Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-3839-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-3839-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
31 Aug 2020
Model evaluation paper |
| 31 Aug 2020
| 31 Aug 2020
Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model
Ilya Stanevich
CORRESPONDING AUTHOR
Department of Physics, University of Toronto, Toronto, Canada
Dylan B. A. Jones
Department of Physics, University of Toronto, Toronto, Canada
Kimberly Strong
Department of Physics, University of Toronto, Toronto, Canada
Robert J. Parker
Earth Observation Science, Department of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation (NCEO) University of Leicester, Leicester, UK
Hartmut Boesch
Earth Observation Science, Department of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation (NCEO) University of Leicester, Leicester, UK
Debra Wunch
Department of Physics, University of Toronto, Toronto, Canada
Justus Notholt
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Christof Petri
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Thorsten Warneke
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Ralf Sussmann
Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Partenkirchen, Germany
Matthias Schneider
Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe, Germany
Frank Hase
Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe, Germany
Rigel Kivi
Finnish Meteorological Institute, Sodankylä, Finland
Nicholas M. Deutscher
Centre for Atmospheric Chemistry, School of Chemistry, University of Wollongong, Wollongong, NSW, Australia
Voltaire A. Velazco
Centre for Atmospheric Chemistry, School of Chemistry, University of Wollongong, Wollongong, NSW, Australia
Kaley A. Walker
Department of Physics, University of Toronto, Toronto, Canada
Feng Deng
Department of Physics, University of Toronto, Toronto, Canada
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26 citations as recorded by crossref.
- Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observations S. Baray et al. 10.5194/acp-21-18101-2021
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
- Multi‐Season Evaluation of CO2 Weather in OCO‐2 MIP Models L. Zhang et al. 10.1029/2021JD035457
- Weaker regional carbon uptake albeit with stronger seasonal amplitude in northern mid-latitudes estimated by higher resolution GEOS-Chem model Z. Liu et al. 10.1016/j.scitotenv.2023.169477
- Impact of the horizontal resolution of GEOS-Chem on land‒ocean and tropic‒extratropic partitioning and seasonal cycle in CO2 inversion Z. Liu et al. 10.1088/1748-9326/ad7870
- A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
- An integrated analysis of contemporary methane emissions and concentration trends over China using in situ and satellite observations and model simulations H. Tan et al. 10.5194/acp-22-1229-2022
- National CO2budgets (2015–2020) inferred from atmospheric CO2observations in support of the global stocktake B. Byrne et al. 10.5194/essd-15-963-2023
- Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations X. Lu et al. 10.5194/acp-21-4637-2021
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
- Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH<sub>4</sub> data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. 10.5194/acp-21-9545-2021
- Exceptional Wildfire Enhancements of PAN, C2H4, CH3OH, and HCOOH Over the Canadian High Arctic During August 2017 T. Wizenberg et al. 10.1029/2022JD038052
- Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model L. Qin et al. 10.1016/j.atmosenv.2023.120207
- How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35) X. Yu et al. 10.5194/gmd-14-7775-2021
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics S. Voshtani et al. 10.3390/rs14020375
- On the role of atmospheric model transport uncertainty in estimating the Chinese land carbon sink A. Schuh et al. 10.1038/s41586-021-04258-9
- Improved Mechanistic Model of the Atmospheric Redox Chemistry of Mercury V. Shah et al. 10.1021/acs.est.1c03160
- Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations Y. Zhang et al. 10.5194/acp-21-3643-2021
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- Remote‐Sensing Derived Trends in Gross Primary Production Explain Increases in the CO2 Seasonal Cycle Amplitude L. He et al. 10.1029/2021GB007220
- Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations D. Varon et al. 10.5194/gmd-15-5787-2022
- A Coupled CH4, CO and CO2 Simulation for Improved Chemical Source Modeling B. Bukosa et al. 10.3390/atmos14050764
- CH4 Fluxes Derived from Assimilation of TROPOMI XCH4 in CarbonTracker Europe-CH4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes A. Tsuruta et al. 10.3390/rs15061620
- Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al. 10.1080/01431161.2023.2240028
- Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
- Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting J. Cooper et al. 10.1039/D1EA00046B
26 citations as recorded by crossref.
- Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observations S. Baray et al. 10.5194/acp-21-18101-2021
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
- Multi‐Season Evaluation of CO2 Weather in OCO‐2 MIP Models L. Zhang et al. 10.1029/2021JD035457
- Weaker regional carbon uptake albeit with stronger seasonal amplitude in northern mid-latitudes estimated by higher resolution GEOS-Chem model Z. Liu et al. 10.1016/j.scitotenv.2023.169477
- Impact of the horizontal resolution of GEOS-Chem on land‒ocean and tropic‒extratropic partitioning and seasonal cycle in CO2 inversion Z. Liu et al. 10.1088/1748-9326/ad7870
- A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
- An integrated analysis of contemporary methane emissions and concentration trends over China using in situ and satellite observations and model simulations H. Tan et al. 10.5194/acp-22-1229-2022
- National CO2budgets (2015–2020) inferred from atmospheric CO2observations in support of the global stocktake B. Byrne et al. 10.5194/essd-15-963-2023
- Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations X. Lu et al. 10.5194/acp-21-4637-2021
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
- Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH<sub>4</sub> data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. 10.5194/acp-21-9545-2021
- Exceptional Wildfire Enhancements of PAN, C2H4, CH3OH, and HCOOH Over the Canadian High Arctic During August 2017 T. Wizenberg et al. 10.1029/2022JD038052
- Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model L. Qin et al. 10.1016/j.atmosenv.2023.120207
- How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35) X. Yu et al. 10.5194/gmd-14-7775-2021
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics S. Voshtani et al. 10.3390/rs14020375
- On the role of atmospheric model transport uncertainty in estimating the Chinese land carbon sink A. Schuh et al. 10.1038/s41586-021-04258-9
- Improved Mechanistic Model of the Atmospheric Redox Chemistry of Mercury V. Shah et al. 10.1021/acs.est.1c03160
- Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations Y. Zhang et al. 10.5194/acp-21-3643-2021
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- Remote‐Sensing Derived Trends in Gross Primary Production Explain Increases in the CO2 Seasonal Cycle Amplitude L. He et al. 10.1029/2021GB007220
- Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations D. Varon et al. 10.5194/gmd-15-5787-2022
- A Coupled CH4, CO and CO2 Simulation for Improved Chemical Source Modeling B. Bukosa et al. 10.3390/atmos14050764
- CH4 Fluxes Derived from Assimilation of TROPOMI XCH4 in CarbonTracker Europe-CH4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes A. Tsuruta et al. 10.3390/rs15061620
- Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al. 10.1080/01431161.2023.2240028
- Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
- Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting J. Cooper et al. 10.1039/D1EA00046B
Latest update: 13 Dec 2024
Short summary
Systematic errors in atmospheric models pose a challenge for inverse modeling studies of methane (CH4) emissions. We evaluated the CH4 simulation in the GEOS-Chem model at the horizontal resolutions of 4° × 5° and 2° × 2.5°. Our analysis identified resolution-dependent biases in the model, which we attributed to discrepancies between the two model resolutions in vertical transport in the troposphere and in stratosphere–troposphere exchange.
Systematic errors in atmospheric models pose a challenge for inverse modeling studies of methane...
