Articles | Volume 18, issue 23
https://doi.org/10.5194/gmd-18-9805-2025
© Author(s) 2025. 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-18-9805-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Enhancing volcanic eruption simulations with the WRF-Chem v4.8
Alexander Ukhov
King Abdullah University of Science and Technology, Division of Physical Sciences and Engineering, Thuwal, Saudi Arabia
Georgiy Stenchikov
King Abdullah University of Science and Technology, Division of Physical Sciences and Engineering, Thuwal, Saudi Arabia
Jordan Schnell
NOAA Global Systems Laboratory, Boulder, CO, USA
CIRES, University of Colorado, Boulder, CO, USA
Ravan Ahmadov
NOAA Global Systems Laboratory, Boulder, CO, USA
Umberto Rizza
National Research Council – Institute of Atmospheric Sciences and Climate (CNR-ISAC), 73100 Lecce, Italy
Georg Grell
NOAA Global Systems Laboratory, Boulder, CO, USA
Ibrahim Hoteit
CORRESPONDING AUTHOR
King Abdullah University of Science and Technology, Division of Physical Sciences and Engineering, Thuwal, Saudi Arabia
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Sagar P. Parajuli, Georgiy L. Stenchikov, Alexander Ukhov, Suleiman Mostamandi, Paul A. Kucera, Duncan Axisa, William I. Gustafson Jr., and Yannian Zhu
Atmos. Chem. Phys., 22, 8659–8682, https://doi.org/10.5194/acp-22-8659-2022, https://doi.org/10.5194/acp-22-8659-2022, 2022
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Rainfall affects the distribution of surface- and groundwater resources, which are constantly declining over the Middle East and North Africa (MENA) due to overexploitation. Here, we explored the effects of dust on rainfall using WRF-Chem model simulations. Although dust is considered a nuisance from an air quality perspective, our results highlight the positive fundamental role of dust particles in modulating rainfall formation and distribution, which has implications for cloud seeding.
Alexander Ukhov, Ravan Ahmadov, Georg Grell, and Georgiy Stenchikov
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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.
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Atmos. Chem. Phys., 20, 16089–16116, https://doi.org/10.5194/acp-20-16089-2020, https://doi.org/10.5194/acp-20-16089-2020, 2020
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Both natural (dust, sea salt) and anthropogenic (sulfate, organic and black carbon) aerosols are common over the Red Sea coastal plains. King Abdullah University of Science and Technology (KAUST), located on the eastern coast of the Red Sea, hosts the only operating lidar system in the Arabian Peninsula, which measures atmospheric aerosols day and night. We use these lidar data and high-resolution WRF-Chem model simulations to study the potential effect of dust aerosols on Red Sea environment.
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Injection of sulfur and water vapour by the Hunga volcanic eruption significantly altered chemical composition and radiative budget of the stratosphere. Yet, whether the eruption could also affect surface climate, especially via indirect pathways, remains poorly understood. Here we investigate these effects using large ensembles of simulations with the CESM2(WACCM6) Earth system model.
Manal Hamdeno, Aida Alvera-Azcárate, George Krokos, and Ibrahim Hoteit
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Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
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Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
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Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, https://doi.org/10.5194/acp-23-3083-2023, 2023
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Plume height is important in wildfire smoke dispersion and affects 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, affects pollution exceedance forecasts and the early warning of extreme air pollution events.
Mohamed Abdelkader, Georgiy Stenchikov, Andrea Pozzer, Holger Tost, and Jos Lelieveld
Atmos. Chem. Phys., 23, 471–500, https://doi.org/10.5194/acp-23-471-2023, https://doi.org/10.5194/acp-23-471-2023, 2023
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We study the effect of injected volcanic ash, water vapor, and SO2 on the development of the volcanic cloud and the stratospheric aerosol optical depth (AOD). Both are sensitive to the initial injection height and to the aging of the volcanic ash shaped by heterogeneous chemistry coupled with the ozone cycle. The paper explains the large differences in AOD for different injection scenarios, which could improve the estimate of the radiative forcing of volcanic eruptions.
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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We use the WRF-Chem model with new implementations of GOES-16 wildfire emissions and plume rise based on fire radiative power (FRP) to interpret aerosol observations during the 2019 NASA–NOAA FIREX-AQ field campaign and perform model evaluations. The model shows significant improvements in simulating the variety of aerosol loading environments sampled during FIREX-AQ. Our results also highlight the importance of accurate wildfire diurnal cycle and aerosol chemical mechanisms in models.
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.
Sagar P. Parajuli, Georgiy L. Stenchikov, Alexander Ukhov, Suleiman Mostamandi, Paul A. Kucera, Duncan Axisa, William I. Gustafson Jr., and Yannian Zhu
Atmos. Chem. Phys., 22, 8659–8682, https://doi.org/10.5194/acp-22-8659-2022, https://doi.org/10.5194/acp-22-8659-2022, 2022
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Rainfall affects the distribution of surface- and groundwater resources, which are constantly declining over the Middle East and North Africa (MENA) due to overexploitation. Here, we explored the effects of dust on rainfall using WRF-Chem model simulations. Although dust is considered a nuisance from an air quality perspective, our results highlight the positive fundamental role of dust particles in modulating rainfall formation and distribution, which has implications for cloud seeding.
M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1045–1052, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, 2022
Li Zhang, Georg A. Grell, Stuart A. McKeen, Ravan Ahmadov, Karl D. Froyd, and Daniel Murphy
Geosci. Model Dev., 15, 467–491, https://doi.org/10.5194/gmd-15-467-2022, https://doi.org/10.5194/gmd-15-467-2022, 2022
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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.
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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Convection parameterization (CP) is a component of atmospheric models aiming to represent the statistical effects of subgrid-scale convective clouds. Because the atmosphere contains circulations with a broad spectrum of scales, the truncation needed to run models in computers requires the introduction of parameterizations to account for processes that are not explicitly resolved. We detail recent developments in the Grell–Freitas CP, which has been applied in several regional and global models.
Anton Lopatin, Oleg Dubovik, David Fuertes, Georgiy Stenchikov, Tatyana Lapyonok, Igor Veselovskii, Frank G. Wienhold, Illia Shevchenko, Qiaoyun Hu, and Sagar Parajuli
Atmos. Meas. Tech., 14, 2575–2614, https://doi.org/10.5194/amt-14-2575-2021, https://doi.org/10.5194/amt-14-2575-2021, 2021
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The article presents novelties in characterizing fine particles suspended in the air by means of combining various measurements that observe light propagation in atmosphere. Several non-coincident observations (some of which require sunlight, while others work only at night) could be united under the assumption that aerosol properties do not change drastically at nighttime. It also proposes how to describe particles' composition in a simplified manner that uses new types of observations.
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.
Sagar P. Parajuli, Georgiy L. Stenchikov, Alexander Ukhov, Illia Shevchenko, Oleg Dubovik, and Anton Lopatin
Atmos. Chem. Phys., 20, 16089–16116, https://doi.org/10.5194/acp-20-16089-2020, https://doi.org/10.5194/acp-20-16089-2020, 2020
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Both natural (dust, sea salt) and anthropogenic (sulfate, organic and black carbon) aerosols are common over the Red Sea coastal plains. King Abdullah University of Science and Technology (KAUST), located on the eastern coast of the Red Sea, hosts the only operating lidar system in the Arabian Peninsula, which measures atmospheric aerosols day and night. We use these lidar data and high-resolution WRF-Chem model simulations to study the potential effect of dust aerosols on Red Sea environment.
Cited articles
Abdelkader, M., Stenchikov, G., Pozzer, A., Tost, H., and Lelieveld, J.: The effect of ash, water vapor, and heterogeneous chemistry on the evolution of a Pinatubo-size volcanic cloud, Atmos. Chem. Phys., 23, 471–500, https://doi.org/10.5194/acp-23-471-2023, 2023. a
Abdul-Razzak, H. and Ghan, S. J.: Parameterization of the influence of organic surfactants on aerosol activation, Journal of Geophysical Research: Atmospheres, 109, https://doi.org/10.1029/2003JD004043, 2004. a
Aquila, V., Oman, L. D., Stolarski, R. S., Colarco, P. R., and Newman, P. A.: Dispersion of the volcanic sulfate cloud from a Mount Pinatubo-like eruption, Journal of Geophysical Research: Atmospheres, 117, https://doi.org/10.1029/2011JD016968, 2012. a
Barnard, J. C., Fast, J. D., Paredes-Miranda, G., Arnott, W. P., and Laskin, A.: Technical Note: Evaluation of the WRF-Chem “Aerosol Chemical to Aerosol Optical Properties” Module using data from the MILAGRO campaign, Atmos. Chem. Phys., 10, 7325–7340, https://doi.org/10.5194/acp-10-7325-2010, 2010. a
Bluth, G. J., Doiron, S. D., Schnetzler, C. C., Krueger, A. J., and Walter, L. S.: Global tracking of the SO2 clouds from the June, 1991 Mount Pinatubo eruptions, Geophysical Research Letters, 19, 151–154, 1992. a
Borrmann, S., Dye, J., Baumgardner, D., Proffitt, M., Margitan, J., Wilson, J., Jonsson, H., Brock, C., Loewenstein, M., Podolske, J., and Ferry, G.: Aerosols as dynamical tracers in the lower stratosphere: Ozone versus aerosol correlation after the Mount Pinatubo eruption, Journal of Geophysical Research: Atmospheres, 100, 11147–11156, 1995. a
Brodtkorb, A. R., Benedictow, A., Klein, H., Kylling, A., Nyiri, A., Valdebenito, A., Sollum, E., and Kristiansen, N.: Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17), Geosci. Model Dev., 17, 1957–1974, https://doi.org/10.5194/gmd-17-1957-2024, 2024. a
Burkholder, J., Sander, S., Abbatt, J., Barker, J., Cappa, C., Crounse, J., Dibble, T., Huie, R., Kolb, C., Kurylo, M., Orkin, V., Percival, C., Wilmouth, D., and Wine P.: Chemical kinetics and photochemical data for use in atmospheric studies; evaluation number 19, Tech. rep., Jet Propulsion Laboratory, National Aeronautics and Space Administration, Pasadena, CA, USA, https://jpldataeval.jpl.nasa.gov/pdf/NASA-JPL%20Evaluation%2019-5.pdf (last access: 8 December 2025), 2020. a
Carn, S. and Krotkov, N.: Ultraviolet satellite measurements of volcanic ash, in: Volcanic ash, Elsevier, 217–231, https://doi.org/10.1016/B978-0-08-100405-0.00018-5, 2016. a
Casadevall, T. J.: The 1989–1990 eruption of Redoubt Volcano, Alaska: impacts on aircraft operations, Journal of volcanology and geothermal research, 62, 301–316, 1994. a
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B. N., Duncan, B. N., Martin, R. V., Logan, J. A., Higurashi, A., and Nakajima, T.: Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and Sun photometer measurements, Journal of the atmospheric sciences, 59, 461–483, 2002. a, b
Clift, R. and Gauvin, W.: Motion of entrained particles in gas streams, The Canadian Journal of Chemical Engineering, 49, 439–448, 1971. a
Cunningham, E.: On the velocity of steady fall of spherical particles through fluid medium, Proceedings of the Royal Society of London, Series A, Containing Papers of a Mathematical and Physical Character, 83, 357–365, 1910. a
Damian, V., Sandu, A., Damian, M., Potra, F., and Carmichael, G. R.: The kinetic preprocessor KPP-a software environment for solving chemical kinetics, Computers & Chemical Engineering, 26, 1567–1579, 2002. a
Davies, C.: Definitive equations for the fluid resistance of spheres, Proceedings of the Physical Society, 57, 259, https://doi.org/10.1088/0959-5309/57/4/301, 1945. a
de Bem, D. L., Anabor, V., Puhales, F. S., Pinheiro, D. K., Grasso, F., Steffenel, L. A., Brenner, L., and Rizza, U.: Investigating Synoptic Influences on Tropospheric Volcanic Ash Dispersion from the 2015 Calbuco Eruption Using WRF-Chem Simulations and Satellite Data, Remote Sensing, 16, 4455, https://doi.org/10.3390/rs16234455, 2024. a
Dee, D. P., Uppalaa, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Quarterly Journal of the royal meteorological society, 137, 553–597, 2011. a
Dessler, A., Schoeberl, M., Wang, T., Davis, S., Rosenlof, K., and Vernier, J.-P.: Variations of stratospheric water vapor over the past three decades, Journal of Geophysical Research: Atmospheres, 119, 12–588, https://doi.org/10.1002/2014JD021712, 2014. a
Egan, S. D., Stuefer, M., Webley, P. W., Lopez, T., Cahill, C. F., and Hirtl, M.: Modeling volcanic ash aggregation processes and related impacts on the April–May 2010 eruptions of Eyjafjallajökull volcano with WRF-Chem, Nat. Hazards Earth Syst. Sci., 20, 2721–2737, https://doi.org/10.5194/nhess-20-2721-2020, 2020. a
Fast, J., Gustafson Jr, W., Easter, R., Zaveri, R., Barnard, J., Chapman, E., Grell, G., and Peckham, S.: Evolution of ozone, particulates, and aerosol direct forcing in an urban area using a new fully-coupled meteorology, chemistry, and aerosol model, J. Geophys. Res, 111, D21305, https://doi.org/10.1029/2005JD006721, 2006. a, b
Folch, A., Costa, A., and Macedonio, G.: FALL3D: A computational model for transport and deposition of volcanic ash, Computers & Geosciences, 35, 1334–1342, 2009. a
Freitas, S. R., Longo, K. M., Alonso, M. F., Pirre, M., Marecal, V., Grell, G., Stockler, R., Mello, R. F., and Sánchez Gácita, M.: PREP-CHEM-SRC – 1.0: a preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models, Geosci. Model Dev., 4, 419–433, https://doi.org/10.5194/gmd-4-419-2011, 2011. a, b
Ghan, S. J. and Zaveri, R. A.: Parameterization of optical properties for hydrated internally mixed aerosol, Journal of Geophysical Research: Atmospheres, 112, https://doi.org/10.1029/2006JD007927, 2007. a
Grell, G. A. and Dévényi, D.: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques, Geophysical Research Letters, 29, 38–1, https://doi.org/10.1029/2002GL015311, 2002. a
Guo, S., Bluth, G. J., Rose, W. I., Watson, I. M., and Prata, A.: Re-evaluation of SO2 release of the 15 June 1991 Pinatubo eruption using ultraviolet and infrared satellite sensors, Geochemistry, Geophysics, Geosystems, 5, https://doi.org/10.1029/2003GC000654, 2004. a, b, c
Hirtl, M., Scherllin-Pirscher, B., Stuefer, M., Arnold, D., Baro, R., Maurer, C., and Mulder, M. D.: Extension of the WRF-Chem volcanic emission preprocessor to integrate complex source terms and evaluation for different emission scenarios of the Grimsvötn 2011 eruption, Nat. Hazards Earth Syst. Sci., 20, 3099–3115, https://doi.org/10.5194/nhess-20-3099-2020, 2020. a
Hong, S.-Y., Dudhia, J., and Chen, S.-H.: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation, Monthly weather review, 132, 103–120, 2004. a
Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with an explicit treatment of entrainment processes, Monthly weather review, 134, 2318–2341, 2006. a
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, Journal of Geophysical Research: Atmospheres, 113, https://doi.org/10.1029/2008JD009944, 2008. a, b
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019. a
Jones, A., Thomson, D., Hort, M., and Devenish, B.: The UK Met Office's next-generation atmospheric dispersion model, NAME III, in: Air pollution modeling and its application XVII, Springer, 580–589, https://doi.org/10.1007/978-0-387-68854-1_62, 2007. a
Liu, M., Hoffmann, L., Griessbach, S., Cai, Z., Heng, Y., and Wu, X.: Improved representation of volcanic sulfur dioxide depletion in Lagrangian transport simulations: a case study with MPTRAC v2.4, Geosci. Model Dev., 16, 5197–5217, https://doi.org/10.5194/gmd-16-5197-2023, 2023. a
Mailler, S., Menut, L., Cholakian, A., and Pennel, R.: AerSett v1.0: a simple and straightforward model for the settling speed of big spherical atmospheric aerosols, Geosci. Model Dev., 16, 1119–1127, https://doi.org/10.5194/gmd-16-1119-2023, 2023. a
Mastin, L. G. and Van Eaton, A. R.: Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes, Atmosphere, 11, 1038, https://doi.org/10.3390/atmos11101038, 2020. a
Mastin, L. G., Guffanti, M., Servranckx, R., Webley, P., Barsotti, S., Dean, K., Durant, A., Ewert, J. W., Neri, A., Rose, W. I., Schneider, D., Siebert, L., Stunder, B., Swanson, G., Tupper, A., Volentik, A., and Waythomas, C. F.: A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions, Journal of volcanology and Geothermal Research, 186, 10–21, 2009. a
Miguez-Macho, G., Stenchikov, G. L., and Robock, A.: Spectral nudging to eliminate the effects of domain position and geometry in regional climate model simulations, Journal of Geophysical Research: Atmospheres, 109, https://doi.org/10.1029/2003JD004495, 2004. a
Paladio-Melosantos, M. L. O., Solidum, R. U., Scott, W. E., Quiambao, R. B., Umbal, J. V., Rodolfo, K. S., Tubianosa, B. S., Delos Reyes, P. J., Alonso, R. A., and Ruelo, H. B.: Tephra falls of the 1991 eruptions of Mount Pinatubo, in: Fire and mud: eruptions and lahars of Mount Pinatubo, Philippines, edited by: Newhall, C. G., and Punongbayan, R. S., 513–535, ISBN-10 0-295-97585-7, 1996. a
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007. a
Pollack, J. B., Toon, O. B., and Khare, B. N.: Optical properties of some terrestrial rocks and glasses, Icarus, 19, 372–389, 1973. a
Pommrich, R., Müller, R., Grooß, J.-U., Konopka, P., Ploeger, F., Vogel, B., Tao, M., Hoppe, C. M., Günther, G., Spelten, N., Hoffmann, L., Pumphrey, H.-C., Viciani, S., D'Amato, F., Volk, C. M., Hoor, P., Schlager, H., and Riese, M.: Tropical troposphere to stratosphere transport of carbon monoxide and long-lived trace species in the Chemical Lagrangian Model of the Stratosphere (CLaMS), Geosci. Model Dev., 7, 2895–2916, https://doi.org/10.5194/gmd-7-2895-2014, 2014. a
Ramachandran, S., Ramaswamy, V., Stenchikov, G. L., and Robock, A.: Radiative impact of the Mount Pinatubo volcanic eruption: Lower stratospheric response, Journal of Geophysical Research: Atmospheres, 105, 24409–24429, 2000. a
Rizza, U., Donnadieu, F., Morichetti, M., Avolio, E., Castorina, G., Semprebello, A., Magazu, S., Passerini, G., Mancinelli, E., and Biensan, C.: Airspace contamination by volcanic ash from sequences of Etna paroxysms: Coupling the WRF-Chem dispersion model with near-source L-band radar observations, Remote Sensing, 15, 3760, https://doi.org/10.3390/rs15153760, 2023. a
Searcy, C., Dean, K., and Stringer, W.: PUFF: A high-resolution volcanic ash tracking model, Journal of Volcanology and Geothermal Research, 80, 1–16, 1998. a
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Wang, W., and Powers, J. G.: A description of the advanced research WRF version 2, Tech. rep., National Center For Atmospheric Research Boulder Co Mesoscale and Microscale Meteorology Div, NCAR/TN-468+STR, 2005. a
Stefanetti, F., Vattioni, S., Dykema, J. A., Chiodo, G., Sedlacek, J., Keutsch, F. N., and Sukhodolov, T.: Stratospheric injection of solid particles reduces side effects on circulation and climate compared to SO2 injections, Environmental Research: Climate, 3, 045028, https://doi.org/10.1088/2752-5295/ad9f93, 2024. a
Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J., Cohen, M. D., and Ngan, F.: NOAA's HYSPLIT atmospheric transport and dispersion modeling system, Bulletin of the American Meteorological Society, 96, 2059–2077, 2015. a
Stenchikov, G., Ukhov, A., Osipov, S., Ahmadov, R., Grell, G., Cady-Pereira, K., Mlawer, E., and Iacono, M.: How does a Pinatubo-size volcanic cloud reach the middle stratosphere?, Journal of Geophysical Research: Atmospheres, 126, e2020JD033829, https://doi.org/10.1029/2020JD033829, 2021. a, b, c, d, e, f, g, h, i, j, k
Stenchikov, G., Ukhov, A., and Osipov, S.: Modeling the Radiative Forcing and Atmospheric Temperature Perturbations Caused by the 2022 Hunga Volcano Explosion, Journal of Geophysical Research: Atmospheres, 130, e2024JD041940, https://doi.org/10.1029/2024JD041940, 2025. a, b, c
Stewart, C., Damby, D. E., Horwell, C. J., Elias, T., Ilyinskaya, E., Tomašek, I., Longo, B. M., Schmidt, A., Carlsen, H. K., Mason, E., Baxter, P. J., Cronin, S., and Witham, C.: Volcanic air pollution and human health: recent advances and future directions, Bulletin of Volcanology, 84, https://doi.org/10.1007/s00445-021-01513-9, 2022. a
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005. a
Stokes, G. G.: On the effect of the internal friction of fluids on the motion of pendulums, 1850. a
Stuefer, M., Freitas, S. R., Grell, G., Webley, P., Peckham, S., McKeen, S. A., and Egan, S. D.: Inclusion of ash and SO2 emissions from volcanic eruptions in WRF-Chem: development and some applications, Geosci. Model Dev., 6, 457–468, https://doi.org/10.5194/gmd-6-457-2013, 2013. a, b, c, d
Suzuki, T.: A theoretical model for dispersion of tephra, Arc volcanism: physics and tectonics, 95–113, https://pages.mtu.edu/~raman/papers2/Suzuki83.pdf (last access: 9 December 2025), 1983. a
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M. A., Mitchell, K., Ek, M., Gayno, G., Wegiel, J., and Cuenca, H.: Implementation and verification of the unified NOAH land surface model in the WRF model, 20th conference on weather analysis and forecasting/16th conference on numerical weather prediction, 11–15, https://www.researchgate.net/publication/286272692_Implementation_and_verification_of_the_united_NOAH_land_surface_model_in_the_WRF_model (last access: 9 December 2025), 2004. a
Ukhov, A.: WRF-Chem code used in this publication along with namelist files and scripts for OH and H2O2 interpolation, Zenodo [code], https://doi.org/10.5281/zenodo.16894619, 2025. a
Ukhov, A., Mostamandi, S., da Silva, A., Flemming, J., Alshehri, Y., Shevchenko, I., and Stenchikov, G.: Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products, and high-resolution WRF-Chem model simulations, Atmos. Chem. Phys., 20, 9281–9310, https://doi.org/10.5194/acp-20-9281-2020, 2020a. a
Ukhov, A., Mostamandi, S., Krotkov, N., Flemming, J., da Silva, A., Li, C., Fioletov, V., McLinden, C., Anisimov, A., Alshehri, Y. M., and Stenchikov, G.: Study of SO Pollution in the Middle East Using MERRA-2, CAMS Data Assimilation Products, and High-Resolution WRF-Chem Simulations, Journal of Geophysical Research: Atmospheres, 125, e2019JD031993, https://doi.org/10.1029/2019JD031993, 2020b. a
Ukhov, A., Ahmadov, R., Grell, G., and Stenchikov, G.: Improving dust simulations in WRF-Chem v4.1.3 coupled with the GOCART aerosol module, Geosci. Model Dev., 14, 473–493, https://doi.org/10.5194/gmd-14-473-2021, 2021. a, b, c, d
Ukhov, A., Stenchikov, G., Osipov, S., Krotkov, N., Gorkavyi, N., Li, C., Dubovik, O., and Lopatin, A.: Inverse modeling of the initial stage of the 1991 Pinatubo volcanic cloud accounting for radiative feedback of volcanic ash, Journal of Geophysical Research: Atmospheres, 128, e2022JD038446, https://doi.org/10.1029/2022JD038446, 2023. a, b, c, d, e, f
Ukhov, A., Stohl, A., Stenchikov, G., and Hoteit, I.: Inverse modeling of SO2 point source emissions in the Middle East, Journal of Geophysical Research: Atmospheres, 130, e2025JD043334, https://doi.org/10.1029/2025JD043334, 2025. a
Webley, P., Steensen, T., Stuefer, M., Grell, G., Freitas, S., and Pavolonis, M.: Analyzing the Eyjafjallajökull 2010 eruption using satellite remote sensing, lidar and WRF-Chem dispersion and tracking model, Journal of Geophysical Research: Atmospheres, 117, https://doi.org/10.1029/2011JD016817, 2012. a, b
Wesely, M.: Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models, Atmospheric environment, 41, 52–63, 2007. a
Wiesner, M. G., Wang, Y., and Zheng, L.: Fallout of volcanic ash to the deep South China Sea induced by the 1991 eruption of Mount Pinatubo (Philippines), Geology, 23, 885–888, 1995. a
Zaveri, R. A., Easter, R. C., Fast, J. D., and Peters, L. K.: Model for simulating aerosol interactions and chemistry (MOSAIC), Journal of Geophysical Research: Atmospheres, 113, https://doi.org/10.1029/2007JD008782, 2008. a
Short summary
Volcanic eruptions are natural hazards impacting aviation, the environment, and climate. Here, we improve the simulation of volcanic material transport using the Weather Research and Forecasting (WRF-Chem) version 4.8. Analysis of ash, sulfate, and SO2 mass budgets was performed. The direct radiative effect of volcanic aerosols was implemented. A preprocessor, PrepEmisSources, was developed to streamline the preparation of volcanic emissions.
Volcanic eruptions are natural hazards impacting aviation, the environment, and climate. Here,...