391 resultados para net radiation partitioning


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Independent measurements of radiation, sensible and latent heat fluxes and the ground heat flux are used to describe the annual cycle of the surface energy budget at a high-arctic permafrost site on Svalbard. During summer, the net short-wave radiation is the dominant energy source, while well developed turbulent processes and the heat flux in the ground lead to a cooling of the surface. About 15% of the net radiation is consumed by the seasonal thawing of the active layer in July and August. The Bowen ratio is found to vary between 0.25 and 2, depending on water content of the uppermost soil layer. During the polar night in winter, the net long-wave radiation is the dominant energy loss channel for the surface, which is mainly compensated by the sensible heat flux and, to a lesser extent, by the ground heat flux, which originates from the refreezing of the active layer. The average annual sensible heat flux of -6.9 W/m**2 is composed of strong positive fluxes in July and August, while negative fluxes dominate during the rest of the year. With 6.8 W/m**2, the latent heat flux more or less compensates the sensible heat flux in the annual average. Strong evaporation occurs during the snow melt period and particularly during the snow-free period in summer and fall. When the ground is covered by snow, latent heat fluxes through sublimation of snow are recorded, but are insignificant for the average surface energy budget. The near-surface atmospheric stratification is found to be predominantly unstable to neutral, when the ground is snow-free, and stable to neutral for snow-covered ground. Due to long-lasting near-surface inversions in winter, an average temperature difference of approximately 3 K exists between the air temperature at 10 m height and the surface temperature of the snow.

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The ground surface temperature is one of the key parameters that determine the thermal regime of permafrost soils in arctic regions. Due to remoteness of most permafrost areas, monitoring of the land surface temperature (LST) through remote sensing is desirable. However, suitable satellite platforms such as MODIS provide spatial resolutions, that cannot resolve the considerable small-scale heterogeneity of the surface conditions characteristic for many permafrost areas. This study investigates the spatial variability of summer surface temperatures of high-arctic tundra on Svalbard, Norway. A thermal imaging system mounted on a mast facilitates continuous monitoring of approximately 100 x 100 m of tundra with a wide variability of different surface covers and soil moisture conditions over the entire summer season from the snow melt until fall. The net radiation is found to be a control parameter for the differences in surface temperature between wet and dry areas. Under clear-sky conditions in July, the differences in surface temperature between wet and dry areas reach up to 10K. The spatial differences reduce strongly in weekly averages of the surface temperature, which are relevant for the soil temperature evolution of deeper layers. Nevertheless, a considerable variability remains, with maximum differences between wet and dry areas of 3 to 4K. Furthermore, the pattern of snow patches and snow-free areas during snow melt in July causes even greater differences of more than 10K in the weekly averages. Towards the end of the summer season, the differences in surface temperature gradually diminish. Due to the pronounced spatial variability in July, the accumulated degree-day totals of the snow-free period can differ by more than 60% throughout the study area. The terrestrial observations from the thermal imaging system are compared to measurements of the land surface temperature from the MODIS sensor. During periods with frequent clear-sky conditions and thus a high density of satellite data, weekly averages calculated from the thermal imaging system and from MODIS LST agree within less than 2K. Larger deviations occur when prolonged cloudy periods prevent satellite measurements. Futhermore, the employed MODIS L2 LST data set contains a number of strongly biased measurements, which suggest an admixing of cloud top temperatures. We conclude that a reliable gap filling procedure to moderate the impact of prolonged cloudy periods would be of high value for a future LST-based permafrost monitoring scheme. The occurrence of sustained subpixel variability of the summer surface temperature is a complicating factor, whose impact needs to be assessed further in conjunction with other spatially variable parameters such as the snow cover and soil properties.