Framework to utilize turbulent flux measurements for mesoscale models and remote sensing applications
P 1.19 in Ecosystem Function
Meteorologically measured fluxes of energy and matter between the surface and the atmosphere originate from a source area of certain extent, located in the upwind sector of the device. The spatial representativeness of such measurements is strongly influenced by the heterogeneity of the landscape. The footprint concept is capable of linking observed data with spatial heterogeneity. This study aims at upscaling EC derived fluxes to a coarser grid size of mesoscale models or moderate resolution remote sensing data.
Here an upscaling scheme is presented, utilizing footprint modelling of the observations and SVAT modelling of fluxes from adjacent land use types, influencing the grid representative flux. The performance of the upscaling routine is evaluated with real datasets, which are considered to be land use specific fluxes in a simple virtual landscape. The measurements stem from the LITFASS experiment 2003 in Lindenberg, Germany and the respective modelled timeseries were derived by the SVAT model SEWAB. Flux contributions of each land-use type are estimated using a forward lagrangian stochastic model. Results show, that the error of accepting the measurements unchanged as grid representative flux can be reduced with the upscaling routine by 30%. This raises potential for further application of this scheme, although the validation measures should be advanced for the intended use in future studies.