Extending a surface-layer Cn2 model for strongly stratified conditions utilizing a numerically generated turbulence dataset

In Wyngaard et al., 1971, a simple model was proposed to estimate Cn2 in the atmospheric surface layer, which only requires routine meteorological information (wind speed and temperature) as input from two heights. This Cn2 model is known to have satisfactory performance in unstable conditions; however, in stable conditions, the model only covers a relatively short range of atmospheric stabilities which significantly limits its applicability during nighttime. To mitigate this limitation, in this study we construct a new Cn2 model utilizing an extensive turbulence dataset generated by a high-fidelity numerical modeling approach (known as direct numerical simulation). The most distinguishing feature of this new Cn2 model is that it covers a wide range of atmospheric stabilities including the strongly stratified (very stable) conditions. To validate this model, approximately four weeks of Cn2 data collected at the Mauna Loa Observatory, Hawaii are used for comparison, and reasonably good agreement is found between the observed and estimated values.