Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7775-2021
© 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-14-7775-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
23 Dec 2021
Model experiment description paper |
| 23 Dec 2021
| 23 Dec 2021
How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35)
Xueying Yu
Department of Soil, Water, and Climate, University of Minnesota, Saint
Paul, Minnesota 55108, United States
Department of Soil, Water, and Climate, University of Minnesota, Saint
Paul, Minnesota 55108, United States
Daven K. Henze
Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, United States
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Dandan Wei, Hariprasad D. Alwe, Dylan B. Millet, Brandon Bottorff, Michelle Lew, Philip S. Stevens, Joshua D. Shutter, Joshua L. Cox, Frank N. Keutsch, Qianwen Shi, Sarah C. Kavassalis, Jennifer G. Murphy, Krystal T. Vasquez, Hannah M. Allen, Eric Praske, John D. Crounse, Paul O. Wennberg, Paul B. Shepson, Alexander A. T. Bui, Henry W. Wallace, Robert J. Griffin, Nathaniel W. May, Megan Connor, Jonathan H. Slade, Kerri A. Pratt, Ezra C. Wood, Mathew Rollings, Benjamin L. Deming, Daniel C. Anderson, and Allison L. Steiner
Geosci. Model Dev., 14, 6309–6329, https://doi.org/10.5194/gmd-14-6309-2021, https://doi.org/10.5194/gmd-14-6309-2021, 2021
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Over the past decade, understanding of isoprene oxidation has improved, and proper representation of isoprene oxidation and isoprene-derived SOA (iSOA) formation in canopy–chemistry models is now recognized to be important for an accurate understanding of forest–atmosphere exchange. The updated FORCAsT version 2.0 improves the estimation of some isoprene oxidation products and is one of the few canopy models currently capable of simulating SOA formation from monoterpenes and isoprene.
Benjamin A. Nault, Duseong S. Jo, Brian C. McDonald, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Jason C. Schroder, James Allan, Donald R. Blake, Manjula R. Canagaratna, Hugh Coe, Matthew M. Coggon, Peter F. DeCarlo, Glenn S. Diskin, Rachel Dunmore, Frank Flocke, Alan Fried, Jessica B. Gilman, Georgios Gkatzelis, Jacqui F. Hamilton, Thomas F. Hanisco, Patrick L. Hayes, Daven K. Henze, Alma Hodzic, James Hopkins, Min Hu, L. Greggory Huey, B. Thomas Jobson, William C. Kuster, Alastair Lewis, Meng Li, Jin Liao, M. Omar Nawaz, Ilana B. Pollack, Jeffrey Peischl, Bernhard Rappenglück, Claire E. Reeves, Dirk Richter, James M. Roberts, Thomas B. Ryerson, Min Shao, Jacob M. Sommers, James Walega, Carsten Warneke, Petter Weibring, Glenn M. Wolfe, Dominique E. Young, Bin Yuan, Qiang Zhang, Joost A. de Gouw, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 11201–11224, https://doi.org/10.5194/acp-21-11201-2021, https://doi.org/10.5194/acp-21-11201-2021, 2021
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Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Martin Keller, Daven K. Henze, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Atmos. Chem. Phys., 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021, https://doi.org/10.5194/acp-21-9545-2021, 2021
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We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
Na Zhao, Xinyi Dong, Kan Huang, Joshua S. Fu, Marianne Tronstad Lund, Kengo Sudo, Daven Henze, Tom Kucsera, Yun Fat Lam, Mian Chin, and Simone Tilmes
Atmos. Chem. Phys., 21, 8637–8654, https://doi.org/10.5194/acp-21-8637-2021, https://doi.org/10.5194/acp-21-8637-2021, 2021
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Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
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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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Hélène Angot, Katelyn McErlean, Lu Hu, Dylan B. Millet, Jacques Hueber, Kaixin Cui, Jacob Moss, Catherine Wielgasz, Tyler Milligan, Damien Ketcherside, M. Syndonia Bret-Harte, and Detlev Helmig
Biogeosciences, 17, 6219–6236, https://doi.org/10.5194/bg-17-6219-2020, https://doi.org/10.5194/bg-17-6219-2020, 2020
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We report biogenic volatile organic compounds (BVOCs) ambient levels and emission rates from key vegetation species in the Alaskan arctic tundra, providing a new data set to further constrain isoprene chemistry under low NOx conditions in models. We add to the growing body of evidence that climate-induced changes in the vegetation composition will significantly affect the BVOC emission potential of the tundra, with implications for atmospheric oxidation processes and climate feedbacks.
Zhen Qu, Daven K. Henze, Owen R. Cooper, and Jessica L. Neu
Atmos. Chem. Phys., 20, 13109–13130, https://doi.org/10.5194/acp-20-13109-2020, https://doi.org/10.5194/acp-20-13109-2020, 2020
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We use satellite observations and chemical transport modeling to quantify sources of NOx, a major air pollutant, over the past decade. We find improved simulations of the magnitude, seasonality, and trends of NO2 and ozone concentrations using these derived emissions. Changes in ozone pollution driven by human and natural sources are identified in different regions. This work shows the benefits of remote-sensing data and inverse modeling for more accurate ozone simulations.
Yiqi Zheng, Joel A. Thornton, Nga Lee Ng, Hansen Cao, Daven K. Henze, Erin E. McDuffie, Weiwei Hu, Jose L. Jimenez, Eloise A. Marais, Eric Edgerton, and Jingqiu Mao
Atmos. Chem. Phys., 20, 13091–13107, https://doi.org/10.5194/acp-20-13091-2020, https://doi.org/10.5194/acp-20-13091-2020, 2020
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This study aims to address a challenge in biosphere–atmosphere interactions: to what extent can biogenic organic aerosol (OA) be modified through human activities? From three surface network observations, we show OA is weakly dependent on sulfate and aerosol acidity in the summer southeast US, on both long-term trends and monthly variability. The results are in strong contrast to a global model, GEOS-Chem, suggesting the need to revisit the representation of aqueous-phase secondary OA formation.
Katherine R. Travis, Colette L. Heald, Hannah M. Allen, Eric C. Apel, Stephen R. Arnold, Donald R. Blake, William H. Brune, Xin Chen, Róisín Commane, John D. Crounse, Bruce C. Daube, Glenn S. Diskin, James W. Elkins, Mathew J. Evans, Samuel R. Hall, Eric J. Hintsa, Rebecca S. Hornbrook, Prasad S. Kasibhatla, Michelle J. Kim, Gan Luo, Kathryn McKain, Dylan B. Millet, Fred L. Moore, Jeffrey Peischl, Thomas B. Ryerson, Tomás Sherwen, Alexander B. Thames, Kirk Ullmann, Xuan Wang, Paul O. Wennberg, Glenn M. Wolfe, and Fangqun Yu
Atmos. Chem. Phys., 20, 7753–7781, https://doi.org/10.5194/acp-20-7753-2020, https://doi.org/10.5194/acp-20-7753-2020, 2020
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Atmospheric models overestimate the rate of removal of trace gases by the hydroxyl radical (OH). This is a concern for studies of the climate and air quality impacts of human activities. Here, we evaluate the performance of a commonly used model of atmospheric chemistry against data from the NASA Atmospheric Tomography Mission (ATom) over the remote oceans where models have received little validation. The model is generally successful, suggesting that biases in OH may be a concern over land.
Shunliu Zhao, Matthew G. Russell, Amir Hakami, Shannon L. Capps, Matthew D. Turner, Daven K. Henze, Peter B. Percell, Jaroslav Resler, Huizhong Shen, Armistead G. Russell, Athanasios Nenes, Amanda J. Pappin, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Charles O. Stanier, and Tianfeng Chai
Geosci. Model Dev., 13, 2925–2944, https://doi.org/10.5194/gmd-13-2925-2020, https://doi.org/10.5194/gmd-13-2925-2020, 2020
Matthew J. Cooper, Randall V. Martin, Daven K. Henze, and Dylan B. A. Jones
Atmos. Chem. Phys., 20, 7231–7241, https://doi.org/10.5194/acp-20-7231-2020, https://doi.org/10.5194/acp-20-7231-2020, 2020
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Comparisons between satellite-retrieved and model-simulated NO2 columns are affected by differences between the model vertical profile and the assumed profile used in the retrieval process. We examine how such differences impact NOx emission estimates from satellite observations. Larger differences between the simulated and assumed profile shape correspond to larger emission errors. This reveals the importance of using consistent profile information when comparing satellite columns to models.
Yi Wang, Jun Wang, Xiaoguang Xu, Daven K. Henze, Zhen Qu, and Kai Yang
Atmos. Chem. Phys., 20, 6631–6650, https://doi.org/10.5194/acp-20-6631-2020, https://doi.org/10.5194/acp-20-6631-2020, 2020
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The use of OMPS satellite observations to inverse-model SO2 and NO2 emissions is presented through the GEOS-Chem adjoint modeling framework. The work is illustrated over China. The robustness of the results is studied through separate and joint inversions of SO2 and NO2 and the consideration of NH3 uncertainty. Independent validation is performed with OMI SO2 and NO2 data. It is shown that simultaneous inversion of NO2 and SO2 from OMPS provides an effective way to rapidly update emissions.
Yi Wang, Jun Wang, Meng Zhou, Daven K. Henze, Cui Ge, and Wei Wang
Atmos. Chem. Phys., 20, 6651–6670, https://doi.org/10.5194/acp-20-6651-2020, https://doi.org/10.5194/acp-20-6651-2020, 2020
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We developed four different methods to downscale SO2 and NO2 emissions derived from OMPS satellite observations (in Part 1) for regional air quality modeling at a spatial resolution that is finer than satellite observations. The VIIRS (city lights), TROPOMI, and OMI satellite data as well as surface data are used to evaluate the model. The method of using the top-down emissions from the past month for the air quality forecast in the present month is also shown to have practical merit.
Sojin Lee, Chul Han Song, Kyung Man Han, Daven K. Henze, Kyunghwa Lee, Jinhyeok Yu, Jung-Hun Woo, Jia Jung, Yunsoo Choi, Pablo E. Saide, and Gregory R. Carmichael
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-116, https://doi.org/10.5194/gmd-2020-116, 2020
Revised manuscript not accepted
Anton Laakso, Peter K. Snyder, Stefan Liess, Antti-Ilari Partanen, and Dylan B. Millet
Earth Syst. Dynam., 11, 415–434, https://doi.org/10.5194/esd-11-415-2020, https://doi.org/10.5194/esd-11-415-2020, 2020
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Geoengineering techniques have been proposed to prevent climate warming in the event of insufficient greenhouse gas emission reductions. Simultaneously, these techniques have an impact on precipitation, which depends on the techniques used, geoengineering magnitude, and background circumstances. We separated the independent and dependent components of precipitation responses to temperature, which were then used to explain the precipitation changes in the studied climate model simulations.
Cheng Chen, Oleg Dubovik, Daven K. Henze, Mian Chin, Tatyana Lapyonok, Gregory L. Schuster, Fabrice Ducos, David Fuertes, Pavel Litvinov, Lei Li, Anton Lopatin, Qiaoyun Hu, and Benjamin Torres
Atmos. Chem. Phys., 19, 14585–14606, https://doi.org/10.5194/acp-19-14585-2019, https://doi.org/10.5194/acp-19-14585-2019, 2019
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Global BC, OC and DD aerosol emissions are inverted from POLDER/PARASOL observations for the year 2010 based on the GEOS-Chem inverse modeling framework. The retrieved emissions are 18.4 Tg yr−1 BC, 109.9 Tg yr−1 OC and 731.6 Tg yr−1 DD, which indicate an increase of 166.7 % for BC and 184.0 % for OC, while a decrease of 42.4 % for DD with respect to GEOS-Chem a priori emission inventories is seen. Global annul mean AOD and AAOD resulting from retrieved emissions are 0.119 and 0.0071 at 550 nm.
Sajeev Philip, Matthew S. Johnson, Christopher Potter, Vanessa Genovesse, David F. Baker, Katherine D. Haynes, Daven K. Henze, Junjie Liu, and Benjamin Poulter
Atmos. Chem. Phys., 19, 13267–13287, https://doi.org/10.5194/acp-19-13267-2019, https://doi.org/10.5194/acp-19-13267-2019, 2019
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This research was conducted to quantify the impact of different prior global biosphere models on the estimate of terrestrial CO2 fluxes when assimilating Orbiting Carbon Observatory-2 (OCO-2) satellite observations. To determine the prior model impact, we apply observing system simulation experiments (OSSEs). Even with the substantial spatiotemporal coverage of OCO-2 data, residual differences in posterior CO2 flux estimates remain due to the choice of prior flux mean and uncertainties.
Xin Chen, Dylan B. Millet, Hanwant B. Singh, Armin Wisthaler, Eric C. Apel, Elliot L. Atlas, Donald R. Blake, Ilann Bourgeois, Steven S. Brown, John D. Crounse, Joost A. de Gouw, Frank M. Flocke, Alan Fried, Brian G. Heikes, Rebecca S. Hornbrook, Tomas Mikoviny, Kyung-Eun Min, Markus Müller, J. Andrew Neuman, Daniel W. O'Sullivan, Jeff Peischl, Gabriele G. Pfister, Dirk Richter, James M. Roberts, Thomas B. Ryerson, Stephen R. Shertz, Chelsea R. Thompson, Victoria Treadaway, Patrick R. Veres, James Walega, Carsten Warneke, Rebecca A. Washenfelder, Petter Weibring, and Bin Yuan
Atmos. Chem. Phys., 19, 9097–9123, https://doi.org/10.5194/acp-19-9097-2019, https://doi.org/10.5194/acp-19-9097-2019, 2019
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Volatile organic compounds (VOCs) affect air quality and modify the lifetimes of other pollutants. We combine a high-resolution 3-D atmospheric model with an ensemble of aircraft observations to perform an integrated analysis of the VOC budget over North America. We find that biogenic emissions provide the main source of VOC reactivity even in most major cities. Our findings point to key gaps in current models related to oxygenated VOCs and to the distribution of VOCs in the free troposphere.
Zainab Q. Hakim, Scott Archer-Nicholls, Gufran Beig, Gerd A. Folberth, Kengo Sudo, Nathan Luke Abraham, Sachin Ghude, Daven K. Henze, and Alexander T. Archibald
Atmos. Chem. Phys., 19, 6437–6458, https://doi.org/10.5194/acp-19-6437-2019, https://doi.org/10.5194/acp-19-6437-2019, 2019
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Surface ozone is an important air pollutant and recent work has calculated that large numbers of people die prematurely because of exposure to high levels of surface ozone in India. However, these calculations require model simulations of ozone as key inputs.
Here we perform the most thorough evaluation of global model surface ozone over India to date. These analyses of model simulations and observations highlight some successes and shortcomings and the need for further process-based studies.
Minqiang Zhou, Bavo Langerock, Kelley C. Wells, Dylan B. Millet, Corinne Vigouroux, Mahesh Kumar Sha, Christian Hermans, Jean-Marc Metzger, Rigel Kivi, Pauli Heikkinen, Dan Smale, David F. Pollard, Nicholas Jones, Nicholas M. Deutscher, Thomas Blumenstock, Matthias Schneider, Mathias Palm, Justus Notholt, James W. Hannigan, and Martine De Mazière
Atmos. Meas. Tech., 12, 1393–1408, https://doi.org/10.5194/amt-12-1393-2019, https://doi.org/10.5194/amt-12-1393-2019, 2019
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N2O is an important atmospheric gas which is observed by two ground-based FTIR networks (TCCON and NDACC). The difference between NDACC and TCCON XN2O measurements is discussed. It is found that the bias between the two networks is within their combined uncertainties. However, TCCON measurements are affected by a priori profiles. In addition, the TCCON and NDACC N2O measurements are compared with the GEOS-Chem model simulations.
Yingying Yan, David Cabrera-Perez, Jintai Lin, Andrea Pozzer, Lu Hu, Dylan B. Millet, William C. Porter, and Jos Lelieveld
Geosci. Model Dev., 12, 111–130, https://doi.org/10.5194/gmd-12-111-2019, https://doi.org/10.5194/gmd-12-111-2019, 2019
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The GEOS-Chem model has been updated with the SAPRC-11 aromatics chemical mechanism to evaluate global and regional effects of aromatics on tropospheric oxidation capacity. Our results reveal relatively slight changes in ozone, hydroxyl radical, and nitrogen oxides on a global mean basis (1–4 %), although remarkable regional differences (5–20 %) exist near the source regions. Improved representation of aromatics is important to simulate the tropospheric oxidation.
Xinyi Dong, Joshua S. Fu, Qingzhao Zhu, Jian Sun, Jiani Tan, Terry Keating, Takashi Sekiya, Kengo Sudo, Louisa Emmons, Simone Tilmes, Jan Eiof Jonson, Michael Schulz, Huisheng Bian, Mian Chin, Yanko Davila, Daven Henze, Toshihiko Takemura, Anna Maria Katarina Benedictow, and Kan Huang
Atmos. Chem. Phys., 18, 15581–15600, https://doi.org/10.5194/acp-18-15581-2018, https://doi.org/10.5194/acp-18-15581-2018, 2018
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We have applied the HTAP phase II multi-model data to investigate the long-range transport impacts on surface concentration and column density of PM from Europe and Russia, Belarus, and Ukraine to eastern Asia, with a special focus on the long-range transport contribution during haze episodes in China. We found that long-range transport plays a more important role in elevating the background concentration of surface PM during the haze days.
Hansen Cao, Tzung-May Fu, Lin Zhang, Daven K. Henze, Christopher Chan Miller, Christophe Lerot, Gonzalo González Abad, Isabelle De Smedt, Qiang Zhang, Michel van Roozendael, François Hendrick, Kelly Chance, Jie Li, Junyu Zheng, and Yuanhong Zhao
Atmos. Chem. Phys., 18, 15017–15046, https://doi.org/10.5194/acp-18-15017-2018, https://doi.org/10.5194/acp-18-15017-2018, 2018
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Our top-down estimates for annual total Chinese NMVOC emissions was 30.7 to 49.5 Tg y−1, including 16.4 to 23.6 Tg y−1 from anthropogenic sources, 12.2 to 22.8 Tg y−1 from biogenic sources, and 2.08 to 3.13 Tg y−1 from biomass burning. Our four inversions consistently showed that the emissions of Chinese anthropogenic NMVOC precursors of glyoxal were larger than the a priori estimates. The glyoxal and formaldehyde constraints helped distinguish the NMVOC species from different sources.
Jan Eiof Jonson, Michael Schulz, Louisa Emmons, Johannes Flemming, Daven Henze, Kengo Sudo, Marianne Tronstad Lund, Meiyun Lin, Anna Benedictow, Brigitte Koffi, Frank Dentener, Terry Keating, Rigel Kivi, and Yanko Davila
Atmos. Chem. Phys., 18, 13655–13672, https://doi.org/10.5194/acp-18-13655-2018, https://doi.org/10.5194/acp-18-13655-2018, 2018
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Focusing on Europe, this HTAP 2 study computes ozone in several global models when reducing anthropogenic emissions by 20 % in different world regions. The differences in model results are explored
by use of a novel stepwise approach combining a tracer, CO and ozone. For ozone the contributions from the rest of the world are larger than from Europe, with the largest contributions from North America and eastern Asia. Contributions do, however, depend on the choice of ozone metric.
Cheng Chen, Oleg Dubovik, Daven K. Henze, Tatyana Lapyonak, Mian Chin, Fabrice Ducos, Pavel Litvinov, Xin Huang, and Lei Li
Atmos. Chem. Phys., 18, 12551–12580, https://doi.org/10.5194/acp-18-12551-2018, https://doi.org/10.5194/acp-18-12551-2018, 2018
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This paper introduces a method to use satellite-observed spectral AOD and AAOD to derive three types of aerosol emission sources simultaneously based on inverse modelling at a high spatial and temporal resolution. This study shows it is possible to estimate aerosol emissions and improve the atmospheric aerosol simulation using detailed aerosol optical and microphysical information from satellite observations.
Ciao-Kai Liang, J. Jason West, Raquel A. Silva, Huisheng Bian, Mian Chin, Yanko Davila, Frank J. Dentener, Louisa Emmons, Johannes Flemming, Gerd Folberth, Daven Henze, Ulas Im, Jan Eiof Jonson, Terry J. Keating, Tom Kucsera, Allen Lenzen, Meiyun Lin, Marianne Tronstad Lund, Xiaohua Pan, Rokjin J. Park, R. Bradley Pierce, Takashi Sekiya, Kengo Sudo, and Toshihiko Takemura
Atmos. Chem. Phys., 18, 10497–10520, https://doi.org/10.5194/acp-18-10497-2018, https://doi.org/10.5194/acp-18-10497-2018, 2018
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Emissions from one continent affect air quality and health elsewhere. Here we quantify the effects of intercontinental PM2.5 and ozone transport on human health using a new multi-model ensemble, evaluating the health effects of emissions from six world regions and three emission source sectors. Emissions from one region have significant health impacts outside of that source region; similarly, foreign emissions contribute significantly to air-pollution-related deaths in several world regions.
Steven T. Turnock, Oliver Wild, Frank J. Dentener, Yanko Davila, Louisa K. Emmons, Johannes Flemming, Gerd A. Folberth, Daven K. Henze, Jan E. Jonson, Terry J. Keating, Sudo Kengo, Meiyun Lin, Marianne Lund, Simone Tilmes, and Fiona M. O'Connor
Atmos. Chem. Phys., 18, 8953–8978, https://doi.org/10.5194/acp-18-8953-2018, https://doi.org/10.5194/acp-18-8953-2018, 2018
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A simple parameterisation was developed in this study to provide a rapid assessment of the impacts and uncertainties associated with future emission control strategies by predicting changes to surface ozone air quality and near-term climate forcing of ozone. Future emissions scenarios based on currently implemented legislation are shown to worsen surface ozone air quality and enhance near-term climate warming, with changes in methane becoming increasingly important in the future.
Stefano Galmarini, Ioannis Kioutsioukis, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Roberto Bellasio, Anna M. K. Benedictow, Roberto Bianconi, Johannes Bieser, Joergen Brandt, Jesper H. Christensen, Augustin Colette, Gabriele Curci, Yanko Davila, Xinyi Dong, Johannes Flemming, Xavier Francis, Andrea Fraser, Joshua Fu, Daven K. Henze, Christian Hogrefe, Ulas Im, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Jan Eiof Jonson, Nutthida Kitwiroon, Astrid Manders, Rohit Mathur, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marie Prank, Martin Schultz, Rajeet S. Sokhi, Kengo Sudo, Paolo Tuccella, Toshihiko Takemura, Takashi Sekiya, and Alper Unal
Atmos. Chem. Phys., 18, 8727–8744, https://doi.org/10.5194/acp-18-8727-2018, https://doi.org/10.5194/acp-18-8727-2018, 2018
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An ensemble of model results relating to ozone concentrations in Europe in 2010 has been produced and studied. The novelty consists in the fact that the ensemble is made of results of models working at two different scales (regional and global), therefore contributing in detail two different parts of the atmospheric spectrum. The ensemble defined as a hybrid has been studied in detail and shown to bring additional value to the assessment of air quality.
Chandra Venkataraman, Michael Brauer, Kushal Tibrewal, Pankaj Sadavarte, Qiao Ma, Aaron Cohen, Sreelekha Chaliyakunnel, Joseph Frostad, Zbigniew Klimont, Randall V. Martin, Dylan B. Millet, Sajeev Philip, Katherine Walker, and Shuxiao Wang
Atmos. Chem. Phys., 18, 8017–8039, https://doi.org/10.5194/acp-18-8017-2018, https://doi.org/10.5194/acp-18-8017-2018, 2018
Jiani Tan, Joshua S. Fu, Frank Dentener, Jian Sun, Louisa Emmons, Simone Tilmes, Kengo Sudo, Johannes Flemming, Jan Eiof Jonson, Sylvie Gravel, Huisheng Bian, Yanko Davila, Daven K. Henze, Marianne T. Lund, Tom Kucsera, Toshihiko Takemura, and Terry Keating
Atmos. Chem. Phys., 18, 6847–6866, https://doi.org/10.5194/acp-18-6847-2018, https://doi.org/10.5194/acp-18-6847-2018, 2018
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We study the distributions of sulfur and nitrogen deposition, which are associated with current environmental issues such as formation of acid rain and ecosystem eutrophication and result in widespread problems such as loss of environmental diversity, harming the crop yield and even food insecurity. According to our study, both the amount and distribution of sulfate and nitrogen deposition have changed significantly in the last decade, particularly in East Asia, South Asia and Southeast Asia.
Kira Sadighi, Evan Coffey, Andrea Polidori, Brandon Feenstra, Qin Lv, Daven K. Henze, and Michael Hannigan
Atmos. Meas. Tech., 11, 1777–1792, https://doi.org/10.5194/amt-11-1777-2018, https://doi.org/10.5194/amt-11-1777-2018, 2018
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Ground-level ozone has negative human health impacts. In the summer of 2015, 13 low-cost sensor monitors were deployed to several neighborhoods around Riverside, California. There were significant spatial differences between monitors. This is important because it means that ozone in certain places may be higher than what EPA monitors report for an area, which is pertinent for residents of those communities. This research helps inform the limitations and advantages of low-cost sensor networks.
Kelley C. Wells, Dylan B. Millet, Nicolas Bousserez, Daven K. Henze, Timothy J. Griffis, Sreelekha Chaliyakunnel, Edward J. Dlugokencky, Eri Saikawa, Gao Xiang, Ronald G. Prinn, Simon O'Doherty, Dickon Young, Ray F. Weiss, Geoff S. Dutton, James W. Elkins, Paul B. Krummel, Ray Langenfelds, and L. Paul Steele
Atmos. Chem. Phys., 18, 735–756, https://doi.org/10.5194/acp-18-735-2018, https://doi.org/10.5194/acp-18-735-2018, 2018
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This paper uses three different frameworks to derive nitrous oxide (N2O) emissions based on global surface observations. One of these frameworks employs a new approach that allows for fast computation and explores a larger solution space than other methods. Our results point to a few conclusions about the global N2O budget, including a larger contribution from tropical sources, an overestimate of natural soil emissions, and an underestimate of agricultural sources particularly in springtime.
Lin Zhang, Youfan Chen, Yuanhong Zhao, Daven K. Henze, Liye Zhu, Yu Song, Fabien Paulot, Xuejun Liu, Yuepeng Pan, Yi Lin, and Binxiang Huang
Atmos. Chem. Phys., 18, 339–355, https://doi.org/10.5194/acp-18-339-2018, https://doi.org/10.5194/acp-18-339-2018, 2018
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Substantial differences exist in current estimates of agricultural ammonia emissions in China, hindering understanding of their environmental consequences. This study applies both bottom-up and top-down methods to better quantify agricultural ammonia sources in China using observations from satellite and surface networks interpreted by a chemical transport model. Our estimate of annual Chinese anthropogenic ammonia emission is 11.7 tg (teragram) for 2008 with a strong seasonality peak in summer.
Jun-Wei Xu, Randall V. Martin, Andrew Morrow, Sangeeta Sharma, Lin Huang, W. Richard Leaitch, Julia Burkart, Hannes Schulz, Marco Zanatta, Megan D. Willis, Daven K. Henze, Colin J. Lee, Andreas B. Herber, and Jonathan P. D. Abbatt
Atmos. Chem. Phys., 17, 11971–11989, https://doi.org/10.5194/acp-17-11971-2017, https://doi.org/10.5194/acp-17-11971-2017, 2017
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We interpret a series of recent airborne and ground-based measurements with the GEOS-Chem model and its adjoint to attribute the sources of Arctic BC. Anthropogenic emissions in eastern and southern Asia make the largest contribution to Arctic BC. Gas flaring emissions from oilfields in western Siberia and from the Tarim oilfield in western China could have striking impacts on Arctic BC loadings.
Ling Qi, Qinbin Li, Daven K. Henze, Hsien-Liang Tseng, and Cenlin He
Atmos. Chem. Phys., 17, 9697–9716, https://doi.org/10.5194/acp-17-9697-2017, https://doi.org/10.5194/acp-17-9697-2017, 2017
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We find that Asian anthropogenic sources are the largest contributors (~ 40 %) to surface BC in spring in the Arctic, inconsistent with previous studies which repeatedly identified sources of surface BC as anthropogenic emissions from Europe and Russia. It takes 12–17 days for Asian anthropogenic emissions to be transported to the Arctic surface. Additionally, a large fraction (40–65 %) of Asian contribution is in the form of chronic pollution on 1- to 2-month timescales.
Michael Weimer, Jennifer Schröter, Johannes Eckstein, Konrad Deetz, Marco Neumaier, Garlich Fischbeck, Lu Hu, Dylan B. Millet, Daniel Rieger, Heike Vogel, Bernhard Vogel, Thomas Reddmann, Oliver Kirner, Roland Ruhnke, and Peter Braesicke
Geosci. Model Dev., 10, 2471–2494, https://doi.org/10.5194/gmd-10-2471-2017, https://doi.org/10.5194/gmd-10-2471-2017, 2017
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In this paper, the recently developed module for trace gas emissions in the online coupled modelling framework ICON-ART for atmospheric chemistry is presented. Algorithms for offline and online calculation of the emissions are described. The module is validated with ground-based as well as airborne measurements of acetone. It is shown that the module performs well and allows the simulation of annual cycles of emission-driven trace gases.
Jonathan J. Guerrette and Daven K. Henze
Atmos. Chem. Phys., 17, 7605–7633, https://doi.org/10.5194/acp-17-7605-2017, https://doi.org/10.5194/acp-17-7605-2017, 2017
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This work describes the implementation and application of a new advanced tool, WRFDA-Chem, for top-down constraints of regional atmospheric chemical emissions. Aircraft and surface observations of black carbon are traced to anthropogenic and biomass burning sources in California during ARCTAS-CARB. The information content of the observations is quantified through variance reduction and degrees of freedom of signal, which can be used to assess observing strategies and emission inventories.
Zhe Jiang, Helen Worden, John R. Worden, Daven K. Henze, Dylan B. A. Jones, Avelino F. Arellano, Emily V. Fischer, Liye Zhu, Kazuyuki Miyazaki, K. Folkert Boersma, and Vivienne H. Payne
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-382, https://doi.org/10.5194/acp-2017-382, 2017
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We investigated the variation of US tropospheric NO2 in the past decade. We demonstrated significant divergence between the time variation in tropospheric NO2 columns from OMI retrievals and surface measurements. Our analysis suggests limited contributions from local effects such as fossil fuel emissions, lightning, or instrument artifacts, and indicates possible important contributions from long-range transport of Asian emissions that are modulated by ENSO.
Min Huang, Gregory R. Carmichael, R. Bradley Pierce, Duseong S. Jo, Rokjin J. Park, Johannes Flemming, Louisa K. Emmons, Kevin W. Bowman, Daven K. Henze, Yanko Davila, Kengo Sudo, Jan Eiof Jonson, Marianne Tronstad Lund, Greet Janssens-Maenhout, Frank J. Dentener, Terry J. Keating, Hilke Oetjen, and Vivienne H. Payne
Atmos. Chem. Phys., 17, 5721–5750, https://doi.org/10.5194/acp-17-5721-2017, https://doi.org/10.5194/acp-17-5721-2017, 2017
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In support of the HTAP phase 2 experiment, we conducted a number of regional-scale Sulfur Transport and dEposition Model base and sensitivity simulations over North America during May–June 2010. The STEM chemical boundary conditions were downscaled from three (GEOS-Chem, RAQMS, and ECMWF C-IFS) global chemical transport models' simulations. Analyses were performed on large spatial–temporal scales relative to HTAP1 and also on subcontinental and event scales including the use of satellite data.
Zhe Jiang, John R. Worden, Helen Worden, Merritt Deeter, Dylan B. A. Jones, Avelino F. Arellano, and Daven K. Henze
Atmos. Chem. Phys., 17, 4565–4583, https://doi.org/10.5194/acp-17-4565-2017, https://doi.org/10.5194/acp-17-4565-2017, 2017
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We constrain the long-term variation in global CO emissions for 2001–2015. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, unchanged anthropogenic CO emissions from Europe since 2008, and likely a positive trend from India and southeast Asia.
Chantelle R. Lonsdale, Jennifer D. Hegarty, Karen E. Cady-Pereira, Matthew J. Alvarado, Daven K. Henze, Matthew D. Turner, Shannon L. Capps, John B. Nowak, J. Andy Neuman, Ann M. Middlebrook, Roya Bahreini, Jennifer G. Murphy, Milos Z. Markovic, Trevor C. VandenBoer, Lynn M. Russell, and Amy Jo Scarino
Atmos. Chem. Phys., 17, 2721–2739, https://doi.org/10.5194/acp-17-2721-2017, https://doi.org/10.5194/acp-17-2721-2017, 2017
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This study takes advantage of the high-resolution observations of NH3(g) made by the TES satellite instrument over Bakersfield during the CalNex campaign, along with campaign measurements, to compare CMAQ model results in the San Joaquin Valley, California. Additionally we evaluate the CMAQ bi-directional ammonia flux results using the CARB emissions inventory against these satellite and campaign measurements, not previously explored in combination.
Camilla Weum Stjern, Bjørn Hallvard Samset, Gunnar Myhre, Huisheng Bian, Mian Chin, Yanko Davila, Frank Dentener, Louisa Emmons, Johannes Flemming, Amund Søvde Haslerud, Daven Henze, Jan Eiof Jonson, Tom Kucsera, Marianne Tronstad Lund, Michael Schulz, Kengo Sudo, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 16, 13579–13599, https://doi.org/10.5194/acp-16-13579-2016, https://doi.org/10.5194/acp-16-13579-2016, 2016
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Air pollution can reach distant regions through intercontinental transport. Here we first present results from the Hemispheric Transport of Air Pollution Phase 2 exercise, where many models performed the same set of coordinated emission-reduction experiments. We find that mitigations have considerable extra-regional effects, and show that this is particularly true for black carbon emissions, as long-range transport elevates aerosols to higher levels where their radiative influence is stronger.
Zeli Tan, Qianlai Zhuang, Daven K. Henze, Christian Frankenberg, Ed Dlugokencky, Colm Sweeney, Alexander J. Turner, Motoki Sasakawa, and Toshinobu Machida
Atmos. Chem. Phys., 16, 12649–12666, https://doi.org/10.5194/acp-16-12649-2016, https://doi.org/10.5194/acp-16-12649-2016, 2016
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Methane emissions from the pan-Arctic could be important in understanding the global carbon cycle but are still poorly constrained to date. This study demonstrated that satellite retrievals can be used to reduce the uncertainty of the estimates of these emissions. We also provided additional evidence for the existence of large methane emissions from pan-Arctic lakes in the Siberian yedoma permafrost region. We found that biogeochemical models should be improved for better estimates.
Zhe Jiang, Kazuyuki Miyazaki, John R. Worden, Jane J. Liu, Dylan B. A. Jones, and Daven K. Henze
Atmos. Chem. Phys., 16, 6537–6546, https://doi.org/10.5194/acp-16-6537-2016, https://doi.org/10.5194/acp-16-6537-2016, 2016
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We quantify the impacts of anthropogenic and natural sources on free tropospheric ozone over the Middle East, using the adjoint of the GEOS-Chem model with updated NOx emissions estimates from an ensemble Kalman filter. We show that the global total contribution of lightning NOx on free tropospheric O3 over the Middle East is about 2 times larger than that from global anthropogenic sources. The summertime free tropospheric O3 enhancement is primarily due to Asian NOx emissions.
Nicolas Bousserez, Daven K. Henze, Brigitte Rooney, Andre Perkins, Kevin J. Wecht, Alexander J. Turner, Vijay Natraj, and John R. Worden
Atmos. Chem. Phys., 16, 6175–6190, https://doi.org/10.5194/acp-16-6175-2016, https://doi.org/10.5194/acp-16-6175-2016, 2016
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This work provides new insight into the observational constraints provided by current low-Earth orbit (LEO) and future potential geostationary (GEO) satellite missions on methane emissions in North America. Using efficient numerical tools, the information content (error reductions, spatial resolution of the constraints) of methane inversions using different instrument configurations (TIR, SWIR and multi-spectral) was estimated at model grid-scale resolution (0.5° × 0.7°).
H.-M. Lee, F. Paulot, D. K. Henze, K. Travis, D. J. Jacob, L. H. Pardo, and B. A. Schichtel
Atmos. Chem. Phys., 16, 525–540, https://doi.org/10.5194/acp-16-525-2016, https://doi.org/10.5194/acp-16-525-2016, 2016
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Sources of nitrogen deposition (Ndep) in Federal Class I areas in the US are investigated, identifying unique features in contributions from different species, sectors and locations. Ndep in many parks is impacted by emissions several hundred km away; the role of oxidized vs reduced sources varies regionally. Emissions reductions in the western US most effectively reduce the extent of areas in critical load exceedance, while reductions in the east most effectively reduce exceedance magnitudes.
M. W. Shephard, C. A. McLinden, K. E. Cady-Pereira, M. Luo, S. G. Moussa, A. Leithead, J. Liggio, R. M. Staebler, A. Akingunola, P. Makar, P. Lehr, J. Zhang, D. K. Henze, D. B. Millet, J. O. Bash, L. Zhu, K. C. Wells, S. L. Capps, S. Chaliyakunnel, M. Gordon, K. Hayden, J. R. Brook, M. Wolde, and S.-M. Li
Atmos. Meas. Tech., 8, 5189–5211, https://doi.org/10.5194/amt-8-5189-2015, https://doi.org/10.5194/amt-8-5189-2015, 2015
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This study provides direct validations of Tropospheric Emission Spectrometer (TES) satellite retrieved profiles against coincident aircraft profiles of carbon monoxide, ammonia, methanol, and formic acid, all of which are of interest for air quality. The comparisons are performed over the Canadian oil sands region during an intensive field campaign in support of the Joint Canada-Alberta Implementation Plan for the Oil Sands Monitoring (JOSM). Initial model evaluations are also provided.
L. Zhu, D. Henze, J. Bash, G.-R. Jeong, K. Cady-Pereira, M. Shephard, M. Luo, F. Paulot, and S. Capps
Atmos. Chem. Phys., 15, 12823–12843, https://doi.org/10.5194/acp-15-12823-2015, https://doi.org/10.5194/acp-15-12823-2015, 2015
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We implement new diurnal variation scheme for ammonia livestock emissions and bidirectional exchange scheme and its adjoint in the GEOS-Chem global chemical transport model. Updated diurnal variability improves modeled-to-hourly in situ measurements comparison. The ammonium soil pool in the bidirectional exchange model largely extends the ammonia lifetime in the atmosphere. Large model biases remain as livestock emissions are still underestimated.
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.
Y. Zhao, L. Zhang, Y. Pan, Y. Wang, F. Paulot, and D. K. Henze
Atmos. Chem. Phys., 15, 10905–10924, https://doi.org/10.5194/acp-15-10905-2015, https://doi.org/10.5194/acp-15-10905-2015, 2015
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Rapid Asian industrialization has led to increased atmospheric nitrogen deposition downwind. This work analyzes the sources and processes controlling atmospheric nitrogen deposition to the northwestern Pacific. Both nitrogen emissions and meteorology, largely controlled by the East Asian Monsoon, determine the seasonality of nitrogen deposition. Ascribing deposition over the marginal seas to nitrogen sources from different regions and sectors shows important contribution from fertilizer use.
P. D. Hamer, K. W. Bowman, D. K. Henze, J.-L. Attié, and V. Marécal
Atmos. Chem. Phys., 15, 10645–10667, https://doi.org/10.5194/acp-15-10645-2015, https://doi.org/10.5194/acp-15-10645-2015, 2015
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Using a simplified air quality forecasting model, we explore how characteristics of air quality observations affect our ability to understand and predict ozone air pollution. We show that the photochemical conditions can strongly influence the observing priorities for ozone prediction, such as which species are observed and how well, when, and how frequently. High-freqency observations of ozone, NOx and HCHO in combination during the morning and afternoon are particularly advantageous.
P. S. Kim, D. J. Jacob, J. A. Fisher, K. Travis, K. Yu, L. Zhu, R. M. Yantosca, M. P. Sulprizio, J. L. Jimenez, P. Campuzano-Jost, K. D. Froyd, J. Liao, J. W. Hair, M. A. Fenn, C. F. Butler, N. L. Wagner, T. D. Gordon, A. Welti, P. O. Wennberg, J. D. Crounse, J. M. St. Clair, A. P. Teng, D. B. Millet, J. P. Schwarz, M. Z. Markovic, and A. E. Perring
Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, https://doi.org/10.5194/acp-15-10411-2015, 2015
L. Zhang, D. K. Henze, G. A. Grell, G. R. Carmichael, N. Bousserez, Q. Zhang, O. Torres, C. Ahn, Z. Lu, J. Cao, and Y. Mao
Atmos. Chem. Phys., 15, 10281–10308, https://doi.org/10.5194/acp-15-10281-2015, https://doi.org/10.5194/acp-15-10281-2015, 2015
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We attempt to reduce uncertainties in BC emissions and improve BC model simulations by developing top-down, spatially resolved, estimates of BC emissions through assimilation of OMI observations of aerosol absorption optical depth (AAOD) with the GEOS-Chem model and its adjoint for April and October of 2006. Despite the limitations and uncertainties, using OMI AAOD to constrain BC sources we are able to improve model representation of BC distributions, particularly over China.
Y. H. Mao, Q. B. Li, D. K. Henze, Z. Jiang, D. B. A. Jones, M. Kopacz, C. He, L. Qi, M. Gao, W.-M. Hao, and K.-N. Liou
Atmos. Chem. Phys., 15, 7685–7702, https://doi.org/10.5194/acp-15-7685-2015, https://doi.org/10.5194/acp-15-7685-2015, 2015
J. J. Guerrette and D. K. Henze
Geosci. Model Dev., 8, 1857–1876, https://doi.org/10.5194/gmd-8-1857-2015, https://doi.org/10.5194/gmd-8-1857-2015, 2015
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WRFPLUS-Chem is a coupled meteorology-chemistry adjoint and tangent linear model, with applications in sensitivity analysis and four-dimensional variational data assimilation. The linearized models are verified against finite difference approximations from the nonlinear forward model, WRF-Chem. A new checkpointing scheme enables data assimilation beyond 6h. New capabilities are demonstrated in an emission sensitivity study.
Z. Jiang, D. B. A. Jones, J. Worden, H. M. Worden, D. K. Henze, and Y. X. Wang
Atmos. Chem. Phys., 15, 6801–6814, https://doi.org/10.5194/acp-15-6801-2015, https://doi.org/10.5194/acp-15-6801-2015, 2015
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We present a high-resolution (0.5 x 0.667) regional CO inversion over North America in the period of June 2004–May 2005, using a combination of GEOS-Chem model and MOPITT CO observations. With optimized lateral boundary conditions, we show that regional inversion analyses can reduce the sensitivity of the CO source estimates to errors in long-range transport and in the distributions of the hydroxyl radical (OH), and consequently, provide better quantification on regional CO source estimates.
D. B. Millet, M. Baasandorj, D. K. Farmer, J. A. Thornton, K. Baumann, P. Brophy, S. Chaliyakunnel, J. A. de Gouw, M. Graus, L. Hu, A. Koss, B. H. Lee, F. D. Lopez-Hilfiker, J. A. Neuman, F. Paulot, J. Peischl, I. B. Pollack, T. B. Ryerson, C. Warneke, B. J. Williams, and J. Xu
Atmos. Chem. Phys., 15, 6283–6304, https://doi.org/10.5194/acp-15-6283-2015, https://doi.org/10.5194/acp-15-6283-2015, 2015
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Formic acid (HCOOH) is an abundant atmospheric acid that affects precipitation chemistry and acidity. HCOOH measurements over the USA are 2-3× larger than can be explained by known sources and sinks, revealing a key gap in current understanding. Observations indicate a large biogenic source plus chemical production across a range of precursors. Model simulations cannot capture the HCOOH diurnal amplitude or nocturnal profile, implying a deposition bias and possibly even larger missing source.
M. Baasandorj, D. B. Millet, L. Hu, D. Mitroo, and B. J. Williams
Atmos. Meas. Tech., 8, 1303–1321, https://doi.org/10.5194/amt-8-1303-2015, https://doi.org/10.5194/amt-8-1303-2015, 2015
B. Yuan, P. R. Veres, C. Warneke, J. M. Roberts, J. B. Gilman, A. Koss, P. M. Edwards, M. Graus, W. C. Kuster, S.-M. Li, R. J. Wild, S. S. Brown, W. P. Dubé, B. M. Lerner, E. J. Williams, J. E. Johnson, P. K. Quinn, T. S. Bates, B. Lefer, P. L. Hayes, J. L. Jimenez, R. J. Weber, R. Zamora, B. Ervens, D. B. Millet, B. Rappenglück, and J. A. de Gouw
Atmos. Chem. Phys., 15, 1975–1993, https://doi.org/10.5194/acp-15-1975-2015, https://doi.org/10.5194/acp-15-1975-2015, 2015
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In this work, secondary formation of formic acid at an urban site and a site in an oil and gas production region is studied. We investigated various gas phase formation pathways of formic acid, including those recently proposed, using a box model. The contributions from aerosol-related processes, fog events and air-snow exchange to formic acid are also quantified.
Z. Jiang, D. B. A. Jones, H. M. Worden, and D. K. Henze
Atmos. Chem. Phys., 15, 1521–1537, https://doi.org/10.5194/acp-15-1521-2015, https://doi.org/10.5194/acp-15-1521-2015, 2015
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Using MOPITT (version 5) tropospheric profile and surface layer retrievals, we constrain global CO emissions in the period of June 2004 – May 2005. The inversions suggest a reduction in CO emission in the tropics and an increase in emissions at middle and high latitudes. The results demonstrate that the use of the surface layer retrievals from MOPITT can significantly mitigate the potential impacts of model bias in OH and long-range transport on CO emission estimates.
Z. Jiang, J. R. Worden, D. B. A. Jones, J.-T. Lin, W. W. Verstraeten, and D. K. Henze
Atmos. Chem. Phys., 15, 99–112, https://doi.org/10.5194/acp-15-99-2015, https://doi.org/10.5194/acp-15-99-2015, 2015
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We use satellite measurements of O3, CO and NO2 from TES, MOPITT and OMI to quantify O3 precursor emissions for 2006 and their impact on free tropospheric O3 over northeastern Asia. Using the adjoint of GEOS-Chem, we found that Chinese emissions have the largest influence on the free tropospheric O3. The contributions from lightning NOx in summer and India and southeastern Asia emissions in winter are sizable, comparable with Chinese emissions.
Q. Zhu, Q. Zhuang, D. Henze, K. Bowman, M. Chen, Y. Liu, Y. He, H. Matsueda, T. Machida, Y. Sawa, and W. Oechel
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-22587-2014, https://doi.org/10.5194/acpd-14-22587-2014, 2014
Revised manuscript not accepted
K. E. Cady-Pereira, S. Chaliyakunnel, M. W. Shephard, D. B. Millet, M. Luo, and K. C. Wells
Atmos. Meas. Tech., 7, 2297–2311, https://doi.org/10.5194/amt-7-2297-2014, https://doi.org/10.5194/amt-7-2297-2014, 2014
Z. Shen, J. Liu, L. W. Horowitz, D. K. Henze, S. Fan, Levy II H., D. L. Mauzerall, J.-T. Lin, and S. Tao
Atmos. Chem. Phys., 14, 6315–6327, https://doi.org/10.5194/acp-14-6315-2014, https://doi.org/10.5194/acp-14-6315-2014, 2014
F. Deng, D. B. A. Jones, D. K. Henze, N. Bousserez, K. W. Bowman, J. B. Fisher, R. Nassar, C. O'Dell, D. Wunch, P. O. Wennberg, E. A. Kort, S. C. Wofsy, T. Blumenstock, N. M. Deutscher, D. W. T. Griffith, F. Hase, P. Heikkinen, V. Sherlock, K. Strong, R. Sussmann, and T. Warneke
Atmos. Chem. Phys., 14, 3703–3727, https://doi.org/10.5194/acp-14-3703-2014, https://doi.org/10.5194/acp-14-3703-2014, 2014
E. V. Fischer, D. J. Jacob, R. M. Yantosca, M. P. Sulprizio, D. B. Millet, J. Mao, F. Paulot, H. B. Singh, A. Roiger, L. Ries, R.W. Talbot, K. Dzepina, and S. Pandey Deolal
Atmos. Chem. Phys., 14, 2679–2698, https://doi.org/10.5194/acp-14-2679-2014, https://doi.org/10.5194/acp-14-2679-2014, 2014
K. C. Wells, D. B. Millet, K. E. Cady-Pereira, M. W. Shephard, D. K. Henze, N. Bousserez, E. C. Apel, J. de Gouw, C. Warneke, and H. B. Singh
Atmos. Chem. Phys., 14, 2555–2570, https://doi.org/10.5194/acp-14-2555-2014, https://doi.org/10.5194/acp-14-2555-2014, 2014
B. S. Meland, X. Xu, D. K. Henze, and J. Wang
Atmos. Meas. Tech., 6, 3441–3457, https://doi.org/10.5194/amt-6-3441-2013, https://doi.org/10.5194/amt-6-3441-2013, 2013
L. Hu, D. B. Millet, S. Y. Kim, K. C. Wells, T. J. Griffis, E. V. Fischer, D. Helmig, J. Hueber, and A. J. Curtis
Atmos. Chem. Phys., 13, 3379–3392, https://doi.org/10.5194/acp-13-3379-2013, https://doi.org/10.5194/acp-13-3379-2013, 2013
Related subject area
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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
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
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)
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
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
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
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
Atmospheric moisture tracking with WAM2layers v3
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
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.
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.
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.
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.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 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, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS 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 e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
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
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. 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 in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
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.
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. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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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-km 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 improved representation of clouds and visibility.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
EGUsphere, https://doi.org/10.5194/egusphere-2024-3401, https://doi.org/10.5194/egusphere-2024-3401, 2024
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We introduce a new version of WAM2layers, 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 became 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 and reliable, and easier to maintain.
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.
Cited articles
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Short summary
We conduct observing system simulation experiments to test how well inverse analyses of high-resolution satellite data from sensors such as TROPOMI can quantify methane emissions. Inversions can improve monthly flux estimates at 25 km even with a spatially biased prior or model transport errors, but results are strongly degraded when both are present. We further evaluate a set of alternate formalisms to overcome limitations of the widely used scale factor approach that arise for missing sources.
We conduct observing system simulation experiments to test how well inverse analyses of...
