Analyzing the turbulent planetary boundary layer by remote sensing systems: the Doppler wind lidar, aerosol elastic lidar and microwave radiometer
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AuthorArruda-Moreira, G.; Guerrero-Rascado, Juan Luis; Benavent Oltra, José Antonio; Ortiz-Amezcua, Pablo; Román, Roberto; Bedoya-Velásquez, Andrés Esteban; Bravo-Aranda, Juan Antonio; Olmo Reyes, Francisco José; Landulfo, Eduardo; Alados Arboledas, Lucas
European Geosciences Union
Arruda Moreira, G. D., Guerrero-Rascado, J. L., Benavent-Oltra, J. A., Ortiz-Amezcua, P., Román, R., E Bedoya-Velásquez, A., ... & Alados-Arboledas, L. (2019). Analyzing the turbulent planetary boundary layer by remote sensing systems: the Doppler wind lidar, aerosol elastic lidar and microwave radiometer. Atmospheric Chemistry and Physics, 19(2), 1263-1280.
SponsorshipThis work was supported by the Andalusia Regional Government through project P12-RNM-2409 and by the Spanish Agencia Estatal de Investigación (AEI) through projects CGL2016-81092-R and CGL2017-90884-REDT. We acknowledge the financial support by the European Union’s Horizon 2020 research and innovation program through project ACTRIS-2 (grant agreement no. 654109).
he planetary boundary layer (PBL) is the lowermost region of troposphere and is endowed with turbulent characteristics, which can have mechanical and/or thermodynamic origins. This behavior gives this layer great importance, mainly in studies about pollutant dispersion and weather forecasting. However, the instruments usually applied in studies of turbulence in the PBL have limitations in spatial resolution (anemometer towers) or temporal resolution (instrumentation aboard an aircraft). Ground-based remote sensing, both active and passive, offers an alternative for studying the PBL. In this study we show the capabilities of combining different remote sensing systems (microwave radiometer – MWR, Doppler lidar – DL – and elastic lidar – EL) for retrieving a detailed picture on the PBL turbulent features. The statistical moments of the high frequency distributions of the vertical wind velocity, derived from DL, and of the backscattered coefficient, derived from EL, are corrected by two methodologies, namely first lag correction and -2=3 law correction. The corrected profiles, obtained from DL data, present small differences when compared with the uncorrected profiles, showing the low influence of noise and the viability of the proposed methodology. Concerning EL, in addition to analyzing the influence of noise, we explore the use of different wavelengths that usually include EL systems operated in extended networks, like the European Aerosol Research Lidar Network (EARLINET),