Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4843-2018
© Author(s) 2018. 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-11-4843-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
04 Dec 2018
Development and technical paper |
| 04 Dec 2018
| 04 Dec 2018
A Lagrangian approach towards extracting signals of urban CO2 emissions from satellite observations of atmospheric column CO2 (XCO2): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, USA
John C. Lin
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, USA
Benjamin Fasoli
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, USA
Tomohiro Oda
Goddard Earth Sciences Technology and Research, Universities Space
Research Association, Columbia, Maryland/Global Modeling and Assimilation
Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Xinxin Ye
Department of Meteorology and Atmospheric Science, Pennsylvania State
University, USA
Thomas Lauvaux
Department of Meteorology and Atmospheric Science, Pennsylvania State
University, USA
Emily G. Yang
Climate and Space Sciences and Engineering, University of Michigan,
Ann Arbor, USA
Eric A. Kort
Climate and Space Sciences and Engineering, University of Michigan,
Ann Arbor, USA
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A consistent estimation of CO2 emissions is complicated due to the scarcity of CO2 observations. In this study, we showcase the potential to improve the CO2 emissions estimations from the NO2 concentrations based on the NO2-to-CO2 ratio, which should be constant for a source co-emitting NO2 and CO2, by comparing satellite observations with atmospheric chemistry and transport model simulations for NO2 and CO2. Furthermore, we demonstrate the significance of the chemistry in NO2 simulations.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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Alexandre Danjou, Grégoire Broquet, Andrew Schuh, François-Marie Bréon, and Thomas Lauvaux
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Revised manuscript accepted for AMT
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We study the capacity of XCO2 space-borne imagery to estimate urban CO2 emissions with synthetic data. We define automatic and standard methods, and objective criteria for image selection. Wind variability and urban emission budget guide the emission estimation error. Images with low wind variability and high urban emissions account for 47 % of images and give a bias on the emission estimation of -7 % of the emissions and a spread of 56 %. Other images give a bias of -31 % and a spread of 99 %.
Jinghui Lian, Thomas Lauvaux, Hervé Utard, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, Olivier Laurent, Ivonne Albarus, Mali Chariot, Simone Kotthaus, Martial Haeffelin, Olivier Sanchez, Olivier Perrussel, Hugo Anne Denier van der Gon, Stijn Nicolaas Camiel Dellaert, and Philippe Ciais
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This study quantifies urban CO2 emissions via an atmospheric inversion for the Paris metropolitan area over a 6-year period from 2016 to 2021. Results show a long-term decreasing trend of about 2 % ± 0.6 % per year in the annual CO2 emissions over Paris. We conclude that our current capacity can deliver near-real-time CO2 emission estimates at the city scale in under a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
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Kai Wu, Paul I. Palmer, Dien Wu, Denis Jouglet, Liang Feng, and Tom Oda
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Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
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E. Ouerghi, T. Ehret, C. de Franchis, G. Facciolo, T. Lauvaux, E. Meinhardt, and J.-M. Morel
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Dustin Roten, John C. Lin, Lewis Kunik, Derek Mallia, Dien Wu, Tomohiro Oda, and Eric A. Kort
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-315, https://doi.org/10.5194/acp-2022-315, 2022
Revised manuscript not accepted
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Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
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Jennifer D. Hegarty, Karen E. Cady-Pereira, Vivienne H. Payne, Susan S. Kulawik, John R. Worden, Valentin Kantchev, Helen M. Worden, Kathryn McKain, Jasna V. Pittman, Róisín Commane, Bruce C. Daube Jr., and Eric A. Kort
Atmos. Meas. Tech., 15, 205–223, https://doi.org/10.5194/amt-15-205-2022, https://doi.org/10.5194/amt-15-205-2022, 2022
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Carbon monoxide (CO) is produced by combustion of substances such as fossil fuels and plays an important role in atmospheric pollution and climate. We evaluated estimates of atmospheric CO derived from outgoing radiation measurements of the Atmospheric Infrared Sounder (AIRS) on a satellite orbiting the Earth against CO measurements from aircraft to show that these satellite measurements are reliable for continuous global monitoring of atmospheric CO concentrations.
Eric J. Hintsa, Fred L. Moore, Dale F. Hurst, Geoff S. Dutton, Bradley D. Hall, J. David Nance, Ben R. Miller, Stephen A. Montzka, Laura P. Wolton, Audra McClure-Begley, James W. Elkins, Emrys G. Hall, Allen F. Jordan, Andrew W. Rollins, Troy D. Thornberry, Laurel A. Watts, Chelsea R. Thompson, Jeff Peischl, Ilann Bourgeois, Thomas B. Ryerson, Bruce C. Daube, Yenny Gonzalez Ramos, Roisin Commane, Gregory W. Santoni, Jasna V. Pittman, Steven C. Wofsy, Eric Kort, Glenn S. Diskin, and T. Paul Bui
Atmos. Meas. Tech., 14, 6795–6819, https://doi.org/10.5194/amt-14-6795-2021, https://doi.org/10.5194/amt-14-6795-2021, 2021
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We built UCATS to study atmospheric chemistry and transport. It has measured trace gases including CFCs, N2O, SF6, CH4, CO, and H2 with gas chromatography, as well as ozone and water vapor. UCATS has been part of missions to study the tropical tropopause; transport of air into the stratosphere; greenhouse gases, transport, and chemistry in the troposphere; and ozone chemistry, on both piloted and unmanned aircraft. Its design, capabilities, and some results are shown and described here.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Pramod Kumar, Grégoire Broquet, Camille Yver-Kwok, Olivier Laurent, Susan Gichuki, Christopher Caldow, Ford Cropley, Thomas Lauvaux, Michel Ramonet, Guillaume Berthe, Frédéric Martin, Olivier Duclaux, Catherine Juery, Caroline Bouchet, and Philippe Ciais
Atmos. Meas. Tech., 14, 5987–6003, https://doi.org/10.5194/amt-14-5987-2021, https://doi.org/10.5194/amt-14-5987-2021, 2021
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This study presents a simple atmospheric inversion modeling framework for the localization and quantification of unknown CH4 and CO2 emissions from point sources based on near-surface mobile concentration measurements and a Gaussian plume dispersion model. It is applied for the estimate of a series of brief controlled releases of CH4 and CO2 with a wide range of rates during the TOTAL TADI-2018 experiment. Results indicate a ~10 %–40 % average error on the estimate of the release rates.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726, https://doi.org/10.5194/acp-21-10707-2021, https://doi.org/10.5194/acp-21-10707-2021, 2021
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Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
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A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
E. Ouerghi, T. Ehret, C. de Franchis, G. Facciolo, T. Lauvaux, E. Meinhardt, and J.-M. Morel
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 81–87, https://doi.org/10.5194/isprs-annals-V-3-2021-81-2021, https://doi.org/10.5194/isprs-annals-V-3-2021-81-2021, 2021
Amy Hrdina, Jennifer G. Murphy, Anna Gannet Hallar, John C. Lin, Alexander Moravek, Ryan Bares, Ross C. Petersen, Alessandro Franchin, Ann M. Middlebrook, Lexie Goldberger, Ben H. Lee, Munkh Baasandorj, and Steven S. Brown
Atmos. Chem. Phys., 21, 8111–8126, https://doi.org/10.5194/acp-21-8111-2021, https://doi.org/10.5194/acp-21-8111-2021, 2021
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Wintertime air pollution in the Salt Lake Valley is primarily composed of ammonium nitrate, which is formed when gas-phase ammonia and nitric acid react. The major point in this work is that the chemical composition of snow tells a very different story to what we measured in the atmosphere. With the dust–sea salt cations observed in PM2.5 and particle sizing data, we can estimate how much nitric acid may be lost to dust–sea salt that is not accounted for and how much more PM2.5 this could form.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
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The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Xueying Yu, Dylan B. Millet, Kelley C. Wells, Daven K. Henze, Hansen Cao, Timothy J. Griffis, Eric A. Kort, Genevieve Plant, Malte J. Deventer, Randall K. Kolka, D. Tyler Roman, Kenneth J. Davis, Ankur R. Desai, Bianca C. Baier, Kathryn McKain, Alan C. Czarnetzki, and A. Anthony Bloom
Atmos. Chem. Phys., 21, 951–971, https://doi.org/10.5194/acp-21-951-2021, https://doi.org/10.5194/acp-21-951-2021, 2021
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Methane concentrations have doubled since 1750. The US Upper Midwest is a key region contributing to such trends, but sources are poorly understood. We collected and analyzed aircraft data to resolve spatial and timing biases in wetland and livestock emission estimates and uncover errors in inventory treatment of manure management. We highlight the importance of intensive agriculture for the regional and US methane budgets and the potential for methane mitigation through improved management.
Pengfei Han, Ning Zeng, Tom Oda, Xiaohui Lin, Monica Crippa, Dabo Guan, Greet Janssens-Maenhout, Xiaolin Ma, Zhu Liu, Yuli Shan, Shu Tao, Haikun Wang, Rong Wang, Lin Wu, Xiao Yun, Qiang Zhang, Fang Zhao, and Bo Zheng
Atmos. Chem. Phys., 20, 11371–11385, https://doi.org/10.5194/acp-20-11371-2020, https://doi.org/10.5194/acp-20-11371-2020, 2020
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An accurate estimation of China’s fossil-fuel CO2 emissions (FFCO2) is significant for quantification of carbon budget and emissions reductions towards the Paris Agreement goals. Here we assessed 9 global and regional inventories. Our findings highlight the significance of using locally measured coal emission factors. We call on the enhancement of physical measurements for validation and provide comprehensive information for inventory, monitoring, modeling, assimilation, and reducing emissions.
Nikolay V. Balashov, Kenneth J. Davis, Natasha L. Miles, Thomas Lauvaux, Scott J. Richardson, Zachary R. Barkley, and Timothy A. Bonin
Atmos. Chem. Phys., 20, 4545–4559, https://doi.org/10.5194/acp-20-4545-2020, https://doi.org/10.5194/acp-20-4545-2020, 2020
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An accurate independent verification methodology to estimate methane (a powerful greenhouse gas) emissions is essential for the effective implementation of policies that aim to reduce the impacts of climate change. In this paper, four uncertainties that complicate the independent estimation of urban methane emissions are identified: the definition of urban domain, background heterogeneity, emissions temporal variability, and missing sources. Ways to improve emission estimates are suggested.
Xiaohua Pan, Charles Ichoku, Mian Chin, Huisheng Bian, Anton Darmenov, Peter Colarco, Luke Ellison, Tom Kucsera, Arlindo da Silva, Jun Wang, Tomohiro Oda, and Ge Cui
Atmos. Chem. Phys., 20, 969–994, https://doi.org/10.5194/acp-20-969-2020, https://doi.org/10.5194/acp-20-969-2020, 2020
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The differences between these six BB emission datasets are large. Our study found that (1) most current biomass burning (BB) aerosol emission datasets derived from satellite observations lead to the underestimation of aerosol optical depth (AOD) in this model in the biomass-burning-dominated regions and (2) it is important to accurately estimate both the magnitudes and spatial patterns of regional BB emissions in order for a model using these emissions to reproduce observed AOD levels.
Alexander Moravek, Jennifer G. Murphy, Amy Hrdina, John C. Lin, Christopher Pennell, Alessandro Franchin, Ann M. Middlebrook, Dorothy L. Fibiger, Caroline C. Womack, Erin E. McDuffie, Randal Martin, Kori Moore, Munkhbayar Baasandorj, and Steven S. Brown
Atmos. Chem. Phys., 19, 15691–15709, https://doi.org/10.5194/acp-19-15691-2019, https://doi.org/10.5194/acp-19-15691-2019, 2019
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Ammonium nitrate is a major component of fine particulate matter of wintertime air pollution in the Great Salt Lake Region (UT, USA). We investigate the sources of ammonia in the region by using aircraft observations and comparing them to modelled ammonia mixing ratios based on emission inventory estimates. The results suggest that ammonia emissions are underestimated, specifically in regions with high agricultural activity, while ammonia in Salt Lake City is mainly of local origin.
Elizabeth Asher, Rebecca S. Hornbrook, Britton B. Stephens, Doug Kinnison, Eric J. Morgan, Ralph F. Keeling, Elliot L. Atlas, Sue M. Schauffler, Simone Tilmes, Eric A. Kort, Martin S. Hoecker-Martínez, Matt C. Long, Jean-François Lamarque, Alfonso Saiz-Lopez, Kathryn McKain, Colm Sweeney, Alan J. Hills, and Eric C. Apel
Atmos. Chem. Phys., 19, 14071–14090, https://doi.org/10.5194/acp-19-14071-2019, https://doi.org/10.5194/acp-19-14071-2019, 2019
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Halogenated organic trace gases, which are a source of reactive halogens to the atmosphere, exert a disproportionately large influence on atmospheric chemistry and climate. This paper reports novel aircraft observations of halogenated compounds over the Southern Ocean in summer and evaluates hypothesized regional sources and emissions of these trace gases through their relationships to additional aircraft observations.
Thomas Lauvaux, Liza I. Díaz-Isaac, Marc Bocquet, and Nicolas Bousserez
Atmos. Chem. Phys., 19, 12007–12024, https://doi.org/10.5194/acp-19-12007-2019, https://doi.org/10.5194/acp-19-12007-2019, 2019
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A small-size ensemble of mesoscale simulations has been filtered to characterize the spatial structures of transport errors in atmospheric CO2 mixing ratios. The extracted error structures in in situ and column CO2 show similar length scales compared to other meteorological variables, including seasonality, which could be used as proxies in regional inversion systems.
Ryan Bares, Logan Mitchell, Ben Fasoli, David R. Bowling, Douglas Catharine, Maria Garcia, Byron Eng, Jim Ehleringer, and John C. Lin
Earth Syst. Sci. Data, 11, 1291–1308, https://doi.org/10.5194/essd-11-1291-2019, https://doi.org/10.5194/essd-11-1291-2019, 2019
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We overview two near-surface trace gas measurement networks with the aim of describing procedures, locations, and data structure with sufficient detail to serve as an in-depth method reference. Additionally, we developed a novel method for quantifying measurement uncertainty produced by these networks providing insight into appropriate applications of the data and differences in data collection methods. This uncertainty metric is broadly applicable to many trace gas and air quality datasets.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Yilong Wang, Philippe Ciais, Grégoire Broquet, François-Marie Bréon, Tomohiro Oda, Franck Lespinas, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, Haoran Xu, Shu Tao, Kevin R. Gurney, Geoffrey Roest, Diego Santaren, and Yongxian Su
Earth Syst. Sci. Data, 11, 687–703, https://doi.org/10.5194/essd-11-687-2019, https://doi.org/10.5194/essd-11-687-2019, 2019
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We address the question of the global characterization of fossil fuel CO2 emission hotspots that may cause coherent XCO2 plumes in space-borne CO2 images, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. For space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 hotspots are identified, covering 72 % of the global emissions. These hotspots define the targets for the purpose of monitoring fossil fuel CO2 emissions from space.
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
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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.
Anna Karion, Thomas Lauvaux, Israel Lopez Coto, Colm Sweeney, Kimberly Mueller, Sharon Gourdji, Wayne Angevine, Zachary Barkley, Aijun Deng, Arlyn Andrews, Ariel Stein, and James Whetstone
Atmos. Chem. Phys., 19, 2561–2576, https://doi.org/10.5194/acp-19-2561-2019, https://doi.org/10.5194/acp-19-2561-2019, 2019
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In this study, we use atmospheric methane concentration observations collected during an airborne campaign to compare different model-based emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We find that the tracer dispersion model has a significant impact on the results because the models differ in their simulation of vertical dispersion. Additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models.
Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman, and Kenneth J. Davis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-342, https://doi.org/10.5194/gmd-2018-342, 2019
Revised manuscript not accepted
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This paper describes a mass-conserving framework for computing time-varying lateral boundary conditions from global model carbon dioxide concentrations for introduction into the WRF-Chem regional model. The goal is to create a laboratory environment in which carbon dioxide transport uncertainties may be explored separately from inversion-derived flux uncertainties. The software is currently available on GitHub at https://github.com/psu-inversion/WRF_Boundary_Coupling.
Benjamin Gaubert, Britton B. Stephens, Sourish Basu, Frédéric Chevallier, Feng Deng, Eric A. Kort, Prabir K. Patra, Wouter Peters, Christian Rödenbeck, Tazu Saeki, David Schimel, Ingrid Van der Laan-Luijkx, Steven Wofsy, and Yi Yin
Biogeosciences, 16, 117–134, https://doi.org/10.5194/bg-16-117-2019, https://doi.org/10.5194/bg-16-117-2019, 2019
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We have compared global carbon budgets calculated from numerical inverse models and CO2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO2 from aircraft measurements. We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.
David Carlson and Tomohiro Oda
Earth Syst. Sci. Data, 10, 2275–2278, https://doi.org/10.5194/essd-10-2275-2018, https://doi.org/10.5194/essd-10-2275-2018, 2018
Jacob K. Hedelius, Junjie Liu, Tomohiro Oda, Shamil Maksyutov, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Jianming Liang, Kevin R. Gurney, Debra Wunch, and Paul O. Wennberg
Atmos. Chem. Phys., 18, 16271–16291, https://doi.org/10.5194/acp-18-16271-2018, https://doi.org/10.5194/acp-18-16271-2018, 2018
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Human activities can cause concentrated emissions of greenhouse gases and other pollutants from cities. There is ongoing effort to convert new satellite observations of pollutants into fluxes for many cities. Here we present a method for determining the flux of three species (CO2, CH4, and CO) from the greater LA area using satellite (CO2 only) and ground-based (all three species) observations. We run tests to estimate uncertainty and find the direct net CO2 flux is 104 ± 26 Tg CO2 yr−1.
Alexander Gvakharia, Eric A. Kort, Mackenzie L. Smith, and Stephen Conley
Atmos. Meas. Tech., 11, 6059–6074, https://doi.org/10.5194/amt-11-6059-2018, https://doi.org/10.5194/amt-11-6059-2018, 2018
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We present a new flight system to measure the atmospheric trace gases N2O, CO2, CO, and H2O. We use a novel calibration technique to correct altitude-dependent artifacts that have hindered similar instruments. In-flight null-tests and comparison with other flight-proven instruments provide validation. This high-precision, high-accuracy system provides opportunities for airborne studies to improve our understanding of N2O emission processes.
Liza I. Díaz-Isaac, Thomas Lauvaux, and Kenneth J. Davis
Atmos. Chem. Phys., 18, 14813–14835, https://doi.org/10.5194/acp-18-14813-2018, https://doi.org/10.5194/acp-18-14813-2018, 2018
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Atmospheric inversions rely on the accurate representation of the atmospheric dynamics in order to produce reliable surface fluxes. In this work, we evaluate the sensitivity of a state-of-the-art mesoscale atmospheric model to the different physics parameterizations and forcing. We conclude that no model configuration is optimal across an entire region. Therefore, we recommend an ensemble approach or the assimilation of meteorological observations in future inversion studies.
Benjamin Fasoli, John C. Lin, David R. Bowling, Logan Mitchell, and Daniel Mendoza
Geosci. Model Dev., 11, 2813–2824, https://doi.org/10.5194/gmd-11-2813-2018, https://doi.org/10.5194/gmd-11-2813-2018, 2018
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The Stochastic Time-Inverted Lagrangian Transport (STILT) model is used to determine the area upstream that influences the air arriving at a given location. We introduce a new framework that makes the STILT model faster and easier to deploy and improves results. We also show how the model can be applied to spatially complex measurement strategies using trace gas observations collected onboard a Salt Lake City, Utah, USA, light-rail train.
Richard P. Fiorella, Ryan Bares, John C. Lin, James R. Ehleringer, and Gabriel J. Bowen
Atmos. Chem. Phys., 18, 8529–8547, https://doi.org/10.5194/acp-18-8529-2018, https://doi.org/10.5194/acp-18-8529-2018, 2018
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Fossil fuel combustion produces water; where fossil fuel combustion is concentrated in urban areas, this humidity source may represent ~ 10 % of total humidity. In turn, this water vapor addition may alter urban meteorology, though the contribution of combustion vapor is difficult to measure. Using stable water isotopes, we estimate that up to 16 % of urban humidity may arise from combustion when the atmosphere is stable during winter, and develop recommendations for application in other cities.
Natasha L. Miles, Douglas K. Martins, Scott J. Richardson, Christopher W. Rella, Caleb Arata, Thomas Lauvaux, Kenneth J. Davis, Zachary R. Barkley, Kathryn McKain, and Colm Sweeney
Atmos. Meas. Tech., 11, 1273–1295, https://doi.org/10.5194/amt-11-1273-2018, https://doi.org/10.5194/amt-11-1273-2018, 2018
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Analyzers measuring methane and methane isotopic ratio were deployed at four towers in the Marcellus Shale natural gas extraction region of Pennsylvania. The methane isotopic ratio is helpful for differentiating emissions from natural gas activities from other sources (e.g., landfills). We describe the analyzer calibration. The signals observed in the study region were generally small, but the instrumental performance demonstrated here could be used in regions with stronger enhancements.
Tomohiro Oda, Shamil Maksyutov, and Robert J. Andres
Earth Syst. Sci. Data, 10, 87–107, https://doi.org/10.5194/essd-10-87-2018, https://doi.org/10.5194/essd-10-87-2018, 2018
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The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a 1 x 1 km global high-resolution fossil fuel CO2 emissions data product. ODIAC first introduced the combined use of point source profiles and nighttime light satellite data to create high-resolution emissions spatial distributions and it has been intensively used in the carbon cycle research community. This manuscript describes the 2016 version of ODIAC data, the modeling approach, and future data production and model developments.
Xinxin Ye, Thomas Lauvaux, Eric A. Kort, Tomohiro Oda, Sha Feng, John C. Lin, Emily Yang, and Dien Wu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1022, https://doi.org/10.5194/acp-2017-1022, 2017
Revised manuscript not accepted
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Rapid global urbanization and significant fossil fuel consumption by cities emphasize the necessity of achieving independent and accurate quantification of the carbon emissions from urban areas. In this paper, we assess the potential of using total column CO2 concentration observed from satellite to quantify fossil-fuel carbon emissions from cities. This study could give insights into the capability of satellite observations on monitoring of the emissions on local scale.
Zachary R. Barkley, Thomas Lauvaux, Kenneth J. Davis, Aijun Deng, Natasha L. Miles, Scott J. Richardson, Yanni Cao, Colm Sweeney, Anna Karion, MacKenzie Smith, Eric A. Kort, Stefan Schwietzke, Thomas Murphy, Guido Cervone, Douglas Martins, and Joannes D. Maasakkers
Atmos. Chem. Phys., 17, 13941–13966, https://doi.org/10.5194/acp-17-13941-2017, https://doi.org/10.5194/acp-17-13941-2017, 2017
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This study quantifies methane emissions from natural gas production in north-eastern Pennsylvania. Methane observations from 10 flights in spring 2015 are compared to model-projected values, and methane emissions from natural gas are adjusted within the model to create the best match between the two data sets. This study find methane emissions from natural gas production to be low and may be indicative of characteristics of the basin that make sources from north-eastern Pennsylvania unique.
Andrew K. Thorpe, Christian Frankenberg, David R. Thompson, Riley M. Duren, Andrew D. Aubrey, Brian D. Bue, Robert O. Green, Konstantin Gerilowski, Thomas Krings, Jakob Borchardt, Eric A. Kort, Colm Sweeney, Stephen Conley, Dar A. Roberts, and Philip E. Dennison
Atmos. Meas. Tech., 10, 3833–3850, https://doi.org/10.5194/amt-10-3833-2017, https://doi.org/10.5194/amt-10-3833-2017, 2017
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At local scales emissions of methane (CH4) and carbon dioxide (CO2) are highly uncertain. The AVIRIS-NG imaging spectrometer maps large regions and generates high-spatial-resolution CH4 and CO2 concentration maps from anthropogenic and natural sources. Examples include CH4 from a processing plant, tank, pipeline leak, seep, mine vent shafts, and CO2 from power plants. This demonstrates a greenhouse gas monitoring capability that targets the two dominant anthropogenic climate-forcing agents.
Henrique F. Duarte, Brett M. Raczka, Daniel M. Ricciuto, John C. Lin, Charles D. Koven, Peter E. Thornton, David R. Bowling, Chun-Ta Lai, Kenneth J. Bible, and James R. Ehleringer
Biogeosciences, 14, 4315–4340, https://doi.org/10.5194/bg-14-4315-2017, https://doi.org/10.5194/bg-14-4315-2017, 2017
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We evaluate the Community Land Model (CLM4.5) against observations at an old-growth coniferous forest site that is subjected to water stress each summer. We found that, after calibration, CLM was able to reasonably simulate the observed fluxes of energy and carbon, carbon stocks, carbon isotope ratios, and ecosystem response to water stress. This study demonstrates that carbon isotopes can expose structural weaknesses in CLM and provide a key constraint that may guide future model development.
Yanni Cao, Guido Cervone, Zachary Barkley, Thomas Lauvaux, Aijun Deng, and Alan Taylor
Geosci. Model Dev., 10, 3425–3440, https://doi.org/10.5194/gmd-10-3425-2017, https://doi.org/10.5194/gmd-10-3425-2017, 2017
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This research investigates the role and importance of reprojecting geographic information system layers used by weather numerical models as input by performing sensitivity studies of greenhouse gas transport and dispersion in northeastern Pennsylvania. To bridge the gap between geographic information system data and atmospheric models, this study presents an innovative approach by creating R code to automatically generate model input from geographic data and analyze the model output.
Stephen Conley, Ian Faloona, Shobhit Mehrotra, Maxime Suard, Donald H. Lenschow, Colm Sweeney, Scott Herndon, Stefan Schwietzke, Gabrielle Pétron, Justin Pifer, Eric A. Kort, and Russell Schnell
Atmos. Meas. Tech., 10, 3345–3358, https://doi.org/10.5194/amt-10-3345-2017, https://doi.org/10.5194/amt-10-3345-2017, 2017
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This paper describes a new method of quantifying surface trace gas emissions (e.g. methane) from small aircraft (e.g. Mooney, Cessna) in about 30 min. This technique greatly enhances our ability to rapidly respond in the event of catastrophic failures such as Aliso Canyon and Deep Water Horizon.
Camille Viatte, Thomas Lauvaux, Jacob K. Hedelius, Harrison Parker, Jia Chen, Taylor Jones, Jonathan E. Franklin, Aijun J. Deng, Brian Gaudet, Kristal Verhulst, Riley Duren, Debra Wunch, Coleen Roehl, Manvendra K. Dubey, Steve Wofsy, and Paul O. Wennberg
Atmos. Chem. Phys., 17, 7509–7528, https://doi.org/10.5194/acp-17-7509-2017, https://doi.org/10.5194/acp-17-7509-2017, 2017
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This study estimates methane emissions at local scale in dairy farms using four new mobile ground-based remote sensing spectrometers (EM27/SUN) and isotopic in situ measurements. Our top-down estimates are in the low end of previous studies. Inverse modeling from a comprehensive high-resolution model simulations (WRF-LES) is used to assess the geographical distribution of the emissions. Both the model and the measurements indicate a mixture of anthropogenic and biogenic emissions.
John C. Lin, Derek V. Mallia, Dien Wu, and Britton B. Stephens
Atmos. Chem. Phys., 17, 5561–5581, https://doi.org/10.5194/acp-17-5561-2017, https://doi.org/10.5194/acp-17-5561-2017, 2017
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Mountainous areas can potentially serve as regions where the key greenhouse gas, carbon dioxide (CO2), can be absorbed from the atmosphere by vegetation, through photosynthesis. Variations in atmospheric CO2 can be used to understand the amount of biospheric fluxes in general. However, CO2 measured in mountains can be difficult to interpret due to the impact from complex atmospheric flows. We show how mountaintop CO2 data can be interpreted by carrying out a series of atmospheric simulations.
A. Anthony Bloom, Thomas Lauvaux, John Worden, Vineet Yadav, Riley Duren, Stanley P. Sander, and David S. Schimel
Atmos. Chem. Phys., 16, 15199–15218, https://doi.org/10.5194/acp-16-15199-2016, https://doi.org/10.5194/acp-16-15199-2016, 2016
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Understanding terrestrial carbon processes is a major challenge in climate science. We define the satellite system required to understand greenhouse gas biogeochemistry: our study is focused on Amazon wetland CH4 emissions. We find that future geostationary satellites will provide the CH4 measurements required to understand wetland CH4 processes. Low-earth orbit satellites will be unable to resolve wetland CH4 processes due to a low number of cloud-free CH4 measurements over the Amazon basin.
Clare K. Wong, Thomas J. Pongetti, Tom Oda, Preeti Rao, Kevin R. Gurney, Sally Newman, Riley M. Duren, Charles E. Miller, Yuk L. Yung, and Stanley P. Sander
Atmos. Chem. Phys., 16, 13121–13130, https://doi.org/10.5194/acp-16-13121-2016, https://doi.org/10.5194/acp-16-13121-2016, 2016
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Methane is the second most important greenhouse gas and a target of new emissions regulations in the United States. Despite its importance, its emissions are poorly understood. In this study, we used a remote sensing instrument located on Mount Wilson to estimate the monthly and annual methane emissions from Los Angeles. Derived methane emissions from Los Angeles showed consistent peaks in late summer/early fall and winter during the study period from 2011 to 2015.
Brett Raczka, Henrique F. Duarte, Charles D. Koven, Daniel Ricciuto, Peter E. Thornton, John C. Lin, and David R. Bowling
Biogeosciences, 13, 5183–5204, https://doi.org/10.5194/bg-13-5183-2016, https://doi.org/10.5194/bg-13-5183-2016, 2016
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We use carbon isotopes of CO2 to improve the performance of a land surface model, a component with earth system climate models. We found that isotope observations can provide important information related to the exchange of carbon and water from vegetation driven by environmental stress from low atmospheric moisture and nitrogen limitation. It follows that isotopes have a unique potential to improve model performance and provide insight into land surface model development.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
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In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Sha Feng, Thomas Lauvaux, Sally Newman, Preeti Rao, Ravan Ahmadov, Aijun Deng, Liza I. Díaz-Isaac, Riley M. Duren, Marc L. Fischer, Christoph Gerbig, Kevin R. Gurney, Jianhua Huang, Seongeun Jeong, Zhijin Li, Charles E. Miller, Darragh O'Keeffe, Risa Patarasuk, Stanley P. Sander, Yang Song, Kam W. Wong, and Yuk L. Yung
Atmos. Chem. Phys., 16, 9019–9045, https://doi.org/10.5194/acp-16-9019-2016, https://doi.org/10.5194/acp-16-9019-2016, 2016
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We developed a high-resolution land–atmosphere modelling system for urban CO2 emissions over the LA Basin. We evaluated various model configurations, FFCO2 products, and the impact of the model resolution. FFCO2 emissions outpace the atmospheric model resolution to represent the CO2 concentration variability across the basin. A novel forward model approach is presented to evaluate the surface measurement network, reinforcing the importance of using high-resolution emission products.
Christian Frankenberg, Susan S. Kulawik, Steven C. Wofsy, Frédéric Chevallier, Bruce Daube, Eric A. Kort, Christopher O'Dell, Edward T. Olsen, and Gregory Osterman
Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, https://doi.org/10.5194/acp-16-7867-2016, 2016
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We use observations from the HIAPER Pole-to-Pole Observations (HIPPO) flights from January 2009 through September 2011 to validate CO2 measurements from satellites (GOSAT, TES, AIRS) and atmospheric inversion models (CarbonTracker CT2013B, MACC v13r1).
Anna Karion, Colm Sweeney, John B. Miller, Arlyn E. Andrews, Roisin Commane, Steven Dinardo, John M. Henderson, Jacob Lindaas, John C. Lin, Kristina A. Luus, Tim Newberger, Pieter Tans, Steven C. Wofsy, Sonja Wolter, and Charles E. Miller
Atmos. Chem. Phys., 16, 5383–5398, https://doi.org/10.5194/acp-16-5383-2016, https://doi.org/10.5194/acp-16-5383-2016, 2016
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Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Here we use carbon dioxide and methane measurements from a tower near Fairbanks AK to investigate regional Alaskan fluxes of CO2 and CH4 for 2012–2014.
F. Deng, D. B. A. Jones, T. W. Walker, M. Keller, K. W. Bowman, D. K. Henze, R. Nassar, E. A. Kort, S. C. Wofsy, K. A. Walker, A. E. Bourassa, and D. A. Degenstein
Atmos. Chem. Phys., 15, 11773–11788, https://doi.org/10.5194/acp-15-11773-2015, https://doi.org/10.5194/acp-15-11773-2015, 2015
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The upper troposphere and lower stratosphere (UTLS) is characterized by strong gradients in the distribution of long-lived tracers, which are sensitive to discrepancies in transport in models. We found that our model overestimates CO2 in the polar UTLS through comparison of modeled CO2 with aircraft observations. We then corrected the modeled CO2 and quantified the impact of the correction on the flux estimates using an atmospheric model together with atmospheric CO2 measured from a satellite.
K. C. Wells, D. B. Millet, N. Bousserez, D. K. Henze, S. Chaliyakunnel, T. J. Griffis, Y. Luan, E. J. Dlugokencky, R. G. Prinn, S. O'Doherty, R. F. Weiss, G. S. Dutton, J. W. Elkins, P. B. Krummel, R. Langenfelds, L. P. Steele, E. A. Kort, S. C. Wofsy, and T. Umezawa
Geosci. Model Dev., 8, 3179–3198, https://doi.org/10.5194/gmd-8-3179-2015, https://doi.org/10.5194/gmd-8-3179-2015, 2015
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This paper introduces a new inversion framework for N2O using GEOS-Chem and its adjoint, which we employed in a series of observing system simulation experiments to evaluate the source and sink constraints provided by surface and aircraft-based N2O measurements. We also applied a new approach for estimating a posteriori uncertainty for high-dimensional inversions, and used it to quantify the spatial and temporal resolution of N2O emission constraints achieved with the current observing network.
C. Viatte, K. Strong, J. Hannigan, E. Nussbaumer, L. K. Emmons, S. Conway, C. Paton-Walsh, J. Hartley, J. Benmergui, and J. Lin
Atmos. Chem. Phys., 15, 2227–2246, https://doi.org/10.5194/acp-15-2227-2015, https://doi.org/10.5194/acp-15-2227-2015, 2015
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Seven tropospheric species (CO, HCN, C2H6, C2H2, CH3OH, HCOOH, and H2CO) released by biomass burning events transported to the high Arctic were monitored with two sets of FTIR measurements, located at Eureka (Nunavut, Canada) and Thule (Greenland), from 2008 to 2012. We compared these data sets with the MOZART-4 chemical transport model to help improve its simulations in the Arctic. Emission factors of these biomass burning products were derived and compared to the literature.
K. W. Wong, D. Fu, T. J. Pongetti, S. Newman, E. A. Kort, R. Duren, Y.-K. Hsu, C. E. Miller, Y. L. Yung, and S. P. Sander
Atmos. Chem. Phys., 15, 241–252, https://doi.org/10.5194/acp-15-241-2015, https://doi.org/10.5194/acp-15-241-2015, 2015
M. Inoue, I. Morino, O. Uchino, Y. Miyamoto, T. Saeki, Y. Yoshida, T. Yokota, C. Sweeney, P. P. Tans, S. C. Biraud, T. Machida, J. V. Pittman, E. A. Kort, T. Tanaka, S. Kawakami, Y. Sawa, K. Tsuboi, and H. Matsueda
Atmos. Meas. Tech., 7, 2987–3005, https://doi.org/10.5194/amt-7-2987-2014, https://doi.org/10.5194/amt-7-2987-2014, 2014
M. O. L. Cambaliza, P. B. Shepson, D. R. Caulton, B. Stirm, D. Samarov, K. R. Gurney, J. Turnbull, K. J. Davis, A. Possolo, A. Karion, C. Sweeney, B. Moser, A. Hendricks, T. Lauvaux, K. Mays, J. Whetstone, J. Huang, I. Razlivanov, N. L. Miles, and S. J. Richardson
Atmos. Chem. Phys., 14, 9029–9050, https://doi.org/10.5194/acp-14-9029-2014, https://doi.org/10.5194/acp-14-9029-2014, 2014
D. Wen, L. Zhang, J. C. Lin, R. Vet, and M. D. Moran
Geosci. Model Dev., 7, 1037–1050, https://doi.org/10.5194/gmd-7-1037-2014, https://doi.org/10.5194/gmd-7-1037-2014, 2014
K. A. Luus, Y. Gel, J. C. Lin, R. E. J. Kelly, and C. R. Duguay
Biogeosciences, 10, 7575–7597, https://doi.org/10.5194/bg-10-7575-2013, https://doi.org/10.5194/bg-10-7575-2013, 2013
J. Worden, K. Wecht, C. Frankenberg, M. Alvarado, K. Bowman, E. Kort, S. Kulawik, M. Lee, V. Payne, and H. Worden
Atmos. Chem. Phys., 13, 3679–3692, https://doi.org/10.5194/acp-13-3679-2013, https://doi.org/10.5194/acp-13-3679-2013, 2013
D. Wen, J. C. Lin, L. Zhang, R. Vet, and M. D. Moran
Geosci. Model Dev., 6, 327–344, https://doi.org/10.5194/gmd-6-327-2013, https://doi.org/10.5194/gmd-6-327-2013, 2013
Related subject area
Atmospheric sciences
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
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
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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Short summary
Urban CO2 enhancement signals can be derived using satellite column CO2 concentrations and atmospheric transport models. However, uncertainties due to model configurations, atmospheric transport, and defined background values can potentially impact the derived urban signals. In this paper, we present a modified Lagrangian model framework that extracts urban CO2 signals from satellite observations and determines potential error impacts.
Urban CO2 enhancement signals can be derived using satellite column CO2 concentrations and...
