Publications

2023, Farhani, G., Martucci, G., Roberts, T., Haefele, A., Sica, R.J., A Bayesian neural network approach for tropospheric temperature retrievals from a lidar instrument, International Journal of Remote Sensing, 44:5, 1611-1627, http://doi.org/10.1080/01431161.2023.2187723
Tags: Algorithm, Lidar, Temperature

2023, Chane Ming, F., Hauchecorne A., Bellisario C., Simoneau P., Keckhut P., Trémoulu S., Listowski C., Berthet G., Jégou F., Khaykin S., Tidiga M. et al., Case Study of a Mesospheric Temperature Inversion over Maïdo Observatory through a Multi-Instrumental Observation, Remote Sensing, 15, 2045, http://doi.org/10.3390/rs15082045
Tags: Lidar, Temperature

2023, Karagkiozidis, D., Koukouli M-E, Bais A, Balis D, Tzoumaka P., Assessment of the NO2 Spatio-Temporal Variability over Thessaloniki, Greece, Using MAX-DOAS Measurements and Comparison with S5P/TROPOMI Observations, Applied Sciences, 13(4):2641, https://doi.org/10.3390/app13042641
Tags: NO2, Satellite, UVVis

2023, Bruno, A.G., Harrison, J. J., Chipperfield, M. P., Moore, D. P., Pope, R. J., Wilson, C., Mahieu, E. and Notholt, J., Atmospheric distribution of HCN from satellite observations and 3-D model simulations, Atmospheric Chemistry and Physics, 23(8), 4849–4861, https://doi.org/10.5194/acp-23-4849-2023
Tags: FTIR, Model, Satellite

2023, Zhou, M., Ni, Q., Cai, Z. et al., Ground-Based Atmospheric CO2, CH4, and CO Column Measurements at Golmud in the Qinghai-Tibetan Plateau and Comparisons with TROPOMI/S5P Satellite Observations, Advances in the Atmospheric Sciences, 40, 223–234, https://doi.org/10.1007/s00376-022-2116-0
Tags: CH4, CO, CO2, FTIR, Satellite

2023, Mariaccia, A., Keckhut P., Hauchecorne A., Khaykin S., Ratynski M., Co‐Located Wind and Temperature Observations at Mid‐Latitudes During Mesospheric Inversion Layer Events, Geophysical Research Letters, 50 (9), pp.e2022GL102683, http://doi.org/10.1029/2022gl102683
Tags: Lidar, Temperature, Wind

2023, Poraicu, C., Müller, J.-F., Stavrakou, T., Fonteyn, D., Tack, F., Deutsch, F., Laffineur, Q., Van Malderen, R., and Veldeman, N., Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium, Geoscientific Model Development, 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023
Tags: NO2, Satellite, Sonde

2022, Wells, K.C., Millet, D. B., Payne, V. H., Vigouroux, C., Aquino, C. A. B., De Mazière, M., de Gouw, J. A., Graus, M., Kurosu, T., Warneke, C., and Wisthaler, A., Next-generation Isoprene Measurements from Space: Detecting Daily Variability at High Resolution, Journal of Geophysical Research: Atmospheres, 127, e2021JD036181, https://doi.org/10.1029/2021JD036181
Tags: C5H8, FTIR, Isoprene, 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

2022, Sullivan, J., A. Apituley, N. Mettig, K. Kreher, K.E. Knowland, M. Allart, A. Piters et al., Tropospheric and Stratospheric Ozone Profiles during the 2019 TROpomi vaLIdation eXperiment (TROLIX-19), Atmospheric Chemistry and Physics, 22, 11137–11153, https://doi.org/10.5194/acp-22-11137-2022
Tags: Lidar, Ozone, Satellite, Validation