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DIRECTED
ENERGY
PROFESSIONAL
SOCIETY
Abstract: 24-Symp-136
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UNCLASSIFIED, PUBLIC RELEASE
Improving Numerical Weather Prediction of Optical Turbulence through Observational constraints
While an improved understanding of spatial variability of atmospheric optical turbulence and the ability to predict the same has been identified as a research priority, little progress has been made in recent years. This presentation will utilize atmospheric numerical modeling to characterize the three-dimensional variability of the refractive index structure function (Cn2). Further, this talk will also examine the role of surface-atmosphere interactions in modulating the spatial variability of Cn2 and the use of in situ and remotely sensed data to improve the prediction of Cn2. We will examine two different computationally inexpensive approaches, one where assimilation of observations will be used to improve prognostication of surface energy budget in predictions of Cn2 in the surface layer. The second approach presented will utilize one-dimensional modeling supplemented with assimilation of satellite observations and in situ observations. These methodologies are being developed for the Atmospheric Characterization Diagnostics System (ACDS) and will be evaluated using observations collected at the Persistent Data Collection Site (PDCS) established in North Alabama.
UNCLASSIFIED, PUBLIC RELEASE
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