Articles | Volume 5, issue 6
https://doi.org/10.5194/amt-5-1387-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-5-1387-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
CH4, CO, and H2O spectroscopy for the Sentinel-5 Precursor mission: an assessment with the Total Carbon Column Observing Network measurements
A. Galli
Netherlands Institute for Space Research (SRON), 3584 CA Utrecht, The Netherlands
A. Butz
Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, 76344 Leopoldshafen, Germany
R. A. Scheepmaker
Netherlands Institute for Space Research (SRON), 3584 CA Utrecht, The Netherlands
O. Hasekamp
Netherlands Institute for Space Research (SRON), 3584 CA Utrecht, The Netherlands
J. Landgraf
Netherlands Institute for Space Research (SRON), 3584 CA Utrecht, The Netherlands
P. Tol
Netherlands Institute for Space Research (SRON), 3584 CA Utrecht, The Netherlands
D. Wunch
Department of Earth Science and Engineering, California Institute of Technology, Pasadena, CA 91125, USA
N. M. Deutscher
Centre for Atmospheric Chemistry, University of Wollongong, Wollongong, NSW 2522, Australia
Institute of Environmental Physics, University of Bremen, 28334 Bremen, Germany
G. C. Toon
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
P. O. Wennberg
Department of Earth Science and Engineering, California Institute of Technology, Pasadena, CA 91125, USA
D. W. T. Griffith
Centre for Atmospheric Chemistry, University of Wollongong, Wollongong, NSW 2522, Australia
I. Aben
Netherlands Institute for Space Research (SRON), 3584 CA Utrecht, The Netherlands
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- Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al. 10.1016/j.rse.2024.114039
- Transfer learning based solution for air quality prediction in smart cities using multimodal data M. Njaime et al. 10.1007/s13762-024-05722-5
- Addition of a channel for XCO observations to a portable FTIR spectrometer for greenhouse gas measurements F. Hase et al. 10.5194/amt-9-2303-2016
- Simulated retrievals for the remote sensing of CO<sub>2</sub>, CH<sub>4</sub>, CO, and H<sub>2</sub>O from geostationary orbit X. Xi et al. 10.5194/amt-8-4817-2015
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23 citations as recorded by crossref.
- The absorption spectrum of water vapor in the 2.2 μm transparency window: High sensitivity measurements and spectroscopic database A. Campargue et al. 10.1016/j.jqsrt.2016.12.016
- On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases E. Malina et al. 10.5194/amt-15-2377-2022
- Information‐rich spectral channels for simulated retrievals of partial column‐averaged methane Z. Su et al. 10.1002/2015EA000120
- HDO and H<sub>2</sub>O total column retrievals from TROPOMI shortwave infrared measurements R. Scheepmaker et al. 10.5194/amt-9-3921-2016
- Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from SCIAMACHY P. Hochstaffl & F. Schreier 10.3390/rs12071084
- Spatial Variation of NO2 and Its Impact Factors in China: An Application of Sentinel-5P Products Z. Zheng et al. 10.3390/rs11161939
- Improved water vapour spectroscopy in the 4174–4300 cm<sup>−1</sup> region and its impact on SCIAMACHY HDO/H<sub>2</sub>O measurements R. Scheepmaker et al. 10.5194/amt-6-879-2013
- Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from TROPOMI P. Hochstaffl et al. 10.3390/rs12213486
- Within-City Variation in Ambient Carbon Monoxide Concentrations: Leveraging Low-Cost Monitors in a Spatiotemporal Modeling Framework J. Bi et al. 10.1289/EHP10889
- Exploring Spatial and Temporal Dynamics of Red Sea Air Quality through Multivariate Analysis, Trajectories, and Satellite Observations B. Mitra et al. 10.3390/rs16020381
- Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al. 10.1016/j.rse.2024.114039
- Transfer learning based solution for air quality prediction in smart cities using multimodal data M. Njaime et al. 10.1007/s13762-024-05722-5
- Addition of a channel for XCO observations to a portable FTIR spectrometer for greenhouse gas measurements F. Hase et al. 10.5194/amt-9-2303-2016
- Simulated retrievals for the remote sensing of CO<sub>2</sub>, CH<sub>4</sub>, CO, and H<sub>2</sub>O from geostationary orbit X. Xi et al. 10.5194/amt-8-4817-2015
- The operational methane retrieval algorithm for TROPOMI H. Hu et al. 10.5194/amt-9-5423-2016
- The impact of spectral resolution on satellite retrieval accuracy of CO<sub>2</sub> and CH<sub>4</sub> A. Galli et al. 10.5194/amt-7-1105-2014
- The Spatial and Temporal Distribution Patterns of XCH4 in China: New Observations from TROPOMI J. Zhang et al. 10.3390/atmos13020177
- Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al. 10.1080/01431161.2023.2240028
- Mapping spectroscopic uncertainties into prospective methane retrieval errors from Sentinel-5 and its precursor R. Checa-Garcia et al. 10.5194/amt-8-3617-2015
- Purity Analysis of Gases Used in the Preparation of Reference Gas Standards Using a Versatile OPO-Based CRDS Spectrometer S. Persijn 10.1155/2018/9845608
- Toward Global Mapping of Methane With TROPOMI: First Results and Intersatellite Comparison to GOSAT H. Hu et al. 10.1002/2018GL077259
- Impact of spaceborne carbon monoxide observations from the S-5P platform on tropospheric composition analyses and forecasts R. Abida et al. 10.5194/acp-17-1081-2017
- A study of synthetic <sup>13</sup>CH<sub>4</sub> retrievals from TROPOMI and Sentinel-5/UVNS E. Malina et al. 10.5194/amt-12-6273-2019
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