Monitoring mountain snowpack evolution using near-surface optical and thermal properties

We developed a near-surface moisture index (NSMI) that models relative moisture using visible and thermal spectra. The NSMI tracks the evolution of spring snowmelt and has potential MODIS applications. An analytical radiative transfer model for computing directional hemispherical reflectance and emissivity derived from the delta-Eddington approximation to the radiative transfer equation was used to produce the NSMI. Modelled reflectance and emissivity, as a function of grain size, were used to produce the NMSI feature space, constructed from the normalized difference snow index (NDSI) on the abscissa and brightness temperature (Tb) on the ordinate. As grain size increases, the dynamic range (sensitivity) of NDSI decreases, saturating around 400-450 μm grain radius. Tb values for various grain sizes at fixed kinetic temperatures between 245 and 273 K and the NDSI were used to construct a simulated NSMI. Field measurements of surface wetness, surface/near-surface grain size, average pack temperature and surface temperature for late February and March were validated in Fraser, Colorado, against measured NSMI using a scene from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Ground-based measurements indicate significant changes in snow surface properties, representing a warming pack across three Cold Land Processes Experiment (CLPX) intensive study areas (ISAs) from February to March. Surface and average pack temperatures in March were warmer for all three sites. ASTER-measured reflectance and Tb were sampled from each CLPX ISA and used to construct the NMSI. The lower elevation ISA (i.e. St Louis Creek) demonstrated higher mean Tb and lower mean NDSI, and the higher elevation ISA (i.e. Alpine) showed higher mean NDSI and lower mean Tb. ASTER-derived NSMI demonstrated behaviour consistent for simulations with deviations due to topography, vegetation, and regional heterogeneity.