Understanding the scintillometer signal: spatial variability of structure parameters using wavelet analysis
Arnold F. Moene, Wageningen University, Wageningen, Netherlands; and B. Gioli
Scintillometers are increasingly being used as a remote sensing instruments in surface-layer research, both to measure surface fluxes of heat, moisture and momentum, and to characterize the turbulent atmosphere in relation to wave propagation. The signal of the scintillometer is related to the average value the structure parameter of the refractive index along the scintillometer path. Variations of the structure parameter along the path can either be inherent to the turbulence, or can be due to heterogeneity of the underlying surface. In order to better understand the formation of the scintillometer signal, information on the this variability is important. To quantify the variability of the structure parameter along the scintillometer path in situ observations of temperature and humidity are used (since the refractive index depends mainly on temperature and humidity, the dependence being a function of the wavelength of the radiation used).
A new method is presented in which a continuous wavelet transform is used to estimate the local power spectra along the path. From these spectra, the local value of the structure parameter can be estimated. Special attention is paid to the determination of the confidence interval of the estimated structure parameter.
The new method is applied to turbulence data collected during the RECAB summer campaign on July 27 2002. The Sky Arrow flux aircraft was flown (at 70 meters) close to the path of a scintillometer installed over a path of 9.8 kilometers at Cabauw (at 43 meters). The analysis gives insight in the probably density function of the structure parameter, it's spatial structure and the correlation between the structure parameter and other quantities (e.g. vertical wind speed). Since flights were repeated along the same lag, also a distinction can be made between stationary and transient variability.
The presented method can also be applied to time series of temperature and humidity (invoking a frozen turbulence hypothesis, only locally in time) to determine the variability of the structure parameter. This opens the way to the analysis of the statistics of the structure parameter from widely available observations obtained at eddy-covariance flux towers. Furthermore, the same method can be applied to velocity time series to obtain localized velocity spectra that can be used to determine the statistics of the dissipation rate.
Session 8B, PRECISION REMOTE SENSING OF THE PBL—II
Tuesday, 10 June 2008, 3:30 PM-4:45 PM, Aula Magna Höger
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