Raman lidar for hydrogen gas concentration monitoring and future radioactive waste management.

A multi-channel Raman lidar has been developed, allowing for the first time simultaneous and high-resolution profiling of hydrogen gas and water vapor. The lidar measures vibrational Raman scattering in the UV (355 nm) domain. It works in a high-bandwidth photon counting regime using fast SiPM detectors and takes into account the spectral overlap between hydrogen and water vapor Raman spectra.

Tentative detection of clear-air turbulence using a ground-based Rayleigh lidar.

Atmospheric gravity waves and turbulence generate small-scale fluctuations of wind, pressure, density, and temperature in the atmosphere. These fluctuations represent a real hazard for commercial aircraft and are known by the generic name of clear-air turbulence (CAT). Numerical weather prediction models do not resolve CAT and therefore provide only a probability of occurrence.

Methodological uncertainties in multi-regression analyses of middle-atmospheric data series.

Multi-regression analyses have often been used recently to detect trends, in particular in ozone or temperature data sets in the stratosphere. The confidence in detecting trends depends on a number of factors which generate uncertainties. Part of these uncertainties comes from the random variability and these are what is usually considered.

Review of ozone and temperature lidar validations performed within the framework of the Network for the Detection of Stratospheric Change.

The use of assimilation tools for satellite validation requires true estimates of the accuracy of the reference data. Since its inception, the Network for Detection of Stratospheric Change (NDSC) has provided systematic lidar measurements of ozone and temperature at several places around the world that are well adapted for satellite validations. Regular exercises have been organised to ensure the data quality at each individual site.