Publications

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, Whiteman, D.N., Di Girolamo P., Behrendt A., Wulfmeyer V. and Franco N., Statistical Analysis of Simulated Spaceborne Thermodynamics Lidar Measurements in the Planetary Boundary Layer, Frontiers in Earth Science, 3:810032, https://doi.org/10.3389/frsen.2022.810032
Tags: Lidar, Temperature

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

2021, Barret, B., et al., Retrieval of Metop-A/IASI N2O Profiles and Validation with NDACC FTIR Data, Atmosphere, https://doi.org/10.3390/atmos12020219
Tags: FTIR, N2O, Satellite

2021, David, L., et al., XCO2 estimates from the OCO-2 measurements using a neural network approach, Atmospheric Measurement Techniques, 14, 117–132, https://doi.org/10.5194/amt-14-117-2021
Tags: FTIR, XCO2

2021, Marlton, G., et al., Using a network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalyses, Atmospheric Chemistry and Physics, 21(8), 6079–6092, https://doi.org/10.5194/acp-21-6079-2021
Tags: Lidar, Model, Temperature

2021, Martucci, G., Navas-Guzmán, F., Renaud, L., Romanens, G., Gamage, S. M., Hervo, M., Jeannet, P., and Haefele, A., Validation of pure rotational Raman temperature data from the Raman Lidar for Meteorological Observations (RALMO) at Payerne, Atmospheric Measurement Techniques, 14, 1333–1353, https://doi.org/10.5194/amt-14-1333-2021
Tags: Lidar, Temperature

2021, Yu, P., Sean M. Davis, Owen B. Toon, Robert W. Portmann, Charles G. Bardeen, John E. Barnes, Hagen Telg, Christopher Maloney and Karen H. Rosenlof, Persistent Stratospheric Warming Due to 2019–2020 Australian Wildfire Smoke, Geophysical Research Letters, 48, 7, https://doi.org/10.1029/2021GL092609
Tags: Lidar, Fire, Temperature

2021, Dogniaux, M., C. Crevoisier, R. Armante, V. Capelle, T. Delahaye, V. Cassé, M. De Mazière, N. M. Deutscher, D.G. Feist, O.E. Garcia, D.W.T. Griffith, F. Hase, L.T. Iraci, R. Kivi, I. Morino, J. Notholt, D.F. Pollard, C.M. Roehl, K. Shiomi, K. Strong, Y. Té, V.A. Velazco, and T. Warneke, The Adaptable 4A Inversion (5AI): description and first XCO2 retrievals from Orbiting Carbon Observatory-2 (OCO-2) observations, Atmospheric Measurement Techniques, 14, 4689–4706, https://doi.org/10.5194/amt-14-4689-2021
Tags: FTIR, Satellite, XCO2

2021, Klanner, L., K. Höveler, D. Khordakova, M. Perfahl, C. Rolf, T. Trickl, H. Vogelmann, A powerful lidar system capable of one-hour measurements of water vapour in the troposphere and the lower stratosphere as well as the temperature in the upper stratosphere and mesosphere, Atmospheric Measurement Techniques, 14, 531–555, https://doi.org/10.5194/amt-14-531-2021
Tags: Lidar, Temperature, H2O