Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4287-2020
https://doi.org/10.5194/gmd-13-4287-2020
Model evaluation paper
 | 
16 Sep 2020
Model evaluation paper |  | 16 Sep 2020

Modelling mineral dust emissions and atmospheric dispersion with MADE3 in EMAC v2.54

Christof G. Beer, Johannes Hendricks, Mattia Righi, Bernd Heinold, Ina Tegen, Silke Groß, Daniel Sauer, Adrian Walser, and Bernadett Weinzierl

Related authors

Revealing dominant patterns of aerosols regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations
Jingmin Li, Mattia Righi, Johannes Hendricks, Christof G. Beer, Ulrike Burkhardt, and Anja Schmidt
EGUsphere, https://doi.org/10.5194/egusphere-2024-1024,https://doi.org/10.5194/egusphere-2024-1024, 2024
Short summary
Impacts of ice-nucleating particles on cirrus clouds and radiation derived from global model simulations with MADE3 in EMAC
Christof G. Beer, Johannes Hendricks, and Mattia Righi
Atmos. Chem. Phys., 24, 3217–3240, https://doi.org/10.5194/acp-24-3217-2024,https://doi.org/10.5194/acp-24-3217-2024, 2024
Short summary
A global climatology of ice-nucleating particles under cirrus conditions derived from model simulations with MADE3 in EMAC
Christof G. Beer, Johannes Hendricks, and Mattia Righi
Atmos. Chem. Phys., 22, 15887–15907, https://doi.org/10.5194/acp-22-15887-2022,https://doi.org/10.5194/acp-22-15887-2022, 2022
Short summary
An aerosol classification scheme for global simulations using the K-means machine learning method
Jingmin Li, Johannes Hendricks, Mattia Righi, and Christof G. Beer
Geosci. Model Dev., 15, 509–533, https://doi.org/10.5194/gmd-15-509-2022,https://doi.org/10.5194/gmd-15-509-2022, 2022
Short summary
Exploring the uncertainties in the aviation soot–cirrus effect
Mattia Righi, Johannes Hendricks, and Christof Gerhard Beer
Atmos. Chem. Phys., 21, 17267–17289, https://doi.org/10.5194/acp-21-17267-2021,https://doi.org/10.5194/acp-21-17267-2021, 2021
Short summary

Related subject area

Climate and Earth system modeling
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024,https://doi.org/10.5194/gmd-17-4923-2024, 2024
Short summary
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024,https://doi.org/10.5194/gmd-17-4871-2024, 2024
Short summary
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024,https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024,https://doi.org/10.5194/gmd-17-4821-2024, 2024
Short summary
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024,https://doi.org/10.5194/gmd-17-4727-2024, 2024
Short summary

Cited articles

Aquila, V., Hendricks, J., Lauer, A., Riemer, N., Vogel, H., Baumgardner, D., Minikin, A., Petzold, A., Schwarz, J. P., Spackman, J. R., Weinzierl, B., Righi, M., and Dall'Amico, M.: MADE-in: a new aerosol microphysics submodel for global simulation of insoluble particles and their mixing state, Geosci. Model Dev., 4, 325–355, https://doi.org/10.5194/gmd-4-325-2011, 2011. a, b, c, d
Astitha, M., Lelieveld, J., Abdel Kader, M., Pozzer, A., and de Meij, A.: Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties, Atmos. Chem. Phys., 12, 11057–11083, https://doi.org/10.5194/acp-12-11057-2012, 2012. a
Balkanski, Y., Schulz, M., Claquin, T., Moulin, C., and Ginoux, P.: Global emissions of mineral aerosol: formulation and validation using satellite imagery, in: Emissions of Atmospheric Trace Compounds, Springer, 18, 239–267, https://doi.org/10.1007/978-1-4020-2167-1_6, 2004. a
Banks, J. R., Brindley, H. E., Stenchikov, G., and Schepanski, K.: Satellite retrievals of dust aerosol over the Red Sea and the Persian Gulf (2005–2015), Atmos. Chem. Phys., 17, 3987–4003, https://doi.org/10.5194/acp-17-3987-2017, 2017. a
Baumgardner, D., Jonsson, H., Dawson, W., O'Connor, D., and Newton, R.: The cloud, aerosol and precipitation spectrometer: a new instrument for cloud investigations, Atmos. Res., 59–60, 251–264, https://doi.org/10.1016/s0169-8095(01)00119-3, 2001. a
Download
Short summary
Mineral dust aerosol plays an important role in the climate system. Previously, dust emissions have often been represented in global models by prescribed monthly-mean emission fields representative of a specific year. We now apply an online calculation of wind-driven dust emissions. This results in an improved agreement with observations, due to a better representation of the highly variable dust emissions. Increasing the model resolution led to an additional performance gain.