree. We will analyze ASD-FR spectra for snow grain size (Nolin and Dozier, 2000) and liquid water content (Green et al., 2002). Our approach is unique in that information will be obtained through a snow column, where previous work has focused only on properties of the surface snow. This important step will extend existing hyperspectral approaches for snow to a 2-dimensional (and by extension 3-d) domain. These two dimensional, vertical images of snow grain size will illuminate previously unexplored interactions between vegetation and snow. What makes this innovative? To date the influence of coniferous vegetation on snowpack microstructure has not been documented. Thus, the proposed research is innovative in that it will quantify the influence of vegetation on snow metamorphism both vertically through the snowpack and horizontally at increasing distances from the vegetation. The application of spectroscopy to measuring snow / vegetation interactions is a new methodology with the potential to advance understanding of the linkages between vegetation and snowpack microstructure beyond any previous attempts. Expected Outcome and Impact: By utilizing an unbiased and rapid technique for monitoring snow properties we will be able to collect spatially continuous (both vertically and horizontally) measurements of snow grain size and liquid water content. This innovative approach will enable us to answer the questions: 1) how does snow grain size change with proximity to vegetation?; 2) how does the control of vegetation on grain size and liquid water content change through the snow accumulation and snowmelt seasons?; and 3) do the feedbacks between vegetation and snowpack metamorphism change as a function of vegetation density? We intend to summarize results pertaining to these questions in a peer-reviewed forum. This research will have an impact on hydrological modeling of seasonally snow covered systems as snow cover ablation rates must be parameterized separately in forested versus unforested areas. The improved understanding of snow vegetation interactions will also impact our understanding of how ecosystems respond to climate variability. Research Plan: The research will consist of a series of intensive observation periods (IOP’s) in which spectroscopic measurements of snow grain size and liquid water content will be made in cardinal directions surrounding six previously selected trees in a mixed conifer forest site in the Valles Caldera National Preserve (VCNP), Jemez Mountains, New Mexico. The VCNP has been chosen as there are substantial leveraging opportunities in the form of housing, snowmobiles, and hydrometeorological instrumentation, focused on other aspects of hydrological / ecological feedbacks. Existing observations of sap flow, CO2 and H2O vapor flux, snow depth and soil moisture will provide information on the response of the vegetation to water inputs and water related stress. At multiple heights above, within and below the canopy existing observations of wind speed, net radiation, temperature and relative humidity will allow us to ascertain the influence of the vegetation on snow surface / atmosphere energy exchange. The characterization of snow grain size distribution surrounding the vegetation proposed under this research will link leveraged observations of snow surface / atmosphere interactions and vegetation response to water inputs / water stress. IOP I will focus on studying snow / vegetation interactions during the premaximum accumulation season (February). IOP II will focus on the wet / dry snow transition period (late March) and IOP III (mid-April) will focus on the ablation season. References Faria, D.A., Pomeroy, J.W., and Essery, R.L.H. (2000), Effect of covariance between ablation and snow water equivalent on depletion of snow-covered area in a forest, Hydrological Processes, 14: 2683- 2695. Green, R. O., Dozier, J., Roberts, D. A., and Painter, T. H. (2002), Spectral snow reflectance models for grain size and liquid water fraction in melting snow for the solar reflected spectrum, Annals of Glaciology, 34: 71-73. Nolin, A. W., and Dozier, J. (2000), A hyperspectral method for remotely sensing the grain size of snow, Remote Sensing of Environment, 74(2): 207-216. |
216 UCB