Articles | Volume 15, issue 2
Geosci. Model Dev., 15, 467–491, 2022
https://doi.org/10.5194/gmd-15-467-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 15, 467–491, 2022
https://doi.org/10.5194/gmd-15-467-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
20 Jan 2022
Model description paper
| 20 Jan 2022
Inline coupling of simple and complex chemistry modules within the global weather forecast model FIM (FIM-Chem v1)
Li Zhang et al.
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Plume height is important in wildfire smoke dispersion and the effects on air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region but higher pollution in downwind regions due to the faster spread of the smoke once ejected, which affects pollution exceedance forecasts and early warning of extreme air pollution events.
Aditya Kumar, R. Bradley Pierce, Ravan Ahmadov, Gabriel Pereira, Saulo Freitas, Georg Grell, Chris Schmidt, Allen Lenzen, Joshua P. Schwarz, Anne E. Perring, Joseph M. Katich, John Hair, Jose L. Jimenez, Pedro Campuzano-Jost, and Hongyu Guo
Atmos. Chem. Phys., 22, 10195–10219, https://doi.org/10.5194/acp-22-10195-2022, https://doi.org/10.5194/acp-22-10195-2022, 2022
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Geosci. Model Dev., 15, 5337–5369, https://doi.org/10.5194/gmd-15-5337-2022, https://doi.org/10.5194/gmd-15-5337-2022, 2022
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Meloë S. F. Kacenelenbogen, Qian Tan, Sharon P. Burton, Otto P. Hasekamp, Karl D. Froyd, Yohei Shinozuka, Andreas J. Beyersdorf, Luke Ziemba, Kenneth L. Thornhill, Jack E. Dibb, Taylor Shingler, Armin Sorooshian, Reed W. Espinosa, Vanderlei Martins, Jose L. Jimenez, Pedro Campuzano-Jost, Joshua P. Schwarz, Matthew S. Johnson, Jens Redemann, and Gregory L. Schuster
Atmos. Chem. Phys., 22, 3713–3742, https://doi.org/10.5194/acp-22-3713-2022, https://doi.org/10.5194/acp-22-3713-2022, 2022
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The impact of aerosols on Earth's radiation budget and human health is important and strongly depends on their composition. One desire of our scientific community is to derive the composition of the aerosol from satellite sensors. However, satellites observe aerosol optical properties (and not aerosol composition) based on remote sensing instrumentation. This study assesses how much aerosol optical properties can tell us about aerosol composition.
Adam T. Ahern, Frank Erdesz, Nicholas L. Wagner, Charles A. Brock, Ming Lyu, Kyra Slovacek, Richard H. Moore, Elizabeth B. Wiggins, and Daniel M. Murphy
Atmos. Meas. Tech., 15, 1093–1105, https://doi.org/10.5194/amt-15-1093-2022, https://doi.org/10.5194/amt-15-1093-2022, 2022
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Particles in the atmosphere play a significant role in climate change by scattering light back into space, reducing the amount of energy available to be absorbed by greenhouse gases. We built a new instrument to measure what direction light is scattered by particles, e.g., wildfire smoke. This is important because, depending on the angle of the sun, some particles scatter light into space (cooling the planet), but some light is also scattered towards the Earth (not cooling the planet).
Charles A. Brock, Karl D. Froyd, Maximilian Dollner, Christina J. Williamson, Gregory Schill, Daniel M. Murphy, Nicholas J. Wagner, Agnieszka Kupc, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jason C. Schroder, Douglas A. Day, Derek J. Price, Bernadett Weinzierl, Joshua P. Schwarz, Joseph M. Katich, Siyuan Wang, Linghan Zeng, Rodney Weber, Jack Dibb, Eric Scheuer, Glenn S. Diskin, Joshua P. DiGangi, ThaoPaul Bui, Jonathan M. Dean-Day, Chelsea R. Thompson, Jeff Peischl, Thomas B. Ryerson, Ilann Bourgeois, Bruce C. Daube, Róisín Commane, and Steven C. Wofsy
Atmos. Chem. Phys., 21, 15023–15063, https://doi.org/10.5194/acp-21-15023-2021, https://doi.org/10.5194/acp-21-15023-2021, 2021
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The Atmospheric Tomography Mission was an airborne study that mapped the chemical composition of the remote atmosphere. From this, we developed a comprehensive description of aerosol properties that provides a unique, global-scale dataset against which models can be compared. The data show the polluted nature of the remote atmosphere in the Northern Hemisphere and quantify the contributions of sea salt, dust, soot, biomass burning particles, and pollution particles to the haziness of the sky.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Saulo R. Freitas, Georg A. Grell, and Haiqin Li
Geosci. Model Dev., 14, 5393–5411, https://doi.org/10.5194/gmd-14-5393-2021, https://doi.org/10.5194/gmd-14-5393-2021, 2021
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Christina J. Williamson, Agnieszka Kupc, Andrew Rollins, Jan Kazil, Karl D. Froyd, Eric A. Ray, Daniel M. Murphy, Gregory P. Schill, Jeff Peischl, Chelsea Thompson, Ilann Bourgeois, Thomas B. Ryerson, Glenn S. Diskin, Joshua P. DiGangi, Donald R. Blake, Thao Paul V. Bui, Maximilian Dollner, Bernadett Weinzierl, and Charles A. Brock
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Atmos. Chem. Phys., 21, 8915–8932, https://doi.org/10.5194/acp-21-8915-2021, https://doi.org/10.5194/acp-21-8915-2021, 2021
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New measurements in the lower stratosphere highlight differences between particles that originated in the troposphere or the stratosphere. The stratospheric-origin particles have relatively large radiative effects because they are at nearly the optimum diameter for light scattering. The tropospheric particles contribute significantly to surface area. These and other chemical and physical properties are then extended to study the implications if material were to be added to the stratosphere.
Janaína P. Nascimento, Megan M. Bela, Bruno B. Meller, Alessandro L. Banducci, Luciana V. Rizzo, Angel Liduvino Vara-Vela, Henrique M. J. Barbosa, Helber Gomes, Sameh A. A. Rafee, Marco A. Franco, Samara Carbone, Glauber G. Cirino, Rodrigo A. F. Souza, Stuart A. McKeen, and Paulo Artaxo
Atmos. Chem. Phys., 21, 6755–6779, https://doi.org/10.5194/acp-21-6755-2021, https://doi.org/10.5194/acp-21-6755-2021, 2021
Alexander Ukhov, Ravan Ahmadov, Georg Grell, and Georgiy Stenchikov
Geosci. Model Dev., 14, 473–493, https://doi.org/10.5194/gmd-14-473-2021, https://doi.org/10.5194/gmd-14-473-2021, 2021
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We discuss and evaluate the effects of inconsistencies found in the WRF-Chem code when using the GOCART module. First, PM surface concentrations were miscalculated. Second, dust optical depth was underestimated by 25 %–30 %. Third, an inconsistency in the process of gravitational settling led to the overestimation of dust column loadings by 4 %–6 %, PM10 by 2 %–4 %, and the rate of gravitational dust settling by 5 %–10 %. We also presented diagnostics that can be used to estimate these effects.
Agnieszka Kupc, Christina J. Williamson, Anna L. Hodshire, Jan Kazil, Eric Ray, T. Paul Bui, Maximilian Dollner, Karl D. Froyd, Kathryn McKain, Andrew Rollins, Gregory P. Schill, Alexander Thames, Bernadett B. Weinzierl, Jeffrey R. Pierce, and Charles A. Brock
Atmos. Chem. Phys., 20, 15037–15060, https://doi.org/10.5194/acp-20-15037-2020, https://doi.org/10.5194/acp-20-15037-2020, 2020
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Tropical upper troposphere over the Atlantic and Pacific oceans is a major source region of new particles. These particles are associated with the outflow from deep convection. We investigate the processes that govern the formation of these particles and their initial growth and show that none of the formation schemes commonly used in global models are consistent with observations. Using newer schemes indicates that organic compounds are likely important as nucleating and initial growth agents.
Steven Albers, Stephen M. Saleeby, Sonia Kreidenweis, Qijing Bian, Peng Xian, Zoltan Toth, Ravan Ahmadov, Eric James, and Steven D. Miller
Atmos. Meas. Tech., 13, 3235–3261, https://doi.org/10.5194/amt-13-3235-2020, https://doi.org/10.5194/amt-13-3235-2020, 2020
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A fast 3D visible-light forward operator is used to realistically visualize, validate, and potentially assimilate ground- and space-based camera and satellite imagery with NWP models. Three-dimensional fields of hydrometeors, aerosols, and 2D land surface variables are considered in the generation of radiance fields and RGB imagery from a variety of vantage points.
Alma Hodzic, Pedro Campuzano-Jost, Huisheng Bian, Mian Chin, Peter R. Colarco, Douglas A. Day, Karl D. Froyd, Bernd Heinold, Duseong S. Jo, Joseph M. Katich, John K. Kodros, Benjamin A. Nault, Jeffrey R. Pierce, Eric Ray, Jacob Schacht, Gregory P. Schill, Jason C. Schroder, Joshua P. Schwarz, Donna T. Sueper, Ina Tegen, Simone Tilmes, Kostas Tsigaridis, Pengfei Yu, and Jose L. Jimenez
Atmos. Chem. Phys., 20, 4607–4635, https://doi.org/10.5194/acp-20-4607-2020, https://doi.org/10.5194/acp-20-4607-2020, 2020
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Organic aerosol (OA) is a key source of uncertainty in aerosol climate effects. We present the first pole-to-pole OA characterization during the NASA Atmospheric Tomography aircraft mission. OA has a strong seasonal and zonal variability, with the highest levels in summer and over fire-influenced regions and the lowest ones in the southern high latitudes. We show that global models predict the OA distribution well but not the relative contribution of OA emissions vs. chemical production.
Karl D. Froyd, Daniel M. Murphy, Charles A. Brock, Pedro Campuzano-Jost, Jack E. Dibb, Jose-Luis Jimenez, Agnieszka Kupc, Ann M. Middlebrook, Gregory P. Schill, Kenneth L. Thornhill, Christina J. Williamson, James C. Wilson, and Luke D. Ziemba
Atmos. Meas. Tech., 12, 6209–6239, https://doi.org/10.5194/amt-12-6209-2019, https://doi.org/10.5194/amt-12-6209-2019, 2019
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Single-particle mass spectrometer (SPMS) instruments characterize the composition of individual aerosol particles in real time. We present a new method that combines SPMS composition with independently measured particle size distributions to determine absolute number, surface area, volume, and mass concentrations of mineral dust, biomass burning, sea salt, and other climate-relevant atmospheric particle types, with a fast time response applicable to aircraft sampling.
Maria A. Zawadowicz, Karl D. Froyd, Anne E. Perring, Daniel M. Murphy, Dominick V. Spracklen, Colette L. Heald, Peter R. Buseck, and Daniel J. Cziczo
Atmos. Chem. Phys., 19, 13859–13870, https://doi.org/10.5194/acp-19-13859-2019, https://doi.org/10.5194/acp-19-13859-2019, 2019
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We report measurements of small particles of biological origin (for example, fragments of bacteria, pollen, or fungal spores) in the atmosphere over the continental United States. We use a recently developed identification technique based on airborne mass spectrometry in conjunction with an extensive aircraft dataset. We show that biological particles are present at altitudes up to 10 km and we quantify typical concentrations.
Huisheng Bian, Karl Froyd, Daniel M. Murphy, Jack Dibb, Anton Darmenov, Mian Chin, Peter R. Colarco, Arlindo da Silva, Tom L. Kucsera, Gregory Schill, Hongbin Yu, Paul Bui, Maximilian Dollner, Bernadett Weinzierl, and Alexander Smirnov
Atmos. Chem. Phys., 19, 10773–10785, https://doi.org/10.5194/acp-19-10773-2019, https://doi.org/10.5194/acp-19-10773-2019, 2019
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We address the GEOS-GOCART sea salt simulations constrained by NASA EVS ATom measurements, as well as those by MODIS and the AERONET MAN. The study covers remote regions over the Pacific, Atlantic, and Southern oceans from near the surface to ~ 12 km altitude and covers both summer and winter seasons. Important sea salt fields, e.g., mass mixing ratio, vertical distribution, size distribution, and marine aerosol AOD, as well as their relationship to relative humidity and emissions, are examined.
Charles A. Brock, Christina Williamson, Agnieszka Kupc, Karl D. Froyd, Frank Erdesz, Nicholas Wagner, Matthews Richardson, Joshua P. Schwarz, Ru-Shan Gao, Joseph M. Katich, Pedro Campuzano-Jost, Benjamin A. Nault, Jason C. Schroder, Jose L. Jimenez, Bernadett Weinzierl, Maximilian Dollner, ThaoPaul Bui, and Daniel M. Murphy
Atmos. Meas. Tech., 12, 3081–3099, https://doi.org/10.5194/amt-12-3081-2019, https://doi.org/10.5194/amt-12-3081-2019, 2019
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From 2016 to 2018 a NASA aircraft profiled the atmosphere from 180 m to ~12 km from the Arctic to the Antarctic over both the Pacific and Atlantic oceans. This program, ATom, sought to sample atmospheric chemical composition to compare with global climate models. We describe the how measurements of particulate matter were made during ATom, and show that the instrument performance was excellent. Data from this project can be used with confidence to evaluate models and compare with satellites.
Daniel M. Murphy, Karl D. Froyd, Huisheng Bian, Charles A. Brock, Jack E. Dibb, Joshua P. DiGangi, Glenn Diskin, Maximillian Dollner, Agnieszka Kupc, Eric M. Scheuer, Gregory P. Schill, Bernadett Weinzierl, Christina J. Williamson, and Pengfei Yu
Atmos. Chem. Phys., 19, 4093–4104, https://doi.org/10.5194/acp-19-4093-2019, https://doi.org/10.5194/acp-19-4093-2019, 2019
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We present the first data on the concentration of sea-salt aerosol throughout most of the depth of the troposphere and a wide range of latitudes. Sea-salt concentrations in the upper troposphere are very small. This puts stringent limits on how sea-salt aerosol affects halogen and nitric acid chemistry there. With a widely distributed source, sea-salt aerosol provides an excellent test of wet scavenging and vertical transport of aerosols in chemical transport models.
Roya Bahreini, Ravan Ahmadov, Stu A. McKeen, Kennedy T. Vu, Justin H. Dingle, Eric C. Apel, Donald R. Blake, Nicola Blake, Teresa L. Campos, Chris Cantrell, Frank Flocke, Alan Fried, Jessica B. Gilman, Alan J. Hills, Rebecca S. Hornbrook, Greg Huey, Lisa Kaser, Brian M. Lerner, Roy L. Mauldin, Simone Meinardi, Denise D. Montzka, Dirk Richter, Jason R. Schroeder, Meghan Stell, David Tanner, James Walega, Peter Weibring, and Andrew Weinheimer
Atmos. Chem. Phys., 18, 8293–8312, https://doi.org/10.5194/acp-18-8293-2018, https://doi.org/10.5194/acp-18-8293-2018, 2018
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We measured organic aerosol (OA) and relevant trace gases during FRAPPÉ in the Colorado Front Range, with the goal of characterizing summertime OA formation. Our results indicate a significant production of secondary OA (SOA) in this region. About 2 μg m−3 of OA was present at background CO levels, suggesting contribution of non-combustion sources to SOA. Contribution of oil- and gas-related activities to anthropogenic SOA was modeled to be ~38 %. Biogenic SOA contributed to >40 % of OA.
Catalina Tsai, Max Spolaor, Santo Fedele Colosimo, Olga Pikelnaya, Ross Cheung, Eric Williams, Jessica B. Gilman, Brian M. Lerner, Robert J. Zamora, Carsten Warneke, James M. Roberts, Ravan Ahmadov, Joost de Gouw, Timothy Bates, Patricia K. Quinn, and Jochen Stutz
Atmos. Chem. Phys., 18, 1977–1996, https://doi.org/10.5194/acp-18-1977-2018, https://doi.org/10.5194/acp-18-1977-2018, 2018
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Nitrous acid (HONO) photolysis is an important source of hydroxyl radicals (OH). Vertical HONO fluxes, observed in the snow-free, wintertime Uintah Basin, Utah, USA, show that chemical formation of HONO on the ground closes the HONO budget. Under high NOx conditions, HONO formation is most likely due to photo-enhanced conversion of NO2 on the ground. Under moderate to low NO2 conditions, photolysis of HNO3 on the ground seems to be the most likely source of HONO.
Katherine M. Manfred, Rebecca A. Washenfelder, Nicholas L. Wagner, Gabriela Adler, Frank Erdesz, Caroline C. Womack, Kara D. Lamb, Joshua P. Schwarz, Alessandro Franchin, Vanessa Selimovic, Robert J. Yokelson, and Daniel M. Murphy
Atmos. Chem. Phys., 18, 1879–1894, https://doi.org/10.5194/acp-18-1879-2018, https://doi.org/10.5194/acp-18-1879-2018, 2018
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In this study, we use a new laser imaging nephelometer to measure the bulk aerosol scattering phase function for biomass burning aerosol from controlled fires. By comparing measurements to models for spherical and fractal particles, we demonstrate that the dominant morphology varies by fuel type. This instrument has unique capabilities to directly measure how morphology affects optical properties, and can be used in the future for important validations of remote sensing retrievals.
Jin Liao, Charles A. Brock, Daniel M. Murphy, Donna T. Sueper, André Welti, and Ann M. Middlebrook
Atmos. Meas. Tech., 10, 3801–3820, https://doi.org/10.5194/amt-10-3801-2017, https://doi.org/10.5194/amt-10-3801-2017, 2017
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The Aerodyne aerosol mass spectrometer (AMS) has emerged as a widely used method for measuring the real-time, submicron, nonrefractory aerosol composition. A large uncertainty in accurate measurements with the AMS (the collection efficiency due to particle bounce) is evaluated in this paper using in situ measurements of particle light scattering. Current calculations of the collection efficiency reasonably predict this effect in acidic environments, resulting in more confidence for AMS results.
Li Zhang, Qinyi Li, Tao Wang, Ravan Ahmadov, Qiang Zhang, Meng Li, and Mengyao Lv
Atmos. Chem. Phys., 17, 9733–9750, https://doi.org/10.5194/acp-17-9733-2017, https://doi.org/10.5194/acp-17-9733-2017, 2017
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Little is known of the integrated impacts of HONO and ClNO2 on lower-tropospheric ozone so far. In this study, we updated WRF-Chem with the CBMZ_ReNOM module, which considers both the sources and chemistry of HONO and ClNO2. The revised model revealed that the two reactive nitrogen compounds significantly affected the oxidation capacity and ozone formation at the surface and within the lower troposphere over polluted regions and noticeably improved summertime O3 predictions over China.
Maria A. Zawadowicz, Karl D. Froyd, Daniel M. Murphy, and Daniel J. Cziczo
Atmos. Chem. Phys., 17, 7193–7212, https://doi.org/10.5194/acp-17-7193-2017, https://doi.org/10.5194/acp-17-7193-2017, 2017
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This paper reports the results of laboratory and field measurements of primary biological aerosol particles using single-particle mass spectrometry (SPMS). Identification of biological particles using SPMS can be challenging, as their mass spectra can present features similar to phosphorus-containing minerals and combustion by-products. Using a large database of laboratory measurements, a criterion for the identification of biological particles has been developed.
Hongyu Guo, Jiumeng Liu, Karl D. Froyd, James M. Roberts, Patrick R. Veres, Patrick L. Hayes, Jose L. Jimenez, Athanasios Nenes, and Rodney J. Weber
Atmos. Chem. Phys., 17, 5703–5719, https://doi.org/10.5194/acp-17-5703-2017, https://doi.org/10.5194/acp-17-5703-2017, 2017
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Fine particle pH is linked to many environmental impacts by affecting particle concentration and composition. Predicted Pasadena, CA (CalNex campaign), PM1 pH is 1.9 and PM2.5 pH 2.7, the latter higher due to sea salts. The model predicted gas–particle partitionings of HNO3–NO3−, NH3–NH4+, and HCl–Cl− are in good agreement, verifying the model predictions. A summary of contrasting locations in the US and eastern Mediterranean shows fine particles are generally highly acidic, with pH below 3.
Qinyi Li, Li Zhang, Tao Wang, Yee Jun Tham, Ravan Ahmadov, Likun Xue, Qiang Zhang, and Junyu Zheng
Atmos. Chem. Phys., 16, 14875–14890, https://doi.org/10.5194/acp-16-14875-2016, https://doi.org/10.5194/acp-16-14875-2016, 2016
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The regional distributions and impacts of N2O5 and ClNO2 remain poorly understood. To address the problem, we developed a chemical transport model further and conducted the first high-resolution simulation of the distributions of the two species. Our research demonstrated the significant impacts of the two gases on the lifetime of nitrogen oxides, secondary nitrate production and ozone formation in southern China and highlighted the necessity of considering this chemistry in air quality models.
Sha Feng, Thomas Lauvaux, Sally Newman, Preeti Rao, Ravan Ahmadov, Aijun Deng, Liza I. Díaz-Isaac, Riley M. Duren, Marc L. Fischer, Christoph Gerbig, Kevin R. Gurney, Jianhua Huang, Seongeun Jeong, Zhijin Li, Charles E. Miller, Darragh O'Keeffe, Risa Patarasuk, Stanley P. Sander, Yang Song, Kam W. Wong, and Yuk L. Yung
Atmos. Chem. Phys., 16, 9019–9045, https://doi.org/10.5194/acp-16-9019-2016, https://doi.org/10.5194/acp-16-9019-2016, 2016
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We developed a high-resolution land–atmosphere modelling system for urban CO2 emissions over the LA Basin. We evaluated various model configurations, FFCO2 products, and the impact of the model resolution. FFCO2 emissions outpace the atmospheric model resolution to represent the CO2 concentration variability across the basin. A novel forward model approach is presented to evaluate the surface measurement network, reinforcing the importance of using high-resolution emission products.
Carsten Warneke, Michael Trainer, Joost A. de Gouw, David D. Parrish, David W. Fahey, A. R. Ravishankara, Ann M. Middlebrook, Charles A. Brock, James M. Roberts, Steven S. Brown, Jonathan A. Neuman, Brian M. Lerner, Daniel Lack, Daniel Law, Gerhard Hübler, Iliana Pollack, Steven Sjostedt, Thomas B. Ryerson, Jessica B. Gilman, Jin Liao, John Holloway, Jeff Peischl, John B. Nowak, Kenneth C. Aikin, Kyung-Eun Min, Rebecca A. Washenfelder, Martin G. Graus, Mathew Richardson, Milos Z. Markovic, Nick L. Wagner, André Welti, Patrick R. Veres, Peter Edwards, Joshua P. Schwarz, Timothy Gordon, William P. Dube, Stuart A. McKeen, Jerome Brioude, Ravan Ahmadov, Aikaterini Bougiatioti, Jack J. Lin, Athanasios Nenes, Glenn M. Wolfe, Thomas F. Hanisco, Ben H. Lee, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Frank N. Keutsch, Jennifer Kaiser, Jingqiu Mao, and Courtney D. Hatch
Atmos. Meas. Tech., 9, 3063–3093, https://doi.org/10.5194/amt-9-3063-2016, https://doi.org/10.5194/amt-9-3063-2016, 2016
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In this paper we describe the experimental approach, the science goals and early results of the NOAA SENEX campaign, which was focused on studying the interactions between biogenic and anthropogenic emissions to form secondary pollutants.
During SENEX, the NOAA WP-3D aircraft conducted 20 research flights between 27 May and 10 July 2013 based out of Smyrna, TN. The SENEX flights included day- and nighttime flights in the Southeast as well as flights over areas with intense shale gas extraction.
Charles A. Brock, Nicholas L. Wagner, Bruce E. Anderson, Alexis R. Attwood, Andreas Beyersdorf, Pedro Campuzano-Jost, Annmarie G. Carlton, Douglas A. Day, Glenn S. Diskin, Timothy D. Gordon, Jose L. Jimenez, Daniel A. Lack, Jin Liao, Milos Z. Markovic, Ann M. Middlebrook, Nga L. Ng, Anne E. Perring, Matthews S. Richardson, Joshua P. Schwarz, Rebecca A. Washenfelder, Andre Welti, Lu Xu, Luke D. Ziemba, and Daniel M. Murphy
Atmos. Chem. Phys., 16, 4987–5007, https://doi.org/10.5194/acp-16-4987-2016, https://doi.org/10.5194/acp-16-4987-2016, 2016
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Microscopic pollution particles make the atmosphere look hazy and also cool the earth by sending sunlight back to space. When the air is moist, these particles swell with water and scatter even more sunlight. We showed that particles formed from organic material – which dominates particulate pollution in the southeastern U.S. – does not take up water very effectively, toward the low end of most previous studies. We also found a better way to mathematically describe this swelling process.
Charles A. Brock, Nicholas L. Wagner, Bruce E. Anderson, Andreas Beyersdorf, Pedro Campuzano-Jost, Douglas A. Day, Glenn S. Diskin, Timothy D. Gordon, Jose L. Jimenez, Daniel A. Lack, Jin Liao, Milos Z. Markovic, Ann M. Middlebrook, Anne E. Perring, Matthews S. Richardson, Joshua P. Schwarz, Andre Welti, Luke D. Ziemba, and Daniel M. Murphy
Atmos. Chem. Phys., 16, 5009–5019, https://doi.org/10.5194/acp-16-5009-2016, https://doi.org/10.5194/acp-16-5009-2016, 2016
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Two research aircraft made dozens of vertical profiles over rural areas in the southeastern US in summer 2013. These measurements show that, in addition to how much pollution was present and how moist the atmosphere was, the size of the pollutant particles affected how much sunlight was reflected back to space. These measurements will help climate modelers determine which characteristics of pollution are important to predict with accuracy.
E. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618, https://doi.org/10.5194/acp-16-1603-2016, https://doi.org/10.5194/acp-16-1603-2016, 2016
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Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
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.
P. Tuccella, G. Curci, G. A. Grell, G. Visconti, S. Crumeyrolle, A. Schwarzenboeck, and A. A. Mensah
Geosci. Model Dev., 8, 2749–2776, https://doi.org/10.5194/gmd-8-2749-2015, https://doi.org/10.5194/gmd-8-2749-2015, 2015
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A parameterization for secondary organic aerosol (SOA) production based on the volatility basis set (VBS) approach has been coupled with microphysics and radiative schemes in the WRF-Chem model. The new chemistry was evaluated on a cloud-resolving scale against ground-based and aircraft measurements collected during the IMPACT-EUCAARI campaign, and complemented with satellite data from MODIS. Sensitivity tests have been performed to study the impact of SOA on cloud prediction and development.
N. L. Wagner, C. A. Brock, W. M. Angevine, A. Beyersdorf, P. Campuzano-Jost, D. Day, J. A. de Gouw, G. S. Diskin, T. D. Gordon, M. G. Graus, J. S. Holloway, G. Huey, J. L. Jimenez, D. A. Lack, J. Liao, X. Liu, M. Z. Markovic, A. M. Middlebrook, T. Mikoviny, J. Peischl, A. E. Perring, M. S. Richardson, T. B. Ryerson, J. P. Schwarz, C. Warneke, A. Welti, A. Wisthaler, L. D. Ziemba, and D. M. Murphy
Atmos. Chem. Phys., 15, 7085–7102, https://doi.org/10.5194/acp-15-7085-2015, https://doi.org/10.5194/acp-15-7085-2015, 2015
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This paper investigates the summertime vertical profile of aerosol over the southeastern US using in situ measurements collected from aircraft. We use a vertical mixing model and measurements of CO to predict the vertical profile of aerosol that we would expect from vertical mixing alone and compare with the observed aerosol profile. We found a modest enhancement of aerosol in the cloudy transition layer during shallow cumulus convection and attribute the enhancement to local aerosol formation.
P. L. Hayes, A. G. Carlton, K. R. Baker, R. Ahmadov, R. A. Washenfelder, S. Alvarez, B. Rappenglück, J. B. Gilman, W. C. Kuster, J. A. de Gouw, P. Zotter, A. S. H. Prévôt, S. Szidat, T. E. Kleindienst, J. H. Offenberg, P. K. Ma, and J. L. Jimenez
Atmos. Chem. Phys., 15, 5773–5801, https://doi.org/10.5194/acp-15-5773-2015, https://doi.org/10.5194/acp-15-5773-2015, 2015
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(1) Four different parameterizations for the formation and chemical evolution of secondary organic aerosol (SOA) are evaluated using a box model representing the Los Angeles region during the CalNex campaign.
(2) The SOA formed only from the oxidation of VOCs is insufficient to explain the observed SOA concentrations.
(3) The amount of SOA mass formed from diesel vehicle emissions is estimated to be 16-27%.
(4) Modeled SOA depends strongly on the P-S/IVOC volatility distribution.
M. Bocquet, H. Elbern, H. Eskes, M. Hirtl, R. Žabkar, G. R. Carmichael, J. Flemming, A. Inness, M. Pagowski, J. L. Pérez Camaño, P. E. Saide, R. San Jose, M. Sofiev, J. Vira, A. Baklanov, C. Carnevale, G. Grell, and C. Seigneur
Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, https://doi.org/10.5194/acp-15-5325-2015, 2015
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Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of concentrations, and perform inverse modeling. Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. We review here the current status of data assimilation in atmospheric chemistry models, with a particular focus on future prospects for data assimilation in CCMM.
R. Ahmadov, S. McKeen, M. Trainer, R. Banta, A. Brewer, S. Brown, P. M. Edwards, J. A. de Gouw, G. J. Frost, J. Gilman, D. Helmig, B. Johnson, A. Karion, A. Koss, A. Langford, B. Lerner, J. Olson, S. Oltmans, J. Peischl, G. Pétron, Y. Pichugina, J. M. Roberts, T. Ryerson, R. Schnell, C. Senff, C. Sweeney, C. Thompson, P. R. Veres, C. Warneke, R. Wild, E. J. Williams, B. Yuan, and R. Zamora
Atmos. Chem. Phys., 15, 411–429, https://doi.org/10.5194/acp-15-411-2015, https://doi.org/10.5194/acp-15-411-2015, 2015
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High 2013 wintertime O3 pollution events associated with oil/gas production within the Uinta Basin are studied using a 3D model. It's able quantitatively to reproduce these events using emission estimates of O3 precursors based on ambient measurements (top-down approach), but unable to reproduce them using a recent bottom-up emission inventory for the oil/gas industry. The role of various physical and meteorological processes, chemical species and pathways contributing to high O3 are quantified.
D. M. Murphy
Atmos. Chem. Phys., 14, 13013–13022, https://doi.org/10.5194/acp-14-13013-2014, https://doi.org/10.5194/acp-14-13013-2014, 2014
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The properties of cirrus clouds depend on the rate at which air cools as the cloud forms. Small-scale motions in the atmosphere have high rates of cooling. This usually leads to very small ice crystals. However, a few random cooling fluctuations will produce only a few ice crystals. This paper shows that these events are important even if they are rare: they lead to particles that sediment and influence a lot of air. The results show dehydration is less sensitive to details of ice nucleation.
M. Pagowski, Z. Liu, G. A. Grell, M. Hu, H.-C. Lin, and C. S. Schwartz
Geosci. Model Dev., 7, 1621–1627, https://doi.org/10.5194/gmd-7-1621-2014, https://doi.org/10.5194/gmd-7-1621-2014, 2014
G. A. Grell and S. R. Freitas
Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014, https://doi.org/10.5194/acp-14-5233-2014, 2014
A. Baklanov, K. Schlünzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. S. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang
Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, https://doi.org/10.5194/acp-14-317-2014, 2014
A. F. dos Santos, S. R. Freitas, J. G. Z. de Mattos, H. F. de Campos Velho, M. A. Gan, E. F. P. da Luz, and G. A. Grell
Adv. Geosci., 35, 123–136, https://doi.org/10.5194/adgeo-35-123-2013, https://doi.org/10.5194/adgeo-35-123-2013, 2013
M. Stuefer, S. R. Freitas, G. Grell, P. Webley, S. Peckham, S. A. McKeen, and S. D. Egan
Geosci. Model Dev., 6, 457–468, https://doi.org/10.5194/gmd-6-457-2013, https://doi.org/10.5194/gmd-6-457-2013, 2013
J. Brioude, W. M. Angevine, R. Ahmadov, S.-W. Kim, S. Evan, S. A. McKeen, E.-Y. Hsie, G. J. Frost, J. A. Neuman, I. B. Pollack, J. Peischl, T. B. Ryerson, J. Holloway, S. S. Brown, J. B. Nowak, J. M. Roberts, S. C. Wofsy, G. W. Santoni, T. Oda, and M. Trainer
Atmos. Chem. Phys., 13, 3661–3677, https://doi.org/10.5194/acp-13-3661-2013, https://doi.org/10.5194/acp-13-3661-2013, 2013
Related subject area
Atmospheric sciences
A lumped species approach for the simulation of secondary organic aerosol production from intermediate-volatility organic compounds (IVOCs): application to road transport in PMCAMx-iv (v1.0)
TrackMatcher – a tool for finding intercepts in tracks of geographical positions
Recovery of sparse urban greenhouse gas emissions
Tropospheric transport and unresolved convection: numerical experiments with CLaMS 2.0/MESSy
MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling
A preliminary evaluation of FY-4A visible radiance data assimilation by the WRF (ARW v4.1.1)/DART (Manhattan release v9.8.0)-RTTOV (v12.3) system for a tropical storm case
Repeatable high-resolution statistical downscaling through deep learning
Atmospherically Relevant Chemistry and Aerosol box model – ARCA box (version 1.2)
MultilayerPy (v1.0): a Python-based framework for building, running and optimising kinetic multi-layer models of aerosols and films
Introduction of the DISAMAR radiative transfer model: determining instrument specifications and analysing methods for atmospheric retrieval (version 4.1.5)
Assessment of the data assimilation framework for the Rapid Refresh Forecast System v0.1 and impacts on forecasts of a convective storm case study
Downscaling atmospheric chemistry simulations with physically consistent deep learning
A machine learning methodology for the generation of a parameterization of the hydroxyl radical
Large-eddy simulations with ClimateMachine v0.2.0: a new open-source code for atmospheric simulations on GPUs and CPUs
Hybrid ensemble-variational data assimilation in ABC-DA within a tropical framework
OpenIFS/AC: atmospheric chemistry and aerosol in OpenIFS 43r3
Simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations during haze episodes
A daily highest air temperature estimation method and spatial–temporal changes analysis of high temperature in China from 1979 to 2018
TransClim (v1.0): a chemistry–climate response model for assessing the effect of mitigation strategies for road traffic on ozone
A description of the first open-source community release of MISTRA-v9.0: a 0D/1D atmospheric boundary layer chemistry model
Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations
Development of an LSTM-Broadcasting deep-learning framework for regional air pollution forecast improvement
Computationally efficient methods for large-scale atmospheric inverse modeling
Improving the joint estimation of CO2 and surface carbon fluxes using a constrained ensemble Kalman filter in COLA (v1.0)
RAP-Net: Region Attention Predictive Network for precipitation nowcasting
Effects of point source emission heights in WRF–STILT: a step towards exploiting nocturnal observations in models
uDALES 1.0: a large-eddy simulation model for urban environments
Development and evaluation of the Aerosol Forecast Member in the National Center for Environment Prediction (NCEP)'s Global Ensemble Forecast System (GEFS-Aerosols v1)
Assimilation of GPM-retrieved ocean surface meteorology data for two snowstorm events during ICE-POP 2018
A multi-pollutant and multi-sectorial approach to screening the consistency of emission inventories
Evaluation of a forest parameterization to improve boundary layer flow simulations over complex terrain. A case study using WRF-LES V4.0.1
Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China
Data Assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation
Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): a protocol for investigating the role of stratospheric polar vortex disturbances in subseasonal to seasonal forecasts
Lightning Assimilation in the Weather Research and Forecasting (WRF) Model Version 4.1.1: Technique Updates and Assessment of the Applications from Regional to Hemispheric Scales
The Mission Support System (MSS v7.0.0) and its use in planning for the SouthTRAC aircraft campaign
Variational inverse modeling within the Community Inversion Framework v1.1 to assimilate δ13C(CH4) and CH4: a case study with model LMDz-SACS
The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model
Validation of turbulent heat transfer models against eddy covariance flux measurements over a seasonally ice-covered lake
Regional evaluation of the performance of the global CAMS chemical modeling system over the United States (IFS cycle 47r1)
A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions
Order of magnitude wall time improvement of variational methane inversions by physical parallelization: a demonstration using TM5-4DVAR
Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in the Weather Research and Forecasting (v4.1.3) model during the ICE-POP 2018 field campaign
A novel method for objective identification of 3-D potential vorticity anomalies
Evaluation of the NAQFC Driven by the NOAA Global Forecast System Version 16: Comparison with the WRF-CMAQ Downscaling Method During the Summer 2019 FIREX-AQ Campaign
Multiple same-level and telescoping nesting in GFDL's dynamical core
A Local Particle Filter and Its Gaussian Mixture Extension Implemented with Minor Modifications to the LETKF
Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties
Assessing the roles emission sources and atmospheric processes play in simulating δ15N of atmospheric NOx and NO3− using CMAQ (version 5.2.1) and SMOKE (version 4.6)
The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at kilometre scale
Stella E. I. Manavi and Spyros N. Pandis
Geosci. Model Dev., 15, 7731–7749, https://doi.org/10.5194/gmd-15-7731-2022, https://doi.org/10.5194/gmd-15-7731-2022, 2022
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The paper describes the first step towards the development of a simulation framework for the chemistry and secondary organic aerosol production of intermediate-volatility organic compounds (IVOCs). These compounds can be a significant source of organic particulate matter. Our approach treats IVOCs as lumped compounds that retain their chemical characteristics. Estimated IVOC emissions from road transport were a factor of 8 higher than emissions used in previous applications.
Peter Bräuer and Matthias Tesche
Geosci. Model Dev., 15, 7557–7572, https://doi.org/10.5194/gmd-15-7557-2022, https://doi.org/10.5194/gmd-15-7557-2022, 2022
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This paper presents a tool for (i) finding temporally and spatially resolved intersections between two- or three-dimensional geographical tracks (trajectories) and (ii) extracting of data in the vicinity of intersections to achieve the optimal combination of various data sets.
Benjamin Zanger, Jia Chen, Man Sun, and Florian Dietrich
Geosci. Model Dev., 15, 7533–7556, https://doi.org/10.5194/gmd-15-7533-2022, https://doi.org/10.5194/gmd-15-7533-2022, 2022
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Gaussian priors (GPs) used in least squares inversion do not reflect the true distributions of greenhouse gas emissions well. A method that does not rely on GPs is sparse reconstruction (SR). We show that necessary conditions for SR are satisfied for cities and that the application of a wavelet transform can further enhance sparsity. We apply the theory of compressed sensing to SR. Our results show that SR needs fewer measurements and is superior for assessing unknown emitters compared to GPs.
Paul Konopka, Mengchu Tao, Marc von Hobe, Lars Hoffmann, Corinna Kloss, Fabrizio Ravegnani, C. Michael Volk, Valentin Lauther, Andreas Zahn, Peter Hoor, and Felix Ploeger
Geosci. Model Dev., 15, 7471–7487, https://doi.org/10.5194/gmd-15-7471-2022, https://doi.org/10.5194/gmd-15-7471-2022, 2022
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Pure trajectory-based transport models driven by meteorology derived from reanalysis products (ERA5) take into account only the resolved, advective part of transport. That means neither mixing processes nor unresolved subgrid-scale advective processes like convection are included. The Chemical Lagrangian Model of the Stratosphere (CLaMS) includes these processes. We show that isentropic mixing dominates unresolved transport. The second most important transport process is unresolved convection.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Yongbo Zhou, Yubao Liu, Zhaoyang Huo, and Yang Li
Geosci. Model Dev., 15, 7397–7420, https://doi.org/10.5194/gmd-15-7397-2022, https://doi.org/10.5194/gmd-15-7397-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Dánnell Quesada-Chacón, Klemens Barfus, and Christian Bernhofer
Geosci. Model Dev., 15, 7353–7370, https://doi.org/10.5194/gmd-15-7353-2022, https://doi.org/10.5194/gmd-15-7353-2022, 2022
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We improved the performance of past perfect prognosis statistical downscaling methods while achieving full model repeatability with GPU-calculated deep learning models using the TensorFlow, climate4R, and VALUE frameworks. We employed the ERA5 reanalysis as predictors and ReKIS (eastern Ore Mountains, Germany, 1 km resolution) as precipitation predictand, while incorporating modern deep learning architectures. The achieved repeatability is key to accomplish further milestones with deep learning.
Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Putian Zhou, Tinja Olenius, Pontus Roldin, and Michael Boy
Geosci. Model Dev., 15, 7257–7286, https://doi.org/10.5194/gmd-15-7257-2022, https://doi.org/10.5194/gmd-15-7257-2022, 2022
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Atmospheric chemistry and aerosol processes form a dynamic and sensitively balanced system, and solving problems regarding air quality or climate requires detailed modelling and coupling of the processes. The models involved are often very complex to use. We have addressed this problem with the new ARCA box model. It puts much of the current knowledge of the nano- and microscale aerosol dynamics and chemistry into usable software and has the potential to become a valuable tool in the community.
Adam Milsom, Amy Lees, Adam M. Squires, and Christian Pfrang
Geosci. Model Dev., 15, 7139–7151, https://doi.org/10.5194/gmd-15-7139-2022, https://doi.org/10.5194/gmd-15-7139-2022, 2022
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MultilayerPy is a Python-based framework facilitating the creation, running and optimisation of state-of-the-art kinetic multi-layer models of aerosol and film processes. Models can be fit to data with local and global optimisation algorithms along with a statistical sampling algorithm, which quantifies the uncertainty in optimised model parameters. This “modelling study in a box” enables more reproducible and reliable results, with model code and outputs produced in a human-readable way.
Johan F. de Haan, Ping Wang, Maarten Sneep, J. Pepijn Veefkind, and Piet Stammes
Geosci. Model Dev., 15, 7031–7050, https://doi.org/10.5194/gmd-15-7031-2022, https://doi.org/10.5194/gmd-15-7031-2022, 2022
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We present an overview of the DISAMAR radiative transfer code, highlighting the novel semi-analytical derivatives for the doubling–adding formulae and the new DISMAS technique for weak absorbers. DISAMAR includes forward simulations and retrievals for satellite spectral measurements from 270 to 2400 nm to determine instrument specifications for passive remote sensing. It has been used in various Sentinel-4/5P/5 projects and in the TROPOMI aerosol layer height and ozone profile products.
Ivette H. Banos, Will D. Mayfield, Guoqing Ge, Luiz F. Sapucci, Jacob R. Carley, and Louisa Nance
Geosci. Model Dev., 15, 6891–6917, https://doi.org/10.5194/gmd-15-6891-2022, https://doi.org/10.5194/gmd-15-6891-2022, 2022
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A prototype data assimilation system for NOAA’s next-generation rapidly updated, convection-allowing forecast system, or Rapid Refresh Forecast System (RRFS) v0.1, is tested and evaluated. The impact of using data assimilation with a convective storm case study is examined. Although the convection in RRFS tends to be overestimated in intensity and underestimated in extent, the use of data assimilation proves to be crucial to improve short-term forecasts of storms and precipitation.
Andrew Geiss, Sam J. Silva, and Joseph C. Hardin
Geosci. Model Dev., 15, 6677–6694, https://doi.org/10.5194/gmd-15-6677-2022, https://doi.org/10.5194/gmd-15-6677-2022, 2022
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This work demonstrates the use of modern machine learning techniques to enhance the resolution of atmospheric chemistry simulations. We evaluate the schemes for an 8 x 10 increase in resolution and find that they perform substantially better than conventional methods. Methods are introduced to target machine learning methods towards this type of problem, most notably by ensuring they do not break known physical constraints.
Daniel C. Anderson, Melanie B. Follette-Cook, Sarah A. Strode, Julie M. Nicely, Junhua Liu, Peter D. Ivatt, and Bryan N. Duncan
Geosci. Model Dev., 15, 6341–6358, https://doi.org/10.5194/gmd-15-6341-2022, https://doi.org/10.5194/gmd-15-6341-2022, 2022
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The hydroxyl radical (OH) is the most important chemical in the atmosphere for removing certain pollutants, including methane, the second-most-important greenhouse gas. We present a methodology to create an easily modifiable parameterization that can calculate OH concentrations in a computationally efficient way. The parameterization, which predicts OH within 5 %, can be integrated into larger climate models to allow for calculation of the interactions between OH, methane, and other chemicals.
Akshay Sridhar, Yassine Tissaoui, Simone Marras, Zhaoyi Shen, Charles Kawczynski, Simon Byrne, Kiran Pamnany, Maciej Waruszewski, Thomas H. Gibson, Jeremy E. Kozdon, Valentin Churavy, Lucas C. Wilcox, Francis X. Giraldo, and Tapio Schneider
Geosci. Model Dev., 15, 6259–6284, https://doi.org/10.5194/gmd-15-6259-2022, https://doi.org/10.5194/gmd-15-6259-2022, 2022
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ClimateMachine is a new open-source Julia-language atmospheric modeling code. We describe its limited-area configuration and the model equations, and we demonstrate applicability through benchmark problems, including atmospheric flow in the shallow cumulus regime. We show that the discontinuous Galerkin numerics and model equations allow global conservation of key variables (up to sources and sinks). We assess CPU strong scaling and GPU weak scaling to show its suitability for large simulations.
Joshua Chun Kwang Lee, Javier Amezcua, and Ross Noel Bannister
Geosci. Model Dev., 15, 6197–6219, https://doi.org/10.5194/gmd-15-6197-2022, https://doi.org/10.5194/gmd-15-6197-2022, 2022
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In this article, we implement a novel data assimilation method for the ABC–DA system which combines traditional data assimilation approaches in a hybrid approach. We document the technical development and test the hybrid approach in idealised experiments within a tropical framework of the ABC–DA system. Our findings indicate that the hybrid approach outperforms individual traditional approaches. Its potential benefits have been highlighted and should be explored further within this framework.
Vincent Huijnen, Philippe Le Sager, Marcus O. Köhler, Glenn Carver, Samuel Rémy, Johannes Flemming, Simon Chabrillat, Quentin Errera, and Twan van Noije
Geosci. Model Dev., 15, 6221–6241, https://doi.org/10.5194/gmd-15-6221-2022, https://doi.org/10.5194/gmd-15-6221-2022, 2022
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We report on the first implementation of atmospheric chemistry and aerosol as part of the OpenIFS model, based on the CAMS global model. We give an overview of the model and evaluate two reference model configurations, with and without the stratospheric chemistry extension, against a variety of observational datasets. This OpenIFS version with atmospheric composition components is open to the scientific user community under a standard OpenIFS license.
Xueyin Ruan, Chun Zhao, Rahul A. Zaveri, Pengzhen He, Xinming Wang, Jingyuan Shao, and Lei Geng
Geosci. Model Dev., 15, 6143–6164, https://doi.org/10.5194/gmd-15-6143-2022, https://doi.org/10.5194/gmd-15-6143-2022, 2022
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Accurate prediction of aerosol pH in chemical transport models is essential to aerosol modeling. This study examines the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) on aerosol pH predictions and the sensitivities to emissions of nonvolatile cations and NH3, aerosol-phase state assumption, and heterogeneous sulfate production. Temporal evolution of aerosol pH during haze cycles in Beijing and the driving factors are also presented and discussed.
Ping Wang, Kebiao Mao, Fei Meng, Zhihao Qin, Shu Fang, and Sayed M. Bateni
Geosci. Model Dev., 15, 6059–6083, https://doi.org/10.5194/gmd-15-6059-2022, https://doi.org/10.5194/gmd-15-6059-2022, 2022
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In order to obtain the key parameters of high-temperature spatial–temporal variation analysis, this study proposed a daily highest air temperature (Tmax) estimation frame to build a Tmax dataset in China from 1979 to 2018. We found that the annual and seasonal mean Tmax in most areas of China showed an increasing trend. The abnormal temperature changes mainly occurred in El Nin~o years or La Nin~a years. IOBW had a stronger influence on China's warming events than other factors.
Vanessa Simone Rieger and Volker Grewe
Geosci. Model Dev., 15, 5883–5903, https://doi.org/10.5194/gmd-15-5883-2022, https://doi.org/10.5194/gmd-15-5883-2022, 2022
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Road traffic emissions of nitrogen oxides, volatile organic compounds and carbon monoxide produce ozone in the troposphere and thus influence Earth's climate. To assess the ozone response to a broad range of mitigation strategies for road traffic, we developed a new chemistry–climate response model called TransClim. It is based on lookup tables containing climate–response relations and thus is able to quickly determine the climate response of a mitigation option.
Josué Bock, Jan Kaiser, Max Thomas, Andreas Bott, and Roland von Glasow
Geosci. Model Dev., 15, 5807–5828, https://doi.org/10.5194/gmd-15-5807-2022, https://doi.org/10.5194/gmd-15-5807-2022, 2022
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MISTRA-v9.0 is an atmospheric boundary layer chemistry model. The model includes a detailed particle description with regards to the microphysics, gas–particle interactions, and liquid phase chemistry within particles. Version 9.0 is the first release of MISTRA as an open-source community model. This paper presents a thorough description of the model characteristics and components. We show some examples of simulations reproducing previous studies with MISTRA with good consistency.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
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Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Haochen Sun, Jimmy C. H. Fung, Yiang Chen, Zhenning Li, Dehao Yuan, Wanying Chen, and Xingcheng Lu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-164, https://doi.org/10.5194/gmd-2022-164, 2022
Revised manuscript accepted for GMD
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This study developed a novel deep-learning layer, the broadcasting layer, to build an end-to-end LSTM based deep-learning model for regional air pollution forecast. By combining the ground observation, WRF-CMAQ simulation, and the Broadcasting-LSTM deep-learning model, forecast accuracy has been significantly improved when compared to other methods. The broadcasting layer and its variants can also be applied in other research areas to supersede the traditional numerical interpolation methods.
Taewon Cho, Julianne Chung, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 15, 5547–5565, https://doi.org/10.5194/gmd-15-5547-2022, https://doi.org/10.5194/gmd-15-5547-2022, 2022
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Atmospheric inverse modeling describes the process of estimating greenhouse gas fluxes or air pollution emissions at the Earth's surface using observations of these gases collected in the atmosphere. The launch of new satellites, the expansion of surface observation networks, and a desire for more detailed maps of surface fluxes have yielded numerous computational and statistical challenges. This article describes computationally efficient methods for large-scale atmospheric inverse modeling.
Zhiqiang Liu, Ning Zeng, Yun Liu, Eugenia Kalnay, Ghassem Asrar, Bo Wu, Qixiang Cai, Di Liu, and Pengfei Han
Geosci. Model Dev., 15, 5511–5528, https://doi.org/10.5194/gmd-15-5511-2022, https://doi.org/10.5194/gmd-15-5511-2022, 2022
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We described the application of a constrained ensemble Kalman filter (CEnKF) in a joint CO2 and surface carbon fluxes estimation study. By assimilating the pseudo-surface and OCO-2 observations, the annual global flux estimation is significantly biased without mass conservation. With the additional CEnKF process, the CO2 mass is strictly constrained, and the estimation of annual fluxes is significantly improved.
Zheng Zhang, Chuyao Luo, Shanshan Feng, Rui Ye, Yunming Ye, and Xutao Li
Geosci. Model Dev., 15, 5407–5419, https://doi.org/10.5194/gmd-15-5407-2022, https://doi.org/10.5194/gmd-15-5407-2022, 2022
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In this paper, we develop a model to predict radar echo sequences and apply it in the precipitation nowcasting field. Different from existing models, we propose two new attention modules. By introducing them, the performance of RAP-Net outperforms other models, especially in those regions with moderate and heavy rainfall. Considering that these regions cause more threats to human activities, the research in our work is significant for preventing natural disasters caused by heavy rainfall.
Fabian Maier, Christoph Gerbig, Ingeborg Levin, Ingrid Super, Julia Marshall, and Samuel Hammer
Geosci. Model Dev., 15, 5391–5406, https://doi.org/10.5194/gmd-15-5391-2022, https://doi.org/10.5194/gmd-15-5391-2022, 2022
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We show that the default representation of point source emissions in WRF–STILT leads to large overestimations when modelling fossil fuel CO2 concentrations for a 30 m high observation site during stable atmospheric conditions. We therefore introduce a novel point source modelling approach in WRF-STILT that takes into account their effective emission heights and results in a much better agreement with observations.
Ivo Suter, Tom Grylls, Birgit S. Sützl, Sam O. Owens, Chris E. Wilson, and Maarten van Reeuwijk
Geosci. Model Dev., 15, 5309–5335, https://doi.org/10.5194/gmd-15-5309-2022, https://doi.org/10.5194/gmd-15-5309-2022, 2022
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Cities are increasingly moving to the fore of climate and air quality research due to their central role in the population’s health and well-being, while suitable models remain scarce. This article describes the development of a new urban LES model, which allows examining the effects of various processes, infrastructure and vegetation on the local climate and air quality. Possible applications are demonstrated and a comparison to an experiment is shown.
Li Zhang, Raffaele Montuoro, Stuart A. McKeen, Barry Baker, Partha S. Bhattacharjee, Georg A. Grell, Judy Henderson, Li Pan, Gregory J. Frost, Jeff McQueen, Rick Saylor, Haiqin Li, Ravan Ahmadov, Jun Wang, Ivanka Stajner, Shobha Kondragunta, Xiaoyang Zhang, and Fangjun Li
Geosci. Model Dev., 15, 5337–5369, https://doi.org/10.5194/gmd-15-5337-2022, https://doi.org/10.5194/gmd-15-5337-2022, 2022
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The NOAA’s air quality predictions contribute to protecting lives and health in the US, which requires sustainable development and improvement of forecast systems. GEFS-Aerosols v1 has been developed in a collaboration between the NOAA research laboratories for operational forecast since September 2020 in the NCEP. The predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational system.
Xuanli Li, Jason B. Roberts, Jayanthi Srikishen, Jonathan L. Case, Walter A. Petersen, Gyuwon Lee, and Christopher R. Hain
Geosci. Model Dev., 15, 5287–5308, https://doi.org/10.5194/gmd-15-5287-2022, https://doi.org/10.5194/gmd-15-5287-2022, 2022
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This research assimilated the Global Precipitation Measurement (GPM) satellite-retrieved ocean surface meteorology data into the Weather Research and Forecasting (WRF) model with the Gridpoint Statistical Interpolation (GSI) system. This was for two snowstorms during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games' (ICE-POP 2018) field experiments. The results indicated a positive impact of the data for short-term forecasts for heavy snowfall.
Philippe Thunis, Alain Clappier, Enrico Pisoni, Bertrand Bessagnet, Jeroen Kuenen, Marc Guevara, and Susana Lopez-Aparicio
Geosci. Model Dev., 15, 5271–5286, https://doi.org/10.5194/gmd-15-5271-2022, https://doi.org/10.5194/gmd-15-5271-2022, 2022
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In this work, we propose a screening method to improve the quality of emission inventories, which are responsible for large uncertainties in air-quality modeling. The first step of screening consists of keeping only emission contributions that are relevant enough. In a second step, the method identifies large differences that provide evidence of methodological divergence or errors. We used the approach to compare two versions of the CAMS-REG European-scale inventory over 150 European cities.
Julian Quimbayo-Duarte, Johannes Wagner, Norman Wildmann, Thomas Gerz, and Juerg Schmidli
Geosci. Model Dev., 15, 5195–5209, https://doi.org/10.5194/gmd-15-5195-2022, https://doi.org/10.5194/gmd-15-5195-2022, 2022
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The ultimate objective of this model evaluation is to improve boundary layer flow representation over complex terrain. The numerical model is tested against observations retrieved during the Perdigão 2017 field campaign (moderate complex terrain). We observed that the inclusion of a forest parameterization in the numerical model significantly improves the representation of the wind field in the atmospheric boundary layer.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-134, https://doi.org/10.5194/gmd-2022-134, 2022
Revised manuscript accepted for GMD
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This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, less training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
Zhiquan Liu, Chris Snyder, Jonathan J. Guerrette, Byoung-Joo Jung, Junmei Ban, Steven Vahl, Yali Wu, Yannick Trémolet, Thomas Auligné, Benjamin Ménétrier, Anna Shlyaeva, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-133, https://doi.org/10.5194/gmd-2022-133, 2022
Revised manuscript accepted for GMD
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JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the MPAS model, was publicly released for community use. This article describes JEDI-MPAS's implementation of ensemble-variable DA technique and demonstrates its robustness and credible performance by incrementally adding three types of microwave radiances (clear-sky AMSU-A, all-sky AMSU-A, clear-sky MHS) to a non-radiance DA experiment. We intend to periodically release new and improved versions of JEDI-MPAS in upcoming years.
Peter Hitchcock, Amy Butler, Andrew Charlton-Perez, Chaim I. Garfinkel, Tim Stockdale, James Anstey, Dann Mitchell, Daniela I. V. Domeisen, Tongwen Wu, Yixiong Lu, Daniele Mastrangelo, Piero Malguzzi, Hai Lin, Ryan Muncaster, Bill Merryfield, Michael Sigmond, Baoqiang Xiang, Liwei Jia, Yu-Kyung Hyun, Jiyoung Oh, Damien Specq, Isla R. Simpson, Jadwiga H. Richter, Cory Barton, Jeff Knight, Eun-Pa Lim, and Harry Hendon
Geosci. Model Dev., 15, 5073–5092, https://doi.org/10.5194/gmd-15-5073-2022, https://doi.org/10.5194/gmd-15-5073-2022, 2022
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This paper describes an experimental protocol focused on sudden stratospheric warmings to be carried out by subseasonal forecast modeling centers. These will allow for inter-model comparisons of these major disruptions to the stratospheric polar vortex and their impacts on the near-surface flow. The protocol will lead to new insights into the contribution of the stratosphere to subseasonal forecast skill and new approaches to the dynamical attribution of extreme events.
Daiwen Kang, Nicholas Heath, Robert Gilliam, Tanya Spero, and Jonathan Pleim
EGUsphere, https://doi.org/10.5194/egusphere-2022-348, https://doi.org/10.5194/egusphere-2022-348, 2022
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Lightning assimilation implemented in the WRF model's Kain-Fritsch convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the Kain-Fritsch scheme on simulations with and without lightning assimilation are assessed. The model's performance is improved significantly by lightning assimilation, but it is sensitive to various factors.
Reimar Bauer, Jens-Uwe Grooß, Jörn Ungermann, May Bär, Markus Geldenhuys, and Lars Hoffmann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-155, https://doi.org/10.5194/gmd-2022-155, 2022
Revised manuscript accepted for GMD
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The Mission Support System (MSS) is an open source software package that has been used for planning flight tracks of scientific aircraft in multiple measurements campaigns during the last decade. Here, we describe the MSS software and its use during the SouthTRAC measurement campaign in 2019. As example for how the MSS software is used in conjunction with many data sets, we describe the planning of a single flight probing orographic gravity waves propagating up into the lower mesosphere.
Joël Thanwerdas, Marielle Saunois, Antoine Berchet, Isabelle Pison, Bruce H. Vaughn, Sylvia Englund Michel, and Philippe Bousquet
Geosci. Model Dev., 15, 4831–4851, https://doi.org/10.5194/gmd-15-4831-2022, https://doi.org/10.5194/gmd-15-4831-2022, 2022
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Estimating CH4 sources by exploiting observations within an inverse modeling framework is a powerful approach. Here, a new system designed to assimilate δ13C(CH4) observations together with CH4 observations is presented. By optimizing both the emissions and associated source signatures of multiple emission categories, this new system can efficiently differentiate the co-located emission categories and provide estimates of CH4 sources that are consistent with isotopic data.
Bok H. Baek, Rizzieri Pedruzzi, Minwoo Park, Chi-Tsan Wang, Younha Kim, Chul-Han Song, and Jung-Hun Woo
Geosci. Model Dev., 15, 4757–4781, https://doi.org/10.5194/gmd-15-4757-2022, https://doi.org/10.5194/gmd-15-4757-2022, 2022
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The Comprehensive Automobile Research System (CARS) is an open-source Python-based automobile emissions inventory model designed to efficiently estimate high-quality emissions. The CARS is designed to utilize the local vehicle activity database, such as vehicle travel distance, road-link-level network information, and vehicle-specific average speed by road type, to generate a temporally and spatially enhanced inventory for policymakers, stakeholders, and the air quality modeling community.
Joonatan Ala-Könni, Kukka-Maaria Kohonen, Matti Leppäranta, and Ivan Mammarella
Geosci. Model Dev., 15, 4739–4755, https://doi.org/10.5194/gmd-15-4739-2022, https://doi.org/10.5194/gmd-15-4739-2022, 2022
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Properties of seasonally ice-covered lakes are not currently sufficiently included in global climate models. To fill this gap, this study evaluates three models that could be used to quantify the amount of heat that moves from and into the lake by the air above it and through evaporation of the ice cover. The results show that the complex nature of the surrounding environment as well as difficulties in accurately measuring the surface temperature of ice introduce errors to these models.
Jason E. Williams, Vincent Huijnen, Idir Bouarar, Mehdi Meziane, Timo Schreurs, Sophie Pelletier, Virginie Marécal, Beatrice Josse, and Johannes Flemming
Geosci. Model Dev., 15, 4657–4687, https://doi.org/10.5194/gmd-15-4657-2022, https://doi.org/10.5194/gmd-15-4657-2022, 2022
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The global CAMS air quality model is used for providing tropospheric ozone information to end users. This paper updates the chemical mechanism employed (CBA) and compares it against two other mechanisms (MOCAGE, MOZART) and a multi-decadal dataset based on a previous version of CBA. We perform extensive validation for the US using multiple surface and aircraft datasets, providing an assessment of biases and the extent of correlation across different seasons during 2014.
Martin Vojta, Andreas Plach, Rona L. Thompson, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2022-275, https://doi.org/10.5194/egusphere-2022-275, 2022
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In light of recent global warming, we aim to improve the methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.
Sudhanshu Pandey, Sander Houweling, and Arjo Segers
Geosci. Model Dev., 15, 4555–4567, https://doi.org/10.5194/gmd-15-4555-2022, https://doi.org/10.5194/gmd-15-4555-2022, 2022
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Inversions are used to calculate methane emissions using atmospheric mole-fraction measurements. Multidecadal inversions are needed to extract information from the long measurement records of methane. However, multidecadal inversion computations can take months to finish. Here, we demonstrate an order of magnitude improvement in wall clock time for an iterative multidecadal inversion by physical parallelization of chemical transport model.
Jeong-Su Ko, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, Gregory Thompson, and Alexis Berne
Geosci. Model Dev., 15, 4529–4553, https://doi.org/10.5194/gmd-15-4529-2022, https://doi.org/10.5194/gmd-15-4529-2022, 2022
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This study evaluates the performance of the four microphysics parameterizations, the WDM6, WDM7, Thompson, and Morrison schemes, in simulating snowfall events during the ICE-POP 2018 field campaign. Eight snowfall events are selected and classified into three categories (cold-low, warm-low, and air–sea interaction cases). The evaluation focuses on the simulated hydrometeors, microphysics budgets, wind fields, and precipitation using the measurement data.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Roderick van der Linden, Michael Maier-Gerber, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 15, 4447–4468, https://doi.org/10.5194/gmd-15-4447-2022, https://doi.org/10.5194/gmd-15-4447-2022, 2022
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Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics. For example, anomalies in the PV field near the tropopause are linked to extreme weather events. In this study, an objective strategy to identify these anomalies is presented and evaluated. As a novel concept, it can be applied to three-dimensional (3-D) data sets. Supported by 3-D visualizations, we illustrate advantages of this new analysis over existing studies along a case study.
Youhua Tang, Patrick Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2022-356, https://doi.org/10.5194/egusphere-2022-356, 2022
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This paper compared two meteorological data for driving the regional air quality model: a regional meteorological modelling using WRF (WRF-CMAQ), and the direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods have mixed performance depending on the corresponding meteorological settings and performances. The direct interpolation is a viable method to drive air quality models.
Joseph Mouallem, Lucas Harris, and Rusty Benson
Geosci. Model Dev., 15, 4355–4371, https://doi.org/10.5194/gmd-15-4355-2022, https://doi.org/10.5194/gmd-15-4355-2022, 2022
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The single-nest capability in GFDL's dynamical core, FV3, is upgraded to support multiple same-level and telescoping nests. Grid nesting adds a refined grid over an area of interest to better resolve small-scale flow features necessary to accurately predict special weather events such as severe storms and hurricanes. This work allows concurrent execution of multiple same-level and telescoping multi-level nested grids in both global and regional setups.
Shunji Kotsuki, Takemasa Miyoshi, Keiichi Kondo, and Roland Potthast
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-69, https://doi.org/10.5194/gmd-2022-69, 2022
Revised manuscript accepted for GMD
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Data assimilation plays an important role in numerical weather prediction (NWP) to combine forecasted states and millions of observations. While data assimilation methods in NWP usually assume the Gaussian error distribution, some variables in the atmosphere are known to have non-Gaussian error statistics such as precipitation. This study extended a widely used ensemble data assimilation algorithm for enabling to assimilate more observation with non-Gaussian error characteristics.
Clara Betancourt, Timo T. Stomberg, Ann-Kathrin Edrich, Ankit Patnala, Martin G. Schultz, Ribana Roscher, Julia Kowalski, and Scarlet Stadtler
Geosci. Model Dev., 15, 4331–4354, https://doi.org/10.5194/gmd-15-4331-2022, https://doi.org/10.5194/gmd-15-4331-2022, 2022
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Ozone is a toxic greenhouse gas with high spatial variability. We present a machine-learning-based ozone-mapping workflow generating a transparent and reliable product. Going beyond standard mapping methods, this work combines explainable machine learning with uncertainty assessment to increase the integrity of the produced map.
Huan Fang and Greg Michalski
Geosci. Model Dev., 15, 4239–4258, https://doi.org/10.5194/gmd-15-4239-2022, https://doi.org/10.5194/gmd-15-4239-2022, 2022
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A new emission input dataset that incorporates nitrogen isotopes has been used in the CMAQ (Community Multiscale Air Quality) modeling system simulation to qualitatively analyze the changes in δ15N values, due to the dispersion, mixing, and transport of the atmospheric NOx emitted from different sources. The dispersion, mixing, and transport of the atmospheric NOx were based on the meteorology files generated from the WRF (Weather Research and Forecasting) model.
Juan Manuel Castillo, Huw W. Lewis, Akhilesh Mishra, Ashis Mitra, Jeff Polton, Ashley Brereton, Andrew Saulter, Alex Arnold, Segolene Berthou, Douglas Clark, Julia Crook, Ananda Das, John Edwards, Xiangbo Feng, Ankur Gupta, Sudheer Joseph, Nicholas Klingaman, Imranali Momin, Christine Pequignet, Claudio Sanchez, Jennifer Saxby, and Maria Valdivieso da Costa
Geosci. Model Dev., 15, 4193–4223, https://doi.org/10.5194/gmd-15-4193-2022, https://doi.org/10.5194/gmd-15-4193-2022, 2022
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A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land, and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air–sea coupling is included.
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Short summary
Applying the chemistry package from WRF-Chem into the Flow-following finite-volume Icosahedra Model, we essentially make it possible to explore the importance of different levels of complexity in gas and aerosol chemistry, as well as in physics parameterizations, for the interaction processes in global modeling systems. The model performance validated by the Atmospheric Tomography Mission aircraft measurements in summer 2016 shows good performance in capturing the aerosol and gas-phase tracers.
Applying the chemistry package from WRF-Chem into the Flow-following finite-volume Icosahedra...
