Articles | Volume 16, issue 3
https://doi.org/10.5194/acp-16-1653-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-1653-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Ability of the 4-D-Var analysis of the GOSAT BESD XCO2 retrievals to characterize atmospheric CO2 at large and synoptic scales
Sébastien Massart
CORRESPONDING AUTHOR
European Centre for Medium-Range Weather Forecasts, Reading, UK
Anna Agustí-Panareda
European Centre for Medium-Range Weather Forecasts, Reading, UK
Jens Heymann
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Michael Buchwitz
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Frédéric Chevallier
Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, IPSL, Gif sur Yvette, France
Maximilian Reuter
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Michael Hilker
Institute of Environmental Physics, University of Bremen, Bremen, Germany
John P. Burrows
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Nicholas M. Deutscher
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Centre for Atmospheric Chemistry, School of Chemistry, University of Wollongong, Wollongong, Australia
Dietrich G. Feist
Max Planck Institute for Biogeochemistry, Jena, Germany
Frank Hase
Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
Ralf Sussmann
Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
Filip Desmet
Department of Chemistry, University of Antwerp, Antwerp, Belgium
Manvendra K. Dubey
Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, USA
David W. T. Griffith
Centre for Atmospheric Chemistry, School of Chemistry, University of Wollongong, Wollongong, Australia
Rigel Kivi
Finnish Meteorological Institute, Arctic Research, Sodankylä, Finland
Christof Petri
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Matthias Schneider
Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
Voltaire A. Velazco
Centre for Atmospheric Chemistry, School of Chemistry, University of Wollongong, Wollongong, Australia
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32 citations as recorded by crossref.
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32 citations as recorded by crossref.
- The CO2 Human Emissions (CHE) Project: First Steps Towards a European Operational Capacity to Monitor Anthropogenic CO2 Emissions G. Balsamo et al. 10.3389/frsen.2021.707247
- Global estimates of gap-free and fine-scale CO2 concentrations during 2014–2020 from satellite and reanalysis data L. Zhang et al. 10.1016/j.envint.2023.108057
- On the potential of a neural-network-based approach for estimating XCO2 from OCO-2 measurements F. Bréon et al. 10.5194/amt-15-5219-2022
- Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. 10.1016/j.rse.2016.12.027
- Monitoring of Atmospheric Carbon Dioxide over a Desert Site Using Airborne and Ground Measurements Q. Wang et al. 10.3390/rs14205224
- Greenhouse gas simulations with a coupled meteorological and transport model: the predictability of CO<sub>2</sub> S. Polavarapu et al. 10.5194/acp-16-12005-2016
- An Urban Scheme for the ECMWF Integrated Forecasting System: Global Forecasts and Residential CO2 Emissions J. McNorton et al. 10.1029/2022MS003286
- A biogenic CO<sub>2</sub> flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO<sub>2</sub> analyses and forecasts A. Agustí-Panareda et al. 10.5194/acp-16-10399-2016
- Improving the inter-hemispheric gradient of total column atmospheric CO<sub>2</sub> and CH<sub>4</sub> in simulations with the ECMWF semi-Lagrangian atmospheric global model A. Agusti-Panareda et al. 10.5194/gmd-10-1-2017
- Towards monitoring the CO2 source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO2 mole fraction V. Thilakan et al. 10.5194/acp-22-15287-2022
- Atmospheric Correction of True-Color RGB Imagery with Limb Area-Blending Based on 6S and Satellite Image Enhancement Techniques Using Geo-Kompsat-2A Advanced Meteorological Imager Data M. Kim et al. 10.1007/s13143-021-00257-y
- Evaluation of Regional CO2 Mole Fractions in the ECMWF CAMS Real‐Time Atmospheric Analysis and NOAA CarbonTracker Near‐Real‐Time Reanalysis With Airborne Observations From ACT‐America Field Campaigns H. Chen et al. 10.1029/2018JD029992
- A comparison of posterior atmospheric CO<sub>2</sub> adjustments obtained from in situ and GOSAT constrained flux inversions S. Polavarapu et al. 10.5194/acp-18-12011-2018
- Using Multisource Data and Time Series Features to Construct a Global Terrestrial CO₂ Coverage by Deep Learning W. Tian et al. 10.1109/TGRS.2024.3462589
- Deriving gapless CO2 concentrations using a geographically weighted neural network: China, 2014–2020 L. Zhang et al. 10.1016/j.jag.2022.103063
- In situ observations of greenhouse gases over Europe during the CoMet 1.0 campaign aboard the HALO aircraft M. Gałkowski et al. 10.5194/amt-14-1525-2021
- CO2 emission of Indonesian fires in 2015 estimated from satellite‐derived atmospheric CO2 concentrations J. Heymann et al. 10.1002/2016GL072042
- Evaluating high-resolution forecasts of atmospheric CO and CO<sub>2</sub> from a global prediction system during KORUS-AQ field campaign W. Tang et al. 10.5194/acp-18-11007-2018
- Worldwide Evaluation of CAMS-EGG4 CO2 Data Re-Analysis at the Surface Level D. Custódio et al. 10.3390/toxics10060331
- Fourier transform spectrometer measurements of column CO<sub>2</sub> at Sodankylä, Finland R. Kivi & P. Heikkinen 10.5194/gi-5-271-2016
- Long-term column-averaged greenhouse gas observations using a COCCON spectrometer at the high-surface-albedo site in Gobabeb, Namibia M. Frey et al. 10.5194/amt-14-5887-2021
- A deep stratosphere-to-troposphere ozone transport event over Europe simulated in CAMS global and regional forecast systems: analysis and evaluation D. Akritidis et al. 10.5194/acp-18-15515-2018
- The GLAM Airborne Campaign across the Mediterranean Basin P. Ricaud et al. 10.1175/BAMS-D-16-0226.1
- Shipborne measurements of XCO<sub>2</sub>, XCH<sub>4</sub>, and XCO above the Pacific Ocean and comparison to CAMS atmospheric analyses and S5P/TROPOMI M. Knapp et al. 10.5194/essd-13-199-2021
- Update on GOSAT TANSO-FTS performance, operations, and data products after more than 6 years in space A. Kuze et al. 10.5194/amt-9-2445-2016
- Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al. 10.5194/acp-22-5961-2022
- Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020 A. Agustí-Panareda et al. 10.5194/acp-23-3829-2023
- Systematic detection of local CH<sub>4</sub> anomalies by combining satellite measurements with high-resolution forecasts J. Barré et al. 10.5194/acp-21-5117-2021
- Versatile and Targeted Validation of Space-Borne XCO2, XCH4 and XCO Observations by Mobile Ground-Based Direct-Sun Spectrometers A. Butz et al. 10.3389/frsen.2021.775805
- Intercomparison of atmospheric CO<sub>2</sub> and CH<sub>4</sub> abundances on regional scales in boreal areas using Copernicus Atmosphere Monitoring Service (CAMS) analysis, COllaborative Carbon Column Observing Network (COCCON) spectrometers, and Sentinel-5 Precursor satellite observations Q. Tu et al. 10.5194/amt-13-4751-2020
- Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals M. Buchwitz et al. 10.5194/amt-14-2141-2021
- Modelling CO<sub>2</sub> weather – why horizontal resolution matters A. Agustí-Panareda et al. 10.5194/acp-19-7347-2019
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Latest update: 21 Nov 2024
Short summary
This study presents the European Centre for Medium-Range Weather Forecasts (ECMWF) monitoring of atmospheric CO2 using measurements from the Greenhouse gases Observing Satellite (GOSAT). We show that the modelled CO2 has a better precision than standard CO2 satellite products compared to ground-based measurements. We also present the CO2 forecast based on our best knowledge of the atmospheric CO2 distribution. We show that it has skill to forecast the largest scale CO2 patterns up to day 5.
This study presents the European Centre for Medium-Range Weather Forecasts (ECMWF) monitoring of...
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