In the near-infrared and visible bandpasses optical propagation theory conventionally assumes that humidity does not contribute to the effects of atmospheric turbulence on optical beams. While this assumption may be reasonable for dry locations, we demonstrate that there is an unequivocal effect owing to the presence of humidity upon the strength of turbulence parameter, C n 2 , from data collected in the Chesapeake Bay area over 100 m length horizontal propagation paths. We describe and apply a novel technique, Hilbert phase analysis, to the relative humidity, temperature, and C n 2 data to show the contribution of the relevant climate variable to C n 2 as a function of time.

Humidity and C 2 n data collected from the Chesapeake Bay area during the 2003/2004 period have been analyzed. We demonstrate that there is an unequivocal correlation between the data during the same time periods, in the absence of solar insolation. This correlation manifests itself as an inverse relationship. We suggest that C 2 n in the infrared region is also function of humidity, in addition to temperature and pressure.

We present new optical turbulence structure parameter measurements, C 2 n , over sea water between La Parguera and Magueyes Island (17.6N 67W) on the southwest coast of Puerto Rico. The 600 meter horizontal paths were located approximately 1.5 m and 10 m above sea level. No data of this type has ever been made available in the literature. Based on the data, we show that the C 2 n measurements are about 7 times less compared to equivalent land data. This strong evidence reinforces our previous argument 1-4 that humidity must be accounted for to better ascertain the near surface atmospheric turbulence effects, which current visible / near infrared C 2 n bulk models fail to do. We also explore the generalised fractal dimension of this littoral data and compare it to our reference land data. We find cases that exhibit monofractal characteristics, that is to say, the effect of rising temperatures during the daylight hours upon turbulence are counterbalanced by humidity, leading to a single characteristic scale for the measurements. In other words, significant moisture changes in the measurement volume cancels optical turbulence increases due to temperature rises.

The Hilbert Huang Transform is a new technique for the analysis of non-stationary signals. It comprises two distinct parts: Empirical Mode Decomposition (EMD) and the Hilbert Transform of each of the modes found from the first step to produce a Hilbert Spectrum. The EMD is an adaptive decomposition of the data, which results in the extraction of Intrinsic Mode Functions (IMFs). We discuss the application of the EMD to the calibration of two optical scintillometers that have been used to measure C 2 n over horizontal paths on a building rooftop, and discuss the advantage of using the Marginal Hilbert Spectrum over the traditional Fourier Power Spectrum.

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