Abstract
We explore the potential of a new method for the estimation of profiles of turbulence statistics in the stable boundary layer (SBL). By applying gradient-based scaling to multicopter unoccupied aircraft system (UAS) profiles of temperature and wind, sampled over sea-ice during the 2018 Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR18) field campaign, turbulence profiles can be derived. We first validate this method by scaling turbulence observations from three levels on a 10-m mast with the corresponding scaling parameters, and compare the resulting non-dimensional parameters to the semi-empirical similarity functions proposed for this scaling scheme. The scaled data of turbulent fluxes and variances from the three levels collapse to their corresponding similarity functions. After the successful validation, we estimate turbulence statistics from UAS profiles by computing profiles of the gradient Richardson number to which we then apply the similarity functions. These UAS profiles are processed from raw time-series data by applying low-pass filters, time-response corrections, altitude corrections, and temporal averaging across successive flights. We present three case studies covering a broad range of SBL conditions to demonstrate the validity of this approach. Comparisons against turbulence statistics from the 10-m mast and a sodar indicate the broad agreement and physically meaningful results of the method. Successful implementation of the method thus offers a powerful diagnostic tool that requires only a multicopter UAS with a simple thermodynamic sensor payload.
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Acknowledgements
The authors would like to express their gratitude for the participants who made the ISOBAR18 campaign a success. Funding for the campaign was provided by the Research Council of Norway (RCN) under the FRINATEK scheme (Project Number: 251042/F20). The WindCube v1 lidar wind profiler used during ISOBAR18 has been made available via the National Norwegian infrastructure project OBLO (Offshore Boundary Layer Observatory) also funded by RCN (Project Number: 227777). Financial assistance for this study was also provided in part by the National Science Foundation under Grant No. 1539070 and the Vice President for Research and Partnerships (VPRP) of the University of Oklahoma (OU). We additionally extend our thanks to the three anonymous reviewers whose comments have markedly improved the quality of the article. We would also like to dedicate this research to the memory of our colleague Zbigniev Sorbjan, who passed away far too early in 2017. His contributions to SBL research and the planning of the ISOBAR campaigns were strong motivators for this study.
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Greene, B.R., Kral, S.T., Chilson, P.B. et al. Gradient-Based Turbulence Estimates from Multicopter Profiles in the Arctic Stable Boundary Layer. Boundary-Layer Meteorol 183, 321–353 (2022). https://doi.org/10.1007/s10546-022-00693-x
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DOI: https://doi.org/10.1007/s10546-022-00693-x