Articles | Volume 21, issue 22
https://doi.org/10.5194/acp-21-16661-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-16661-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Nov 2021
Research article |
| 16 Nov 2021
| 16 Nov 2021
Spatial distributions of XCO2 seasonal cycle amplitude and phase over northern high-latitude regions
Nicole Jacobs
Department of Chemistry and the Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA
Department of Chemistry and the Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA
Kelly A. Graham
Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL, USA
Christopher Holmes
Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL, USA
Frank Hase
Karlsruhe Institute of Technology (KIT), Institute of Meteorology
and Climate Research, Karlsruhe, Germany
Thomas Blumenstock
Karlsruhe Institute of Technology (KIT), Institute of Meteorology
and Climate Research, Karlsruhe, Germany
Qiansi Tu
Karlsruhe Institute of Technology (KIT), Institute of Meteorology
and Climate Research, Karlsruhe, Germany
Matthias Frey
Karlsruhe Institute of Technology (KIT), Institute of Meteorology
and Climate Research, Karlsruhe, Germany
National Institute for Environmental Studies, Tsukuba, Japan
Manvendra K. Dubey
Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, NM, USA
Harrison A. Parker
Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, NM, USA
California Institute of Technology, Pasadena, CA, USA
Debra Wunch
Department of Physics, University of Toronto, Toronto, Canada
Rigel Kivi
Finnish Meteorological Institute, Sodankylä, Finland
Pauli Heikkinen
Finnish Meteorological Institute, Sodankylä, Finland
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
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Cited
11 citations as recorded by crossref.
- Satellite-Based Reconstruction of Atmospheric CO2 Concentration over China Using a Hybrid CNN and Spatiotemporal Kriging Model Y. Hua et al. 10.3390/rs16132433
- Remote‐Sensing Derived Trends in Gross Primary Production Explain Increases in the CO2 Seasonal Cycle Amplitude L. He et al. 10.1029/2021GB007220
- The effect of anthropogenic emission, meteorological factors, and carbon dioxide on the surface ozone increase in China from 2008 to 2018 during the East Asia summer monsoon season D. Ma et al. 10.5194/acp-23-6525-2023
- Deriving gapless CO2 concentrations using a geographically weighted neural network: China, 2014–2020 L. Zhang et al. 10.1016/j.jag.2022.103063
- Variability of Atmospheric CO2 Over the Arctic Ocean: Insights From the O‐Buoy Chemical Observing Network K. Graham et al. 10.1029/2022JD036437
- Multi-year observations reveal a larger than expected autumn respiration signal across northeast Eurasia B. Byrne et al. 10.5194/bg-19-4779-2022
- Characterizing Average Seasonal, Synoptic, and Finer Variability in Orbiting Carbon Observatory‐2 XCO2 Across North America and Adjacent Ocean Basins K. Mitchell et al. 10.1029/2022JD036696
- The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product N. Jacobs et al. 10.5194/amt-17-1375-2024
- Reconstructing annual XCO2 at a 1 km×1 km spatial resolution across China from 2012 to 2019 based on a spatial CatBoost method C. Wu et al. 10.1016/j.envres.2023.116866
- Seamless reconstruction and spatiotemporal analysis of satellite-based XCO2 incorporating temporal characteristics: A case study in China during 2015–2020 J. He et al. 10.1016/j.asr.2024.07.007
- Dynamic Coupling Between Atmospheric CO2 Concentration and Land Surface Temperature in Major Urban Agglomerations in China: Insights for Sustainable Urban Development Q. Sun et al. 10.3390/su16219484
11 citations as recorded by crossref.
- Satellite-Based Reconstruction of Atmospheric CO2 Concentration over China Using a Hybrid CNN and Spatiotemporal Kriging Model Y. Hua et al. 10.3390/rs16132433
- Remote‐Sensing Derived Trends in Gross Primary Production Explain Increases in the CO2 Seasonal Cycle Amplitude L. He et al. 10.1029/2021GB007220
- The effect of anthropogenic emission, meteorological factors, and carbon dioxide on the surface ozone increase in China from 2008 to 2018 during the East Asia summer monsoon season D. Ma et al. 10.5194/acp-23-6525-2023
- Deriving gapless CO2 concentrations using a geographically weighted neural network: China, 2014–2020 L. Zhang et al. 10.1016/j.jag.2022.103063
- Variability of Atmospheric CO2 Over the Arctic Ocean: Insights From the O‐Buoy Chemical Observing Network K. Graham et al. 10.1029/2022JD036437
- Multi-year observations reveal a larger than expected autumn respiration signal across northeast Eurasia B. Byrne et al. 10.5194/bg-19-4779-2022
- Characterizing Average Seasonal, Synoptic, and Finer Variability in Orbiting Carbon Observatory‐2 XCO2 Across North America and Adjacent Ocean Basins K. Mitchell et al. 10.1029/2022JD036696
- The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product N. Jacobs et al. 10.5194/amt-17-1375-2024
- Reconstructing annual XCO2 at a 1 km×1 km spatial resolution across China from 2012 to 2019 based on a spatial CatBoost method C. Wu et al. 10.1016/j.envres.2023.116866
- Seamless reconstruction and spatiotemporal analysis of satellite-based XCO2 incorporating temporal characteristics: A case study in China during 2015–2020 J. He et al. 10.1016/j.asr.2024.07.007
- Dynamic Coupling Between Atmospheric CO2 Concentration and Land Surface Temperature in Major Urban Agglomerations in China: Insights for Sustainable Urban Development Q. Sun et al. 10.3390/su16219484
Latest update: 20 Nov 2024
Short summary
Spatial patterns of carbon dioxide seasonal cycle amplitude and summer drawdown timing derived from the OCO-2 satellite over northern high latitudes agree well with corresponding estimates from two models. The Asian boreal forest is anomalous with the largest amplitude and earliest seasonal drawdown. Modeled land contact tracers suggest that accumulated CO2 exchanges during atmospheric transport play a major role in shaping carbon dioxide seasonality in northern high-latitude regions.
Spatial patterns of carbon dioxide seasonal cycle amplitude and summer drawdown timing derived...
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