Improved representation of the global dust cycle using observational constraints on dust properties and abundance

This work was developed with support from the National Science Foundation (NSF) grants 1552519 and 1856389 and the Army Research Office under Cooperative Agreement Number W911NF-20-2-0150 awarded to J.F.K, from the University of California President’s Postdoctoral Fellowship awarded to A.A.A., from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 708119 awarded to S.A. and No. 789630 awarded to M.K. R. C.-G. received funding from the European Union’s Horizon 2020 research and innovation grant 641816 (CRESCENDO), and from JSPS KAKENHI Grant Number 20H04329 and Integrated Research Program for Advancing Climate Models (TOUGOU) Grant Number JPMXD0717935715 from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan to A.I. P.R.C. and A.R.- L. acknowledge support from the NASA Atmospheric Composition: Modeling and Analysis Program (R. Eckman, program manager) and the NASA Center for Climate Simulation (NCCS) for computational resources, Y.H. acknowledges NASA grant 80NSSC19K1346, awarded under the Future Investigators in NASA Earth and Space Science and Technology (FINESST) program, and R.L.M. acknowledges support from the NASA Modeling, Analysis and Prediction Program (NNG14HH42I). C.P.G.P. acknowledges support by the European Research Council (grant no. 773051, FRAGMENT), the EU H2020 project FORCES (grant no. 821205), the AXA Research Fund, and the Spanish Ministry of Science, Innovation and Universities (RYC-2015-18690 and CGL2017-88911-R). M.K. and C.P.G.P. acknowledge PRACE for awarding access to MareNostrum at Barcelona Supercomputing Center to run MONARCH. L.L. acknowledges support from the NASA EMIT project and the Earth Venture – Instrument program (grant no. E678605). We also acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. We further thank Anna Benedictow for assistance in accessing the AeroCom modeling data, the AeroCom modeling groups for making their simulations available, Joseph Prospero and Nicolas Huneeus for providing dust surface concentration data from in situ measurements from the University of Miami Ocean Aerosol Network, and the investigators of the Sahelian Dust Transect for making their dust concentration measurements available. The MERRA-2 data used in this study/project have been provided by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center