Publications

2022, Summa, D., F. Madonna, N. Franco, B. De Rosa, and P. Di Girolamo , Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1, Atmospheric Measurement Techniques, 15, 4153–4170, https://doi.org/10.5194/amt-15-4153-2022
Tags: Lidar, Model

2022, Di Girolamo, P., De Rosa, B., Summa, D., Franco, N., & Veselovskii, I. , Measurements of aerosol size and microphysical properties: A comparison between Raman lidar and airborne sensors, Journal of Geophysical Research: Atmospheres, 127, e2021JD036086, https://doi.org/10.1029/2021JD036086
Tags: Aerosol, CalVal, Lidar

2022, Steinbrecht, W. , Leblanc, T, Lidars in the Network for Detection of Atmospheric Composition Change (NDACC) and the Tropospheric Ozone Lidar Network (TOLNet), Handbook of Air Quality and Climate Change, pp. 1-24, Ed. Springer Nature, https://doi.org/10.1007/978-981-15-2527-8_55-1
Tags: Lidar, Ozone

2022, Ardalan, M., Keckhut P., Hauchecorne A., Wing R., Meftah M., Farhani G., Updated Climatology of Mesospheric Temperature Inversions Detected by Rayleigh Lidar above Observatoire de Haute Provence, France, Using a K-Mean Clustering Technique, Atmosphere, 13 (5), pp.814, https://doi.org/10.3390/atmos13050814
Tags: Lidar, Temperature

2022, Chouza, F., Leblanc, T., Brewer, M., Wang, P., Martucci, G., Haefele, A., Vérèmes, H., Duflot, V., Payen, G., and Keckhut, P., The impact of aerosol fluorescence on long-term water vapor monitoring by Raman lidar and evaluation of a potential correction method, Atmospheric Measurement Techniques, 15, 4241–4256, https://doi.org/10.5194/amt-15-4241-2022
Tags: Aerosol, H2O, Lidar

2022, Le Du, T., Keckhut P., Hauchecorne A., Simoneau P., Observation of Gravity Wave Vertical Propagation through a Mesospheric Inversion Layer, Atmosphere, 13 (7), pp.1003, https://doi.org/10.3390/atmos13071003
Tags: Lidar, Temperature

2022, Chang, K., Cooper O., Gaudel A., Allaart M., Ancellet G., Clark H., Godin-Beekmann S., Leblanc T., van Malderen R., Nédélec P., Petropavlovskikh I. et al., Impact of the COVID‐19 Economic Downturn on Tropospheric Ozone Trends: An Uncertainty Weighted Data Synthesis for Quantifying Regional Anomalies Above Western North America and Europe, AGU Advances, 3 (2), pp.e2021AV000542, https://dx.doi.org/10.1029/2021av000542
Tags: COVID, Lidar, Ozone, Trends

2022, Shan, C., Wang, W., Xie, Y., Wu, P., Xu, J., Zeng, X., Zha, L., Zhu, Q., Sun, Y., Hu, Q., Liu, C., and Jones, N., Observations of atmospheric CO2 and CO based on in-situ and ground-based remote sensing measurements at Hefei site, Science of the Total Environment, 851, 158188, https://doi.org/10.1016/j.scitotenv.2022.158188
Tags: CO, CO2, FTIR

2022, Jalali, A., K.A. Walker, K. Strong, R.R. Buchholz, M.N. Deeter, D. Wunch, S. Roche, T. Wizenberg, E. Lutsch, E. McGee, H.M. Worden, P.F. Fogal, and J.R. Drummond, A comparison of carbon monoxide retrievals between the MOPITT satellite and Canadian High-Arctic ground-based NDACC and TCCON FTIR measurements, Atmospheric Measurement Techniques, 15, 6837–6863, https://doi.org/10.5194/amt-15-6837- 2022
Tags: CO, FTIR, Satellite

2022, Trieu, T.T.N., I. Morino, O. Uchino, Y. Tsutsumi, T. Sakai, T. Nagai, A. Yamazaki, H. Okumura, K. Arai, K. Shiomi, D.F. Pollard, B. Liley , Influences of aerosols and thin cirrus clouds on GOSAT XCO2 and XCH4 using Total Carbon Column Observing Network, sky radiometer, and lidar data, International Journal of Remote Sensing, 43:5, 1770-1799, https://doi.org/10.1080/01431161.2022.2038395
Tags: Aerosol, Clouds, FTIR, Lidar, Satellite, UVVis, XCH4, XCO2