Topographical and ecohydrological controls on land surface temperature in an alpine catchment
Della Chiesa S
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In mountain areas, land surface temperature (LST) is a key parameter in the surface energy budget and is controlled by a complex interplay of topography, incoming radiation and atmospheric processes, as well as soil moisture distribution, different land covers and vegetation types. In this contribution, the LST spatial distribution of the Stubai Valley in the Austrian Alps is simulated by the ecohydrological model GEOtop. This simulation is compared with ground observations and a Landsat image in order to assess the capacity of the model to represent land surface interactions in complex terrain, as well as to evaluate the relative importance of different environmental factors. The model describes the energy and mass exchanges between soil, vegetation and atmosphere. It takes account of land cover, soil moisture and the implications of topography on air temperature and solar radiation. The GEOtop model is able to reproduce the spatial patterns of the LST distribution estimated from remote sensing, with a correlation coefficient of 0·88 and minimal calibration of the model parameters. Results show that, for the humid climate considered in this study, the major factors controlling LST spatial distribution are incoming solar radiation and land cover variability. Along mountain ridges and south-exposed steep slopes, soil moisture distribution has only a minor effect on LST. North- and south-facing slopes reveal a distinct thermal behaviour. In fact, LST appears to follow the air temperature vertical gradient along north-facing slopes, while along south-facing slopes, the LST vertical gradient is strongly modified by land cover type. Both Landsat observations and model simulations confirm field evidence of strong warming of alpine low vegetation during sunny days and indicate that these effects have an impact at a regional scale. Our results indicate that in order to simulate LST in mountain environments using a spatially distributed hydrological model, a key factor is the capacity to explicitly simulate the effects of complex topography on the surface energy exchange processes.