Articles | Volume 19, issue 8
https://doi.org/10.5194/acp-19-5695-2019
© Author(s) 2019. 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-19-5695-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Apr 2019
Research article |
| 30 Apr 2019
| 30 Apr 2019
Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model
Liza I. Díaz-Isaac
CORRESPONDING AUTHOR
Department of Meteorology and Atmospheric Science, Pennsylvania
State University, University Park, PA, USA
now at: Scripps Institution of Oceanography, University of California,
San Diego, CA, USA
Thomas Lauvaux
Department of Meteorology and Atmospheric Science, Pennsylvania
State University, University Park, PA, USA
Marc Bocquet
CEREA, joint laboratory École des Ponts ParisTech and EDF R&D,
Université Paris-Est, Champs-sur-Marne, France
Kenneth J. Davis
Department of Meteorology and Atmospheric Science, Pennsylvania
State University, University Park, PA, USA
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Tobias Sebastian Finn, Charlotte Durand, Alban Farchi, Marc Bocquet, Yumeng Chen, Alberto Carrassi, and Véronique Dansereau
The Cryosphere, 17, 2965–2991, https://doi.org/10.5194/tc-17-2965-2023, https://doi.org/10.5194/tc-17-2965-2023, 2023
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We combine deep learning with a regional sea-ice model to correct model errors in the sea-ice dynamics of low-resolution forecasts towards high-resolution simulations. The combined model improves the forecast by up to 75 % and thereby surpasses the performance of persistence. As the error connection can additionally be used to analyse the shortcomings of the forecasts, this study highlights the potential of combined modelling for short-term sea-ice forecasting.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
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Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
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Zachary Barkley, Kenneth Davis, Natasha Miles, Scott Richardson, Aijun Deng, Benjamin Hmiel, David Lyon, and Thomas Lauvaux
Atmos. Chem. Phys., 23, 6127–6144, https://doi.org/10.5194/acp-23-6127-2023, https://doi.org/10.5194/acp-23-6127-2023, 2023
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Using methane monitoring instruments attached to towers, we measure methane concentrations and quantify methane emissions coming from the Marcellus and Permian oil and gas basins. In the Marcellus, emissions were 3 times higher than the state inventory across the entire monitoring period. In the Permian, we see a sharp decline in emissions aligning with the onset of the COVID-19 pandemic. Tower observational networks can be utilized in other basins for long-term monitoring of emissions.
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
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Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
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Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Rory A. Barton-Grimley, Amin R. Nehrir, Susan A. Kooi, James E. Collins, David B. Harper, Anthony Notari, Joseph Lee, Joshua P. DiGangi, Yonghoon Choi, and Kenneth J. Davis
Atmos. Meas. Tech., 15, 4623–4650, https://doi.org/10.5194/amt-15-4623-2022, https://doi.org/10.5194/amt-15-4623-2022, 2022
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Vanessa C. Monteiro, Natasha L. Miles, Scott J. Richardson, Zachary Barkley, Bernd J. Haupt, David Lyon, Benjamin Hmiel, and Kenneth J. Davis
Earth Syst. Sci. Data, 14, 2401–2417, https://doi.org/10.5194/essd-14-2401-2022, https://doi.org/10.5194/essd-14-2401-2022, 2022
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We describe a network of five ground-based in situ towers, equipped to measure concentrations of methane, carbon dioxide, hydrogen sulfide, and the isotopic ratio of methane, in the Permian Basin, United States. The main goal is to use methane concentrations with atmospheric models to determine methane emissions from one of the Permian sub-basins. These datasets can improve emissions estimations, leading to best practices in the oil and natural gas industry, and policies for emissions reduction.
E. Ouerghi, T. Ehret, C. de Franchis, G. Facciolo, T. Lauvaux, E. Meinhardt, and J.-M. Morel
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 147–154, https://doi.org/10.5194/isprs-annals-V-3-2022-147-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-147-2022, 2022
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
David F. Baker, Emily Bell, Kenneth J. Davis, Joel F. Campbell, Bing Lin, and Jeremy Dobler
Geosci. Model Dev., 15, 649–668, https://doi.org/10.5194/gmd-15-649-2022, https://doi.org/10.5194/gmd-15-649-2022, 2022
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The OCO-2 satellite measures many closely spaced column-averaged CO2 values around its orbit. To give these data proper weight in flux inversions, their error correlations must be accounted for. Here we lay out a 1-D error model with correlations that die out exponentially along-track to do so. A correlation length scale of ∼20 km is derived from column CO2 measurements from an airborne lidar flown underneath OCO-2 for use in this model. The model's performance is compared to previous ones.
Pramod Kumar, Grégoire Broquet, Camille Yver-Kwok, Olivier Laurent, Susan Gichuki, Christopher Caldow, Ford Cropley, Thomas Lauvaux, Michel Ramonet, Guillaume Berthe, Frédéric Martin, Olivier Duclaux, Catherine Juery, Caroline Bouchet, and Philippe Ciais
Atmos. Meas. Tech., 14, 5987–6003, https://doi.org/10.5194/amt-14-5987-2021, https://doi.org/10.5194/amt-14-5987-2021, 2021
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This study presents a simple atmospheric inversion modeling framework for the localization and quantification of unknown CH4 and CO2 emissions from point sources based on near-surface mobile concentration measurements and a Gaussian plume dispersion model. It is applied for the estimate of a series of brief controlled releases of CH4 and CO2 with a wide range of rates during the TOTAL TADI-2018 experiment. Results indicate a ~10 %–40 % average error on the estimate of the release rates.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Atmos. Chem. Phys., 21, 13247–13267, https://doi.org/10.5194/acp-21-13247-2021, https://doi.org/10.5194/acp-21-13247-2021, 2021
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The assessment of the environmental consequences of a radionuclide release depends on the estimation of its source. This paper aims to develop inverse Bayesian methods which combine transport models with measurements, in order to reconstruct the ensemble of possible sources.
Three methods to quantify uncertainties based on the definition of probability distributions and the physical models are proposed and evaluated for the case of 106Ru releases over Europe in 2017.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726, https://doi.org/10.5194/acp-21-10707-2021, https://doi.org/10.5194/acp-21-10707-2021, 2021
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Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
E. Ouerghi, T. Ehret, C. de Franchis, G. Facciolo, T. Lauvaux, E. Meinhardt, and J.-M. Morel
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 81–87, https://doi.org/10.5194/isprs-annals-V-3-2021-81-2021, https://doi.org/10.5194/isprs-annals-V-3-2021-81-2021, 2021
Tao Zheng, Sha Feng, Kenneth J. Davis, Sandip Pal, and Josep-Anton Morguí
Geosci. Model Dev., 14, 3037–3066, https://doi.org/10.5194/gmd-14-3037-2021, https://doi.org/10.5194/gmd-14-3037-2021, 2021
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Carbon dioxide is the most important greenhouse gas. We develop the numerical model that represents carbon dioxide transport in the atmosphere. This model development is based on the MPAS model, which has a variable-resolution capability. The purpose of developing carbon dioxide transport in MPAS is to allow for high-resolution transport model simulation that is not limited by the lateral boundaries. It will also form the base for a future development of MPAS-based carbon inversion system.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
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The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Xueying Yu, Dylan B. Millet, Kelley C. Wells, Daven K. Henze, Hansen Cao, Timothy J. Griffis, Eric A. Kort, Genevieve Plant, Malte J. Deventer, Randall K. Kolka, D. Tyler Roman, Kenneth J. Davis, Ankur R. Desai, Bianca C. Baier, Kathryn McKain, Alan C. Czarnetzki, and A. Anthony Bloom
Atmos. Chem. Phys., 21, 951–971, https://doi.org/10.5194/acp-21-951-2021, https://doi.org/10.5194/acp-21-951-2021, 2021
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Methane concentrations have doubled since 1750. The US Upper Midwest is a key region contributing to such trends, but sources are poorly understood. We collected and analyzed aircraft data to resolve spatial and timing biases in wetland and livestock emission estimates and uncover errors in inventory treatment of manure management. We highlight the importance of intensive agriculture for the regional and US methane budgets and the potential for methane mitigation through improved management.
Petter Weibring, Dirk Richter, James G. Walega, Alan Fried, Joshua DiGangi, Hannah Halliday, Yonghoon Choi, Bianca Baier, Colm Sweeney, Ben Miller, Kenneth J. Davis, Zachary Barkley, and Michael D. Obland
Atmos. Meas. Tech., 13, 6095–6112, https://doi.org/10.5194/amt-13-6095-2020, https://doi.org/10.5194/amt-13-6095-2020, 2020
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The present study describes an autonomously operated instrument for high-precision (20–40 parts per trillion in 1 s) measurements of ethane during actual airborne operations on a small aircraft platform (NASA's King Air B200). This paper discusses the dynamic nature of airborne performance due to various aircraft-induced perturbations, methods devised to identify such events, and solutions we have enacted to circumvent these perturbations.
Nikolay V. Balashov, Kenneth J. Davis, Natasha L. Miles, Thomas Lauvaux, Scott J. Richardson, Zachary R. Barkley, and Timothy A. Bonin
Atmos. Chem. Phys., 20, 4545–4559, https://doi.org/10.5194/acp-20-4545-2020, https://doi.org/10.5194/acp-20-4545-2020, 2020
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An accurate independent verification methodology to estimate methane (a powerful greenhouse gas) emissions is essential for the effective implementation of policies that aim to reduce the impacts of climate change. In this paper, four uncertainties that complicate the independent estimation of urban methane emissions are identified: the definition of urban domain, background heterogeneity, emissions temporal variability, and missing sources. Ways to improve emission estimates are suggested.
Colin Grudzien, Marc Bocquet, and Alberto Carrassi
Geosci. Model Dev., 13, 1903–1924, https://doi.org/10.5194/gmd-13-1903-2020, https://doi.org/10.5194/gmd-13-1903-2020, 2020
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All scales of a dynamical physical process cannot be resolved accurately in a multiscale, geophysical model. The behavior of unresolved scales of motion are often parametrized by a random process to emulate their effects on the dynamically resolved variables, and this results in a random–dynamical model. We study how the choice of a numerical discretization of such a system affects the model forecast and estimation statistics, when the random–dynamical model is unbiased in its parametrization.
Thomas Lauvaux, Liza I. Díaz-Isaac, Marc Bocquet, and Nicolas Bousserez
Atmos. Chem. Phys., 19, 12007–12024, https://doi.org/10.5194/acp-19-12007-2019, https://doi.org/10.5194/acp-19-12007-2019, 2019
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A small-size ensemble of mesoscale simulations has been filtered to characterize the spatial structures of transport errors in atmospheric CO2 mixing ratios. The extracted error structures in in situ and column CO2 show similar length scales compared to other meteorological variables, including seasonality, which could be used as proxies in regional inversion systems.
Marc Bocquet, Julien Brajard, Alberto Carrassi, and Laurent Bertino
Nonlin. Processes Geophys., 26, 143–162, https://doi.org/10.5194/npg-26-143-2019, https://doi.org/10.5194/npg-26-143-2019, 2019
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This paper describes an innovative way to use data assimilation to infer the dynamics of a physical system from its observation only. The method can operate with noisy and partial observation of the physical system. It acts as a deep learning technique specialised to dynamical models without the need for machine learning tools. The method is successfully tested on chaotic dynamical systems: the Lorenz-63, Lorenz-96, and Kuramoto–Sivashinski models and a two-scale Lorenz model.
Julien Brajard, Alberto Carrassi, Marc Bocquet, and Laurent Bertino
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-136, https://doi.org/10.5194/gmd-2019-136, 2019
Revised manuscript not accepted
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We explore the possibility of combining data assimilation with machine learning. We introduce a new hybrid method for a two-fold scope: (i) emulating hidden, possibly chaotic, dynamics and (ii) predicting its future states. Numerical experiments have been carried out using the chaotic Lorenz 96 model, proving both the convergence of the hybrid method and its statistical skills including short-term forecasting and emulation of the long-term dynamics.
Julian Kostinek, Anke Roiger, Kenneth J. Davis, Colm Sweeney, Joshua P. DiGangi, Yonghoon Choi, Bianca Baier, Frank Hase, Jochen Groß, Maximilian Eckl, Theresa Klausner, and André Butz
Atmos. Meas. Tech., 12, 1767–1783, https://doi.org/10.5194/amt-12-1767-2019, https://doi.org/10.5194/amt-12-1767-2019, 2019
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We demonstrate the successful adaption of a laser-based spectrometer for airborne in situ trace gas measurements. The modified instrument allows for precise and simultaneous airborne observation of five climatologically relevant gases. We further report on instrument performance during a first field deployment over the eastern and central USA.
Anna Karion, Thomas Lauvaux, Israel Lopez Coto, Colm Sweeney, Kimberly Mueller, Sharon Gourdji, Wayne Angevine, Zachary Barkley, Aijun Deng, Arlyn Andrews, Ariel Stein, and James Whetstone
Atmos. Chem. Phys., 19, 2561–2576, https://doi.org/10.5194/acp-19-2561-2019, https://doi.org/10.5194/acp-19-2561-2019, 2019
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In this study, we use atmospheric methane concentration observations collected during an airborne campaign to compare different model-based emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We find that the tracer dispersion model has a significant impact on the results because the models differ in their simulation of vertical dispersion. Additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models.
Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman, and Kenneth J. Davis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-342, https://doi.org/10.5194/gmd-2018-342, 2019
Revised manuscript not accepted
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This paper describes a mass-conserving framework for computing time-varying lateral boundary conditions from global model carbon dioxide concentrations for introduction into the WRF-Chem regional model. The goal is to create a laboratory environment in which carbon dioxide transport uncertainties may be explored separately from inversion-derived flux uncertainties. The software is currently available on GitHub at https://github.com/psu-inversion/WRF_Boundary_Coupling.
Dien Wu, John C. Lin, Benjamin Fasoli, Tomohiro Oda, Xinxin Ye, Thomas Lauvaux, Emily G. Yang, and Eric A. Kort
Geosci. Model Dev., 11, 4843–4871, https://doi.org/10.5194/gmd-11-4843-2018, https://doi.org/10.5194/gmd-11-4843-2018, 2018
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Urban CO2 enhancement signals can be derived using satellite column CO2 concentrations and atmospheric transport models. However, uncertainties due to model configurations, atmospheric transport, and defined background values can potentially impact the derived urban signals. In this paper, we present a modified Lagrangian model framework that extracts urban CO2 signals from satellite observations and determines potential error impacts.
Alban Farchi and Marc Bocquet
Nonlin. Processes Geophys., 25, 765–807, https://doi.org/10.5194/npg-25-765-2018, https://doi.org/10.5194/npg-25-765-2018, 2018
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Data assimilation looks for an optimal way to learn from observations of a dynamical system to improve the quality of its predictions. The goal is to filter out the noise (both observation and model noise) to retrieve the true signal. Among all possible methods, particle filters are promising; the method is fast and elegant, and it allows for a Bayesian analysis. In this review paper, we discuss implementation techniques for (local) particle filters in high-dimensional systems.
Liza I. Díaz-Isaac, Thomas Lauvaux, and Kenneth J. Davis
Atmos. Chem. Phys., 18, 14813–14835, https://doi.org/10.5194/acp-18-14813-2018, https://doi.org/10.5194/acp-18-14813-2018, 2018
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Atmospheric inversions rely on the accurate representation of the atmospheric dynamics in order to produce reliable surface fluxes. In this work, we evaluate the sensitivity of a state-of-the-art mesoscale atmospheric model to the different physics parameterizations and forcing. We conclude that no model configuration is optimal across an entire region. Therefore, we recommend an ensemble approach or the assimilation of meteorological observations in future inversion studies.
Colin Grudzien, Alberto Carrassi, and Marc Bocquet
Nonlin. Processes Geophys., 25, 633–648, https://doi.org/10.5194/npg-25-633-2018, https://doi.org/10.5194/npg-25-633-2018, 2018
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Using the framework Lyapunov vectors, we analyze the asymptotic properties of ensemble based Kalman filters and how these are influenced by dynamical chaos, especially in the context of random model errors and small ensemble sizes. Particularly, we show a novel derivation of the evolution of forecast uncertainty for ensemble-based Kalman filters with weakly-nonlinear error growth, and discuss its impact for filter design in geophysical models.
Olivier Pannekoucke, Marc Bocquet, and Richard Ménard
Nonlin. Processes Geophys., 25, 481–495, https://doi.org/10.5194/npg-25-481-2018, https://doi.org/10.5194/npg-25-481-2018, 2018
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The forecast of weather prediction uncertainty is a real challenge and is crucial for risk management. However, uncertainty prediction is beyond the capacity of supercomputers, and improvements of the technology may not solve this issue. A new uncertainty prediction method is introduced which takes advantage of fluid equations to predict simple quantities which approximate real uncertainty but at a low numerical cost. A proof of concept is shown by an academic model derived from fluid dynamics.
Anthony Fillion, Marc Bocquet, and Serge Gratton
Nonlin. Processes Geophys., 25, 315–334, https://doi.org/10.5194/npg-25-315-2018, https://doi.org/10.5194/npg-25-315-2018, 2018
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This study generalizes a paper by Pires et al. (1996) to state-of-the-art data assimilation techniques, such as the iterative ensemble Kalman smoother (IEnKS). We show that the longer the time window over which observations are assimilated, the better the accuracy of the IEnKS. Beyond a critical time length that we estimate, we show that this accuracy finally degrades. We show that the use of the quasi-static minimizations but generalized to the IEnKS yields a significantly improved accuracy.
Natasha L. Miles, Douglas K. Martins, Scott J. Richardson, Christopher W. Rella, Caleb Arata, Thomas Lauvaux, Kenneth J. Davis, Zachary R. Barkley, Kathryn McKain, and Colm Sweeney
Atmos. Meas. Tech., 11, 1273–1295, https://doi.org/10.5194/amt-11-1273-2018, https://doi.org/10.5194/amt-11-1273-2018, 2018
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Analyzers measuring methane and methane isotopic ratio were deployed at four towers in the Marcellus Shale natural gas extraction region of Pennsylvania. The methane isotopic ratio is helpful for differentiating emissions from natural gas activities from other sources (e.g., landfills). We describe the analyzer calibration. The signals observed in the study region were generally small, but the instrumental performance demonstrated here could be used in regions with stronger enhancements.
Xinxin Ye, Thomas Lauvaux, Eric A. Kort, Tomohiro Oda, Sha Feng, John C. Lin, Emily Yang, and Dien Wu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1022, https://doi.org/10.5194/acp-2017-1022, 2017
Revised manuscript not accepted
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Rapid global urbanization and significant fossil fuel consumption by cities emphasize the necessity of achieving independent and accurate quantification of the carbon emissions from urban areas. In this paper, we assess the potential of using total column CO2 concentration observed from satellite to quantify fossil-fuel carbon emissions from cities. This study could give insights into the capability of satellite observations on monitoring of the emissions on local scale.
Zachary R. Barkley, Thomas Lauvaux, Kenneth J. Davis, Aijun Deng, Natasha L. Miles, Scott J. Richardson, Yanni Cao, Colm Sweeney, Anna Karion, MacKenzie Smith, Eric A. Kort, Stefan Schwietzke, Thomas Murphy, Guido Cervone, Douglas Martins, and Joannes D. Maasakkers
Atmos. Chem. Phys., 17, 13941–13966, https://doi.org/10.5194/acp-17-13941-2017, https://doi.org/10.5194/acp-17-13941-2017, 2017
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This study quantifies methane emissions from natural gas production in north-eastern Pennsylvania. Methane observations from 10 flights in spring 2015 are compared to model-projected values, and methane emissions from natural gas are adjusted within the model to create the best match between the two data sets. This study find methane emissions from natural gas production to be low and may be indicative of characteristics of the basin that make sources from north-eastern Pennsylvania unique.
Yanni Cao, Guido Cervone, Zachary Barkley, Thomas Lauvaux, Aijun Deng, and Alan Taylor
Geosci. Model Dev., 10, 3425–3440, https://doi.org/10.5194/gmd-10-3425-2017, https://doi.org/10.5194/gmd-10-3425-2017, 2017
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This research investigates the role and importance of reprojecting geographic information system layers used by weather numerical models as input by performing sensitivity studies of greenhouse gas transport and dispersion in northeastern Pennsylvania. To bridge the gap between geographic information system data and atmospheric models, this study presents an innovative approach by creating R code to automatically generate model input from geographic data and analyze the model output.
Camille Viatte, Thomas Lauvaux, Jacob K. Hedelius, Harrison Parker, Jia Chen, Taylor Jones, Jonathan E. Franklin, Aijun J. Deng, Brian Gaudet, Kristal Verhulst, Riley Duren, Debra Wunch, Coleen Roehl, Manvendra K. Dubey, Steve Wofsy, and Paul O. Wennberg
Atmos. Chem. Phys., 17, 7509–7528, https://doi.org/10.5194/acp-17-7509-2017, https://doi.org/10.5194/acp-17-7509-2017, 2017
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This study estimates methane emissions at local scale in dairy farms using four new mobile ground-based remote sensing spectrometers (EM27/SUN) and isotopic in situ measurements. Our top-down estimates are in the low end of previous studies. Inverse modeling from a comprehensive high-resolution model simulations (WRF-LES) is used to assess the geographical distribution of the emissions. Both the model and the measurements indicate a mixture of anthropogenic and biogenic emissions.
A. Anthony Bloom, Thomas Lauvaux, John Worden, Vineet Yadav, Riley Duren, Stanley P. Sander, and David S. Schimel
Atmos. Chem. Phys., 16, 15199–15218, https://doi.org/10.5194/acp-16-15199-2016, https://doi.org/10.5194/acp-16-15199-2016, 2016
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Understanding terrestrial carbon processes is a major challenge in climate science. We define the satellite system required to understand greenhouse gas biogeochemistry: our study is focused on Amazon wetland CH4 emissions. We find that future geostationary satellites will provide the CH4 measurements required to understand wetland CH4 processes. Low-earth orbit satellites will be unable to resolve wetland CH4 processes due to a low number of cloud-free CH4 measurements over the Amazon basin.
Sha Feng, Thomas Lauvaux, Sally Newman, Preeti Rao, Ravan Ahmadov, Aijun Deng, Liza I. Díaz-Isaac, Riley M. Duren, Marc L. Fischer, Christoph Gerbig, Kevin R. Gurney, Jianhua Huang, Seongeun Jeong, Zhijin Li, Charles E. Miller, Darragh O'Keeffe, Risa Patarasuk, Stanley P. Sander, Yang Song, Kam W. Wong, and Yuk L. Yung
Atmos. Chem. Phys., 16, 9019–9045, https://doi.org/10.5194/acp-16-9019-2016, https://doi.org/10.5194/acp-16-9019-2016, 2016
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We developed a high-resolution land–atmosphere modelling system for urban CO2 emissions over the LA Basin. We evaluated various model configurations, FFCO2 products, and the impact of the model resolution. FFCO2 emissions outpace the atmospheric model resolution to represent the CO2 concentration variability across the basin. A novel forward model approach is presented to evaluate the surface measurement network, reinforcing the importance of using high-resolution emission products.
Susan L. Brantley, Roman A. DiBiase, Tess A. Russo, Yuning Shi, Henry Lin, Kenneth J. Davis, Margot Kaye, Lillian Hill, Jason Kaye, David M. Eissenstat, Beth Hoagland, Ashlee L. Dere, Andrew L. Neal, Kristen M. Brubaker, and Dan K. Arthur
Earth Surf. Dynam., 4, 211–235, https://doi.org/10.5194/esurf-4-211-2016, https://doi.org/10.5194/esurf-4-211-2016, 2016
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In order to better understand and forecast the evolution of the environment from the top of the vegetation canopy down to bedrock, numerous types of intensive measurements have been made over several years in a small watershed. The ability to expand such a study to larger areas and different environments requiring fewer measurements is essential. This study presents one possible approach to such an expansion, to collect necessary and sufficient measurements in order to forecast this evolution.
J.-M. Haussaire and M. Bocquet
Geosci. Model Dev., 9, 393–412, https://doi.org/10.5194/gmd-9-393-2016, https://doi.org/10.5194/gmd-9-393-2016, 2016
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The focus is on the development of low-order models of atmospheric transport and chemistry and their use for data assimilation purposes. A new low-order coupled chemistry meteorology model is developed. It consists of the Lorenz40-variable model used as a wind field coupled with a simple ozone photochemistry module. Advanced ensemble variational methods are applied to this model to obtain insights on the use of data assimilation with coupled models, in an offline mode or in an online mode.
M. Bocquet, P. N. Raanes, and A. Hannart
Nonlin. Processes Geophys., 22, 645–662, https://doi.org/10.5194/npg-22-645-2015, https://doi.org/10.5194/npg-22-645-2015, 2015
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The popular data assimilation technique known as the ensemble Kalman filter (EnKF) suffers from sampling errors due to the limited size of the ensemble. This deficiency is usually cured by inflating the sampled error covariances and by using localization. This paper further develops and discusses the finite-size EnKF, or EnKF-N, a variant of the EnKF that does not require inflation. It expands the use of the EnKF-N to a wider range of dynamical regimes.
M. Bocquet, H. Elbern, H. Eskes, M. Hirtl, R. Žabkar, G. R. Carmichael, J. Flemming, A. Inness, M. Pagowski, J. L. Pérez Camaño, P. E. Saide, R. San Jose, M. Sofiev, J. Vira, A. Baklanov, C. Carnevale, G. Grell, and C. Seigneur
Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, https://doi.org/10.5194/acp-15-5325-2015, 2015
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Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of concentrations, and perform inverse modeling. Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. We review here the current status of data assimilation in atmospheric chemistry models, with a particular focus on future prospects for data assimilation in CCMM.
L. Haszpra, Z. Barcza, T. Haszpra, Zs. Pátkai, and K. J. Davis
Atmos. Meas. Tech., 8, 1657–1671, https://doi.org/10.5194/amt-8-1657-2015, https://doi.org/10.5194/amt-8-1657-2015, 2015
A. W. King, R. J. Andres, K. J. Davis, M. Hafer, D. J. Hayes, D. N. Huntzinger, B. de Jong, W. A. Kurz, A. D. McGuire, R. Vargas, Y. Wei, T. O. West, and C. W. Woodall
Biogeosciences, 12, 399–414, https://doi.org/10.5194/bg-12-399-2015, https://doi.org/10.5194/bg-12-399-2015, 2015
Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette, M. Sicard, G. D'Amico, J. F. Léon, L. Alados-Arboledas, A. Amodeo, P. Augustin, J. Bach, L. Belegante, I. Binietoglou, X. Bush, A. Comerón, H. Delbarre, D. García-Vízcaino, J. L. Guerrero-Rascado, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, F. Molero, N. Montoux, A. Muñoz, C. Muñoz, D. Nicolae, A. Papayannis, G. Pappalardo, J. Preissler, V. Rizi, F. Rocadenbosch, K. Sellegri, F. Wagner, and F. Dulac
Atmos. Chem. Phys., 14, 12031–12053, https://doi.org/10.5194/acp-14-12031-2014, https://doi.org/10.5194/acp-14-12031-2014, 2014
M. O. L. Cambaliza, P. B. Shepson, D. R. Caulton, B. Stirm, D. Samarov, K. R. Gurney, J. Turnbull, K. J. Davis, A. Possolo, A. Karion, C. Sweeney, B. Moser, A. Hendricks, T. Lauvaux, K. Mays, J. Whetstone, J. Huang, I. Razlivanov, N. L. Miles, and S. J. Richardson
Atmos. Chem. Phys., 14, 9029–9050, https://doi.org/10.5194/acp-14-9029-2014, https://doi.org/10.5194/acp-14-9029-2014, 2014
Y. Wang, K. N. Sartelet, M. Bocquet, and P. Chazette
Atmos. Chem. Phys., 14, 3511–3532, https://doi.org/10.5194/acp-14-3511-2014, https://doi.org/10.5194/acp-14-3511-2014, 2014
T. W. Hilton, K. J. Davis, and K. Keller
Biogeosciences, 11, 217–235, https://doi.org/10.5194/bg-11-217-2014, https://doi.org/10.5194/bg-11-217-2014, 2014
O. Saunier, A. Mathieu, D. Didier, M. Tombette, D. Quélo, V. Winiarek, and M. Bocquet
Atmos. Chem. Phys., 13, 11403–11421, https://doi.org/10.5194/acp-13-11403-2013, https://doi.org/10.5194/acp-13-11403-2013, 2013
M. Bocquet and P. Sakov
Nonlin. Processes Geophys., 20, 803–818, https://doi.org/10.5194/npg-20-803-2013, https://doi.org/10.5194/npg-20-803-2013, 2013
M. R. Koohkan, M. Bocquet, Y. Roustan, Y. Kim, and C. Seigneur
Atmos. Chem. Phys., 13, 5887–5905, https://doi.org/10.5194/acp-13-5887-2013, https://doi.org/10.5194/acp-13-5887-2013, 2013
Y. Wang, K. N. Sartelet, M. Bocquet, and P. Chazette
Atmos. Chem. Phys., 13, 269–283, https://doi.org/10.5194/acp-13-269-2013, https://doi.org/10.5194/acp-13-269-2013, 2013
Related subject area
Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
The importance of moist thermodynamics on neutral buoyancy height for plumes from anthropogenic sources
Partitioning anthropogenic and natural methane emissions in Finland during 2000–2021 by combining bottom-up and top-down estimates
The role of OCO-3 XCO2 retrievals in estimating global terrestrial net ecosystem exchanges
Inverse modelling of New Zealand's carbon dioxide balance estimates a larger than expected carbon sink
The improved Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST): update, validation and applications
Quantifying transboundary transport flux of CO over the Tibetan Plateau: variabilities and drivers
Tracing the origins of stratospheric ozone intrusions: direct vs. indirect pathways and their impacts on Central and Eastern China in spring–summer 2019
Flow-dependent observation errors for greenhouse gas inversions in an ensemble Kalman smoother
Observational and model evidence for a prominent stratospheric influence on variability in tropospheric nitrous oxide
Estimation of Canada's methane emissions: inverse modelling analysis using the Environment and Climate Change Canada (ECCC) measurement network
Spatiotemporal source apportionment of ozone pollution over the Greater Bay Area
Potential of 14C-based vs. ΔCO-based ΔffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions
Combined CO2 measurement record indicates decreased Amazon forest carbon uptake, offset by Savannah carbon release
On the uncertainty of anthropogenic aromatic volatile organic compound emissions: model evaluation and sensitivity analysis
A mechanism of stratospheric O3 intrusion into the atmospheric environment: a case study of the North China Plain
Influence of atmospheric circulation on the interannual variability of transport from global and regional emissions into the Arctic
Surface networks in the Arctic may miss a future methane bomb
Potential of using CO2 observations over India in a regional carbon budget estimation by improving the modelling system
A bottom-up emission estimate for the 2022 Nord Stream gas leak: derivation, simulations, and evaluation
European CH4 inversions with ICON-ART coupled to the CarbonTracker Data Assimilation Shell
Extreme weather exacerbates ozone pollution in the Pearl River Delta, China: role of natural processes
Multidecadal ozone trends in China and implications for human health and crop yields: a hybrid approach combining a chemical transport model and machine learning
On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO2 in WRF-Chem – comparisons to in situ, satellite, and MAX-DOAS observations
Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling
The sensitivity of Southern Ocean atmospheric dimethyl sulfide (DMS) to modeled oceanic DMS concentrations and emissions
Impacts of maritime shipping on air pollution along the US East Coast
Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model
Impact of transport model resolution and a priori assumptions on inverse modeling of Swiss F-gas emissions
Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs
Can we use atmospheric CO2 measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris
A new steady-state gas–particle partitioning model of polycyclic aromatic hydrocarbons: implication for the influence of the particulate proportion in emissions
An analysis of CMAQ gas-phase dry deposition over North America through grid-scale and land-use-specific diagnostics in the context of AQMEII4
Rethinking the role of transport and photochemistry in regional ozone pollution: insights from ozone concentration and mass budgets
Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport
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
Development of a CMAQ–PMF-based composite index for prescribing an effective ozone abatement strategy: a case study of sensitivity of surface ozone to precursor volatile organic compound species in southern Taiwan
Comment on “Climate consequences of hydrogen emissions” by Ocko and Hamburg (2022)
Constraining emissions of volatile organic compounds from western US wildfires with WE-CAN and FIREX-AQ airborne observations
Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action
Coupled mesoscale–microscale modeling of air quality in a polluted city using WRF-LES-Chem
Impact of aerosol optics on vertical distribution of ozone in autumn over Yangtze River Delta
A view of the European carbon flux landscape through the lens of the ICOS atmospheric observation network
Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020
Evaluation of simulated CO2 power plant plumes from six high-resolution atmospheric transport models
Impacts of urbanization on air quality and the related health risks in a city with complex terrain
Optimizing 4 years of CO2 biospheric fluxes from OCO-2 and in situ data in TM5: fire emissions from GFED and inferred from MOPITT CO data
Development and application of a multi-scale modeling framework for urban high-resolution NO2 pollution mapping
Towards monitoring the CO2 source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO2 mole fraction
Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations
Estimated regional CO2 flux and uncertainty based on an ensemble of atmospheric CO2 inversions
Sepehr Fathi, Paul Makar, Wanmin Gong, Junhua Zhang, Katherine Hayden, and Mark Gordon
Atmos. Chem. Phys., 25, 2385–2405, https://doi.org/10.5194/acp-25-2385-2025, https://doi.org/10.5194/acp-25-2385-2025, 2025
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Our study explores the influence of water phase changes in plumes from industrial sources on atmospheric dispersion of emitted pollutants and air quality. Employing PRISM (Plume-Rise-Iterative-Stratified-Moist), a new method, we found that considering these effects significantly improves predictions of pollutant dispersion. This insight enhances our understanding of environmental impacts, enabling more accurate air quality modelling and fostering more effective pollution management strategies.
Maria K. Tenkanen, Aki Tsuruta, Hugo Denier van der Gon, Lena Höglund-Isaksson, Antti Leppänen, Tiina Markkanen, Ana Maria Roxana Petrescu, Maarit Raivonen, Hermanni Aaltonen, and Tuula Aalto
Atmos. Chem. Phys., 25, 2181–2206, https://doi.org/10.5194/acp-25-2181-2025, https://doi.org/10.5194/acp-25-2181-2025, 2025
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Accurate national methane (CH4) emission estimates are essential for tracking progress towards climate goals. This study compares estimates from Finland, which use different methods and scales, and shows how well a global model estimates emissions within a country. The bottom-up estimates vary a lot, but constraining them with atmospheric CH4 measurements brought the estimates closer together. We also highlight the importance of quantifying natural emissions alongside anthropogenic emissions.
Xingyu Wang, Fei Jiang, Hengmao Wang, Zhengqi Zhang, Mousong Wu, Jun Wang, Wei He, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 25, 867–880, https://doi.org/10.5194/acp-25-867-2025, https://doi.org/10.5194/acp-25-867-2025, 2025
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The role of OCO-3 XCO2 retrievals in estimating global terrestrial carbon fluxes is unclear. We investigate this by assimilating OCO-3 XCO2 retrievals alone and in combination with OCO-2 XCO2. The assimilation of OCO-3 XCO2 alone underestimates global land sinks, mainly at high latitudes, due to the lack of observations beyond 52° S and 52° N, large variations in the number of data, and varying observation times, while the joint assimilation of OCO-2 and OCO-3 XCO2 has the best performance.
Beata Bukosa, Sara Mikaloff-Fletcher, Gordon Brailsford, Dan Smale, Elizabeth D. Keller, W. Troy Baisden, Miko U. F. Kirschbaum, Donna L. Giltrap, Lìyı̌n Liáng, Stuart Moore, Rowena Moss, Sylvia Nichol, Jocelyn Turnbull, Alex Geddes, Daemon Kennett, Dora Hidy, Zoltán Barcza, Louis A. Schipper, Aaron M. Wall, Shin-Ichiro Nakaoka, Hitoshi Mukai, and Andrea Brandon
EGUsphere, https://doi.org/10.5194/egusphere-2024-3866, https://doi.org/10.5194/egusphere-2024-3866, 2025
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We used atmospheric measurements and inverse modeling to estimate New Zealand's carbon dioxide (CO₂) emissions and removals from 2011 to 2020. Our study reveals that New Zealand's land absorbs more CO₂ than previously estimated, particularly in areas dominated by indigenous forests. Our results highlight gaps in current national CO₂ estimates and methods, suggesting a need for further research to improve emissions reporting and refine approaches to track progress toward climate mitigation goals.
Zhou Zang, Jane Liu, David Tarasick, Omid Moeini, Jianchun Bian, Jinqiang Zhang, Anne M. Thompson, Roeland Van Malderen, Herman G. J. Smit, Ryan M. Stauffer, Bryan J. Johnson, and Debra E. Kollonige
Atmos. Chem. Phys., 24, 13889–13912, https://doi.org/10.5194/acp-24-13889-2024, https://doi.org/10.5194/acp-24-13889-2024, 2024
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The Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST) provides a global-scale, long-term ozone climatology that is horizontally and vertically resolved. In this study, we improved, updated and validated TOST from 1970 to 2021. Based on this TOST dataset, we characterized global ozone variations spatially in both the troposphere and stratosphere and temporally by season and decade. We also showed a stagnant lower stratospheric ozone variation since the late 1990s.
Zhenda Sun, Hao Yin, Zhongfeng Pan, Chongyang Li, Xiao Lu, Youwen Sun, and Cheng Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3252, https://doi.org/10.5194/egusphere-2024-3252, 2024
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This study investigates the variability and driving force of transboundary transport flux of carbon monoxide (CO) over the Tibetan Plateau from May 2018 to April 2024. We discovered that CO levels peak in late autumn and winter, driven mainly by external influx from South Asia, while internal emissions have decreased slightly. The findings reveal a growing trend in CO concentrations in the region, emphasizing the Tibetan Plateau's role as a significant receptor for transboundary pollutants.
Kai Meng, Tianliang Zhao, Yongqing Bai, Ming Wu, Le Cao, Xuewei Hou, Yuehan Luo, and Yongcheng Jiang
Atmos. Chem. Phys., 24, 12623–12642, https://doi.org/10.5194/acp-24-12623-2024, https://doi.org/10.5194/acp-24-12623-2024, 2024
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We studied the impact of stratospheric intrusions (SIs) on tropospheric and near-surface ozone in Central and Eastern China from a stratospheric source tracing perspective. SIs contribute the most in the eastern plains, with a contribution exceeding 15 %, and have a small contribution to the west and south. Western Siberia and Mongolia are the most critical source areas for indirect and direct SIs, with the Rossby wave and northeast cold vortex being important driving circulation systems.
Michael Steiner, Luca Cantarello, Stephan Henne, and Dominik Brunner
Atmos. Chem. Phys., 24, 12447–12463, https://doi.org/10.5194/acp-24-12447-2024, https://doi.org/10.5194/acp-24-12447-2024, 2024
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Atmospheric greenhouse gas inversions have great potential to independently check reported bottom-up emissions; however they are subject to large uncertainties. It is paramount to address and reduce the largest source of uncertainty, which stems from the representation of atmospheric transport in the models. In this study, we show that the use of a temporally varying flow-dependent atmospheric transport uncertainty can enhance the accuracy of emission estimation in an idealized experiment.
Cynthia D. Nevison, Qing Liang, Paul A. Newman, Britton B. Stephens, Geoff Dutton, Xin Lan, Roisin Commane, Yenny Gonzalez, and Eric Kort
Atmos. Chem. Phys., 24, 10513–10529, https://doi.org/10.5194/acp-24-10513-2024, https://doi.org/10.5194/acp-24-10513-2024, 2024
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This study examines the drivers of interannual variability in tropospheric N2O. New insights are obtained from aircraft data and a chemistry–climate model that explicitly simulates stratospheric N2O. The stratosphere is found to be the dominant driver of N2O variability in the Northern Hemisphere, while both the stratosphere and El Niño cycles are important in the Southern Hemisphere. These results are consistent with known atmospheric dynamics and differences between the hemispheres.
Misa Ishizawa, Douglas Chan, Doug Worthy, Elton Chan, Felix Vogel, Joe R. Melton, and Vivek K. Arora
Atmos. Chem. Phys., 24, 10013–10038, https://doi.org/10.5194/acp-24-10013-2024, https://doi.org/10.5194/acp-24-10013-2024, 2024
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Methane (CH4) emissions in Canada for 2007–2017 were estimated using Canada’s surface greenhouse gas measurements. The estimated emissions show no significant trend, but emission uncertainty was reduced as more measurement sites became available. Notably for climate change, we find the wetland CH4 emissions show a positive correlation with surface air temperature in summer. Canada’s measurement network could monitor future CH4 emission changes and compliance with climate change mitigation goals.
Yiang Chen, Xingcheng Lu, and Jimmy C. H. Fung
Atmos. Chem. Phys., 24, 8847–8864, https://doi.org/10.5194/acp-24-8847-2024, https://doi.org/10.5194/acp-24-8847-2024, 2024
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This study investigates the contribution of pollutants from different emitting periods to ozone episodes over the Greater Bay Area. The analysis reveals the variation in major spatiotemporal contributors to the O3 pollution under the influence of typhoons and subtropical high pressure. Through temporal contribution analysis, our work offers a new perspective on the evolution of O3 pollution and can aid in developing effective and timely control policies under unfavorable weather conditions.
Fabian Maier, Christian Rödenbeck, Ingeborg Levin, Christoph Gerbig, Maksym Gachkivskyi, and Samuel Hammer
Atmos. Chem. Phys., 24, 8183–8203, https://doi.org/10.5194/acp-24-8183-2024, https://doi.org/10.5194/acp-24-8183-2024, 2024
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We investigate the usage of discrete radiocarbon (14C)-based fossil fuel carbon dioxide (ffCO2) concentration estimates vs. continuous carbon monoxide (CO)-based ffCO2 estimates to evaluate the seasonal cycle of ffCO2 emissions in an urban region with an inverse modeling framework. We find that the CO-based ffCO2 estimates allow us to reconstruct robust seasonal cycles, which show the distinct COVID-19 drawdown in 2020 and can be used to validate emission inventories.
Santiago Botía, Saqr Munassar, Thomas Koch, Danilo Custodio, Luana S. Basso, Shujiro Komiya, Jost V. Lavric, David Walter, Manuel Gloor, Giordane Martins, Stijn Naus, Gerbrand Koren, Ingrid Luijkx, Stijn Hantson, John B. Miller, Wouter Peters, Christian Rödenbeck, and Christoph Gerbig
EGUsphere, https://doi.org/10.5194/egusphere-2024-1735, https://doi.org/10.5194/egusphere-2024-1735, 2024
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This study uses CO2 data from the Amazon Tall Tower Observatory and airborne profiles to estimate net carbon exchange. We found that the biogeographic Amazon is a net carbon sink, while the Cerrado and Caatinga biomes are net carbon sources, resulting in an overall neutral balance. To further reduce the uncertainty in our estimates we call for an expansion of the monitoring capacity, especially in the Amazon-Andes foothills.
Kevin Oliveira, Marc Guevara, Oriol Jorba, Hervé Petetin, Dene Bowdalo, Carles Tena, Gilbert Montané Pinto, Franco López, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7137–7177, https://doi.org/10.5194/acp-24-7137-2024, https://doi.org/10.5194/acp-24-7137-2024, 2024
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In this work, we assess and evaluate benzene, toluene, and xylene primary emissions and air quality levels in Spain by combining observations, emission inventories, and air quality modelling techniques. The comparison between modelled and observed levels allows identifying uncertainty sources within the emission input. This contributes to improving air quality models' performance when simulating these compounds, leading to better support for the design of effective pollution control strategies.
Yuehan Luo, Tianliang Zhao, Kai Meng, Jun Hu, Qingjian Yang, Yongqing Bai, Kai Yang, Weikang Fu, Chenghao Tan, Yifan Zhang, Yanzhe Zhang, and Zhikuan Li
Atmos. Chem. Phys., 24, 7013–7026, https://doi.org/10.5194/acp-24-7013-2024, https://doi.org/10.5194/acp-24-7013-2024, 2024
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We reveal a significant mechanism of stratospheric O3 intrusion (SI) into the atmospheric environment induced by an extratropical cyclone system. This system facilitates the downward transport of stratospheric O3 to the near-surface layer by vertical coupling, involving the upper westerly trough, the middle northeast cold vortex, and the lower extratropical cyclone in the troposphere. On average, stratospheric O3 contributed 26.77 % to near-surface O3 levels over the North China Plain.
Cheng Zheng, Yutian Wu, Mingfang Ting, and Clara Orbe
Atmos. Chem. Phys., 24, 6965–6985, https://doi.org/10.5194/acp-24-6965-2024, https://doi.org/10.5194/acp-24-6965-2024, 2024
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Trace gases and aerosols in the Arctic, which typically originate from midlatitude and tropical emission regions, modulate the Arctic climate via their radiative and chemistry impacts. Thus, long-range transport of these substances is important for understanding the current and the future change of Arctic climate. By employing chemistry–climate models, we explore how year-to-year variations in the atmospheric circulation modulate atmospheric long-range transport into the Arctic.
Sophie Wittig, Antoine Berchet, Isabelle Pison, Marielle Saunois, and Jean-Daniel Paris
Atmos. Chem. Phys., 24, 6359–6373, https://doi.org/10.5194/acp-24-6359-2024, https://doi.org/10.5194/acp-24-6359-2024, 2024
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The aim of this work is to analyse how accurately a methane bomb event could be detected with the current and a hypothetically extended stationary observation network in the Arctic. For this, we incorporate synthetically modelled possible future CH4 concentrations based on plausible emission scenarios into an inverse modelling framework. We analyse how well the increase is detected in different Arctic regions and evaluate the impact of additional observation sites in this respect.
Vishnu Thilakan, Dhanyalekshmi Pillai, Jithin Sukumaran, Christoph Gerbig, Haseeb Hakkim, Vinayak Sinha, Yukio Terao, Manish Naja, and Monish Vijay Deshpande
Atmos. Chem. Phys., 24, 5315–5335, https://doi.org/10.5194/acp-24-5315-2024, https://doi.org/10.5194/acp-24-5315-2024, 2024
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This study investigates the usability of CO2 mixing ratio observations over India to infer regional carbon sources and sinks. We demonstrate that a high-resolution modelling system can represent the observed CO2 variations reasonably well by improving the transport and flux variations at a fine scale. Future carbon data assimilation systems can thus benefit from these recently available CO2 observations when fine-scale variations are adequately represented in the models.
Rostislav Kouznetsov, Risto Hänninen, Andreas Uppstu, Evgeny Kadantsev, Yalda Fatahi, Marje Prank, Dmitrii Kouznetsov, Steffen Manfred Noe, Heikki Junninen, and Mikhail Sofiev
Atmos. Chem. Phys., 24, 4675–4691, https://doi.org/10.5194/acp-24-4675-2024, https://doi.org/10.5194/acp-24-4675-2024, 2024
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By relying solely on publicly available media reports, we were able to infer the temporal evolution and the injection height for the Nord Stream gas leaks in September 2022. The inventory specifies locations, vertical distributions, and temporal evolution of the methane sources. The inventory can be used to simulate the event with atmospheric transport models. The inventory is supplemented with a set of observational data tailored to evaluate the results of the simulated atmospheric dispersion.
Michael Steiner, Wouter Peters, Ingrid Luijkx, Stephan Henne, Huilin Chen, Samuel Hammer, and Dominik Brunner
Atmos. Chem. Phys., 24, 2759–2782, https://doi.org/10.5194/acp-24-2759-2024, https://doi.org/10.5194/acp-24-2759-2024, 2024
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The Paris Agreement increased interest in estimating greenhouse gas (GHG) emissions of individual countries, but top-down emission estimation is not yet considered policy-relevant. It is therefore paramount to reduce large errors and to build systems that are based on the newest atmospheric transport models. In this study, we present the first application of ICON-ART in the inverse modeling of GHG fluxes with an ensemble Kalman filter and present our results for European CH4 emissions.
Nan Wang, Hongyue Wang, Xin Huang, Xi Chen, Yu Zou, Tao Deng, Tingyuan Li, Xiaopu Lyu, and Fumo Yang
Atmos. Chem. Phys., 24, 1559–1570, https://doi.org/10.5194/acp-24-1559-2024, https://doi.org/10.5194/acp-24-1559-2024, 2024
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This study explores the influence of extreme-weather-induced natural processes on ozone pollution, which is often overlooked. By analyzing meteorological factors, natural emissions, chemistry pathways and atmospheric transport, we discovered that these natural processes could substantially exacerbate ozone pollution. The findings contribute to a deeper understanding of ozone pollution and offer valuable insights for controlling ozone pollution in the context of global warming.
Jia Mao, Amos P. K. Tai, David H. Y. Yung, Tiangang Yuan, Kong T. Chau, and Zhaozhong Feng
Atmos. Chem. Phys., 24, 345–366, https://doi.org/10.5194/acp-24-345-2024, https://doi.org/10.5194/acp-24-345-2024, 2024
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Surface ozone (O3) is well-known for posing great threats to both human health and agriculture worldwide. However, a multidecadal assessment of the impacts of O3 on public health and agriculture in China is lacking without sufficient O3 observations. We used a hybrid approach combining a chemical transport model and machine learning to provide a robust dataset of O3 concentrations over the past 4 decades in China, thereby filling the gap in the long-term O3 trend and impact assessment in China.
Leon Kuhn, Steffen Beirle, Vinod Kumar, Sergey Osipov, Andrea Pozzer, Tim Bösch, Rajesh Kumar, and Thomas Wagner
Atmos. Chem. Phys., 24, 185–217, https://doi.org/10.5194/acp-24-185-2024, https://doi.org/10.5194/acp-24-185-2024, 2024
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NO₂ is an important air pollutant. It was observed that the WRF-Chem model shows significant deviations in NO₂ abundance when compared to measurements. We use a 1-month simulation over central Europe to show that these deviations can be mostly resolved by reparameterization of the vertical mixing routine. In order to validate our results, they are compared to in situ, satellite, and MAX-DOAS measurements.
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023, https://doi.org/10.5194/acp-23-15235-2023, 2023
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We show declining trends in NH3 emissions over Europe for 2013–2020 using advanced dispersion and inverse modelling and satellite measurements from CrIS. Emissions decreased by −26% since 2013, showing that the abatement strategies adopted by the European Union have been very efficient. Ammonia emissions are low in winter and peak in summer due to temperature-dependent soil volatilization. The largest decreases were observed in central and western Europe in countries with high emissions.
Yusuf A. Bhatti, Laura E. Revell, Alex J. Schuddeboom, Adrian J. McDonald, Alex T. Archibald, Jonny Williams, Abhijith U. Venugopal, Catherine Hardacre, and Erik Behrens
Atmos. Chem. Phys., 23, 15181–15196, https://doi.org/10.5194/acp-23-15181-2023, https://doi.org/10.5194/acp-23-15181-2023, 2023
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Aerosols are a large source of uncertainty over the Southern Ocean. A dominant source of sulfate aerosol in this region is dimethyl sulfide (DMS), which is poorly simulated by climate models. We show the sensitivity of simulated atmospheric DMS to the choice of oceanic DMS data set and emission scheme. We show that oceanic DMS has twice the influence on atmospheric DMS than the emission scheme. Simulating DMS more accurately in climate models will help to constrain aerosol uncertainty.
Maryam Golbazi and Cristina Archer
Atmos. Chem. Phys., 23, 15057–15075, https://doi.org/10.5194/acp-23-15057-2023, https://doi.org/10.5194/acp-23-15057-2023, 2023
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We use scientific models to study the impact of ship emissions on air quality along the US East Coast. We find an increase in three major pollutants (PM2.5, NO2, and SO2) in coastal regions. However, we detect a reduction in ozone (O3) levels in major coastal cities. This reduction is linked to the significant emissions of nitrogen oxides (NOx) from ships, which scavenged O3, especially in highly polluted urban areas experiencing an NOx-limited regime.
Xinxu Zhao, Jia Chen, Julia Marshall, Michal Gałkowski, Stephan Hachinger, Florian Dietrich, Ankit Shekhar, Johannes Gensheimer, Adrian Wenzel, and Christoph Gerbig
Atmos. Chem. Phys., 23, 14325–14347, https://doi.org/10.5194/acp-23-14325-2023, https://doi.org/10.5194/acp-23-14325-2023, 2023
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We develop a modeling framework using the Weather Research and Forecasting model at a high spatial resolution (up to 400 m) to simulate atmospheric transport of greenhouse gases and interpret column observations. Output is validated against weather stations and column measurements in August 2018. The differential column method is applied, aided by air-mass transport tracing with the Stochastic Time-Inverted Lagrangian Transport (STILT) model, also for an exploratory measurement interpretation.
Ioannis Katharopoulos, Dominique Rust, Martin K. Vollmer, Dominik Brunner, Stefan Reimann, Simon J. O'Doherty, Dickon Young, Kieran M. Stanley, Tanja Schuck, Jgor Arduini, Lukas Emmenegger, and Stephan Henne
Atmos. Chem. Phys., 23, 14159–14186, https://doi.org/10.5194/acp-23-14159-2023, https://doi.org/10.5194/acp-23-14159-2023, 2023
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The effectiveness of climate change mitigation needs to be scrutinized by monitoring greenhouse gas (GHG) emissions. Countries report their emissions to the UN in a bottom-up manner. By combining atmospheric observations and transport models someone can independently validate emission estimates in a top-down fashion. We report Swiss emissions of synthetic GHGs based on kilometer-scale transport and inverse modeling, highlighting the role of appropriate resolution in complex terrain.
Tianfeng Chai, Xinrong Ren, Fong Ngan, Mark Cohen, and Alice Crawford
Atmos. Chem. Phys., 23, 12907–12933, https://doi.org/10.5194/acp-23-12907-2023, https://doi.org/10.5194/acp-23-12907-2023, 2023
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The SO2 emissions of three power plants are estimated using aircraft observations and an ensemble of HYSPLIT dispersion simulations with different plume rise parameters. The emission estimates using the runs with the lowest root mean square errors (RMSEs) and the runs with the best correlation coefficients between the predicted and observed mixing ratios both agree well with the Continuous Emissions Monitoring Systems (CEMS) data. The RMSE-based plume rise appears to be more reasonable.
Jinghui Lian, Thomas Lauvaux, Hervé Utard, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, Olivier Laurent, Ivonne Albarus, Mali Chariot, Simone Kotthaus, Martial Haeffelin, Olivier Sanchez, Olivier Perrussel, Hugo Anne Denier van der Gon, Stijn Nicolaas Camiel Dellaert, and Philippe Ciais
Atmos. Chem. Phys., 23, 8823–8835, https://doi.org/10.5194/acp-23-8823-2023, https://doi.org/10.5194/acp-23-8823-2023, 2023
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This study quantifies urban CO2 emissions via an atmospheric inversion for the Paris metropolitan area over a 6-year period from 2016 to 2021. Results show a long-term decreasing trend of about 2 % ± 0.6 % per year in the annual CO2 emissions over Paris. We conclude that our current capacity can deliver near-real-time CO2 emission estimates at the city scale in under a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.
Fu-Jie Zhu, Peng-Tuan Hu, and Wan-Li Ma
Atmos. Chem. Phys., 23, 8583–8590, https://doi.org/10.5194/acp-23-8583-2023, https://doi.org/10.5194/acp-23-8583-2023, 2023
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A new steady-state gas–particle partitioning model of polycyclic aromatic hydrocarbons was established based on the level-III multimedia fugacity model, which proved that the particulate proportion of PAHs in emissions was a crucial factor for G–P partitioning of PAHs. In addition, gaseous and particulate interference was also derived in the new steady-state model determined by the particulate proportion in emission that could derivate the G–P partitioning quotients from the equilibrium state.
Christian Hogrefe, Jesse O. Bash, Jonathan E. Pleim, Donna B. Schwede, Robert C. Gilliam, Kristen M. Foley, K. Wyat Appel, and Rohit Mathur
Atmos. Chem. Phys., 23, 8119–8147, https://doi.org/10.5194/acp-23-8119-2023, https://doi.org/10.5194/acp-23-8119-2023, 2023
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Under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in the widely used CMAQ model. The results illustrate how these tools can provide insights into similarities and differences between the two CMAQ dry deposition options that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.
Kun Qu, Xuesong Wang, Xuhui Cai, Yu Yan, Xipeng Jin, Mihalis Vrekoussis, Maria Kanakidou, Guy P. Brasseur, Jin Shen, Teng Xiao, Limin Zeng, and Yuanhang Zhang
Atmos. Chem. Phys., 23, 7653–7671, https://doi.org/10.5194/acp-23-7653-2023, https://doi.org/10.5194/acp-23-7653-2023, 2023
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Basic understandings of ozone processes, especially transport and chemistry, are essential to support ozone pollution control, but studies often have different views on their relative importance. We developed a method to quantify their contributions in the ozone mass and concentration budgets based on the WRF-CMAQ model. Results in a polluted region highlight the differences between two budgets. For future studies, two budgets are both needed to fully understand the effects of ozone processes.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
Atmos. Chem. Phys., 23, 7363–7382, https://doi.org/10.5194/acp-23-7363-2023, https://doi.org/10.5194/acp-23-7363-2023, 2023
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Surface observations of methane show that the seasonal cycle amplitude (SCA) of methane is decreasing in the northern high latitudes (NHLs) but increased globally (1995–2020). The NHL decrease is counterintuitive, as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate changes in SCA in the NHLs. We find well-mixed methane and changes in emissions from Canada, the Middle East, and Europe are the largest contributors to the SCA in NHLs.
Danyang Ma, Tijian Wang, Hao Wu, Yawei Qu, Jian Liu, Jane Liu, Shu Li, Bingliang Zhuang, Mengmeng Li, and Min Xie
Atmos. Chem. Phys., 23, 6525–6544, https://doi.org/10.5194/acp-23-6525-2023, https://doi.org/10.5194/acp-23-6525-2023, 2023
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Increasing surface ozone (O3) concentrations have long been a significant environmental issue in China, despite the Clean Air Action Plan launched in 2013. Most previous research ignores the contributions of CO2 variations. Our study comprehensively analyzed O3 variation across China from various perspectives and highlighted the importance of considering CO2 variations when designing long-term O3 control policies, especially in high-vegetation-coverage areas.
Jackson Hian-Wui Chang, Stephen M. Griffith, Steven Soon-Kai Kong, Ming-Tung Chuang, and Neng-Huei Lin
Atmos. Chem. Phys., 23, 6357–6382, https://doi.org/10.5194/acp-23-6357-2023, https://doi.org/10.5194/acp-23-6357-2023, 2023
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A novel CMAQ–PMF-based composite index is developed to identify the key VOC source species for an effective ozone abatement strategy. The index provides information as to which VOC species are key to ozone formation and where to reduce sources of these VOC species. Using the composite index, we recommended the VOC control measures in southern Taiwan should prioritize solvent usage, vehicle emissions, and the petrochemical industry.
Lei Duan and Ken Caldeira
Atmos. Chem. Phys., 23, 6011–6020, https://doi.org/10.5194/acp-23-6011-2023, https://doi.org/10.5194/acp-23-6011-2023, 2023
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Ocko and Hamburg (2022) emphasize the short-term climate impact of hydrogen, and we present an analysis that places greater focus on long-term outcomes. We have derived equations that describe the time-evolving impact of hydrogen and show that higher methane leakage is primarily responsible for the warming potential of blue hydrogen, while hydrogen leakage plays a less critical role. Fossil fuels show more prominent longer-term climate impacts than clean hydrogen under all emission scenarios.
Lixu Jin, Wade Permar, Vanessa Selimovic, Damien Ketcherside, Robert J. Yokelson, Rebecca S. Hornbrook, Eric C. Apel, I-Ting Ku, Jeffrey L. Collett Jr., Amy P. Sullivan, Daniel A. Jaffe, Jeffrey R. Pierce, Alan Fried, Matthew M. Coggon, Georgios I. Gkatzelis, Carsten Warneke, Emily V. Fischer, and Lu Hu
Atmos. Chem. Phys., 23, 5969–5991, https://doi.org/10.5194/acp-23-5969-2023, https://doi.org/10.5194/acp-23-5969-2023, 2023
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Air quality in the USA has been improving since 1970 due to anthropogenic emission reduction. Those gains have been partly offset by increased wildfire pollution in the western USA in the past 20 years. Still, we do not understand wildfire emissions well due to limited measurements. Here, we used a global transport model to evaluate and constrain current knowledge of wildfire emissions with recent observational constraints, showing the underestimation of wildfire emissions in the western USA.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
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We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Yuting Wang, Yong-Feng Ma, Domingo Muñoz-Esparza, Jianing Dai, Cathy Wing Yi Li, Pablo Lichtig, Roy Chun-Wang Tsang, Chun-Ho Liu, Tao Wang, and Guy Pierre Brasseur
Atmos. Chem. Phys., 23, 5905–5927, https://doi.org/10.5194/acp-23-5905-2023, https://doi.org/10.5194/acp-23-5905-2023, 2023
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Air quality in urban areas is difficult to simulate in coarse-resolution models. This work exploits the WRF (Weather Research and Forecasting) model coupled with a large-eddy simulation (LES) component and online chemistry to perform high-resolution (33.3 m) simulations of air quality in a large city. The evaluation of the simulations with observations shows that increased model resolution improves the representation of the chemical species near the pollution sources.
Shuqi Yan, Bin Zhu, Shuangshuang Shi, Wen Lu, Jinhui Gao, Hanqing Kang, and Duanyang Liu
Atmos. Chem. Phys., 23, 5177–5190, https://doi.org/10.5194/acp-23-5177-2023, https://doi.org/10.5194/acp-23-5177-2023, 2023
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We analyze ozone response to aerosol mixing states in the vertical direction by WRF-Chem simulations. Aerosols generally lead to turbulent suppression, precursor accumulation, low-level photolysis reduction, and upper-level photolysis enhancement under different underlying surface and pollution conditions. Thus, ozone decreases within the entire boundary layer during the daytime, and the decrease is the least in aerosol external mixing states compared to internal and core shell mixing states.
Ida Storm, Ute Karstens, Claudio D'Onofrio, Alex Vermeulen, and Wouter Peters
Atmos. Chem. Phys., 23, 4993–5008, https://doi.org/10.5194/acp-23-4993-2023, https://doi.org/10.5194/acp-23-4993-2023, 2023
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In this study, we evaluate what is in the influence regions of the ICOS atmospheric measurement stations to gain insight into what land cover types and land-cover-associated fluxes the network represents. Subsequently, insights about strengths, weaknesses, and potential gaps can assist in future network expansion decisions. The network is concentrated in central Europe, which leads to a general overrepresentation of coniferous forest and cropland and underrepresentation of grass and shrubland.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Dominik Brunner, Gerrit Kuhlmann, Stephan Henne, Erik Koene, Bastian Kern, Sebastian Wolff, Christiane Voigt, Patrick Jöckel, Christoph Kiemle, Anke Roiger, Alina Fiehn, Sven Krautwurst, Konstantin Gerilowski, Heinrich Bovensmann, Jakob Borchardt, Michal Galkowski, Christoph Gerbig, Julia Marshall, Andrzej Klonecki, Pascal Prunet, Robert Hanfland, Margit Pattantyús-Ábrahám, Andrzej Wyszogrodzki, and Andreas Fix
Atmos. Chem. Phys., 23, 2699–2728, https://doi.org/10.5194/acp-23-2699-2023, https://doi.org/10.5194/acp-23-2699-2023, 2023
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We evaluated six atmospheric transport models for their capability to simulate the CO2 plumes from two of the largest power plants in Europe by comparing the models against aircraft observations collected during the CoMet (Carbon Dioxide and Methane Mission) campaign in 2018. The study analyzed how realistically such plumes can be simulated at different model resolutions and how well the planned European satellite mission CO2M will be able to quantify emissions from power plants.
Chenchao Zhan, Min Xie, Hua Lu, Bojun Liu, Zheng Wu, Tijian Wang, Bingliang Zhuang, Mengmeng Li, and Shu Li
Atmos. Chem. Phys., 23, 771–788, https://doi.org/10.5194/acp-23-771-2023, https://doi.org/10.5194/acp-23-771-2023, 2023
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With the development of urbanization, urban land use and anthropogenic
emissions increase, affecting urban air quality and, in turn, the health risks associated with air pollutants. In this study, we systematically evaluate the impacts of urbanization on air quality and the corresponding health risks in a highly urbanized city with severe air pollution and complex terrain. This work focuses on the health risks caused by urbanization and can provide valuable insight for air pollution strategies.
Hélène Peiro, Sean Crowell, and Berrien Moore III
Atmos. Chem. Phys., 22, 15817–15849, https://doi.org/10.5194/acp-22-15817-2022, https://doi.org/10.5194/acp-22-15817-2022, 2022
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CO data can provide a powerful constraint on fire fluxes, supporting more accurate estimation of biospheric CO2 fluxes. We converted CO fire flux into CO2 fire prior, which is then used to adjust CO2 respiration. We applied this to two other fire flux products. CO2 inversions constrained by satellites or in situ data are then performed. Results show larger variations among the data assimilated than across the priors, but tropical flux from in situ inversions is sensitive to priors.
Zhaofeng Lv, Zhenyu Luo, Fanyuan Deng, Xiaotong Wang, Junchao Zhao, Lucheng Xu, Tingkun He, Yingzhi Zhang, Huan Liu, and Kebin He
Atmos. Chem. Phys., 22, 15685–15702, https://doi.org/10.5194/acp-22-15685-2022, https://doi.org/10.5194/acp-22-15685-2022, 2022
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This study developed a hybrid model, CMAQ-RLINE_URBAN, to predict the urban NO2 concentrations at a high spatial resolution. To estimate the influence of various street canyons on the dispersion of air pollutants, a new parameterization scheme was established based on computational fluid dynamics and machine learning methods. This work created a new method to identify the characteristics of vehicle-related air pollution at both city and street scales simultaneously and accurately.
Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew
Atmos. Chem. Phys., 22, 15287–15312, https://doi.org/10.5194/acp-22-15287-2022, https://doi.org/10.5194/acp-22-15287-2022, 2022
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This paper demonstrates how we can use atmospheric observations to improve the CO2 flux estimates in India. This is achieved by improving the representation of terrain, mesoscale transport, and flux variations. We quantify the impact of the unresolved variations in the current models on optimally estimated fluxes via inverse modelling and quantify the associated flux uncertainty. We illustrate how a parameterization scheme captures this variability in the coarse models.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Naveen Chandra, Prabir K. Patra, Yousuke Niwa, Akihiko Ito, Yosuke Iida, Daisuke Goto, Shinji Morimoto, Masayuki Kondo, Masayuki Takigawa, Tomohiro Hajima, and Michio Watanabe
Atmos. Chem. Phys., 22, 9215–9243, https://doi.org/10.5194/acp-22-9215-2022, https://doi.org/10.5194/acp-22-9215-2022, 2022
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This paper is intended to accomplish two goals: (1) quantify mean and uncertainty in non-fossil-fuel CO2 fluxes estimated by inverse modeling and (2) provide in-depth analyses of regional CO2 fluxes in support of emission mitigation policymaking. CO2 flux variability and trends are discussed concerning natural climate variability and human disturbances using multiple lines of evidence.
Cited articles
Alhamed, A., Lakshmivarahan S., and Stensrud, D. J.: Cluster analysis of
multimodel ensemble data from SAMEX, Mon. Weather Rev., 130, 226–256,
https://doi.org/10.1175/1520-0493 (2002)130,0226:CAOMED.2.0.CO;2, 2002.
Anderson, J. L.: A method for producing and evaluating probabilistic
forecasts from ensemble model integrations, J. Climate, 9, 1518–1530,
https://doi.org/10.1175/1520-0442(1996)009<1518:AMFPAE>2.0.CO;2,
1996.
Andrews, A. E., Kofler, J. D., Trudeau, M. E., Williams, J. C., Neff, D. H.,
Masarie, K. A., Chao, D. Y., Kitzis, D. R., Novelli, P. C., Zhao, C. L.,
Dlugokencky, E. J., Lang, P. M., Crotwell, M. J., Fischer, M. L., Parker, M.
J., Lee, J. T., Baumann, D. D., Desai, A. R., Stanier, C. O., De Wekker, S.
F. J., Wolfe, D. E., Munger, J. W., and Tans, P. P.: CO2, CO, and
CH4 measurements from tall towers in the NOAA Earth System Research
Laboratory's Global Greenhouse Gas Reference Network: instrumentation,
uncertainty analysis, and recommendations for future high-accuracy greenhouse
gas monitoring efforts, Atmos. Meas. Tech., 7, 647–687,
https://doi.org/10.5194/amt-7-647-2014, 2014.
Angevine, W. M., Brioude, J., McKeen, S., and Holloway, J. S.: Uncertainty in
Lagrangian pollutant transport simulations due to meteorological uncertainty
from a mesoscale WRF ensemble, Geosci. Model Dev., 7, 2817–2829,
https://doi.org/10.5194/gmd-7-2817-2014, 2014.
Baker, D. F., Law, R. M., Gurney, K. R., Rayner, P., Peylin, P., Denning, A.
S., Bousquet, P., Bruhwiler, L., Chen, Y. H., Ciais, P., Fung, I. Y.,
Heimann, M., John, J., Maki, T., Maksyutov, S., Masarie, K., Prather, M.,
Pak, B., Taguchi, S., and Zhu, Z.: TransCom 3 inversion intercomparison:
Impact of transport model errors on the interannual variability of regional
CO2 fluxes, 1988–2003, Global Biogeochem. Cy., 20, GB1002,
https://doi.org/10.1029/2004GB002439, 2006.
Berner, J., Shutts, G. J., Leutbecher, M., and Palmer, T. N.: A Spectral
Stochastic Kinetic Energy Backscatter Scheme and Its Impact on Flow-Dependent
Predictability in the ECMWF Ensemble Prediction System, J. Atmos. Sci., 66,
603–626, https://doi.org/10.1175/2008JAS2677.1, 2009.
Buizza, R., Houtekamer, P. L., Pellerin, G., Toth, Z., Zhu, Y., and Wei, M.:
A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems,
Mon. Weather Rev., 133, 1076–1097, https://doi.org/10.1175/MWR2905.1, 2005.
Candille, G. and Talagrand, O.: Evaluation of probabilistic prediction
systems for a scalar variable, Q. J. Roy. Meteor. Soc., 131, 2131–2150,
https://doi.org/10.1256/qj.04.71, 2005.
Černý, V.: Thermodynamical approach to the traveling salesman
problem: An efficient simulation algorithm, J. Optim. Theory Appl., 45,
41–51, https://doi.org/10.1007/BF00940812, 1985.
Corbin, K. D., Denning, A. S., Lokupitiya, E. Y., Schuh, A. E., Miles, N. L.,
Davis, K. J., Richardson, S., and Baker, I. T.: Assessing the impact of crops
on regional CO2 fluxes and atmospheric concentrations, Tellus B,
62, 521–532, https://doi.org/10.1111/j.1600-0889.2010.00485.x, 2010.
Crosby, J. L.: Computer Simulation in Genetics, John Wiley, Hoboken, N. J.,
1973.
Davis, K. J., Bakwin, P. S., Yi, C., Berger, B. W., Zhao, C., Teclaw, R. M.,
and Isebrands, J. G.: The annual cycles of CO2 and H2O
exchange over a northern mixed forest as observed from a very tall tower,
Glob. Change Biol., 9, 1278–1293,
https://doi.org/10.1046/j.1365-2486.2003.00672.x, 2003.
Denning, A. S., Fung, I. Y., and Randall, D.: Latitudinal gradient of
atmospheric CO2 due to seasonal exchange with land biota, Nature,
376, 240–243, https://doi.org/10.1038/376240a0, 1995.
Díaz-Isaac, L. I., Lauvaux, T., Davis, K. J., Miles, N. L., Richardson,
S. J., Jacobson, A. R., and Andrews, A. E.: Model-data comparison of MCI
field campaign atmospheric CO2 mole fractions, J. Geophys.
Res.-Atmos., 119, 10536–10551, https://doi.org/10.1002/2014JD021593, 2014.
Díaz-Isaac, L. I., Lauvaux, T., and Davis, K. J.: Impact of physical
parameterizations and initial conditions on simulated atmospheric transport
and CO2 mole fractions in the US Midwest, Atmos. Chem. Phys., 18,
14813–14835, https://doi.org/10.5194/acp-18-14813-2018, 2018.
Enting, I. G.: Inverse problems in atmospheric constituent studies: III,
Estimating errors in surface sources, Inverse Probl., 9, 649–665,
https://doi.org/10.1088/0266-5611/9/6/004, 1993.
Evensen, G.: Inverse Methods and Data Assimilation in Nonlinear Ocean Models,
Phys. D Nonlinear Phenom., 77, 108–129, https://doi.org/10.1016/0167-2789(94)90130-9,
1994a.
Evensen, G.: Sequential data assimilation with a nonlinear quasi-
geostrophic model using Monte Carlo methods to forecast error statistics, J.
Geophys. Res., 99, 10143–10162, 1994b.
Feng, S., Lauvaux, T., Newman, S., Rao, P., Ahmadov, R., Deng, A.,
Díaz-Isaac, L. I., Duren, R. M., Fischer, M. L., Gerbig, C., Gurney, K.
R., Huang, J., Jeong, S., Li, Z., Miller, C. E., O'Keeffe, D., Patarasuk, R.,
Sander, S. P., Song, Y., Wong, K. W., and Yung, Y. L.: Los Angeles megacity:
a high-resolution land-atmosphere modelling system for urban CO2
emissions, Atmos. Chem. Phys., 16, 9019–9045,
https://doi.org/10.5194/acp-16-9019-2016, 2016.
Fraser, A. and Burnell, D.: Computer Models in Genetics, McGraw-Hill, New
York, 1970.
Garaud, D. and Mallet, V.: Automatic calibration of an ensemble for
uncertainty estimation and probabilistic forecast: Application to air
quality, J. Geophys. Res., 116, D19304, https://doi.org/10.1029/2011JD015780, 2011.
Gerbig, C., Lin, J. C, Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens,
B. B., Bakwin, P. S., and Grainger, C. A.: Towards constraining
regional-scale fluxes of CO2 with atmospheric observations over a
continent: 1. Observed spatial variability from airborne platforms, J.
Geophys. Res., 108, 4756, https://doi.org/10.1029/2002JD003018, 2003.
Gerbig, C., Körner, S., and Lin, J. C.: Vertical mixing in atmospheric
tracer transport models: error characterization and propagation, Atmos. Chem.
Phys., 8, 591–602, https://doi.org/10.5194/acp-8-591-2008, 2008.
Gourdji, S. M., Hirsch, A. I., Mueller, K. L., Yadav, V., Andrews, A. E., and
Michalak, A. M.: Regional-scale geostatistical inverse modeling of North
American CO2 fluxes: a synthetic data study, Atmos. Chem. Phys.,
10, 6151–6167, https://doi.org/10.5194/acp-10-6151-2010, 2010.
Gurney, K. R., Law, R. M., Denning, A.S., Rayner, P. J., Baker, D., Bousquet,
P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fan, S., Fung, I. Y., Gloor, M.,
Heimann, M., Higuchi, K., John, J., Maki, T., Maksyutov, S., Masarie, K.,
Peylin, P., Prather, M., Pak, B. C., Randerson, J., Sarmiento, J., Taguchi,
S., Takahashi, T., and Yuen, C.-W.: Towards robust regional estimates of
CO2 sources and sinks using atmospheric transport models, Nature,
415, 626–630, https://doi.org/10.1038/415626a, 2002.
Hamill, T. M.: Interpretation of rank histograms for verifying ensemble
forecasts, Mon. Weather Rev., 129, 550–560, 2001.
Hamill, T. M. and Colucci, S. J.: Verification of Eta–RSM Short-Range
Ensemble Forecasts, Mon. Weather Rev., 125, 1312–1327,
https://doi.org/10.1175/1520-0493(1997)125<1312:VOERSR>2.0.CO;2, 1997.
Hilton, T. W., Davis, K. J., Keller, K., and Urban, N. M.: Improving North
American terrestrial CO2 flux diagnosis using spatial structure in
land surface model residuals, Biogeosciences, 10, 4607–4625,
https://doi.org/10.5194/bg-10-4607-2013, 2013.
Holland J. H.: Adaptation in Natural and Artificial Systems, University of
Michigan Press, Ann Arbor, 236 pp., 1975.
Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical dif- fusion package with
an explicit treatment of entrain- ment processes., Mon. Weather Rev., 134,
2318–2341, https://doi.org/10.1175/MWR3199.1, 2006.
Houtekamer, P. L. and Mitchell, H. L.: A Sequential Ensemble Kalman Filter
for Atmospheric Data Assimilation, Mon. Weather Rev., 129, 123–137,
https://doi.org/10.1175/1520-0493(2001)129<0123:ASEKFF>2.0.CO;2, 2001.
Houweling, S., Aben, I., Breon, F.-M., Chevallier, F., Deutscher, N.,
Engelen, R., Gerbig, C., Griffith, D., Hungershoefer, K., Macatangay, R.,
Marshall, J., Notholt, J., Peters, W., and Serrar, S.: The importance of
transport model uncertainties for the estimation of CO2 sources and
sinks using satellite measurements, Atmos. Chem. Phys., 10, 9981–9992,
https://doi.org/10.5194/acp-10-9981-2010, 2010.
Huntzinger, D. N., Post, W. M., Wei, Y., Michalak, A. M., West, T. O.,
Jacobson, A. R., Baker, I. T., Chen, J. M., Davis, K. J., Hayes, D. J.,
Hoffman, F. M., Jain, A. K., Liu, S., McGuire, A. D., Neilson, R. P., Potter,
C., Poulter, B., Price, D., Raczka, B. M., Tian, H. Q., Thornton, P.,
Tomelleri, E., Viovy, N., Xiao, J., Yuan, W., Zeng, N., Zhao, M., and Cook,
R.: North American Carbon Program (NACP) regional interim synthesis:
Terrestrial biospheric model intercomparison, Ecol. Model., 232, 144–157,
https://doi.org/10.1016/J.Ecolmodel.2012.02.004, 2012.
Janjic, Z.: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme
in the NCEP Meso model, National Centers for En- vironmental Prediction, USA,
Office Note No. 437, 2002.
Johnson, A., Wang, X., Xue, M., and Kong, F.: Hierarchical Cluster Analysis
of a Convection-Allowing Ensemble during the Hazardous Weather Testbed 2009
Spring Experiment, Part II: Ensemble Clustering over the Whole Experiment
Period, Mon. Weather Rev., 139, 3694–3710, https://doi.org/10.1175/MWR-D-11-00016.1,
2011.
Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P.: Optimization by Simulated
Annealing, Science, 220, 671–680, https://doi.org/10.1126/science.220.4598.671, 1983.
Kretschmer, R., Gerbig, C., Karstens, U., and Koch, F.-T.: Error
characterization of CO2 vertical mixing in the atmospheric
transport model WRF-VPRM, Atmos. Chem. Phys., 12, 2441–2458,
https://doi.org/10.5194/acp-12-2441-2012, 2012.
Lauvaux, T. and Davis, K. J.: Planetary boundary layer errors in mesoscale
inversions of column-integrated CO2 measurements, J. Geophys.
Res.-Atmos., 119, 490–508, https://doi.org/10.1002/2013JD020175, 2014.
Lauvaux, T., Pannekoucke, O., Sarrat, C., Chevallier, F., Ciais, P., Noilhan,
J., and Rayner, P. J.: Structure of the transport uncertainty in mesoscale
inversions of CO2 sources and sinks using ensemble model
simulations, Biogeosciences, 6, 1089–1102,
https://doi.org/10.5194/bg-6-1089-2009, 2009.
Law, R. M., Peters, W., Rödenbeck, C., Aulagnier, C., Baker, I.,
Bergmann, D. J., Bousquet, P., Brandt, J., Bruhwiler, L., Cameron-Smith, P.
J., Christensen, J. H., Delage, F., Denning, A. S., Fan, S., Geels, C.,
Houweling, S., Imasu, R., Karstens, U., Kawa, S. R., Kleist, J., Krol, M. C.,
Lin, S. J., Lokupitiya, R., Maki, T., Maksyutov, S., Niwa, Y., Onishi, R.,
Parazoo, N., Patra, P. K., Pieterse, G., Rivier, L., Satoh, M., Serrar, S.,
Taguchi, S., Takigawa, M., Vautard, R., Vermeulen, A. T., and Zhu, Z.:
TransCom model simulations of hourly atmospheric CO2: Experimental
overview and diurnal cycle results for 2002, Global Biogeochem. Cy., 22,
GB3009, https://doi.org/10.1029/2007GB003050, 2008.
Lee, J.: Techniques for Down-Selecting Numerical Weather Prediction
Ensembles, Ph.D. Dissertation, The Pennsylvania State University, University
Park, 131 pp., 2012.
Lee, J. A., Kolczynski, W. C., McCandless, T. C., and Haupt, S. E.: An
Objective Methodology for Configuring and Down-Selecting an NWP Ensemble for
Low-Level Wind Prediction, Mon. Weather Rev., 140, 2270–2286,
https://doi.org/10.1175/MWR-D-11-00065.1, 2012.
Lee, J. A., Haupt, S. E. H. and Young, G. S.: Down-Selecting Numerical
Weather Prediction Multi-Physics Ensembles with Hierarchical Cluster
Analysis, J. Climatol. Weather Forecast., 4, 1–16,
https://doi.org/10.4172/2332-2594.1000156, 2016.
Lin, J. C. and Gerbig, C.: Accounting for the effect of transport errors on
tracer inversions, Geophys. Res. Lett., 32, 1–5, https://doi.org/10.1029/2004GL021127,
2005.
Ménétrier, B., Montmerle, T., Michel, Y., and Berre, L.: Linear
Filtering of Sample Covariances for Ensemble-Based Data Assimilation, Part I:
Optimality Criteria and Application to Variance Filtering and Covariance
Localization, Mon. Weather Rev., 143, 1622–1643,
https://doi.org/10.1175/MWR-D-14-00157.1, 2015.
Miles, N. L., Richardson, S. J., Davis, K. J., Lauvaux, T., Andrews, A. E.,
West, T. O., Bandaru, V., and Crosson, E. R.: Large amplitude spatial and
temporal gradients in atmospheric boundary layer CO2 mole fractions
detected with a tower-based network in the U.S. upper Midwest, J. Geophys.
Res.-Biogeo., 117, 01019, https://doi.org/10.1029/2011JG001781, 2012.
Miles, N. L., Richardson, S. J., Davis, K. J., Andrews, A. E., Griffis, T.
J., Bandaru, V., and Hosman, K. P.: NACP MCI: Tower Atmospheric CO2
Concentrations, Upper Midwest Region, USA, 2007–2009, Oak Ridge National
Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA,
https://doi.org/10.3334/ORNLDAAC/1202, 2013.
Miller, S. M., Hayek, M. N., Andrews, A. E., Fung, I., and Liu, J.: Biases in
atmospheric CO2 estimates from correlated meteorology modeling
errors, Atmos. Chem. Phys., 15, 2903–2914,
https://doi.org/10.5194/acp-15-2903-2015, 2015.
Nakanishi, M. and Niino, H.: An improved Mellor-Yamada Level-3 model with
condensation physics: Its design and verification, Bound.-Lay. Meteorol.,
112, 1–31, https://doi.org/10.1023/B:BOUN.0000020164.04146.98, 2004.
Patra, P. K., Law, R. M., Peters, W., Rödenbeck, C., Takigawa, M.,
Aulagnier, C., Baker, I., Bergmann, D. J., Bousquet, P., Brandt, J.,
Bruhwiler, L., Cameron-Smith, P. J., Christensen, J. H., Delage, F., Denning,
A. S., Fan, S., Geels, C., Houweling, S., Imasu, R., Karstens, U., Kawa, S.
R., Kleist, J., Krol, M. C., Lin, S. J., Lokupitiya, R., Maki, T., Maksyutov,
S., Niwa, Y., Onishi, R., Parazoo, N., Pieterse, G., Rivier, L., Satoh, M.,
Serrar, S., Taguchi, S., Vautard, R., Vermeulen, A. T., and Zhu, Z.: TransCom
model simulations of hourly atmospheric CO2: Analysis of
synoptic-scale variations for the period 2002-2003, Global Biogeochem. Cy.,
22, GB4013, https://doi.org/10.1029/2007GB003081, 2008.
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway, T. J.,
Masarie, K., Miller, J. B., Bruhwiler, L. M. P., Pétron, G., Hirsch, A.
I., Worthy, D. E. J., van der Werf, G. R., Randerson, J. T., Wennberg, P. O.,
Krol, M. C., and Tans, P. P.: An atmospheric perspective on North American
carbon dioxide exchange: CarbonTracker, P. Natl. Acad. Sci. USA, 104,
18925–18930, https://doi.org/10.1073/pnas.0708986104, 2007.
Peylin, P., Law, R. M., Gurney, K. R., Chevallier, F., Jacobson, A. R., Maki,
T., Niwa, Y., Patra, P. K., Peters, W., Rayner, P. J., Rödenbeck, C., van
der Laan-Luijkx, I. T., and Zhang, X.: Global atmospheric carbon budget:
results from an ensemble of atmospheric CO2 inversions,
Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013,
2013.
Pickett-Heaps, C. A., Rayner, P. J., Law, R. M., Ciais, P., Patra, P. K.,
Bousquet, P., Peylin, P., Maksyutov, S., Marshall, J., Rödenbeck, C.,
Langenfelds, R. L., Steele, L. P., Francey, R. J., Tans, P., and Sweeney, C.:
Atmospheric CO2 inversion validation using vertical profile
measurements: Analysis of four independent inversion models, J. Geophys.
Res.-Atmos., 116, 3773–3779, https://doi.org/10.1029/2010JD014887, 2011.
Riccio, A., Ciaramella, A., Giunta, G., Galmarini, S., Solazzo, E., and
Potempski, S.: On the systematic reduction of data complexity in multimodel
atmospheric dispersion ensemble modeling, J. Geophys. Res.-Atmos., 117,
D05314, https://doi.org/10.1029/2011JD016503, 2012.
Richardson, S. J., Miles, N. L., Davis, K. J., Crosson, E. R., Rella, C. W.,
and Andrews, A. E.: Field testing of cavity ring-down spectroscopy analyzers
measuring carbon dioxide and water vapor, J. Atmos. Ocean. Tech., 29,
397–406, https://doi.org/10.1175/JTECH-D-11-00063.1, 2012.
Roulston, M. S. and Smith, L. A.: Combining dynamical and statistical
ensembles, Tellus A, 55, 16–30, https://doi.org/10.1034/j.1600-0870.2003.201378.x, 2003.
Sarmiento, D. P., Davis, K. J., Deng, A., Lauvaux, T., Brewer, A., and
Hardesty, M.: A comprehensive assessment of land surface-atmosphere
interactions in a WRF/Urban modeling system for Indianapolis, Elementa, 5,
https://doi.org/10.1525/elementa.132, 2017.
Sarmiento, J. L., Gloor, M., Gruber, N., Beaulieu, C., Jacobson, A. R.,
Mikaloff Fletcher, S. E., Pacala, S., and Rodgers, K.: Trends and regional
distributions of land and ocean carbon sinks, Biogeosciences, 7, 2351–2367,
https://doi.org/10.5194/bg-7-2351-2010, 2010.
Schuh, A. E., Lauvaux, T., West, T. O., Denning, A. S., Davis, K. J., Miles,
N., Richardson, S., Uliasz, M., Lokupitiya, E., Cooley, D., Andrews, A., and
Ogle, S.: Evaluating atmospheric CO2 inversions at multiple scales
over a highly inventoried agricultural landscape, Glob. Change Biol., 19,
1424–1439, https://doi.org/10.1111/gcb.12141, 2013.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M.,
Duda, M., Huang, X. Y., Wang, W., and Powers, J. G.: A description of the
advanced research WRF version 3, NCAR, Tech. Note, Mesoscale and Microscale
Meteorology Division, National Center for Atmospheric Research, Boulder,
Colorado, USA, 2008.
Solazzo, E. and Galmarini, S.: The Fukushima-137Cs deposition case
study: Properties of the multi-model ensemble, J. Environ. Radioact., 139,
226–233, https://doi.org/10.1016/j.jenvrad.2014.02.017, 2014.
Stephens, B. B., Gurney, K. R., Tans, P. P., Sweeney, C., Peters, W.,
Bruhwiler, L., Ciais, P., Ramonet, M., Bousquet, P., Nakazawa, T., Aoki, S.,
Machida, T., Inoue, G., Vinnichenko, N., Lloyd, J., Jordan, A., Heimann, M.,
Shibistova, O., Langenfelds, R. L., Steele, L. P., Francey, R. J., and
Denning, A. S.: Weak northern and strong tropical land carbon uptake from
vertical profiles of atmospheric CO2, Science, 316, 1732–1735,
https://doi.org/10.1126/science.1137004, 2007.
Stull, R. B.: An Introduction to Boundary Layer Meteorology, Kluwer Academic,
Dordrecht, 666 pp., 1988.
Talagrand, O., Vautard, R., and Strauss, B.: Evaluation of Probabilistic
Prediction System, in: Workshop on Predictability, ECMWF, Reading, U. K.,
1999.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res., 106, 7183–7192, https://doi.org/10.1029/2000JD900719, 2001.
Thompson, G., Rasmussen, R. M., and Manning, K.: Explicit Forecasts of Winter
Precipitation Using an Improved Bulk Micro- physics Scheme, Part I:
Description and Sensitivity Analysis, Mon. Weather Rev., 132, 519–542, 2004.
Wang, W., Davis, K. J., Yi, C., Patton, E. G., Butler, M. P., Ricciuto, D.
M., and Bakwin, P. S.: A note on top-down and bottom-up gradient functions
over a forested site, Bound.-Lay. Meteorol., 124, 305–314,
https://doi.org/10.1007/s10546-007-9162-0, 2007.
Whitaker, J. S. and Loughe, A. F.: The Relationship between Ensemble Spread
and Ensemble Mean Skill, Mon. Weather Rev., 126, 3292–3302,
https://doi.org/10.1175/1520-0493(1998)126<3292:TRBESA>2.0.CO;2, 1998.
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, 3rd edn.,
Academic Press, Oxford, Waltham, MA, 2011.
Williams, I. N., Riley, W. J., Torn, M. S., Berry, J. A., and Biraud, S. C.:
Using boundary layer equilibrium to reduce uncertainties in transport models
and CO2 flux inversions, Atmos. Chem. Phys., 11, 9631–9641,
https://doi.org/10.5194/acp-11-9631-2011, 2011.
Yussouf, N., Stensrud, D. J., and Lakshmivarahan, S.: Cluster analysis of
multimodel ensemble data over New England, Mon. Weather Rev., 132,
2452–2462, https://doi.org/10.1175/1520-0493(2004)132<2452:CAOMED>2.0.CO;2, 2004.
Yver, C. E., Graven, H. D., Lucas, D. D., Cameron-Smith, P. J., Keeling, R.
F., and Weiss, R. F.: Evaluating transport in the WRF model along the
California coast, Atmos. Chem. Phys., 13, 1837–1852,
https://doi.org/10.5194/acp-13-1837-2013, 2013.
Short summary
We demonstrate that transport model errors, one of the main contributors to the uncertainty in regional CO2 inversions, can be represented by a small-size ensemble carefully calibrated with meteorological data. Our results also confirm transport model errors represent a significant fraction of the model–data mismatch in CO2 mole fractions and hence in regional inverse CO2 fluxes.
We demonstrate that transport model errors, one of the main contributors to the uncertainty in...
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