Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3633-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3633-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
17 Jun 2021
Model description paper |
| 17 Jun 2021
| 17 Jun 2021
A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1)
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, UT, USA
now at: Division of Geological and Planetary Sciences, California
Institute of Technology, Pasadena, CA, USA
John C. Lin
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, UT, USA
Henrique F. Duarte
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, UT, USA
now at: Earth System Science Center, National Institute for
Space Research, São José dos Campos, Brazil
Vineet Yadav
NASA Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Nicholas C. Parazoo
NASA Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Tomohiro Oda
Goddard Earth Sciences Technology and Research, Universities Space
Research Association, Columbia, MD, USA
Global Modeling and Assimilation Office, NASA Goddard Space Flight
Center, Greenbelt, MD, USA
Department of Atmospheric and Oceanic Science, University of Maryland,
College Park, MD, USA
Eric A. Kort
Climate and Space Sciences and Engineering, University of Michigan,
Ann Arbor, MI, USA
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Revised manuscript not accepted
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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.
Brad Weir, Lesley E. Ott, George J. Collatz, Stephan R. Kawa, Benjamin Poulter, Abhishek Chatterjee, Tomohiro Oda, and Steven Pawson
Atmos. Chem. Phys., 21, 9609–9628, https://doi.org/10.5194/acp-21-9609-2021, https://doi.org/10.5194/acp-21-9609-2021, 2021
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We present a collection of carbon surface fluxes, the Low-order Flux Inversion (LoFI), derived from satellite observations of the Earth's surface and calibrated to match long-term inventories and atmospheric and oceanic records. Simulations using LoFI reproduce background atmospheric carbon dioxide measurements with comparable skill to the leading surface flux products. Available both retrospectively and as a forecast, LoFI enables the study of the carbon cycle as it occurs.
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
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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.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754, https://doi.org/10.5194/bg-18-2727-2021, https://doi.org/10.5194/bg-18-2727-2021, 2021
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Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Christoph A. Keller, Mathew J. Evans, K. Emma Knowland, Christa A. Hasenkopf, Sruti Modekurty, Robert A. Lucchesi, Tomohiro Oda, Bruno B. Franca, Felipe C. Mandarino, M. Valeria Díaz Suárez, Robert G. Ryan, Luke H. Fakes, and Steven Pawson
Atmos. Chem. Phys., 21, 3555–3592, https://doi.org/10.5194/acp-21-3555-2021, https://doi.org/10.5194/acp-21-3555-2021, 2021
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This study combines surface observations and model simulations to quantify the impact of COVID-19 restrictions on air quality across the world. The presented methodology removes the confounding impacts of meteorology on air pollution. Our results indicate that surface concentrations of nitrogen dioxide, an important air pollutant emitted during the combustion of fossil fuels, declined by up to 60 % following the implementation of COVID-19 containment measures.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Shamil Maksyutov, Tomohiro Oda, Makoto Saito, Rajesh Janardanan, Dmitry Belikov, Johannes W. Kaiser, Ruslan Zhuravlev, Alexander Ganshin, Vinu K. Valsala, Arlyn Andrews, Lukasz Chmura, Edward Dlugokencky, László Haszpra, Ray L. Langenfelds, Toshinobu Machida, Takakiyo Nakazawa, Michel Ramonet, Colm Sweeney, and Douglas Worthy
Atmos. Chem. Phys., 21, 1245–1266, https://doi.org/10.5194/acp-21-1245-2021, https://doi.org/10.5194/acp-21-1245-2021, 2021
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In order to improve the top-down estimation of the anthropogenic greenhouse gas emissions, a high-resolution inverse modelling technique was developed for applications to global transport modelling of carbon dioxide and other greenhouse gases. A coupled Eulerian–Lagrangian transport model and its adjoint are combined with surface fluxes at 0.1° resolution to provide high-resolution forward simulation and inverse modelling of surface fluxes accounting for signals from emission hot spots.
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.
Yuming Jin, Ralph F. Keeling, Eric J. Morgan, Eric Ray, Nicholas C. Parazoo, and Britton B. Stephens
Atmos. Chem. Phys., 21, 217–238, https://doi.org/10.5194/acp-21-217-2021, https://doi.org/10.5194/acp-21-217-2021, 2021
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We propose a new atmospheric coordinate (Mθe) based on equivalent potential temperature (θe) but with mass as the unit. This coordinate is useful in studying the spatial and temporal distribution of long-lived chemical tracers (CO2, CH4, O2 / N2, etc.) from sparse data, like airborne observation. Using this coordinate and sparse airborne observation (HIPPO and ATom), we resolve the Northern Hemisphere mass-weighted average CO2 seasonal cycle with high accuracy.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
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We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
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Satellite measurements of solar-induced chlorophyll fluorescence (SIF) provide a global measure of photosynthetic change. This enables scientists to better track carbon cycle responses to environmental change and tune biochemical processes in vegetation models for an improved simulation of future change. We use tower-instrumented SIF measurements and controlled model experiments to assess the state of the art in terrestrial biosphere SIF modeling and find a wide range of sensitivities to light.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
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Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
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.
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.
Alexandra G. Konings, A. Anthony Bloom, Junjie Liu, Nicholas C. Parazoo, David S. Schimel, and Kevin W. Bowman
Biogeosciences, 16, 2269–2284, https://doi.org/10.5194/bg-16-2269-2019, https://doi.org/10.5194/bg-16-2269-2019, 2019
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We estimate heterotrophic respiration (Rh) – the respiration from microbes in the soil – using satellite estimates of the net carbon flux and other quantities. Rh is an important carbon flux but is rarely studied by itself. Our method is the first to estimate how Rh varies in both space and time. The resulting new estimate of Rh is compared to the best currently available alternative, which is based on interpolating field measurements globally. The two estimates disagree and are both uncertain.
Robert R. Bogue, Florian M. Schwandner, Joshua B. Fisher, Ryan Pavlick, Troy S. Magney, Caroline A. Famiglietti, Kerry Cawse-Nicholson, Vineet Yadav, Justin P. Linick, Gretchen B. North, and Eliecer Duarte
Biogeosciences, 16, 1343–1360, https://doi.org/10.5194/bg-16-1343-2019, https://doi.org/10.5194/bg-16-1343-2019, 2019
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This study examined rainforest responses to elevated CO2 coming from volcanoes in Costa Rica. Comparing tree species, we found that leaf function responded when exposed to increasing CO2 levels. The chemical signature of volcanic CO2 is different than background CO2. Trees exposed to volcanic CO2 also had chemical signatures which showed the influence of volcanic CO2: trees not only
breathe inand are made of volcanic CO2 but also retain that exposure history for decades.
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.
Dien Wu, John C. Lin, Benjamin Fasoli, Tomohiro Oda, Xinxin Ye, Thomas Lauvaux, Emily G. Yang, and Eric A. Kort
Geosci. Model Dev., 11, 4843–4871, https://doi.org/10.5194/gmd-11-4843-2018, https://doi.org/10.5194/gmd-11-4843-2018, 2018
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Urban CO2 enhancement signals can be derived using satellite column CO2 concentrations and atmospheric transport models. However, uncertainties due to model configurations, atmospheric transport, and defined background values can potentially impact the derived urban signals. In this paper, we present a modified Lagrangian model framework that extracts urban CO2 signals from satellite observations and determines potential error impacts.
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.
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.
Scot M. Miller, Anna M. Michalak, Vineet Yadav, and Jovan M. Tadić
Atmos. Chem. Phys., 18, 6785–6799, https://doi.org/10.5194/acp-18-6785-2018, https://doi.org/10.5194/acp-18-6785-2018, 2018
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere globally. We evaluate the extent to which current OCO-2 observations can inform scientific understanding of the biospheric carbon balance. We find that current observations are best-equipped to constrain the biospheric carbon balance across continental or hemispheric regions and provide limited information on smaller regions.
Nicholas C. Parazoo, Charles D. Koven, David M. Lawrence, Vladimir Romanovsky, and Charles E. Miller
The Cryosphere, 12, 123–144, https://doi.org/10.5194/tc-12-123-2018, https://doi.org/10.5194/tc-12-123-2018, 2018
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Carbon models suggest the permafrost carbon feedback (soil carbon emissions from permafrost thaw) acts as a slow, unobservable leak. We investigate if permafrost temperature provides an observable signal to detect feedbacks. We find a slow carbon feedback in warm sub-Arctic permafrost soils, but potentially rapid feedback in cold Arctic permafrost. This is surprising since the cold permafrost region is dominated by tundra and underlain by deep, cold permafrost thought impervious to such changes.
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.
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.
Kristal R. Verhulst, Anna Karion, Jooil Kim, Peter K. Salameh, Ralph F. Keeling, Sally Newman, John Miller, Christopher Sloop, Thomas Pongetti, Preeti Rao, Clare Wong, Francesca M. Hopkins, Vineet Yadav, Ray F. Weiss, Riley M. Duren, and Charles E. Miller
Atmos. Chem. Phys., 17, 8313–8341, https://doi.org/10.5194/acp-17-8313-2017, https://doi.org/10.5194/acp-17-8313-2017, 2017
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We present the first carbon dioxide (CO2) and methane (CH4) measurements from an extensive surface network as part of the Los Angeles Megacity Carbon Project. We describe methods that are essential for understanding carbon fluxes from complex urban environments. CO2 and CH4 levels are spatially and temporally variable, with urban sites showing significant enhancements relative to background. In 2015, the median afternoon enhancement near downtown Los Angeles was ~15 ppm CO2 and ~80 ppb CH4.
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.
Vineet Yadav and Anna M. Michalak
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-204, https://doi.org/10.5194/gmd-2016-204, 2016
Revised manuscript has not been submitted
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Multiplication of two matrices that consists of few non-zero entries is a fundamental operation in problems that involve estimation of greenhouse gas fluxes from atmospheric measurements. To increase computational efficiency of estimating these quantities, modification of the standard matrix multiplication algorithm for multiplying these matrices is proposed in this research.
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.
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
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
D. Wunch, P. O. Wennberg, J. Messerschmidt, N. C. Parazoo, G. C. Toon, N. M. Deutscher, G. Keppel-Aleks, C. M. Roehl, J. T. Randerson, T. Warneke, and J. Notholt
Atmos. Chem. Phys., 13, 9447–9459, https://doi.org/10.5194/acp-13-9447-2013, https://doi.org/10.5194/acp-13-9447-2013, 2013
S. Maksyutov, H. Takagi, V. K. Valsala, M. Saito, T. Oda, T. Saeki, D. A. Belikov, R. Saito, A. Ito, Y. Yoshida, I. Morino, O. Uchino, R. J. Andres, and T. Yokota
Atmos. Chem. Phys., 13, 9351–9373, https://doi.org/10.5194/acp-13-9351-2013, https://doi.org/10.5194/acp-13-9351-2013, 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
J. Brioude, W. M. Angevine, R. Ahmadov, S.-W. Kim, S. Evan, S. A. McKeen, E.-Y. Hsie, G. J. Frost, J. A. Neuman, I. B. Pollack, J. Peischl, T. B. Ryerson, J. Holloway, S. S. Brown, J. B. Nowak, J. M. Roberts, S. C. Wofsy, G. W. Santoni, T. Oda, and M. Trainer
Atmos. Chem. Phys., 13, 3661–3677, https://doi.org/10.5194/acp-13-3661-2013, https://doi.org/10.5194/acp-13-3661-2013, 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
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Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
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A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
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Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
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We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
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We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
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Short summary
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.
A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to...
