Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5547-2022
https://doi.org/10.5194/gmd-15-5547-2022
Development and technical paper
 | 
20 Jul 2022
Development and technical paper |  | 20 Jul 2022

Computationally efficient methods for large-scale atmospheric inverse modeling

Taewon Cho, Julianne Chung, Scot M. Miller, and Arvind K. Saibaba

Related authors

A Joint Reconstruction and Model Selection Approach for Large Scale Inverse Modeling
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot Miller, and Arvind Saibaba
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-90,https://doi.org/10.5194/gmd-2024-90, 2024
Revised manuscript accepted for GMD
Short summary
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023,https://doi.org/10.5194/essd-15-963-2023, 2023
Short summary
Data reduction for inverse modeling: an adaptive approach v1.0
Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller
Geosci. Model Dev., 14, 4683–4696, https://doi.org/10.5194/gmd-14-4683-2021,https://doi.org/10.5194/gmd-14-4683-2021, 2021
Short summary
Linking global terrestrial CO2 fluxes and environmental drivers: inferences from the Orbiting Carbon Observatory 2 satellite and terrestrial biospheric models
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021,https://doi.org/10.5194/acp-21-6663-2021, 2021
Short summary
Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite
Scot M. Miller, Arvind K. Saibaba, Michael E. Trudeau, Marikate E. Mountain, and Arlyn E. Andrews
Geosci. Model Dev., 13, 1771–1785, https://doi.org/10.5194/gmd-13-1771-2020,https://doi.org/10.5194/gmd-13-1771-2020, 2020
Short summary

Related subject area

Atmospheric sciences
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024,https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024,https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024,https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024,https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024,https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary

Cited articles

Baker, D. F., Doney, S. C., and Schimel, D. S.: Variational data assimilation for atmospheric CO2, Tellus B, 58, 359–365, https://doi.org/10.1111/j.1600-0889.2006.00218.x, 2006. a
Bardsley, J.: Computational Uncertainty Quantification for Inverse Problems, Computer Science and Engineering, SIAM, ISBN 978-1-611975-37-6, 2018. a
Barlow, J. L.: Reorthogonalization for the Golub–Kahan–Lanczos bidiagonal reduction, Numer. Math., 124, 237–278, 2013. a
Benning, M. and Burger, M.: Modern regularization methods for inverse problems, Acta Numer., 27, 1–111, 2018. a
Björck, Å.: Numerical Methods for Least Squares Problems, SIAM, Philadelphia, https://doi.org/10.1137/1.9781611971484, 1996. a
Download
Short summary
Atmospheric inverse modeling describes the process of estimating greenhouse gas fluxes or air pollution emissions at the Earth's surface using observations of these gases collected in the atmosphere. The launch of new satellites, the expansion of surface observation networks, and a desire for more detailed maps of surface fluxes have yielded numerous computational and statistical challenges. This article describes computationally efficient methods for large-scale atmospheric inverse modeling.