Approaches for aggregating heterogeneous surface parameters and fluxes for mesoscale and climate models

Land surface and climate processes possess dynamics and heterogeneities across a wide range of scales. This study explores the utility of, and procedures for, using local scale measurements to obtain large-scale information. An aggregation scheme is proposed to bridge the scale gap between the scale of measurements including remote sensors and climate and mesoscale models. The proposed scheme derives a set of effective parameters which obeys the energy balance equation exactly and partitions the surface fluxes accurately at different scales. It produces a unique set of aggregated land surface parameters that are easily measurable through remote sensing and have sound mathematical and physical basis. It is shown that aggregated ground heat flux, emissivity and albedo may be obtained by simple areally weighted averaging while temperature, aerodynamic and surface resistances require more involved aggregation operators. The effective surface temperature, although it requires a complicated operator involving subgrid-scale temperature and surface emissivity, is easily measurable through remote sensing. The proposed scheme was compared and contrasted with existing effective parameter approaches. It was shown that several effective parameters of the previous schemes can be easily derived from the proposed scheme by introducing additional assumptions and simplifications.