Computing Refractive-Index Structure Parameter Cn2 Using COAMPS

Turbulent refractive-index fluctuations have significant effects on the Electro-magnetic/Electro-optical wave propagation in the atmosphere. The single most important parameter that provides information about these fluctuations is the refractive-index structure parameter, usually denoted by Cn². There have been many efforts in the community to parameterize Cn² from meteorological observations as well as numerical weather predictions ranging from the surface layer representation based on the Monin-Obukhov Similarity Theory (MOST) to the area-averaged estimates from high-resolution NWP model output. This work adopts a predictive approach based on the second-order turbulence closure method within the PBL parameterization in Navy’s Coupled Atmosphere/Ocean Mesoscale Prediction System (COAMPS). The results from the parameterization were compared with data from both observations and large-eddy simulations.

Our parameterization follows the well-known formulation that relates the structure parameter of any scalar to the turbulence kinetic energy dissipation rate and the molecular destruction rate of that scalar variance. Three new predictive turbulence variables are included in COAMPS. They are temperature variance, water vapor variances, and covariance of temperature and water vapor. Three structure parameters for temperature, water vapor, and the covariance of temperature and water can be derived from these predicted variance and covariance together with the mixing length from the PBL model. Consequently, C_n² at any wave propagation frequency can be derived from these three structure parameters. A single column version of COAMPS was applied to a case under convective condition observed on October 12, 2017 during CASPER-West, October – November 2017. The 1-D results compare well against the data from COAMPS-LES simulations and observations. Near the surface, the parameterized temperature structure parameter is very close to that derived from the turbulence measurement and from the LES. All the parameterized structure parameters closely follow the MOST results near the surface. In the boundary layer inversion, however, all the parameterization values appear to be significantly smaller than those from the LES. This deficiency may be related to a weaker transfer coefficient within the inversion. We are currently investigating various issues related to the performance of the parameterization. Work is also under way to evaluate the parameterization in COAMPS regional simulations.