The determination of the depth of daytime and nighttime mixing layers must be known very accurately to relate boundary-layer concentrations of gases or particles to upstream fluxes. The mixing-height is parametrized in numerical weather prediction models, so improving the determination of the mixing height will improve the quality of the estimated gas and particle budgets. Datasets of mixing-height diurnal cycles with high temporal and spatial resolutions are sought by various end users. Lidars and ceilometers provide vertical profiles of backscatter from aerosol particles. As aerosols are predominantly concentrated in the mixing layer, lidar backscatter profiles can be used to trace the depth of the mixing layer. Large numbers of automatic profiling lidars and ceilometers are deployed by meteorological services and other agencies in several European countries providing systems to monito
Abstract. Ground-based remote sensing observatories have a crucial role to play in providing data to improve our understanding of atmospheric processes, to test the performance of atmospheric models, and to develop new methods for future space-borne observations. Institut Pierre Simon Laplace, a French research institute in environmental sciences, created the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA), an atmospheric observatory with these goals in mind. Today SIRTA, located 20 km south of Paris, operates a suite a state-of-the-art active and passive remote sensing instruments dedicated to routine monitoring of cloud and aerosol properties, and key atmospheric parameters. Detailed description of the state of the atmospheric column is progressively archived and made accessible to the scientific community. This paper describes the SIRTA infrastructure and database, and provides an overview of the scientific research associated with the observatory. Researchers using SIRTA data conduct research on atmospheric processes involving complex interactions between clouds, aerosols and radiative and dynamic processes in the atmospheric column. Atmospheric modellers working with SIRTA observations develop new methods to test their models and innovative analyses to improve parametric representations of sub-grid processes that must be accounted for in the model. SIRTA provides the means to develop data interpretation tools for future active remote sensing missions in space (e.g. CloudSatCorrespondence to: M. Haeffelin (martial.haeffelin@lmd.polytechnique.fr) and CALIPSO). SIRTA observation and research activities take place in networks of atmospheric observatories that allow scientists to access consistent data sets from diverse regions on the globe.
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