Estimation of Energy Fluxes and Soil Moisture From AATSR, MERIS and SimSphere Land Surface Process Model
Petropoulos, George1; Carlson, Toby2

Use of simulation process models combined with Earth Observation (EO) data provides a promising direction towards deriving accurately spatiotemporal estimates of key parameters characterising land surface interactions such as latent (LE) and sensible (H) heat fluxes as well as soil surface moisture.

Such approaches aim to combine the horizontal coverage and spectral resolution of remote sensing data with the vertical coverage and fine temporal continuity of those models. Use of such techniques is at present also investigated for operational implementation scenario.

One such synergistic approach is the so-called "triangle" method, which is based on a contextual interpretation of a satellite-derived scatterplot of land surface temperature (Ts) versus a Fractional Vegetation Cover (Fr) combined with a SVAT model .

In our study we present the results obtained from the implementation of this technique using satellite observations from the Advanced Along Track Scanning Radiometer (AATSR) and Medium Resolution Imaging Spectrometer (MERIS), combined with the SimSphere SVAT model. Accuracy of the investigated methodology is verified using concurrent validated in-situ observations from operational ground observational networks from different regions in Europe representing a variety of climatic, topographic and environmental conditions. Main findings are presented and discussed herein, underlying also the main challenges that still hinder accurate spatiotemporal estimation of these key land surface parameters from space.

The present work was conducted in the framework of the PROgRESSIon (Prototyping the Retrievals of Energy Fluxes and Soil Moisture Content) project, funded by the European Space Agency (ESA) Support to Science Element (STSE). The project aims at exploring the development of a series of prototype products for the estimation of turbulent heat fluxes and SMC derived from the synergy of SimSphere land surface model with EO observations from advanced technologically designed medium resolution ESA-funded or co-funded instruments.

KEYWORDS: surface soil moisture, remote sensing, triangle, SimSphere, AATSR, MERIS.