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A multitemporal method to map snow cover in mountainous terrain is proposed to guide Landsat climate data record (CDR) development. The Landsat image archive including MSS, TM, and ETM + imagery was used to construct a prototype Landsat snow cover CDR for the interior northwestern United States. Landsat snow cover CDRs are designed to capture snow-covered area (SCA) variability at discrete bi-monthly intervals that correspond to ground-based snow telemetry (SNOTEL) snow-water-equivalent (SWE) measurements. The June 1 bi-monthly interval was selected for initial CDR development, and was based on peak snowmelt timing for this mountainous region. Fifty-four Landsat images from 1975 to 2011 were preprocessed that included image registration, top-of-the-atmosphere (TOA) reflectance conversion, cloud and shadow masking, and topographic normalization. Snow covered pixels were retrieved using the normalized difference snow index (NDSI) and unsupervised classification, and pixels having greater (less) than 50% snow cover were classified presence (absence). A normalized SCA equation was derived to independently estimate SCA given missing image coverage and cloud-shadow contamination. Relative frequency maps of missing pixels were assembled to assess whether systematic biases were embedded within this Landsat CDR. Our results suggest that it is possible to confidently estimate historical bi-monthly SCA from partially cloudy Landsat images. This multitemporal method is intended to guide Landsat CDR development for freshwaterscarce regions of the western US to monitor climate-driven changes in mountain snowpack extent.

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Abstract:Daily swath MODIS Terra Collection 6 fractional snow cover (MOD10_L2) estimates were validated with two-day Landsat TM/ ETM + snow-covered area estimates across central Idaho and southwestern Montana, USA. Snow cover maps during spring snowmelt for 2000, 2001, 2002, 2003, 2005, 2007, and 2009 were compared between MODIS Terra and Landsat TM/ ETM + using least-squared regression. Strong spatial and temporal map agreement was found between MODIS Terra fractional snow cover and Landsat TM/ETM + snow-covered area, although map disagreement was observed for two validation dates. High-altitude cirrus cloud contamination during low snow conditions as well as late season transient snowfall resulted in map disagreement. MODIS Terra's spatial resolution limits retrieval of thin-patchy snow cover, especially during partially cloudy conditions. Landsat's image acquisition frequency can introduce difficulty when discriminating between transient and resident mountain snow cover. Furthermore, transient snowfall later in the snowmelt season, which is a stochastic accumulation event that does not usually persist beyond the daily timescale, will skew decadal snow-covered area variability if bi-monthly climate data record development is the objective. As a quality control step, ground-based daily snow telemetry snow-water-equivalent measurements can be used to verify transient snowfall events. Users of daily MODIS Terra fractional snow products should be aware that local solar illumination and sensor viewing geometry might influence fractional snow cover estimation in mountainous terrain. Cross-sensor interoperability has been confirmed between MODIS Terra and Landsat TM/ETM + when mapping snow from the visible/infrared spectrum. This relationship is strong and supports operational multi-sensor snow cover mapping, specifically climate data record development to expand cryosphere, climate, and hydrological science applications.

The objective of this research was to determine whether the dendroclimatic responses of young Quercus alba (aged 29-126 years) differ from those of old Q. alba (149-312 years). We collected Q. alba increment cores across a range of size classes from Buffalo Mountain Natural Area Preserve, an oak-hickory forest in southcentral Virginia, USA. Tree cores were crossdated and raw ring widths were detrended to remove the influence of increasing circumference with age, microsite, and local stand dynamics. Standardized ring widths were averaged to develop two master chronologies from the 20 oldest and youngest trees. Ring-width indices were correlated with temperature, precipitation, and Palmer Drought Severity Index (PDSI). Annual tree-ring growth in old and young Q. alba was significantly correlated with precipitation from the previous growing season, but was not significantly correlated with temperature. Only the old trees showed a significant correlation between annual ring width and PDSI. These results may indicate that growth in old trees is more sensitive to drought than in young trees. If future climate change includes the predicted increase in midgrowing season droughts, tree-level responses are likely to be age-dependent with older trees experiencing relatively greater reductions in growth.