Articles | Volume 15, issue 17
Atmos. Chem. Phys., 15, 9747–9763, 2015
https://doi.org/10.5194/acp-15-9747-2015
Atmos. Chem. Phys., 15, 9747–9763, 2015
https://doi.org/10.5194/acp-15-9747-2015

Research article 01 Sep 2015

Research article | 01 Sep 2015

Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions

A. Babenhauserheide et al.

Related authors

On the improved stability of the version 7 MIPAS ozone record
Alexandra Laeng, Ellen Eckert, Thomas von Clarmann, Michael Kiefer, Daan Hubert, Gabriele Stiller, Norbert Glatthor, Manuel López-Puertas, Bernd Funke, Udo Grabowski, Johannes Plieninger, Sylvia Kellmann, Andrea Linden, Stefan Lossow, Arne Babenhauserheide, Lucien Froidevaux, and Kaley Walker
Atmos. Meas. Tech., 11, 4693–4705, https://doi.org/10.5194/amt-11-4693-2018,https://doi.org/10.5194/amt-11-4693-2018, 2018
Short summary
MIPAS IMK/IAA carbon tetrachloride (CCl4) retrieval and first comparison with other instruments
Ellen Eckert, Thomas von Clarmann, Alexandra Laeng, Gabriele P. Stiller, Bernd Funke, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Arne Babenhauserheide, Gerald Wetzel, Christopher Boone, Andreas Engel, Jeremy J. Harrison, Patrick E. Sheese, Kaley A. Walker, and Peter F. Bernath
Atmos. Meas. Tech., 10, 2727–2743, https://doi.org/10.5194/amt-10-2727-2017,https://doi.org/10.5194/amt-10-2727-2017, 2017
Short summary

Related subject area

Subject: Gases | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Uncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases
Efisio Solazzo, Monica Crippa, Diego Guizzardi, Marilena Muntean, Margarita Choulga, and Greet Janssens-Maenhout
Atmos. Chem. Phys., 21, 5655–5683, https://doi.org/10.5194/acp-21-5655-2021,https://doi.org/10.5194/acp-21-5655-2021, 2021
Short summary
Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India
Ashique Vellalassery, Dhanyalekshmi Pillai, Julia Marshall, Christoph Gerbig, Michael Buchwitz, Oliver Schneising, and Aparnna Ravi
Atmos. Chem. Phys., 21, 5393–5414, https://doi.org/10.5194/acp-21-5393-2021,https://doi.org/10.5194/acp-21-5393-2021, 2021
Short summary
Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observations
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021,https://doi.org/10.5194/acp-21-4637-2021, 2021
Short summary
COVID-19 lockdowns highlight a risk of increasing ozone pollution in European urban areas
Stuart K. Grange, James D. Lee, Will S. Drysdale, Alastair C. Lewis, Christoph Hueglin, Lukas Emmenegger, and David C. Carslaw
Atmos. Chem. Phys., 21, 4169–4185, https://doi.org/10.5194/acp-21-4169-2021,https://doi.org/10.5194/acp-21-4169-2021, 2021
Short summary
Large-eddy simulation of traffic-related air pollution at a very high resolution in a mega-city: evaluation against mobile sensors and insights for influencing factors
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021,https://doi.org/10.5194/acp-21-2917-2021, 2021
Short summary

Cited articles

Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I., Krummel, P., Steele, P., Langenfelds, R., Torn, M., Biraud, S., Stephens, B., Andrews, A., and Worthy, D.: Global CO2 fluxes estimated from GOSAT retrievals of total column CO2, Atmos. Chem. Phys., 13, 8695–8717, https://doi.org/10.5194/acp-13-8695-2013, 2013.
Bruhwiler, L. M. P., Michalak, A. M., Peters, W., Baker, D. F., and Tans, P.: An improved Kalman Smoother for atmospheric inversions, Atmos. Chem. Phys., 5, 2691–2702, https://doi.org/10.5194/acp-5-2691-2005, 2005.
Bruhwiler, L. M. P., Michalak, A. M., and Tans, P. P.: Spatial and temporal resolution of carbon flux estimates for 1983–2002, Biogeosciences, 8, 1309–1331, https://doi.org/10.5194/bg-8-1309-2011, 2011.
Chatterjee, A. and Michalak, A. M.: Technical Note: Comparison of ensemble Kalman filter and variational approaches for CO2 data assimilation, Atmos. Chem. Phys., 13, 11643–11660, https://doi.org/10.5194/acp-13-11643-2013, 2013.
Download
Short summary
We compare two different data assimilation systems for estimating sources and sinks of CO_2 from concentration measurements. The systems are CarbonTracker and TM5-4DVar, which have both been used in a number of scientific studies. We analyze the differences between both models as well as the sensitivity of the estimated sources and sinks to the observation coverage. The results provide a lower limit for the uncertainty of surface carbon fluxes with the current measurement network.
Altmetrics
Final-revised paper
Preprint