Topographical and ecohydrological controls on land surface temperature in an alpine catchment

Abstract

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 0Ð88 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.

Seasonality of MODIS LST over Southern Italy and correlation with land cover, topography and solar radiation

“…7 and 8) confirms the well-known relationship between surface temperature and topography. In fact, LST decreases with increasing elevation [Hais and Kučera, 2009] for two major reasons: air temperature decreases with elevation and vegetation tends to be vertically organized [Bertoldi et al, 2010]. Our results highlight a significant difference in this relationship between the day-and night-time LST.…”

“…Indeed, higher elevation regions are characterized by average monthly LST lower than the lowlands and this difference is greater during the summer months (June to August) when, for example, the plain area of the Apulia region is warmer than the higher regions along the Apennines. Moreover, mountain areas are characterized by extreme variability of topography (steep slopes and altitude variations) which could also determine a significant variability of LST [Bertoldi et al, 2010] …”

“…Vegetation characteristics play a primary role on how incoming solar radiation, which during the day is the direct source of energy, affects LST [Geiger et al, 2003]. The different effects of incoming radiation on the land cover types are mainly related to their stature and structure which influence turbulent heat transfer, radiation divergence and transpiration [Korner et al, 2003;Wohlfahrt et al, 2003;Bertoldi et al, 2010], hence LST. The absence of solar radiation at night annul the role of vegetation; indeed, the points of LST are homogeneously scattered along the regression line for all months of the year (Fig.…”

“…In this study we analyze day-time and night-time MODIS LST over Southern Italy as provided by the MOD11A2 product to investigate spatio-temporal variability of the surface temperature as a function of the land cover, topography (altitude) and potential solar radiation. According to previous studies, topography, land cover and incoming solar radiation and land cover are the major controlling factors on LST spatial distribution [Bertoldi et al, 2010]. Due to the relatively small size of the study area, latitudinal changes, which also influence surface temperatures, can be assumed negligible.…”

Modelling Evapotranspiration and the Surface Energy Budget in Alpine Catchments

“…Vegetation is organized along altitudinal gradients, and canopy structural properties influence turbulent heat transfer processes, radiation divergence (Wohlfahrt et al, 2003), surface temperature (Bertoldi et al, 2010), therefore transpiration, and, consequently, ET.…”