Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Journal Article · 03 August 2023 · Atmospheric Chemistry and Physics (Online)

DOI: https://doi.org/10.5194/acp-23-8623-2023 · OSTI ID:2421874

Gonçalves Ageitos, María  ^[1]; Obiso, Vincenzo ^[2]; Miller, Ron L.  ^[3]; Jorba, Oriol  ^[4]; Klose, Martina  ^[5]; Dawson, Matt ^[6]; Balkanski, Yves  ^[7]; Perlwitz, Jan  ^[8]; Basart, Sara  ^[4]; Di Tomaso, Enza ^[9]; Escribano, Jerónimo  ^[4]; Macchia, Francesca  ^[4]; Montané, Gilbert ^[4]; Mahowald, Natalie M.  ^[10]; Green, Robert O. ^[11]; Thompson, David R.  ^[11]; Pérez García-Pando, Carlos  ^[12]

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1. Univ. Politecnica de Catalunya (Spain); Barcelona Supercomputing Center (BSC) (Spain); Universitat Politècnica de Catalunya, Terrassa (Spain)
2. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Barcelona Supercomputing Center (BSC) (Spain)
3. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Columbia Univ., New York, NY (United States)
4. Barcelona Supercomputing Center (BSC) (Spain)
5. Barcelona Supercomputing Center (BSC) (Spain); Karlsruhe Inst. of Technology (KIT) (Germany)
6. Barcelona Supercomputing Center (BSC) (Spain); National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
7. Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA-Saclay), Gif-sur-Yvette (France). Laboratoire des Sciences du Climat et de l’Environnement (LSCE)
8. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Climate, Aerosol, and Pollution Research, LLC, The Bronx, NY (United States)
9. Barcelona Supercomputing Center (BSC) (Spain); European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn (Germany)
10. Cornell Univ., Ithaca, NY (United States)
11. California Institute of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Laboratory (JPL)
12. Barcelona Supercomputing Center (BSC) (Spain); Univ. Autonoma de Barcelona (Spain). Inst. Catalana de Recerca i Estudis Avancats (ICREA)

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ~ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ~ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

• Research Organization: Univ. of California, Irvine, CA (United States)
• Sponsoring Organization: European Space Agency (ESA); Helmholtz Association of German Research Centres; Ministerio de Economía y Competitividad of Spain; National Aeronautics and Space Administration (NASA); USDOE Office of Science (SC)
• Grant/Contract Number: SC0021302
• OSTI ID: 2421874
• Journal Information: Atmospheric Chemistry and Physics (Online), Journal Name: Atmospheric Chemistry and Physics (Online) Journal Issue: 15 Vol. 23; ISSN 1680-7324
• Publisher: Copernicus Publications, EGUCopyright Statement
• Country of Publication: United States
• Language: English