Atmospheric turbulence over crops : confronting theories with observations

Atmospheric turbulence plays a key role in hydrological and carbon cycles, and in weather and climate. Understanding and forecasting turbulence is thereby relevant for human life and environment. We deal with some major challenges for studying atmospheric turbulence over crops. Land-atmosphere interactions are specifically complex because of surface heterogeneity. Also, boundary-layer entrainment complicates measuring and studying surface fluxes. Furthermore, the absence of high-frequency observations and of measurements of underlying soil and vegetation processes impedes studying land-atmosphere interactions. We show the applicability of analytical footprint models over a heterogeneous land surface, and the validity of Monin-Obukhov similarity theory for a strongly-convective boundary-layer.  Moreover, we present improvements on a scheme that can be used to estimate the amount of atmospheric turbulence from single-level weather data. We furthermore suggest to improve the partitioning theory that is used to distinguish soil processes from plant processes in eddy-covariance flux observations