204-1 An Overview of Scintillometry.
See more from this Division: ASA Section: Climatology & ModelingSee more from this Session: Symposium--Evapotranspiration: Monitoring, Modeling and Mapping At Point, Field, and Regional Scales: I
Tuesday, October 23, 2012: 8:00 AM
Duke Energy Convention Center, Room 234, Level 2
Scintillometry is a state-of-the-art measurement technique for the estimation of turbulent fluxes (e.g., sensible heat flux, momentum flux). This technique essentially makes use of the principle of ‘scintillation’ – turbulence-induced fluctuations of the observed intensity of a remote light source. Over the years, different types of scintillometers have been developed using different wavelengths, aperture sizes and configurations (e.g., small-aperture, large-aperture, microwave). In this presentation, we will provide a cogent overview of various scintillometers along with their unique strengths and weaknesses. Irrespective of configurations, all the present-day scintillometers utilize the Monin-Obukhov (M-O) similarity theory to estimate heat and momentum fluxes. The M-O similarity functions are empirically derived from fast-response turbulence observations collected during different field campaigns. We will argue that the application of point-measurements-derived similarity functions in scintillometry (where fluxes are estimated over an area) is conceptually flawed. An alternative approach for the derivation of the similarity functions, based on an extensive database of high-resolution dynamic (tuning-free) large-eddy simulations, will be discussed during this presentation. Last, we will touch upon various applications of scintillometry with an emphasis on evapotranspiration (ET). In this context, we will illustrate the potential of using unconventional data (e.g., weighing lysimeters for ET validation) and methodologies (e.g., artificial neural networks for ET prediction) in scintillometry.
See more from this Division: ASA Section: Climatology & ModelingSee more from this Session: Symposium--Evapotranspiration: Monitoring, Modeling and Mapping At Point, Field, and Regional Scales: I