992 resultados para Shasta snow wreath


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Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I-SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I-SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000-2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis.

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It is known that the Amundsenisen Icefield in Southern Spitzbergen (Svalbard achipelago) is temperate with an upper layer of snow and firn. It is an accumulation area and, though ice/water mass balance is clearly subject to time evolution, observation data on the long-term elevation changes over the past 40 years (Nuth et al., 2010) allow to assume constant icefield surface. Within our study of the plausibility of a subglacial lake (Glowacki et al., 2007), here, we focus on the sensitivity of the system to the thermal effect of the firn and snow layers.

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Within our study of the plausibility of a subglacial lake under the Amundsenisen Icefield in Southern Spitzbergen, Svalbard achipelago (Glowacki et al., 2007), here we focus on the sensitivity of the system to the thermal effect of the firn and snow layers. Rough heat balance analysis shows that the firn layer plays an important role by driving the heat release to the atmosphere, so that its influence on the ice-water phase transition cannot be neglected (Bucchignani et al., 2012).

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We report experimental results of near-surface winter temperatures along and adjacent to the channel bed of a High Arctic river on Melville Island, Canada. Temperature loggers 5cm below the ground surface in areas where the terrain suggests varying snow accumulation patterns revealed that the maximum winter difference between air and near-surface temperatures ranged from 0 to +30°C during the winter of 2012–13, and that shallow near-surface freezing conditions were delayed for up to 21 days in some locations. Cooling to -10°C was delayed for up to 117 days. Modelled temperature at the top of permafrost indicates that permafrost at locations with thick snow can be up to 8°C warmer than those with thin snow. This thermal evidence for an ameliorated surface environment indicates the potential for substantial extended microbial and biogeochemical cycling during early winter. Rapid thaw of the bed during initiation of snowmelt in spring also indicates a high degree of hydrological connectivity. Therefore, snow-filled channels may contribute to biogeochemical and aquatic cycling in High Arctic rivers.

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1Recent studies demonstrated the sensitivity of northern forest ecosystems to changes in the amount and duration of snow cover at annual to decadal time scales. However, the consequences of snowfall variability remain uncertain for ecological variables operating at longer time scales, especially the distributions of forest communities. 2The Great Lakes region of North America offers a unique setting to examine the long-term effects of variable snowfall on forest communities. Lake-effect snow produces a three-fold gradient in annual snowfall over tens of kilometres, and dramatic edaphic variations occur among landform types resulting from Quaternary glaciations. We tested the hypothesis that these factors interact to control the distributions of mesic (dominated by Acer saccharum, Tsuga canadensis and Fagus grandifolia) and xeric forests (dominated by Pinus and Quercus spp.) in northern Lower Michigan. 3We compiled pre-European-settlement vegetation data and overlaid these data with records of climate, water balance and soil, onto Landtype Association polygons in a geographical information system. We then used multivariate adaptive regression splines to model the abundance of mesic vegetation in relation to environmental controls. 4Snowfall is the most predictive among five variables retained by our model, and it affects model performance 29% more than soil texture, the second most important variable. The abundance of mesic trees is high on fine-textured soils regardless of snowfall, but it increases with snowfall on coarse-textured substrates. Lake-effect snowfall also determines the species composition within mesic forests. The weighted importance of A. saccharum is significantly greater than of T. canadensis or F. grandifolia within the lake-effect snowbelt, whereas T. canadensis is more plentiful outside the snowbelt. These patterns are probably driven by the influence of snowfall on soil moisture, nutrient availability and fire return intervals. 5Our results imply that a key factor dictating the spatio-temporal patterns of forest communities in the vast region around the Great Lakes is how the lake-effect snowfall regime responds to global change. Snowfall reductions will probably cause a major decrease in the abundance of ecologically and economically important species, such as A. saccharum.

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The atmospheric chemistry of iodine and bromine in polar regions is of interest due to the key role of halogens in many atmospheric processes, particularly tropospheric ozone destruction. Bromine is emitted from the open ocean but is enriched above first-year sea ice during springtime bromine explosion events, whereas iodine is emitted from biological communities hosted by sea ice. It has been previously demonstrated that bromine and iodine are present in Antarctic ice over glacial-interglacial cycles. Here we investigate seasonal variability of bromine and iodine in polar snow and ice, to evaluate their emission, transport and deposition in Antarctica and the Arctic and better understand potential links to sea ice. We find that bromine enrichment (relative to sea salt content) and iodine concentrations in polar ice do vary seasonally in Arctic snow and Antarctic ice and we relate such variability to satellite-based observations of tropospheric halogen concentrations. Peaks of bromine enrichment in Arctic snow and Antarctic ice occur in spring and summer, when sunlight is present. Iodine concentrations are largest in winter Antarctic ice strata, contrary to contemporary observations of summer maxima in iodine emissions.