Abstract
A comparative study and evaluation of mixing-layer height estimation was conducted, using data from remote sensing and in-situ instrumentation, radiosondes, synoptic analyses and model simulations. The data were collected during an experimental campaign conducted at the Athens International Airport, Greece, from 15 to 26 September 2007. Mixing-layer height from the sodar dataset was estimated taking into account the backscatter signal, temperature, Richardson number profiles and surface-based measurements, while for the ceilometer data, the optical attenuated aerosol backscatter intensity first derivative was utilized. Numerical simulations using the Penn State/NCAR MM5 numerical mesoscale model and the Weather Research and Forecast numerical model were also performed. Comparative results under different meteorological conditions (local flows, moderate to strong background flows) are presented and discussed. According to our results under moderate to strong winds the existing mechanical turbulence creates good signal conditions for the two remote systems leading to a good overall agreement between the two methodologies, while both models give reliable estimations of the mixing height. The sodar-RASS system is more suitable under low to moderate winds or when local flows are developed with weak stability, while the ceilometer system is more suitable for moderate to strong winds, which is associated with a homogeneous atmosphere and weaker low-level temperature inversions. In the models, the existing approach for atmospheric boundary-layer depth simulation usually provides higher compared to remote sensing values, especially during local flow events. An alternative approach for the estimation of mixing height by the models, the estimation and use of the diffusion coefficient profiles, is a promising methodology regarding the comparison with the sodar-RASS mixing-height estimations.
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Helmis, C.G., Sgouros, G., Tombrou, M. et al. A Comparative Study and Evaluation of Mixing-Height Estimation Based on Sodar-RASS, Ceilometer Data and Numerical Model Simulations. Boundary-Layer Meteorol 145, 507–526 (2012). https://doi.org/10.1007/s10546-012-9743-4
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DOI: https://doi.org/10.1007/s10546-012-9743-4