Avaluació amb imatges de satèl.lit de les propietats físiques del sòl requerides en models meteorològics

Abstract

Mesoscale models, with grid resolution higher than synoptic models, and with advanced physical parameterizations, have been an important tool for meteorological research over the past twenty years. Important improvements on mesoscale models have occurred in the last decade. The availability of high-performance workstations at affordable prices; the sharing of mesoscale models within the community; and finally the real-time accessibility of forecast data from the operational runs; have allowed using mesoscale models for real-time numerical weather prediction (NWP) at high resolutions (~1 km). As mesoscale models continue to increase in spatial resolution, correctly treating the land surface processes is becoming increasingly important for the model to be able to capture local mesoscale circulations induced by land surface forcing. Mesoscale models are incorporating progressively advanced land surface modules in order to properly initialize the state of the ground. Physical model improvements should be complemented with more accurate surface properties initiation data. The present work is focused in this point. An operational methodology has been developed, in order to calculate, from satellite imagery, the surface properties for Catalonia, in the NE of Spain. Satellite observations constitute the only available means for global or regional repetitive monitoring of the surface properties at homogeneous resolution. Prior to calculations, a bibliographical research has been done, in order to choose the most adequate methodology according to the remote sensing data available and the studied region. Monthly mean surface parameters have been calculated for the working region from an AVHRR data set of year 2000. Besides the resulting images, surface parameters have also been calculated for the land-use categories in the region. Calculated parameters are: Albedo Emissivity Normalized Difference vegetation Index (NDVI) Surface temperature Thermal inertia In order to test the obtained parameters, two simulations have been done with the MM5 mesoscale model. The Fifth-Generation NCAR / Penn State Mesoscale Model (MM5) is a limited-area, non-hydrostatic, terrain-following sigma-coordinate model designed to simulate or predict mesoscale and regional-scale atmospheric circulation. A first simulation, using MM5 default values, has been compared with a second simulation where the local physical parameters have been introduced. Besides the change of the surface parameters, the default MM5 land-use map has also been changed, using a more recent land-use map of the region. Results have shown that differences in surface parameters basically rely on thermal inertia. Besides, the land-use maps comparison had shown important differences between classifications that also affect the final composition of surface parameters that get into the model. Modifications on the second simulation have been sufficiently significant to produce variations in the performance of the model. The cloud development differs basically in the location and dimensions of the clouds, that drives to a different superficial radiative budget affecting the evolution of air temperature at low levels. The different results in cumulus simulation produced important differences in the surface wind field and the updrafts. The changes introduced are sufficiently significant to obtain also slight variations in the pattern of accumulated precipitation for the simulated period. Comparisons with ground measurements of wind and temperature have been done in the test regions. Similar errors are obtained with the two land-use maps and physical parameters, without a clear improvement in the performance of the meteorological model. The simulations done in this work contributes evidence to the high influence of surface scheme applications of mesoscale models at high spatial resolution. In the context of dialogue between remote sensing scientists and numerical climate modelers, it is expected that more research should be done to investigate the sensibility of the mesoscale models to improvements in the surface properties characterization.