Attenuating absorption contribution on Cn² estimates with a large-aperture scintillometer

Abstract : Large aperture scintillometers (LAS) are often used to characterise atmospheric turbulence by measuring the structure parameter of the refractive index Cn². However, absorption phenomena can lead to an overestimation of Cn². By applying an accurate numerical filtering technique called the Gabor Transform to the signal output of a LAS, we improved our knowledge of the accuracy of the measured Cn² by determining and attenuating the contribution of absorption. Two studies will be led on a 12-day dataset using either fixed band pass or adaptive filtering. The first one consists in evaluating the best-fitted filter for which the resulting Cn² is independent of meteorological conditions, especially wind speed, and the second one consists in accurately attenuating absorption phenomena. A reference Cn² (hereafter 'reconstructed Cn²') will be created by accurately removing absorption from the scintillation spectrum, and will be used to evaluate each filter. By comparing the 'reconstructed Cn²' with a raw Cn² measured by a scintillometer we found that the average relative contribution of absorption to the measurement of Cn² is approximately 1.6%. However, the absorption phenomenon is highly variable; occasionally, in the worst cases, we estimated that the absorption phenomenon could represent 81% of the value of Cn². Some explanations for this high variability are proposed with respect to theoretical considerations. Amongst the fixed band pass filtering used in this paper, we concluded on the preferential use of a band pass filter [0.2- 400 Hz] for Cn² at 60%. Using an adaptive filter on the 12-day dataset really improves the filtering accuracy on both points discussed in this paper.
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Boundary Layer Meteorology, 2011, pp.1-46
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Pierre Adrien Solignac, Aurore Brut, Jean-Louis Selves, Jean-Pierre Béteille, Jean-Philippe Gastellu-Etchegorry. Attenuating absorption contribution on Cn² estimates with a large-aperture scintillometer. Boundary Layer Meteorology, 2011, pp.1-46. 〈ird-00657464〉

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