Articles | Volume 14, issue 7
Geosci. Model Dev., 14, 4249–4260, 2021
Geosci. Model Dev., 14, 4249–4260, 2021

Development and technical paper 06 Jul 2021

Development and technical paper | 06 Jul 2021

Grid-independent high-resolution dust emissions (v1.0) for chemical transport models: application to GEOS-Chem (12.5.0)

Jun Meng et al.

Related authors

Interpretation of geostationary satellite aerosol optical depth (AOD) over East Asia in relation to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and seasonality
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys. Discuss.,,, 2021
Revised manuscript under review for ACP
Short summary
Grid-Stretching Capability for the GEOS-Chem 13.0.0 Atmospheric Chemistry Model
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev. Discuss.,,, 2020
Revised manuscript accepted for GMD
Short summary

Related subject area

Atmospheric sciences
Incorporation of volcanic SO2 emissions in the Hemispheric CMAQ (H-CMAQ) version 5.2 modeling system and assessing their impacts on sulfate aerosol over the Northern Hemisphere
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Geosci. Model Dev., 14, 5751–5768,,, 2021
Short summary
Efficient ensemble generation for uncertain correlated parameters in atmospheric chemical models: a case study for biogenic emissions from EURAD-IM version 5
Annika Vogel and Hendrik Elbern
Geosci. Model Dev., 14, 5583–5605,,, 2021
Short summary
Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0
Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao
Geosci. Model Dev., 14, 5607–5622,,, 2021
Short summary
Atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0: description and evaluation
Timofei Sukhodolov, Tatiana Egorova, Andrea Stenke, William T. Ball, Christina Brodowsky, Gabriel Chiodo, Aryeh Feinberg, Marina Friedel, Arseniy Karagodin-Doyennel, Thomas Peter, Jan Sedlacek, Sandro Vattioni, and Eugene Rozanov
Geosci. Model Dev., 14, 5525–5560,,, 2021
Short summary
Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506,,, 2021
Short summary

Cited articles

Bergin, M. H., Ghoroi, C., Dixit, D., Schauer, J. J., and Shindell, D. T.: Large Reductions in Solar Energy Production Due to Dust and Particulate Air Pollution, Environ. Sci. Tech. Let., 4, 339–344,, 2017. 
Bindle, L., Martin, R. V., Cooper, M. J., Lundgren, E. W., Eastham, S. D., Auer, B. M., Clune, T. L., Weng, H., Lin, J., Murray, L. T., Meng, J., Keller, C. A., Pawson, S., and Jacob, D. J.: Grid-Stretching Capability for the GEOS-Chem 13.0.0 Atmospheric Chemistry Model, Geosci. Model Dev. Discuss. [preprint],, in review, 2020. 
Bristow, C. S., Hudson-Edwards, K. A., and Chappell, A.: Fertilizing the Amazon and equatorial Atlantic with West African dust, Geophys. Res. Lett., 37, L14807,, 2010. 
Chen, H., Navea, J. G., Young, M. A., and Grassian, V. H.: Heterogeneous Photochemistry of Trace Atmospheric Gases with Components of Mineral Dust Aerosol, J. Phys. Chem. A, 115, 490–499,, 2011. 
Short summary
Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emission strengths calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with an optimized global dust strength, presented in this work, can be implemented into GEOS-Chem as offline emission inventory so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.