Global impact of mineral dust on cloud droplet number concentration

Abstract

Abstract. The importance of wind-blown mineral dust for cloud droplet formation is studied by considering (i) the adsorption of water on the surface of insoluble particles, (ii) particle coating by soluble material (atmospheric aging) which augments cloud condensation nuclei (CCN) activity, and (iii) the effect of dust on inorganic aerosol concentrations through thermodynamic interactions with mineral cations. The ECHAM5/MESSy Atmospheric Chemistry (EMAC) model is used to simulate the composition of global atmospheric aerosol, while the ISORROPIA-II thermodynamic equilibrium model treats the interactions of K + -Ca 2+ -Mg 2+ -NHaerosol with gas-phase inorganic constituents. Dust is considered a mixture of inert material with reactive minerals and its emissions are calculated online by taking into account the soil particle size distribution and chemical composition of different deserts worldwide. The impact of dust on droplet formation is treated through the "unified dust activation parameterization" that considers the inherent hydrophilicity from adsorption and acquired hygroscopicity from soluble salts during aging. Our simulations suggest that the presence of dust increases cloud droplet number concentration (CDNC) over major deserts (e.g., up to 20 % over the Sahara and the Taklimakan desert) and decreases CDNC over polluted areas (e.g., up to 10 % over southern Europe and 20 % over northeastern Asia). This leads to a global net decrease in CDNC by 11 %. The adsorption activation of insoluble aerosols and the mineral dust chemistry are shown to be equally important for the cloud droplet formation over the main deserts; for example, these effects increase CDNC by 20 % over the Sahara. Remote from deserts the application of adsorption theory is critically important since the increased water uptake by the large aged dust particles (i.e., due to the added hydrophilicity by the soluble coating) reduce the maximum supersaturation and thus cloud droplet formation from the relatively smaller anthropogenic particles (e.g., CDNC decreases by 10 % over southern Europe and 20 % over northeastern Asia by applying adsorption theory). The global average CDNC decreases by 10 % by considering adsorption activation, while changes are negligible when accounting for the mineral dust chemistry. Sensitivity simulations indicate that CDNC is also sensitive to the mineral dust mass and inherent hydrophilicity, and not to the chemical composition of the emitted dust.

ORACLE 2-D (v2.0): an efficient module to compute the volatility and oxygen content of organic aerosol with a global chemistry–climate model

“…The interface structure of MESSy links the base model with several atmospheric submodels that online simulate gas-phase chemistry (MECCA; Sander et al, 2011), inorganic aerosol microphysics and dynamics (GMXe; Pringle et al, 2010), organic aerosol formation and growth (ORACLE; Tsimpidi et al, 2014), emissions (ONLEM and OFFLEM; Kerkweg et al, 2006b), dry deposition and sedimentation (DRYDEP and SEDI; Kerkweg et al, 2006a), cloud scavenging (SCAV; Tost et al, 2006), cloud microphysics (CLOUD; Bacer et al, 2018), and aerosol optical properties (AEROPT; Lauer et al, 2007). EMAC has been extensively described and evaluated against ground-based and satellite observations (Pozzer et al, 2012;Tsimpidi et al, 2014Tsimpidi et al, , 2016Tsimpidi et al, , 2017Karydis et al, 2016Karydis et al, , 2017. In this study, the applied spectral resolution of the EMAC model is T63L31, corresponding to a horizontal grid resolution of 1.875 • × 1.875 • and 31 vertical layers extending to 18 km of altitude (10 hPa).…”

Implementation of a comprehensive ice crystal formation parameterization for cirrus and mixed-phase clouds in the EMAC model (based on MESSy 2.53)

“…4 we will extend the comparison with various observations. Finally, physical loss processes, like dry deposition, wet deposition, and sedimentation of aerosol, are explicitly considered by the submodels DRYDEP, SEDI, and SCAV (Kerkweg et al, 2006;Tost et al, 2006a).…”

Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF

“…Furthermore, aerosol ERF depends on many poorly understood interactions of aerosols with components of the physical climate system. Important sources of uncertainty are known to be aerosol emission fluxes (Granier et al, 2011), representations of complex sub-grid processes such as clouds (Haerter et al, 2009;Lohmann and Ferrachat, 2010;Guo et al, 2013;Gettleman et al, 2013;Golaz et al, 2013;Neubauer et al, 2014;Lohmann, 2017), precipitation responses Croft et al, 2012;Michibata and Takemura, 2015), aerosol processes (Croft et al, 2012;Textor et al, 2006Textor et al, , 2007Storelvmo et al, 2009;Kasoar et al, 2016), radiation calculations Wilcox et al, 2015) and subsequent feedbacks on atmospheric dynamics (Booth et al, 2012;Bollasina et al, 2013;Kirtman et al, 2013;Villarini and Vecchi, 2013;Allen et al, 2014) and surface temperatures (Golaz et al, 2013).…”