Quantifying the range of the dust direct radiative effect due to source mineralogy uncertainty
The large uncertainty in the mineral dust direct radiative effect (DRE) hinders projections of future climate change due to anthropogenic activity. Resolving modeled dust mineral speciation allows for spatially and temporally varying refractive indices consistent with dust aerosol composition. Here, for the first time, we quantify the range in dust DRE at the top of the atmosphere (TOA) due to current uncertainties in the surface soil mineralogical content using a dust mineral-resolving climate model. We propagate observed uncertainties in soil mineral abundances from two soil mineralogy atlases along with the optical properties of each mineral into the DRE and compare the resultant range with other sources of uncertainty across six climate models. The shortwave DRE responds region-specifically to the dust burden depending on the mineral speciation and underlying shortwave surface albedo: positively when the regionally averaged annual surface albedo is larger than 0.28 and negatively otherwise. Among all minerals examined, the shortwave TOA DRE and single scattering albedo at the 0.44–0.63 µm band are most sensitive to the fractional contribution of iron oxides to the total dust composition. The global net (shortwave plus longwave) TOA DRE is estimated to be within −0.23 to +0.35 W m−2. Approximately 97 % of this range relates to uncertainty in the soil abundance of iron oxides. Representing iron oxide with solely hematite optical properties leads to an overestimation of shortwave DRE by +0.10 W m−2 at the TOA, as goethite is not as absorbing as hematite in the shortwave spectrum range. Our study highlights the importance of iron oxides to the shortwave DRE: they have a disproportionally large impact on climate considering their small atmospheric mineral mass fractional burden (∼2 %). An improved description of iron oxides, such as those planned in the Earth Surface Mineral Dust Source Investigation (EMIT), is thus essential for more accurate estimates of the dust DRE. ; A portion of this work was funded by the Earth Surface Mineral Dust Source Investigation (EMIT), a NASA Earth Ventures-Instrument (EVI-4) Mission. Longlei Li, Natalie M. Mahowald, and Douglas S. Hamilton were supported by the Atkinson Centre for a Sustainable Future. Jasper F. Kok received support from NSF grant 1552519. Martina Klose received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 789630 (DUST.ES). Carlos Pérez García-Pando and Maria Gonçalves Ageitos received support from the European Research Council (grant no. 773051, FRAGMENT), EU H2020 project FORCES (grant no. 821205), the AXA Research Fund, the Spanish Ministry of Science, Innovation and Universities (RYC-2015-18690 and NUTRIENT: CGL2017- 88911-R), and PRACE and RES for awarding access to MareNostrum at the Barcelona Supercomputing Center to run MONARCH. Ron L. Miller received for support from the NASA Modeling, Analysis and Prediction Program (NNG14HH42I). ; Peer Reviewed ; Postprint (published version)