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Anne W. Nolin and Christopher Daly

Abstract

One of the most visible and widely felt impacts of climate warming is the change (mostly loss) of low-elevation snow cover in the midlatitudes. Snow cover that accumulates at temperatures close to the ice-water phase transition is at greater risk to climate warming than cold climate snowpacks because it affects both precipitation phase and ablation rates. This study maps areas in the Pacific Northwest region of the United States that are potentially at risk of converting from a snow-dominated to a rain-dominated winter precipitation regime, under a climate-warming scenario. A data-driven, climatological approach of snow cover classification is used to reveal these “at risk” snow zones and also to examine the relative frequency of warm winters for the region. For a rain versus snow temperature threshold of 0°C the at-risk snow class covers an area of about 9200 km2 in the Pacific Northwest region and represents approximately 6.5 km3 of water. Many areas of the Pacific Northwest would see an increase in the number of warm winters, but the impacts would likely be concentrated in the Cascade and Olympic Ranges. A number of lower-elevation ski areas could experience negative impacts because of the shift from winter snows to winter rains. The results of this study point to the potential for using existing datasets to better understand the potential impacts of climate warming.

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Anne W. Nolin and Eileen A. Hall-McKim

Abstract

The interannual and intraseasonal variability of the North American monsoon is of great interest because a large proportion of the annual precipitation for Arizona and New Mexico arrives during the summer monsoon. Forty-one years of daily monsoon season precipitation data for Arizona and New Mexico were studied using wavelet analysis. This time-localized spectral analysis method reveals that periodicities of less than 8 days are positively correlated with mean daily precipitation during the 1 July–15 September monsoon period. Roughly 17% of the years indicate no significant periodicity during the monsoon period for either region and are associated with low monsoon precipitation. High- and low-frequency modes explain an equivalent percentage of the variance in monsoon precipitation in both Arizona and New Mexico, and in many years concurrent multiple periodicities occur. Wavelet analysis was effective in identifying the contribution of high-frequency modes that had not been discerned in previous studies. These results suggest that precipitation processes during the monsoon season are modulated by phenomena operating at synoptic (2–8 days) and longer (>8 days) time scales and point to the need for further studies to better understand the associated atmospheric processes.

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Susan Marshall, Robert J. Oglesby, and Anne W. Nolin

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A set of model runs was made with the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3 (CCM3) to investigate and help assess the relative roles of snow cover anomalies and initial atmospheric states on the subsequent accumulation and ablation seasons. In order to elucidate the physical mechanisms responsible for the large impact in one case but small impact in the other, two experiments with CCM3 were made that imposed an exaggerated initial snow cover [1-m snow water equivalent (SWE)] over the western U.S. domain. One run was started on 1 December, the other on 1 February. These runs made it clear that the high albedo of snow was the dominant physical process. An additional set of runs with realistic yearly snow anomalies was also made. Results suggest that for runs starting in February (late winter), the initial prescription of snow cover is more important than the initial atmospheric state in determining the subsequent evolution of snow cover. For runs starting in December (early winter), the results are less clear, with neither the initial snow cover nor the initial state of the atmosphere appearing to be the dominant factor. In February, when the sun is relatively high in the sky and days are longer, the albedo effect is a dominant factor; while in December the sun was too low in the sky and days too short for the albedo effect to be important. As the winter season progressed, the subsequent accumulation of snow eliminated the effects of the initial December anomalies.

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David J. Diner, Gregory P. Asner, Roger Davies, Yuri Knyazikhin, Jan-Peter Muller, Anne W. Nolin, Bernard Pinty, Crystal B. Schaaf, and Julienne Stroeve

The physical interpretation of simultaneous multiangle observations represents a relatively new approach to remote sensing of terrestrial geophysical and biophysical parameters. Multiangle measurements enable retrieval of physical scene characteristics, such as aerosol type, cloud morphology and height, and land cover (e.g., vegetation canopy type), providing improved albedo accuracies as well as compositional, morphological, and structural information that facilitates addressing many key climate, environmental, and ecological issues. While multiangle data from wide field-of-view scanners have traditionally been used to build up directional “signatures” of terrestrial scenes through multitemporal compositing, these approaches either treat the multiangle variation as a problem requiring correction or normalization or invoke statistical assumptions that may not apply to specific scenes. With the advent of a new generation of global imaging spectroradiometers capable of acquiring simultaneous visible/near-IR multiangle observations, namely, the Along-Track Scanning Radiometer-2, the Polarization and Directionality of the Earth's Reflectances instrument, and the Multiangle Imaging SpectroRadiometer, both qualitatively new approaches as well as quantitative improvements in accuracy are achievable that exploit the multiangle signals as unique and rich sources of diagnostic information. This paper discusses several applications of this technique to scientific problems in terrestrial atmospheric and surface geophysics and biophysics.

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