Publications
2022, Malina, E., Veihelmann, B., Buschmann, M., Deutscher, N. M., Feist, D. G., and Morino, I., On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases, Atmospheric Measurement Techniques, 15, 2377–2406, https://doi.org/10.5194/amt-15-2377-2022
Tags: CH4, FTIR
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, Lutsch, E., D. Wunch, D. B. A. Jones, C. Clerbaux, J. W. Hannigan, T.-L. He, I. Ortega, S. Roche, K. Strong, and H. M. Worden, Can the data assimilation of CO from MOPITT or IASI constrain high-latitude wildfire emissions? A Case Study of the 2017 Canadian Wildfires, Earth and Space Science, p. 44, https://doi.org/10.1002/essoar.10510875.1
Tags: CO, Fire, Model, Satellite
2021, John, S.S., N. M. Deutscher, C. Paton-Walsh, V. A. Velazco, N. B. Jones and D. W. T. Griffith, 2019–20 Australian Bushfires and Anomalies in Carbon Monoxide Surface and Column Measurements, Atmosphere, 12(6), 755, https://doi.org/10.3390/atmos12060755
Tags: FTIR, Fire, CO
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, 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, Wizenberg, T., K. Strong, K. Walker, E. Lutsch, T. Borsdorff, and J. Landgraf, Intercomparison of CO measurements from TROPOMI, ACE-FTS, and a high-Arctic ground-based Fourier transform spectrometer, Atmospheric Measurement Techniques, 14, 7707-7728, https://doi.org/10.5194/amt-14-7707-2021
Tags: CO, FTIR, Satellite
2021, You, Y., B. Byrne, O. Colebatch, R.L. Mittermeier, F. Vogel, and K. Strong, Quantifying the impact of the COVID-19 pandemic restrictions on CO, CO2, and CH4 in downtown Toronto using open-path Fourier transform spectroscopy, Atmosphere, 12(7), 848, https://doi.org/10.3390/atmos12070848
Tags: FTIR, CO, CO2, CH4
2021, Zhang, Y., et al., Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations, Atmospheric Chemistry and Physics, 21, https://doi.org/10.5194/acp-21-3643-2021
Tags: CH4, FTIR, Satellite
2021, Stanevich, I., D.B.A. Jones, K. Strong, M. Keller, D.K. Henze, R.J. Parker, H. Boesch, D. Wunch, J. Notholt, C. Petri, T. Warneke, R. Sussmann, M. Schneider, F. Hase, R. Kivi, N.M. Deutscher, V.A. Velazco, K.A. Walker, and F. Deng, Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH4 data with weak-constraint four-dimensional variational data assimilation, Atmospheric Chemistry and Physics, 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021
Tags: FTIR, Satellite, CH4, XCH4