Analyzing the turbulent planetary boundary layer by remote sensing systems: the Doppler wind lidar, aerosol elastic lidar and microwave radiometer
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Arruda-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, LucasEditorial
European Geosciences Union
Fecha
2019-01-31Referencia bibliográfica
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.
Patrocinador
This 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).Resumen
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),