Abstract
The surface energy balance has been modelled over the region of Sicily, Italy, in order to monitor the moisture status of natural vegetation and agricultural land by following the evolution of the evaporative fraction. In order to ensure the transferability of the approach throughout Europe, emphasis was placed on applying data from operationally available sources only. Daily meteorological parameters have been taken from the synoptic network, remote sensing data stem from the AVHHR sensor aboard the NOAA satellites, and land cover data have been taken from the European CORINE database.
In the one-source model EVA, the sensible heat flux has been estimated from the difference between the surface skin temperature and the surface-measured air temperature, and the formulation of a bulk aerodynamic resistance. The latent heat flux has been determined as the residual of the difference between the estimated available energy and the sensible heat flux. Additionally, daily rates of evapotranspiration have been estimated by assuming a constant evaporative fraction over the entire day. This simplistic approach is thought to make best use of the limited data available.
Validation by direct measurements of the energy balance components has been impossible, so that EVA model results had to be compared to few pan evaporation data, evapotranspiration estimates from the standard method of Priestley-Taylor and to results of the GCM of ECMWF. This comparison highlights the limited value of point measurements on the one hand and results from global circulation models on the other hand for validation purposes on the intermediate regional scale.
It is expected that near-future sensors will provide physical parameters more accurately so that more sophisticated models can be confidently applied in regions with a restricted number of ground measurements. In this sense part of the validation problem will be overcome in the future.
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Niemeyer, S., Vogt, J. (2001). Integration of operationally available remote sensing and synoptic data for surface energy balance modelling and environmental applications on the regional scale. In: Beniston, M., Verstraete, M.M. (eds) Remote Sensing and Climate Modeling: Synergies and Limitations. Advances in Global Change Research, vol 7. Springer, Dordrecht. https://doi.org/10.1007/0-306-48149-9_14
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DOI: https://doi.org/10.1007/0-306-48149-9_14
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