Articles | Volume 15, issue 12
https://doi.org/10.5194/acp-15-7039-2015
https://doi.org/10.5194/acp-15-7039-2015
Research article
 | 
30 Jun 2015
Research article |  | 30 Jun 2015

Balancing aggregation and smoothing errors in inverse models

A. J. Turner and D. J. Jacob

Related authors

Simulating out-of-sample atmospheric transport to enable flux inversions
Nikhil Dadheech and Alexander J. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3441,https://doi.org/10.5194/egusphere-2025-3441, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Emulating chemistry-climate dynamics with a linear inverse model
Eric John Mei, Gregory J. Hakim, Max Taniguchi-King, Dominik Stiller, and Alexander J. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3258,https://doi.org/10.5194/egusphere-2025-3258, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
High-resolution greenhouse gas flux inversions using a machine learning surrogate model for atmospheric transport
Nikhil Dadheech, Tai-Long He, and Alexander J. Turner
Atmos. Chem. Phys., 25, 5159–5174, https://doi.org/10.5194/acp-25-5159-2025,https://doi.org/10.5194/acp-25-5159-2025, 2025
Short summary
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025,https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
State-wide California 2020 Carbon Dioxide Budget Estimated with OCO-2 and OCO-3 satellite data
Matthew S. Johnson, Sofia D. Hamilton, Seongeun Jeong, Yuyan Cui, Dien Wu, Alex Turner, and Marc Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2024-2152,https://doi.org/10.5194/egusphere-2024-2152, 2024
Short summary

Related subject area

Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Influence of nitrogen oxides and volatile organic compounds emission changes on tropospheric ozone variability, trends and radiative effect
Suvarna Fadnavis, Yasin Elshorbany, Jerald Ziemke, Brice Barret, Alexandru Rap, P. R. Satheesh Chandran, Richard J. Pope, Vijay Sagar, Domenico Taraborrelli, Eric Le Flochmoen, Juan Cuesta, Catherine Wespes, Folkert Boersma, Isolde Glissenaar, Isabelle De Smedt, Michel Van Roozendael, Hervé Petetin, and Isidora Anglou
Atmos. Chem. Phys., 25, 8229–8254, https://doi.org/10.5194/acp-25-8229-2025,https://doi.org/10.5194/acp-25-8229-2025, 2025
Short summary
Tropospheric ozone trends and attributions over East and Southeast Asia in 1995–2019: an integrated assessment using statistical methods, machine learning models, and multiple chemical transport models
Xiao Lu, Yiming Liu, Jiayin Su, Xiang Weng, Tabish Ansari, Yuqiang Zhang, Guowen He, Yuqi Zhu, Haolin Wang, Ganquan Zeng, Jingyu Li, Cheng He, Shuai Li, Teerachai Amnuaylojaroen, Tim Butler, Qi Fan, Shaojia Fan, Grant L. Forster, Meng Gao, Jianlin Hu, Yugo Kanaya, Mohd Talib Latif, Keding Lu, Philippe Nédélec, Peer Nowack, Bastien Sauvage, Xiaobin Xu, Lin Zhang, Ke Li, Ja-Ho Koo, and Tatsuya Nagashima
Atmos. Chem. Phys., 25, 7991–8028, https://doi.org/10.5194/acp-25-7991-2025,https://doi.org/10.5194/acp-25-7991-2025, 2025
Short summary
Characterization of reactive oxidized nitrogen in the global upper troposphere using recent and historic commercial and research aircraft campaigns and GEOS-Chem
Nana Wei, Eloise A. Marais, Gongda Lu, Robert G. Ryan, and Bastien Sauvage
Atmos. Chem. Phys., 25, 7925–7940, https://doi.org/10.5194/acp-25-7925-2025,https://doi.org/10.5194/acp-25-7925-2025, 2025
Short summary
Soil deposition of atmospheric hydrogen constrained using planetary-scale observations
Alexander K. Tardito Chaudhri and David S. Stevenson
Atmos. Chem. Phys., 25, 7369–7385, https://doi.org/10.5194/acp-25-7369-2025,https://doi.org/10.5194/acp-25-7369-2025, 2025
Short summary
Comparative ozone production sensitivity to NOx and VOCs in Quito, Ecuador, and Santiago, Chile
María Cazorla, Melissa Trujillo, Rodrigo Seguel, and Laura Gallardo
Atmos. Chem. Phys., 25, 7087–7109, https://doi.org/10.5194/acp-25-7087-2025,https://doi.org/10.5194/acp-25-7087-2025, 2025
Short summary

Cited articles

Bishop, C. M.: Pattern Recognition and Machine Learning, Springer, 1st Edn., New York, 2007.
Bocquet, M.: Towards optimal choices of control space representation for geophysical data assimilation, Mon. Weather Rev., 137, 2331–2348, https://doi.org/10.1175/2009MWR2789.1, 2009.
Bocquet, M. and Wu, L.: Bayesian design of control space for optimal assimilation of observations. II: Asymptotics solution, Q. J. Roy. Meteor. Soc., 137, 1357–1368, https://doi.org/10.1002/qj.841, 2011.
Bocquet, M., Wu, L., and Chevallier, F.: Bayesian design of control space for optimal assimilation of observations. Part I: Consistent multiscale formalism, Q. J. Roy. Meteor. Soc., 137, 1340–1356, https://doi.org/10.1002/qj.837, 2011.
Bousserez, N., Henze, D. K., Perkins, A., Bowman, K. W., Lee, M., Liu, J., Deng, F., and Jones, D. B. A.: Improved analysis-error covariance matrix for high-dimensional variational inversions: application to source estimation using a 3D atmospheric transport model, Q. J. Roy. Meteor. Soc., https://doi.org/10.1002/qj.2495, online first, 2015.
Share
Altmetrics
Final-revised paper
Preprint