Deriving an effective lake depth from satellite lake surface temperature data: a feasibility study with MODIS data

Modelling lakes in Numerical Weather Prediction (NWP) is important to produce accurate evaporation rates and surface temperature forecasts. Lake depth is a crucial external parameter for the implementation of lake models into NWP systems, since it controls the dynamical range of lake temperature amplitudes on diurnal to seasonal time scales. However, a global lake-depth dataset does not exist at present. A novel method to derive an effective lake depth on the basis of the remotely-sensed lake water-surface temperature (LWST) is presented here. A technique is proposed to adjust a simple two-layer Fresh-water Lake model (FLake) depth such that simulated annual cycle of LWST matches satellite-based LWST climatology as closely as possible. The method was applied to 47 European lakes and the results show convergence of the solutions. Merits and limitations of this approach are discussed. Preliminary validation of a derived bathymetry of the American Great Lakes is presented.