Editing IPCC:AR6/SRCCL/Chapter-2 (section)

==== 2.4.1.1 Mineral dust as a short-lived climate forcer from land ====

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Depending on the dust mineralogy, mixing state and size, dust particles can absorb or scatter shortwave and longwave radiation. Dust particles serve as cloud condensation nuclei and ice nuclei. They can influence the microphysical properties of clouds, their lifetime and precipitation rate (Kok et al. 2018 <sup>[[#fn:r809|809]]</sup> ). New and improved understanding of processes controlling emissions and transport of dust, its regional patterns and variability, as well as its chemical composition, has been developed since AR5.

While satellites remain the primary source of information to locate dust sources and atmospheric burden, in-situ data remains critical to constrain optical and mineralogical properties of the dust (DiBiagio et al. 2017 <sup>[[#fn:r810|810]]</sup> ; Rocha-Lima et al. 2018 <sup>[[#fn:r811|811]]</sup> ). Dust particles are composed of minerals, including iron oxides which strongly absorb shortwave radiation and provide nutrients for marine ecosystems. Another mineral such as feldspar is an efficient ice nuclei (Harrison et al. 2016 <sup>[[#fn:r812|812]]</sup> ). Dust mineralogy varies depending on the native soils, so global databases were developed to characterise the mineralogical composition of soils for use in weather and climate models (Journet et al. 2014 <sup>[[#fn:r813|813]]</sup> ; Perlwitz et al. 2015 <sup>[[#fn:r814|814]]</sup> ). New field campaigns, as well as new analyses of observations from prior campaigns, have produced insights into the role of dust in western Africa in climate system, such as long-ranged transport of dust across the Atlantic (Groß et al. 2015 <sup>[[#fn:r815|815]]</sup> ) and the characterisation of aerosol particles and their ability to act as ice and cloud condensation nuclei (Price et al. 2018 <sup>[[#fn:r816|816]]</sup> ). Size distribution at emission is another key parameter controlling dust interactions with radiation. Most models now use the parametrisation of Kok (2011) <sup>[[#fn:r817|817]]</sup> based on the theory of brittle material. It was shown that most models underestimate the size of the global dust cycle (Kok 2011 <sup>[[#fn:r818|818]]</sup> ).

Characterisation of spatial and temporal distribution of dust emissions is essential for weather prediction and climate projections ( ''high confidence'' ). Although there is a growing confidence in characterising the seasonality and peak of dust emissions (i.e., spring–summer (Wang et al. 2015 <sup>[[#fn:r819|819]]</sup> )) and how the meteorological and soil conditions control dust sources, an understanding of long-term future dust dynamics, inter-annual dust variability and how they will affect future climate still requires substantial work. Dust is also important at high latitude, where it has an impact on snow-covered surface albedo and weather (Bullard et al. 2016 <sup>[[#fn:r820|820]]</sup> ).

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