Publications
2022, Taylor, T.E., C.W. O'Dell, D. Crisp, A. Kuze, H. Lindqvist, P.O. Wennberg, A. Chatterjee, M.
Gunson, A. Eldering, B. Fisher, M. Kiel, R.R. Nelson, A. Merrelli, G. Osterman, F. Chevallier,
P.I. Palmer, L. Feng, N.M. Deutscher, M.K. Dubey, D.G. Feist, O.E. Garcia, D. Grifith, F. Hase,
L. Iraci, R. Kivi, C. Liu, M. De Mazière, I. Morino, J. Notholt, Y.-S. Oh, H. Ohyama, D.F.
Pollard, M. Rettinger, C.M. Roehl, M. Schneider, M.K. Sha, K. Shiomi, K. Strong, R.Sussmann,
Y. Té, V.A. Velazco, M. Vrekoussis, T. Warneke, and D. Wunch, An 11-year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm, Earth System Science Data, 14, 325-360, https://doi.org/10.5194/essd-14-325-2022
Tags: Algorithm, FTIR, Satellite, XCO2
2022, Butz, A., Hanft V., Kleinschek R., Frey M. M., Müller A., Knapp M., Morino I., Agusti-Panareda A., Hase F., Landgraf J., Vardag S., Tanimoto H., Versatile and Targeted Validation of Space-Borne XCO2, XCH4 and XCO Observations by Mobile Ground-Based Direct-Sun Spectrometers, Frontiers in Remote Sensing, 2, 53, https://doi.org/10.3389/frsen.2021.775805
Tags: FTIR, Validation, XCH4, XCO, XCO2
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, 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, 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, Massie, S.T., et al., Analysis of 3D cloud effects in OCO-2 XCO2 retrievals, Atmospheric Measurement Techniques, 14, 1475–1499, https://doi.org/10.5194/amt-14-1475-2021
Tags: FTIR, XCO2
2021, Noel, S., et al., XCO2 retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm, Atmospheric Measurement Techniques, 14, 3837–3869, https://doi.org/10.5194/amt-14-3837-2021
Tags: FTIR, XCO2
2021, Tu, Q., Hase, F., Blumenstock, T., Schneider, M., Schneider, A., Kivi, R., Heikkinen, P., Ertl, B., Diekmann, C., Khosrawi, F., Sommer, M., Borsdorff, T., and Raffalski, U., Intercomparison of arctic XH2O observations from three ground-based Fourier transform infrared networks and application for satellite validation, Atmospheric Measurement Techniques, 14, 1993–2011, https://doi.org/10.5194/amt-14-1993-2021
Tags: FTIR, Arctic, XH2O, Satellite
2021, Tu, Q., F. Hase, T. Blumenstock, M. Schneider, A. Schneider, R. Kivi, P. Heikkinen, B. Ertl, C. Diekmann, F. Khosrawi, M. Sommer, T. Borsdorff, and U. Raffalski, Intercomparison of arctic xh2o observations from three ground-based Fourier transform infrared networks and application for satellite validation, , Atmospheric Measurement Techniques, 14(3), 1993-2011, https://doi.org/10.5194/amt-14-1993-2021
Tags: FTIR, Polar, Satellite, Sonde, XH2O
2020, Yang, D., et al., Toward high precision XCO2 retrievals from TanSat observations: Retrieval improvement and validation against TCCON measurements, Journal of Geophysical Research: Atmospheres, 125, e2020JD032794, https://doi.org/10.1029/2020JD032794
Tags: FTIR, XCO2