Coupled estimation of surface heat fluxes and vegetation dynamics from remotely sensed land surface temperature and fraction of photosynthetically active radiation

Remotely sensed Land Surface Temperature (LST) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) are assimilated, respectively, into the Surface Energy Balance (SEB) equation and a Vegetation Dynamics Model (VDM) in order to estimate surface fluxes and vegetation dynamics. The problem is posed in terms of three unknown and dimensionless parameters: (1) neutral bulk heat transfer coefficient, which scales the sum of turbulent heat fluxes, (2) soil and canopy evaporative fractions that characterize partitioning among the turbulent heat fluxes over soil and vegetation, and (3) specific leaf area, which captures seasonal phenology and vegetation dynamics. The model is applied over the Gourma site in Mali, the northern region of the West African Monsoon (WAM) domain. The application of the model over the Gourma site shows that spaceborne LST observations can be used to constrain the SEB equation and obtain its key two unknown parameters (i.e., neutral bulk heat transfer coefficient and evaporative fraction). We demonstrate that the spatial patterns of estimated neutral bulk heat transfer coefficient and evaporative fraction resemble, respectively, those of independently observed vegetation index and soil moisture. The framework also yields estimates of surface energy balance components. The daily sensible, latent, and ground heat flux estimates at the Agoufou site that is located in the south of the Gourma region have, respectively, a root-mean-square error (RMSE) of 53.6, 34.4, and 45.1 Wm-2. The daily sensible heat flux estimates at the Bamba site, which is located in the north of the Gourma domain, have a RMSE of 42.6 Wm-2. The results also show that remotely sensed FPAR observations can constrain the VDM and retrieve its main unknown parameter (specific leaf area) over large-scale domains without costly in situ measurements. The results indicate that the estimated specific leaf area values vary reasonably with the expected influential environmental variables such as precipitation, air temperature, and solar radiation. Assimilating FPAR observations into the VDM can also provide an estimate of Leaf Area Index (LAI) dynamics. The estimated LAI values are comparable in magnitude, spatial pattern and temporal evolution with satellite retrievals.