Multi-point Monin-Obukhov similarity horizontal array turbulence study
The Multi-point Monin-Obukhov similarity horizontal array turbulence study (M2HATS) will investigate the recently developed multi-point Monin-Obukhov similarity (MMO) in the convective atmospheric surface layer (CBL). The original Monin-Obukhov similarity (MOST) has been the theoretical foundation for understanding the surface layer of the atmospheric boundary layer (ABL). However, it fails to scale some essential statistics, such as the horizontal velocity variances and the large-scale horizontal velocity spectra in the convective surface layer, rendering the surface-layer similarity in MOST incomplete.
To address the limitations of MOST, the PI team recently proposed a generalized Monin-Obukhov similarity hypothesis, MMO, which establishes complete surface-layer similarity, represented by multi-point statistics.
Therefore, MMO overcomes the limitations of MOST, providing a new framework for comprehensive predictions and analyses of similar surface layer properties. In their prior research, the PI team derived MMO, and the scaling ranges from first principles using the method of matched asymptotic expansions.
The objective of M2HATS is to acquire data in the atmospheric boundary layer to test the MMO prediction of the surface layer similarity properties and to obtain the similarity functions. Since MMO and MOST are based on the surface layer parameters, comparisons of the MMO prediction with field measurements require predictions beyond these processes, such as the effects of the capping inversion height, the Coriolis force, and moderate baroclinicity. The science team will conduct field measurements to systematically test the predictions using field data and establish/revise the expansion coefficients and the functional forms of the MMO similarity functions.
Chenning Tong, Clemson University
Shane Mayor, California State University at Chico
EOL Facility Project Managers
Bill Brown, ISS
Steve Oncley, ISFS
Scott Spuler, MPD
EOL Archive, NCAR/EOL/DMS