Articles | Volume 14, issue 5
https://doi.org/10.5194/gmd-14-3037-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3037-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and evaluation of CO2 transport in MPAS-A v6.3
Department of Geography and Environmental Studies, Central Michigan University, Mount Pleasant, MI, USA
Institute for Great Lakes Research, Central Michigan University, Mount Pleasant, MI, USA
Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, USA
now at: Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
Kenneth J. Davis
Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, USA
Sandip Pal
Department of Geosciences, Texas Tech University, Lubbock, TX, USA
Josep-Anton Morguí
Environmental Science and Technology Institute, Universitat Autònoma de Barcelona, ICTA-UAB, Bellaterra, Spain
Department of Evolutionary Biology, Ecology and Environmental Sciences, Universitat de Barcelona, BEECA-UB, Barcelona, Spain
Related authors
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
Short summary
Short summary
The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Tao Zheng, Nancy H. F. French, and Martin Baxter
Geosci. Model Dev., 11, 1725–1752, https://doi.org/10.5194/gmd-11-1725-2018, https://doi.org/10.5194/gmd-11-1725-2018, 2018
Short summary
Short summary
We developed WRF-CO2 4D-Var, a carbon dioxide data assimilation system based on the online atmospheric chemistry–transport model WRF-Chem. The accuracy of the model for sensitivity calculation and inverse modeling is assessed with pseudo-observation data. In this system, carbon dioxide is treated as an atmospheric tracer and its influence on meteorology is ignored. This system provides a useful model tool for regional-scale carbon source attribution and uncertainty assessment.
Roger Curcoll, Josep-Anton Morguí, Alba Àgueda, Lídia Cañas, Sílvia Borràs, Arturo Vargas, and Claudia Grossi
EGUsphere, https://doi.org/10.5194/egusphere-2024-1370, https://doi.org/10.5194/egusphere-2024-1370, 2024
Short summary
Short summary
In this work, the methane emissions from the rice crops of the Ebro Delta were estimated with the Radon Tracer Method, using backtrajectories and radon and methane observations. Estimated fluxes show a strong seasonality with maximums in October, corresponding with the period of harvest and straw incorporation. The estimated annual methane emission was about 262.8 kg CH4 ha‑1. Results were compared with fluxes obtained with static chambers showing a stunning agreement between both methodologies.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
Short summary
Short summary
The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
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
Short summary
Short summary
We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
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
Short summary
Short summary
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.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
Short summary
Short summary
Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
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
Short summary
Short summary
HALO is a multi-functional lidar that measures CH4 columns and profiles of H2O mixing ratio and aerosol/cloud optical properties. HALO supports carbon cycle, weather dynamics, and radiation science suborbital research and is a technology testbed for future space-based differential absorption lidar missions. In 2019 HALO collected CH4 columns and aerosol/cloud profiles during the ACT-America campaign. Here we assess HALO's CH4 accuracy and precision compared to co-located in situ observations.
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
Short summary
Short summary
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.
Roger Curcoll, Josep-Anton Morguí, Armand Kamnang, Lídia Cañas, Arturo Vargas, and Claudia Grossi
Atmos. Meas. Tech., 15, 2807–2818, https://doi.org/10.5194/amt-15-2807-2022, https://doi.org/10.5194/amt-15-2807-2022, 2022
Short summary
Short summary
Low-cost air enquirer kits, including CO2 and environmental parameter sensors, have been designed, built, and tested in a new steady-state through-flow chamber for simultaneous measurements of CO2 fluxes in soil and CO2 concentrations in air. A CO2 calibration and multiparametric fitting reduced the total uncertainty of CO2 concentration by 90 %. This system allows continuous measurement of CO2 fluxes and CO2 ambient air, with low cost (EUR 1200), low energy demand (<5 W), and low maintenance.
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
Short summary
Short summary
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.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
Short summary
Short summary
We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Claudia Grossi, Scott D. Chambers, Olivier Llido, Felix R. Vogel, Victor Kazan, Alessandro Capuana, Sylvester Werczynski, Roger Curcoll, Marc Delmotte, Arturo Vargas, Josep-Anton Morguí, Ingeborg Levin, and Michel Ramonet
Atmos. Meas. Tech., 13, 2241–2255, https://doi.org/10.5194/amt-13-2241-2020, https://doi.org/10.5194/amt-13-2241-2020, 2020
Short summary
Short summary
The sustainable support of radon metrology at the environmental level offers new scientific possibilities for the quantification of greenhouse gas (GHG) emissions and the determination of their source terms as well as for the identification of radioactive sources for the assessment of radiation exposure. This study helps to harmonize the techniques commonly used for atmospheric radon and radon progeny activity concentration measurements.
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
Short summary
Short summary
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.
Anna Agustí-Panareda, Michail Diamantakis, Sébastien Massart, Frédéric Chevallier, Joaquín Muñoz-Sabater, Jérôme Barré, Roger Curcoll, Richard Engelen, Bavo Langerock, Rachel M. Law, Zoë Loh, Josep Anton Morguí, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Coleen Roehl, Alex T. Vermeulen, Thorsten Warneke, and Debra Wunch
Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, https://doi.org/10.5194/acp-19-7347-2019, 2019
Short summary
Short summary
This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO2 patterns associated with evolving weather. The modelling of CO2 weather is crucial to interpret the variability from ground-based and satellite CO2 observations, which can then be used to infer CO2 fluxes in atmospheric inversions. The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO2 flux distribution.
Liza I. Díaz-Isaac, Thomas Lauvaux, Marc Bocquet, and Kenneth J. Davis
Atmos. Chem. Phys., 19, 5695–5718, https://doi.org/10.5194/acp-19-5695-2019, https://doi.org/10.5194/acp-19-5695-2019, 2019
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Tao Zheng, Nancy H. F. French, and Martin Baxter
Geosci. Model Dev., 11, 1725–1752, https://doi.org/10.5194/gmd-11-1725-2018, https://doi.org/10.5194/gmd-11-1725-2018, 2018
Short summary
Short summary
We developed WRF-CO2 4D-Var, a carbon dioxide data assimilation system based on the online atmospheric chemistry–transport model WRF-Chem. The accuracy of the model for sensitivity calculation and inverse modeling is assessed with pseudo-observation data. In this system, carbon dioxide is treated as an atmospheric tracer and its influence on meteorology is ignored. This system provides a useful model tool for regional-scale carbon source attribution and uncertainty assessment.
Claudia Grossi, Felix R. Vogel, Roger Curcoll, Alba Àgueda, Arturo Vargas, Xavier Rodó, and Josep-Anton Morguí
Atmos. Chem. Phys., 18, 5847–5860, https://doi.org/10.5194/acp-18-5847-2018, https://doi.org/10.5194/acp-18-5847-2018, 2018
Short summary
Short summary
To gain a full picture of the Spanish (and European) GHG balance, understanding of CH4 emissions in different regions is a critical challenge, as is the improvement of bottom-up inventories for all European regions. This study uses, among other elements, GHG, meteorological and 222Rn tracer data from a Spanish region to understand the main causes of temporal variability of GHG mixing ratios. The study can offer new insights into regional emissions by identifying the impacts of changing sources.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Sally Newman, Xiaomei Xu, Kevin R. Gurney, Ying Kuang Hsu, King Fai Li, Xun Jiang, Ralph Keeling, Sha Feng, Darragh O'Keefe, Risa Patarasuk, Kam Weng Wong, Preeti Rao, Marc L. Fischer, and Yuk L. Yung
Atmos. Chem. Phys., 16, 3843–3863, https://doi.org/10.5194/acp-16-3843-2016, https://doi.org/10.5194/acp-16-3843-2016, 2016
Short summary
Short summary
Combining 14C and 13C data from the Los Angeles, CA megacity with background data allows source attribution of CO2 emissions among biosphere, natural gas, and gasoline. The 8-year record of CO2 emissions from fossil fuel burning is consistent with "The Great Recession" of 2008–2010. The long-term trend and source attribution are consistent with government inventories. Seasonal patterns agree with the high-resolution Hestia-LA emission data product, when seasonal wind directions are considered.
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
Short summary
Short summary
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.
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
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
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
A. Font, C. S. B. Grimmond, J.-A. Morguí, S. Kotthaus, M. Priestman, and B. Barratt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-13465-2013, https://doi.org/10.5194/acpd-13-13465-2013, 2013
Revised manuscript not accepted
Related subject area
Atmospheric sciences
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Orbital-Radar v1.0.0: A tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
New explicit formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations
Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3
The CHIMERE chemistry-transport model v2023r1
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1
Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary
Short summary
We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
Short summary
Short summary
Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
Short summary
Short summary
RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
Short summary
Short summary
We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
Short summary
We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
Short summary
Short summary
Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
Short summary
Short summary
Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
Short summary
Short summary
AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
Short summary
Short summary
Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
Short summary
Short summary
Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
Short summary
Short summary
The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
Short summary
Short summary
A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
Short summary
Short summary
The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
Short summary
Short summary
Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
Short summary
Short summary
This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
Short summary
Short summary
Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
Short summary
Short summary
This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
Short summary
Short summary
Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
Short summary
Short summary
TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
Short summary
Short summary
Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
Short summary
Short summary
We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
Short summary
Short summary
A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
Short summary
Short summary
In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
Short summary
Short summary
A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
Short summary
Short summary
Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
Short summary
Short summary
We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1437, https://doi.org/10.5194/egusphere-2024-1437, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can well reproduce the distribution of PAHs. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change of BaP is less than PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although "the Action Plan" has been implemented.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
Short summary
Short summary
Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
Short summary
Short summary
Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
Short summary
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Cited articles
Agustí-Panareda, A., Massart, S., Chevallier, F., Boussetta, S., Balsamo, G., Beljaars, A., Ciais, P., Deutscher, N. M., Engelen, R., Jones, L., Kivi, R., Paris, J.-D., Peuch, V.-H., Sherlock, V., Vermeulen, A. T., Wennberg, P. O., and Wunch, D.: Forecasting global atmospheric CO2, Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, 2014. a, b, c
Agusti-Panareda, A., Diamantakis, M., Bayona, V., Klappenbach, F., and Butz, A.: Improving the inter-hemispheric gradient of total column atmospheric CO2 and CH4 in simulations with the ECMWF semi-Lagrangian atmospheric global model, Geosci. Model Dev., 10, 1–18, https://doi.org/10.5194/gmd-10-1-2017, 2017. a
Agustí-Panareda, A., Diamantakis, M., Massart, S., Chevallier, F., Muñoz-Sabater, J., Barré, J., Curcoll, R., Engelen, R., Langerock, B., Law, R. M., Loh, Z., Morguí, J. A., Parrington, M., Peuch, V.-H., Ramonet, M., Roehl, C., Vermeulen, A. T., Warneke, T., and Wunch, D.: Modelling CO2 weather – why horizontal resolution matters, Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, 2019. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q
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. a, b, c, d, e, f, g
Baker, D. F., Doney, S. C., and Schimel, D. S.: Variational data assimilation
for atmospheric CO2, Tellus B, 58, 359–365, 2006. a
Blumenstock, T., Hase, F., Schneider, M., García, O. E., and Sepúlveda, E.:
TCCON data from Izana (ES), Release GGG2014.R1,
https://doi.org/10.14291/TCCON.GGG2014.IZANA01.R1, 2017. a
Borge, R., Alexandrov, V., del Vas, J. J., Lumbreras, J., and Rodriguez, E.: A
comprehensive sensitivity analysis of the WRF model for air quality
applications over the Iberian Peninsula, Atmos. Environ., 42,
8560–8574, https://doi.org/10.1016/j.atmosenv.2008.08.032, 2008. a
Brunke, E., Labuschagne, C., Parker, B., Scheel, H., and Whittlestone, S.:
Baseline air mass selection at Cape Point, South Africa: application of
Rn-222 and other filter criteria to CO2, Atmos. Environ., 38,
5693–5702, https://doi.org/10.1016/j.atmosenv.2004.04.024, 2004. a
Chen, F. and Dudhia, J.: Coupling an advanced land surface-hydrology model
with the Penn State-NCAR MM5 modeling system. Part I: Model implementation
and sensitivity, Mon. Weather Rev., 129, 569–585,
https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. a, b
Conway, T. J. and Thoning, K. W.: Short-term variations of atmospheric carbon
dioxide at the South Pole, Anarctic J., 25, 236–238, 1990. a
Davies, T.: Lateral boundary conditions for limited area models, Q.
J. Roy. Meteor. Soc., 140, 185–196,
https://doi.org/10.1002/qj.2127, 2014. a
Davis, K., Baier, B., Z., B., Bowman, K., Boyer, A., and Browell, E.:
Atmospheric Carbon and Transport (ACT) – America: A multi‐year airborne
mission to study fluxes and transport of CO2 and CH4 across the eastern
United States, American Geophysical Union Fall Meeting, San Francisco, CA, USA, 2018a. a
Davis, K. J., Obland, M. D., Lin, B., Lauvaux, T., O'Dell, C., Meadows, B., Browell, E. V., DiGangi, J. P., Sweeney, C., McGill, M. J., Barrick, J. D., Nehrir, A. R., Yang, M. M., Bennett, J. R., Baier, B. C., Roiger, A., Pal, S., Gerken, T., Fried, A., Feng, S., Shrestha, R., Shook, M. A., Chen, G., Campbell, L. J., Barkley, Z. R., and Pauly, R. M.: ACT–America: L3 Merged In Situ Atmospheric Trace Gases and Flask Data, Eastern USA [Data set], ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1593, 2018b. a, b
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Koehler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park,
B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart,
F.: The ERA-Interim reanalysis: configuration and performance of the data
assimilation system, Q. J. Roy. Meteor.
Soc.,, 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a, b
De Mazière, M., Sha, M. K., Desmet, F., Hermans, C., Scolas, F., Kumps, N.,
Metzger, J.-M., Duflot, V., and Cammas, J.-P.: TCCON data from Réunion
Island (RE), Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.REUNION01.R0/ 1149288, 2014. a
Deutscher, N. M., Notholt, J., Messerschmidt, J., Weinzierl, C., Warneke, T.,
Petri, C., and Grupe, P.: TCCON data from Bialystok (PL), Release GGG2014.R1,
https://doi.org/10.14291/TCCON.GGG2014.BIALYSTOK01.R1/ 1183984, 2015. a
Diamantakis, M. and Flemming, J.: Global mass fixer algorithms for conservative tracer transport in the ECMWF model, Geosci. Model Dev., 7, 965–979, https://doi.org/10.5194/gmd-7-965-2014, 2014. a, b
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. a
Díaz-Isaac, L. I., Lauvaux, T., Bocquet, M., and Davis, K. J.: Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model, Atmos. Chem. Phys., 19, 5695–5718, https://doi.org/10.5194/acp-19-5695-2019, 2019. a
Feist, D. G., Arnold, S. G., John, N., and Geibel, M. C.: TCCON data from
Ascension Island, Saint Helena, Ascension and Tristan da Cunha, Release
GGG2014R0, TCCON data archive, hosted by the Carbon Dioxide Information
Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA,
https://doi.org/10.14291/tccon.ggg2014.ascension01.R0/1149285, 2014. a
Feng, S., Lauvaux, T., Barkley, Z. R., Butler, M. B., Deng, A.,
Gaudet, B., and Davis, K. J.: Full WRF-Chem output in support of the NASA
Atmospheric Carbon and Transport (ACT)-America project (7/1/2016 –
7/31/2019). The Pennsylvania State University Data Commons, University Park,
Pennsylvania, USA, https://doi.org/10.26208/49kd-b637, 2020. a
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. a, b
Feng, S., Lauvaux, T., Davis, K. J., Keller, K., Zhou, Y., Williams, C., Schuh,
A. E., Liu, J., and Baker, I.: Seasonal Characteristics of Model
Uncertainties From Biogenic Fluxes, Transport, and Large-Scale Boundary
Inflow in Atmospheric CO2 Simulations Over North America, J.
Geophys. Res.-Atmos., 124, 14325–14346,
https://doi.org/10.1029/2019JD031165, 2019. a, b
Francey, R. J., Steele, L. P., Spencer, D. A., Langenfelds, R. L., Law, R. M.,
Krummel, P. B., Fraser, P. J., Etheridge, D. M., Derek, N., Coram, S. A.,
Cooper, L. N., Allison, C. E., Porter, L., and Baly, S.: The CSIRO
(Australia) measurement of greenhouse gases in the global atmosphere, report
of the 11th WMO/IAEA Meeting of Experts on Carbon Dioxide Concentration and
Related Tracer Measurement Techniques, Tokyo, Japan, September 2001, edited
by: Toru, S. and Kazuto, S., World Meteorological Organization Global
Atmosphere Watch, Geneva, Switzerland, 2003. a
Fritsch, J. M. and Chappell, C. F.: Numerical prediction of convectively
driven mesoscale pressure systems. Part I: convective parameterization,
J. Atmos. Sci., 37, 1722–1733,
https://doi.org/10.1175/1520-0469(1980)037<1722:NPOCDM>2.0.CO;2, 1980. a
Gaudry, A., Monfray, P., Polian, G., Bonsang, G., Ardouin, B., Jegou, A., and
Lambert, G.: Nonseasonnal variations of atmospheric CO2 concentrations at
Amsterdam Island, Tellus B, 43,
136–143, https://doi.org/10.1034/j.1600-0889.1991.00008.x, 1991. a
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. a
Gerbig, C., Dolman, A. J., and Heimann, M.: On observational and modelling strategies targeted at regional carbon exchange over continents, Biogeosciences, 6, 1949–1959, https://doi.org/10.5194/bg-6-1949-2009, 2009. a
Gockede, M., Turner, D. P., Michalak, A. M., Vickers, D., and Law, B. E.:
Sensitivity of a subregional scale atmospheric inverse CO2 modeling
framework to boundary conditions, J. Geophys. Res., 115, D24112,
https://doi.org/10.1029/2010JD014443, 2010. a
Golaz, J.-C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q., Wolfe, J. D., Abeshu, G.,
Anantharaj, V., Asay-Davis, X. S., Bader, D. C., Baldwin, S. A., Bisht, G., Bogenschutz, P. A.,
Branstetter, M., Brunke, M. A., Brus, S. R., Burrows, S. M., Cameron-Smith, P. J., Donahue, A. S.,
Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar, J. G., Fyke, J. G., Griffin, B. M.,
Hannay, 15 C., Harrop, B. E., Hoffman, M. J., Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N.,
Jones, P. W., Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H.-Y., Lin, W., Lipscomb, W. H.,
Ma, P.-L., Mahajan, S., Maltrud, M. E., Mametjanov, A., McClean, J. L., McCoy, R. B., Neale, R. B.,
Price, S. F., Qian, Y., Rasch, P. J., Eyre, J. E. J. R., Riley, W. J., Ringler, T. D., Roberts, A. F., Roesler,
E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B., Tang, J., Taylor, M. A., Thornton, P. E., Turner, A.
K., Veneziani, M., Wan, H., Wang, H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie, S.,
Yang, Y., Yoon, J.-H., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang, C., Zhang, K., Zhang, Y.,
Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM Coupled Model Version 1: Overview and
Evaluation at Standard Resolution, J. Adv. Model. Earth
Sy., 11, 2089–2129, https://doi.org/10.1029/2018MS001603, 2019. a
Gomez-Pelaez, A. J. and Ramos, R.: Improvements in the Carbon Dioxide and
Methane Continuous Measurement Programs at Izana Global GAW Station (Spain)
during 2007–2009, in: GAW report (No. 194) of the 15th WMO/IAEA Meeting of
Experts on Carbon Dioxide, Other Greenhouse Gases, and Related Tracer
Measurement Techniques, Jena, Germany; 7–10 September 2009, edited by:
Brand, W. A., World Meteorological Organization, TD No. 1553, 2005. a
Grell, G., Freitas, S. R., Stuefer, M., and Fast, J.: Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts, Atmos. Chem. Phys., 11, 5289–5303, https://doi.org/10.5194/acp-11-5289-2011, 2011. a
Griffith, D. W., Deutscher, N. M., Velazco, V. A., Wennberg, P. O., Yavin, Y.,
Keppel-Aleks, G., Washenfelder, R. A., Toon, G. C., Blavier, J.-F.,
Paton-Walsh, C., Jones, N. B., Kettlewell, G. C., Connor, B. J., Macatangay,
R. C., Roehl, C., Ryczek, M., Glowacki, J., Culgan, T., and Bryant, G. W.:
TCCON data from Darwin (AU), Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.DARWIN01.R0/ 1149290, 2014a. a
Griffith, D. W., Velazco, V. A., Deutscher, N. M., Paton-Walsh, C., Jones,
N. B., Wilson, S. R., Macatangay, R. C., Kettlewell, G. C., Buchholz, R. R.,
and Riggenbach, M. O.: TCCON data from Wollongong (AU), Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.WOLLONGONG01.R0/ 1149291, 2014b. a
Halter, B., Harris, J., and Conway, T.: Component signals in the record of
atmospheric carbon dioxide concentration at American Samoa, J.
Geophys. Res.-Atmos., 93, 15914–15918,
https://doi.org/10.1029/JD093iD12p15914, 1988. a
Hase, F., Blumenstock, T., Dohe, S., Groß, J., and Kiel, M.: TCCON data from
Karlsruhe (DE), Release GGG2014.R1,
https://doi.org/10.14291/TCCON.GGG2014.KARLSRUHE01. R1/1182416, 2015. a
Haszpra, L., Barcza, Z., Bakwin, P., Berger, B., Davis, K., and Weidinger, T.:
Measuring system for the long-term monitoring of biosphere/atmosphere
exchange of carbon dioxide, J. Geophys. Res.-Atmos.,
106, 3057–3069, https://doi.org/10.1029/2000JD900600, 2001. a
Hatakka, J., Aalto, T., Aaltonen, V., Aurela, M., Hakola, H., Komppula, M.,
Laurila, T., Lihavainen, H., Paatero, J., Salminen, K., and Viisanen, Y.:
Overview of the atmospheric research activities and results at Pallas GAW
station, Boreal Environ. Res., 8, 365–383, 2003. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horanyi, A.,
Munoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons,
A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati,
G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Holm, E., Janiskova, M., Keeley,
S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I.,
Vamborg, F., Villaume, S., and Thepaut, J.-N.: The ERA5 global reanalysis,
Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020. a
Hong, S., Dudhia, J., and Chen, S.: A revised approach to ice microphysical
processes for the bulk parameterization of clouds and precipitation,
Mon. Weather Rev., 132, 103–120,
https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2, 2004. a
Hu, L., Andrews, A. E., Thoning, K. W., Sweeney, C., Miller, J. B., Michalak,
A. M., Dlugokencky, E., Tans, P. P., Shiga, Y. P., Mountain, M., Nehrkorn,
T., Montzka, S. A., McKain, K., Kofler, J., Trudeau, M., Michel, S. E.,
Biraud, S. C., Fischer, M. L., Worthy, D. E. J., Vaughn, B. H., White, J.
W. C., Yadav, V., Basu, S., and van der Velde, I. R.: Enhanced North American
carbon uptake associated with El Niño, Sci. Adv., 5, eaaw0076,
https://doi.org/10.1126/sciadv.aaw0076, 2019. a
Hu, X.-M., Nielsen-Gammon, J. W., and Zhang, F.: Evaluation of Three Planetary
Boundary Layer Schemes in the WRF Model, J. Appl. Meteorol.
Climatol., 49, 1831–1844, 2010. a
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A.,
and Collins, W. D.: Radiative forcing by long-lived greenhouse gases:
Calculations with the AER radiative transfer models, J. Geophys.
Res.-Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008. a, b, c
Iraci, L. T., Podolske, J. R., Hillyard, P. W., Roehl, C., Wennberg, P. O.,
Blavier, J.-F., Landeros, J., Allen, N., Wunch, D., Zavaleta, J., Quigley,
E., Osterman, G. B., Albertson, R., Dunwoody, K., and Boyden, H.: TCCON data
from Edwards (US), Release GGG2014.R1,
https://doi.org/10.14291/TCCON.GGG2014.EDWARDS01.R1/ 1255068, 2016. a
Jacobson, A. R., Fletcher, S. E. M., Gruber, N., Sarmiento, J. L., and Gloor,
M.: A joint atmosphere-ocean inversion for surface fluxes of carbon dioxide:
1. Methods and global-scale fluxes, Global Biogeochem. Cycles, 21, GB1020,
https://doi.org/10.1029/2006GB002703, 2007. a
Jacobson, A. R., Schuldt, K. N., Miller, J. B., Oda, T., Tans, P., Arlyn
Andrews, Mund, J., Ott, L., Collatz, G. J., Aalto, T., Afshar, S., Aikin,
K., Aoki, S., Apadula, F., Baier, B., Bergamaschi, P., Beyersdorf, A.,
Biraud, S. C., Bollenbacher, A., Bowling, D., Brailsford, G., Abshire, J. B.,
Chen, G., Huilin Chen, Lukasz Chmura, Sites Climadat, Colomb, A.,
Conil, S., Cox, A., Cristofanelli, P., Cuevas, E., Curcoll, R., Sloop, C. D.,
Davis, K., Wekker, S. D., Delmotte, M., DiGangi, J. P., Dlugokencky, E.,
Ehleringer, J., Elkins, J. W., Emmenegger, L., Fischer, M. L., Forster, G.,
Frumau, A., Galkowski, M., Gatti, L. V., Gloor, E., Griffis, T., Hammer, S.,
Haszpra, L., Hatakka, J., Heliasz, M., Hensen, A., Hermanssen, O., Hintsa,
E., Holst, J., Jaffe, D., Karion, A., Kawa, S. R., Keeling, R., Keronen, P.,
Kolari, P., Kominkova, K., Kort, E., Krummel, P., Kubistin, D., Labuschagne,
C., Langenfelds, R., Laurent, O., Laurila, T., Lauvaux, T., Law, B., Lee, J.,
Lehner, I., Leuenberger, M., Levin, I., Levula, J., Lin, J., Lindauer, M.,
Loh, Z., Lopez, M., Myhre, C. L., Machida, T., Mammarella, I., Manca, G.,
Manning, A., Manning, A., Marek, M. V., Marklund, P., Martin, M. Y.,
Matsueda, H., McKain, K., Meijer, H., Meinhardt, F., Miles, N., Miller,
C. E., Mölder, M., Montzka, S., Moore, F., Josep-Anton Morgui, Morimoto,
S., Munger, B., Jaroslaw Necki, Newman, S., Nichol, S., Niwa, Y.,
O'Doherty, S., Mikaell Ottosson-Löfvenius, Paplawsky, B., Peischl, J.,
Peltola, O., Jean-Marc Pichon, Piper, S., Plass-Dölmer, C., Ramonet, M.,
Reyes-Sanchez, E., Richardson, S., Riris, H., Ryerson, T., Saito, K.,
Sargent, M., Sasakawa, M., Sawa, Y., Say, D., Scheeren, B., Schmidt, M.,
Schmidt, A., Schumacher, M., Shepson, P., Shook, M., Stanley, K.,
Steinbacher, M., Stephens, B., Sweeney, C., Thoning, K., Torn, M., Turnbull,
J., Tørseth, K., Bulk, P. V. D., Laan-Luijkx, I. T. V. D., Dinther, D. V.,
Vermeulen, A., Viner, B., Vitkova, G., Walker, S., Weyrauch, D., Wofsy, S.,
Worthy, D., Dickon Young, and Miroslaw Zimnoch: CarbonTracker CT2019, https://doi.org/10.25925/39M3-6069, 2020. a, b, c, d, e, f, g, h, i
Kain, J. S. and Fritsch, J. M.: A one-dimensional entraining detraining plume
model and its application in convective parameterization, J.
Atmos. Sci., 47, 2784–2802,
https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2, 1990. a
Kawakami, S., Ohyama, H., Arai, K., Okumura, H., Taura, C., Fukamachi, T., and
Sakashita, M.: TCCON data from Saga (JP), Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.SAGA01.R0/1149 283, 2014. a
Kivi, R., Heikkinen, P., and Kyro: TCCON data from Sodankyla, Finland, Release
GGG2014R0., TCCON data archive, hosted by the Carbon Dioxide Information
Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA,
https://doi.org/10.14291/tccon.ggg2014.sodankyla01.R0/1149280, 2014. a
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. a
Krol, M., Houweling, S., Bregman, B., van den Broek, M., Segers, A., van Velthoven, P., Peters, W., Dentener, F., and Bergamaschi, P.: The two-way nested global chemistry-transport zoom model TM5: algorithm and applications, Atmos. Chem. Phys., 5, 417–432, https://doi.org/10.5194/acp-5-417-2005, 2005. a, b
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. a
Lauvaux, T., Schuh, A. E., Uliasz, M., Richardson, S., Miles, N., Andrews, A. E., Sweeney, C., Diaz, L. I., Martins, D., Shepson, P. B., and Davis, K. J.: Constraining the CO2 budget of the corn belt: exploring uncertainties from the assumptions in a mesoscale inverse system, Atmos. Chem. Phys., 12, 337–354, https://doi.org/10.5194/acp-12-337-2012, 2012. a, b, c
Loh, Z. M., Law, R. M., Ziehn, T., van der Schoot M. V., Krummel, P. B.,
Steele, L. P., Etheridge, D. M., Spencer, D. A., Gregory, R. L., Langenfelds,
R. L., Stavert, A. R., and Thornton, D. P.: The Australian Greenhouse Gas
Observation Network: Current status and vision for the future. 10th
International Carbon Dioxide Conference (ICDC10), 21–25 August
2017, Interlaken, Switzerland,
available at: http://www.icdc10.unibe.ch/unibe/portal/fak_naturwis/micro_icdc10/content/e342182/e604227/e604229/files623284/Loh_Zoe.pdf (last access: 25 May 2021),
2017. a
Lopez, M., Schmidt, M., Ramonet, M., Bonne, J.-L., Colomb, A., Kazan, V., Laj, P., and Pichon, J.-M.: Three years of semicontinuous greenhouse gas measurements at the Puy de Dôme station (central France), Atmos. Meas. Tech., 8, 3941–3958, https://doi.org/10.5194/amt-8-3941-2015, 2015. a
Louis, J. F.: A parametric model of vertical eddy flux in the atmosphere,
Bound.-Lay. Meteorol., 17, 187–202, 1979. a
Masarie, K. A., Peters, W., Jacobson, A. R., and Tans, P. P.: ObsPack: a framework for the preparation, delivery, and attribution of atmospheric greenhouse gas measurements, Earth Syst. Sci. Data, 6, 375–384, https://doi.org/10.5194/essd-6-375-2014, 2014. a
Morgui, J. A., Agueda, A., Batet, O., Curcoll, R., Ealo, M., G. C.,
Occhipinti, P., Sanchez-Garcia, L., Arias, R., and Rodo, X.: ClimaDat: A
long-term network to study at different scales climatic processes and
interactions between climatic compartments, Geophys. Res. Abstr.,
EGU13-10265, EGU General Assembly 2013, Vienna, Austria, 2013. a, b, c, d
Morino, I., Matsuzaki, T., and Horikawa, M.: TCCON data from Tsukuba (JP),
125HR, Release GGG2014.R1, https://doi.org/10.14291/TCCON.GGG2014.TSUKUBA02.R1/ 1241486,
2016a. a
Morino, I., Yokozeki, N., Matsuzaki, T., and Horikawa, M.: TCCON data from
Rikubetsu (JP), Release GGG2014.R1,
https://doi.org/10.14291/TCCON.GGG2014.TSUKUBA02.R1/ 1241486, 2016b. a
Necki, J., Schmidt, M., Rozanski, K., Zimnoch, M., Korus, A., Lasa, J., Graul,
R., and Levin, I.: Six-year record of atmospheric carbon dioxide and methane
at a high-altitude mountain site in Poland, Tellus B, 55, 94–104,
https://doi.org/10.1034/j.1600-0889.2003.01446.x, 2003. a
Noh, Y., Cheon, W., Hong, S., and Raasch, S.: Improvement of the K-profile
model for the planetary boundary layer based on large eddy simulation data,
Bound.-Lay. Meteorol., 107, 401–427, https://doi.org/10.1023/A:1022146015946,
2003. a
Notholt, J., Petri, C., Warneke, T., Deutscher, N. M., Palm, M., Buschmann, M.,
Weinzierl, C., Macatangay, R. C., and Grupe, P.: TCCON data from Bremen (DE),
Release GGG2014.R0, https://doi.org/10.14291/TCCON.GGG2014.BREMEN01.R0/ 1149275, 2014. a
O'Dell, C. W., Connor, B., Bösch, H., O'Brien, D., Frankenberg, C., Castano, R., Christi, M., Eldering, D., Fisher, B., Gunson, M., McDuffie, J., Miller, C. E., Natraj, V., Oyafuso, F., Polonsky, I., Smyth, M., Taylor, T., Toon, G. C., Wennberg, P. O., and Wunch, D.: The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations, Atmos. Meas. Tech., 5, 99–121, https://doi.org/10.5194/amt-5-99-2012, 2012. a
Pal, S.: ACT-America: Profile-based Planetary Boundary Layer Heights, Eastern
USA, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1706, 2019. a
Pal, S. and Davis, K.: ACT-America Field Campaign Catalogue, ORNL DAAC, Oak
Ridge, Tennessee, USA,
available at: https://actamerica.ornl.gov/campaigns.html (last access: 25 May 2021), 2020. a
Pal, S., Davis, K. J., Lauvaux, T., Browell, E. V., Gaudet, B. J., and Stauffer, D.:
Observations of Greenhouse Gas Changes Across Summer Frontal Boundaries in
the Eastern United States, J. Geophys. Res.-Atmos., 125, e2019JD030526,
https://doi.org/10.1029/2019JD030526, 2020. a, b, c, d, e, f, g, h, i, j, k, l
Patra, P. K., Law, R. M., Peters, W., Roedenbeck, 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. Cycles, 22, gB4013,
https://doi.org/10.1029/2007GB003081, 2008. a, b
Peterson, J., Komhyr, W., Waterman, L., Gammon, R., Thoning, K., and Conway,
T.: Atmospheric CO2 variations at Barrow, Alaska,1973-1982, J.
Atmos. Chem., 4, 491–510, https://doi.org/10.1007/BF00053848, 1986. a
Pillai, D., Gerbig, C., Kretschmer, R., Beck, V., Karstens, U., Neininger, B., and Heimann, M.: Comparing Lagrangian and Eulerian models for CO2 transport – a step towards Bayesian inverse modeling using WRF/STILT-VPRM, Atmos. Chem. Phys., 12, 8979–8991, https://doi.org/10.5194/acp-12-8979-2012, 2012. a
Polavarapu, S. M., Neish, M., Tanguay, M., Girard, C., de Grandpré, J., Semeniuk, K., Gravel, S., Ren, S., Roche, S., Chan, D., and Strong, K.: Greenhouse gas simulations with a coupled meteorological and transport model: the predictability of CO2, Atmos. Chem. Phys., 16, 12005–12038, https://doi.org/10.5194/acp-16-12005-2016, 2016. a, b, c, d, e
Putman, W. M. and Lin, S.-H.: Finite-volume transport on various cubed-sphere
grids, J. Comput. Phys., 227, 55–78,
https://doi.org/10.1016/j.jcp.2007.07.022, 2007. a
Ramonet, M., Ciais, P., Aalto, T., Aulagnier, C., Chevallier, F., Cipriano, D.,
Conway, T. J., Haszpra, L., Kazan, V., Meinhardt, F., Paris, J.-D., Schmidt,
M., Simmonds, P., Xueref-Remy, I., and Necki, J. N.: A recent build-up of
atmospheric CO2 over Europe. Part 1: observed signals and possible
explanations, Tellus B, 62,
1–13, https://doi.org/10.1111/j.1600-0889.2009.00442.x, 2010. a
Rayner, P. J., Michalak, A. M., and Chevallier, F.: Fundamentals of data assimilation applied to biogeochemistry, Atmos. Chem. Phys., 19, 13911–13932, https://doi.org/10.5194/acp-19-13911-2019, 2019. a
Ringler, T., Ju, L., and Gunzburger, M.: A multiresolution method for climate
system modeling: application of spherical centroidal Voronoi tessellations,
Ocean Dynam., 58, 475–498, https://doi.org/10.1007/s10236-008-0157-2, 2008. a
Ringler, T. D., Thuburn, J., Klemp, J. B., and Skamarock, W. C.: A unified
approach to energy conservation and potential vorticity dynamics for
arbitrarily-structured C-grids, J. Comput. Phys., 229,
3065–3090, https://doi.org/10.1016/j.jcp.2009.12.007, 2010. a
Sarrat, C., Noilhan, J., Lacarrere, P., Donier, S., Lac, C., Calvet, J. C.,
Dolman, A. J., Gerbig, C., Neininger, B., Ciais, P., Paris, J. D., Boumard,
F., Ramonet, M., and Butet, A.: Atmospheric CO2 modeling at the regional
scale: Application to the CarboEurope Regional Experiment, J.
Geophys. Res.-Atmos., 112, D12105, https://doi.org/10.1029/2006JD008107, 2007. a
Schibig, M. F., Steinbacher, M., Buchmann, B., van der Laan-Luijkx, I. T., van der Laan, S., Ranjan, S., and Leuenberger, M. C.: Comparison of continuous in situ CO2 observations at Jungfraujoch using two different measurement techniques, Atmos. Meas. Tech., 8, 57–68, https://doi.org/10.5194/amt-8-57-2015, 2015. a
Schmidt, M., Graul, R., Sartorius, H., and Levin, I.: The Schauinsland CO2
record: 30 years of continental observations and their implications for the
variability of the European CO2 budget, J. Geophys.
Res.-Atmos., 108, 4619, https://doi.org/10.1029/2002JD003085, 2003. a
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, Global Change Biol., 19,
1424–1439, https://doi.org/10.1111/gcb.12141, 2013. a
Schuh, A. E., Jacobson, A. R., Basu, S., Weir, B., Baker, D., Bowman, K.,
Chevallier, F., Crowell, S., Davis, K. J., Deng, F., Denning, S., Feng, L.,
Jones, D., Liu, J., and Palmer, I, P.: Quantifying the Impact of Atmospheric
Transport Uncertainty on CO2 Surface Flux Estimates, Global Biogeochem.
Cycles, 33, 484–500, https://doi.org/10.1029/2018GB006086, 2019. a
Sherlock, V., Connor, B., Robinson, J., Shiona, H., Smale, D., and Pollard,
D. F.: TCCON data from Lauder (NZ), 120HR, Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.LAUDER01.R0/ 1149293, 2014. a
Skamarock, W. C. and Gassmann, A.: Conservative Transport Schemes for
Spherical Geodesic Grids: High-Order Flux Operators for ODE-Based Time
Integration, Mon. Weather Rev., 139, 2962–2975,
https://doi.org/10.1175/MWR-D-10-05056.1, 2011. a, b, c, d
Stephens, B. B., Miles, N. L., Richardson, S. J., Watt, A. S., and Davis, K. J.: Atmospheric CO2 monitoring with single-cell NDIR-based analyzers, Atmos. Meas. Tech., 4, 2737–2748, https://doi.org/10.5194/amt-4-2737-2011, 2011. a, b, c
Sussmann, R. and Rettinger, M.: TCCON data from Garmisch (DE), Release
GGG2014.R0, https://doi.org/10.14291/TCCON.GGG2014.GARMISCH01.R0/ 1149299, 2015. a
Thoning, K., Tans, P., and Komhyr, W.: Atmospheric carbon dioxide at Mauna Loa
Observatory, 2. Analysis of the NOAA/GMCC data, 1974–1985, J.
Geophys. Res.-Atmos., 94, 8549–8565,
https://doi.org/10.1029/JD094iD06p08549, 1989. a
Thuburn, J.: Rossby wave dispersion on the C-grid, Atmos. Sci.
Lett., 8, 37–42, https://doi.org/10.1002/asl.148, 2007. a
Tsutsumi, Y., Matsueda, H., and Nishioka, S.: Consistency of the CO2 primary
standards in JMA, 12th WMO/IAEA meeting of experts on carbon dioxide
concentration and related tracers measurement techniques, Toronto, Canada,
15–18 September 2003, Global Atmosphere Watch Report No. 161,
WMO/TD-No.1275, 2005. a, b, c
Vermeulen, A. T., Hensen, A., Popa, M. E., van den Bulk, W. C. M., and Jongejan, P. A. C.: Greenhouse gas observations from Cabauw Tall Tower (1992–2010), Atmos. Meas. Tech., 4, 617–644, https://doi.org/10.5194/amt-4-617-2011, 2011. a
Walko, R. L. and Avissar, R.: The Ocean-Land-Atmosphere Model (OLAM). Part I:
Shallow-Water Tests, Mon. Weather Rev., 136, 4033–4044,
https://doi.org/10.1175/2008MWR2522.1, 2008a. a
Walko, R. L. and Avissar, R.: The Ocean-Land-Atmosphere Model (OLAM). Part II:
Formulation and Tests of the Nonhydrostatic Dynamic Core, Mon. Weather
Rev., 136, 4045–4062, https://doi.org/10.1175/2008MWR2523.1,
2008b. a
Warneke, T., Messerschmidt, J., Notholt, J., Weinzierl, C., Deutscher, N. M.,
Petri, C., and Grupe, P.: TCCON data from Orléans (FR), Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.ORLEANS01.R0/ 1149276, 2014. a
Wennberg, P. O., Roehl, C. M., Wunch, D., Toon, G. C., Blavier, J.-F.,
Washenfelder, R., Keppel-Aleks, G., Allen, N. T., and Ayers, J.: TCCON data
from Park Falls (US), Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.PARKFALLS01.R0/ 1149161, 2014a. a
Wennberg, P. O., Wunch, D., Roehl, C. M., Blavier, J.-F., Toon, G. C., Allen,
N. T., Dowell, P., Teske, K., Martin, C., and Martin, J.: TCCON data from
Lamont (US), Release GGG2014.R0,
https://doi.org/10.14291/TCCON.GGG2014.LAMONT01.R0/ 1149159, 2014b. a
Williamson, D.: Semi-Lagrangian moisture transport in the NMC spectral model,
Tells A, 42, 413–428,
https://doi.org/10.3402/tellusa.v42i4.11887, 1990. a
Wilson, P.: Insight into the Carbon Cycle from Continuous Measurements of
Oxygen and Carbon Dioxide at Weybourne Atmospheric Observatory, UK,, PhD
thesis, University of East Anglia, Norwich, UK, 2013. a
Wunch, D., Toon, G. C., Wennberg, P. O., Wofsy, S. C., Stephens, B. B., Fischer, M. L., Uchino, O., Abshire, J. B., Bernath, P., Biraud, S. C., Blavier, J.-F. L., Boone, C., Bowman, K. P., Browell, E. V., Campos, T., Connor, B. J., Daube, B. C., Deutscher, N. M., Diao, M., Elkins, J. W., Gerbig, C., Gottlieb, E., Griffith, D. W. T., Hurst, D. F., Jiménez, R., Keppel-Aleks, G., Kort, E. A., Macatangay, R., Machida, T., Matsueda, H., Moore, F., Morino, I., Park, S., Robinson, J., Roehl, C. M., Sawa, Y., Sherlock, V., Sweeney, C., Tanaka, T., and Zondlo, M. A.: Calibration of the Total Carbon Column Observing Network using aircraft profile data, Atmos. Meas. Tech., 3, 1351–1362, https://doi.org/10.5194/amt-3-1351-2010, 2010.
a
Zheng, T., Nassar, R., and Baxter, M.: Estimating power plant CO2 emission
using OCO-2 XCO2 and high resolution WRF-Chem simulations, Environ.
Res. Lett., 14, 085001, https://doi.org/10.1088/1748-9326/ab25ae, 2019. a, b
Zheng, T., French, N. H. F., and Baxter, M.: Development of the WRF-CO2 4D-Var assimilation system v1.0, Geosci. Model Dev., 11, 1725–1752, https://doi.org/10.5194/gmd-11-1725-2018, 2018. a, b
Short summary
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.
Carbon dioxide is the most important greenhouse gas. We develop the numerical model that...