Articles | Volume 17, issue 3
Atmos. Chem. Phys., 17, 1901–1929, 2017
Atmos. Chem. Phys., 17, 1901–1929, 2017

Research article 09 Feb 2017

Research article | 09 Feb 2017

Global scale variability of the mineral dust long-wave refractive index: a new dataset of in situ measurements for climate modeling and remote sensing

Claudia Di Biagio1, Paola Formenti1, Yves Balkanski2, Lorenzo Caponi1,3, Mathieu Cazaunau1, Edouard Pangui1, Emilie Journet1, Sophie Nowak4, Sandrine Caquineau5, Meinrat O. Andreae6,12, Konrad Kandler7, Thuraya Saeed8, Stuart Piketh9, David Seibert10, Earle Williams11, and Jean-François Doussin1 Claudia Di Biagio et al.
  • 1Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA), UMR7583, CNRS, Université Paris Est Créteil et Université Paris Diderot, Institut Pierre et Simon Laplace, Créteil, France
  • 2Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, 91191, Gif sur Yvette, France
  • 3Department of Physics & INFN, University of Genoa, Genoa, Italy
  • 4Plateforme RX UFR de chimie, Université Paris Diderot, Paris, France
  • 5IRD-Sorbonne Universités (UPMC, Univ. Paris 06), CNRS-MNHN, LOCEAN Laboratory, IRD France-Nord, 93143 Bondy, France
  • 6Biogeochemistry Department, Max Planck Institute for Chemistry, P.O. box 3060, 55020, Mainz, Germany
  • 7Institut für Angewandte Geowissenschaften, Technische Universität Darmstadt, Schnittspahnstr. 9, 64287 Darmstadt, Germany
  • 8Science department, College of Basic Education, Public Authority for Applied Education and Training, Al-Ardeya, Kuwait
  • 9Climatology Research Group, Unit for Environmental Science and Management, North-West University, Potchefstroom, South Africa
  • 10Walden University, Minneapolis, Minnesota, USA
  • 11Parsons Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  • 12Geology and Geophysics Department, King Saud University, Riyadh, Saudi Arabia

Abstract. Modeling the interaction of dust with long-wave (LW) radiation is still a challenge because of the scarcity of information on the complex refractive index of dust from different source regions. In particular, little is known about the variability of the refractive index as a function of the dust mineralogical composition, which depends on the specific emission source, and its size distribution, which is modified during transport. As a consequence, to date, climate models and remote sensing retrievals generally use a spatially invariant and time-constant value for the dust LW refractive index.

In this paper, the variability of the mineral dust LW refractive index as a function of its mineralogical composition and size distribution is explored by in situ measurements in a large smog chamber. Mineral dust aerosols were generated from 19 natural soils from 8 regions: northern Africa, the Sahel, eastern Africa and the Middle East, eastern Asia, North and South America, southern Africa, and Australia. Soil samples were selected from a total of 137 available samples in order to represent the diversity of sources from arid and semi-arid areas worldwide and to account for the heterogeneity of the soil composition at the global scale. Aerosol samples generated from soils were re-suspended in the chamber, where their LW extinction spectra (3–15 µm), size distribution, and mineralogical composition were measured. The generated aerosol exhibits a realistic size distribution and mineralogy, including both the sub- and super-micron fractions, and represents in typical atmospheric proportions the main LW-active minerals, such as clays, quartz, and calcite. The complex refractive index of the aerosol is obtained by an optical inversion based upon the measured extinction spectrum and size distribution.

Results from the present study show that the imaginary LW refractive index (k) of dust varies greatly both in magnitude and spectral shape from sample to sample, reflecting the differences in particle composition. In the 3–15 µm spectral range, k is between ∼ 0.001 and 0.92. The strength of the dust absorption at ∼ 7 and 11.4 µm depends on the amount of calcite within the samples, while the absorption between 8 and 14 µm is determined by the relative abundance of quartz and clays. The imaginary part (k) is observed to vary both from region to region and for varying sources within the same region. Conversely, for the real part (n), which is in the range 0.84–1.94, values are observed to agree for all dust samples across most of the spectrum within the error bars. This implies that while a constant n can be probably assumed for dust from different sources, a varying k should be used both at the global and the regional scale. A linear relationship between the magnitude of the imaginary refractive index at 7.0, 9.2, and 11.4 µm and the mass concentration of calcite and quartz absorbing at these wavelengths was found. We suggest that this may lead to predictive rules to estimate the LW refractive index of dust in specific bands based on an assumed or predicted mineralogical composition, or conversely, to estimate the dust composition from measurements of the LW extinction at specific wavebands.

Based on the results of the present study, we recommend that climate models and remote sensing instruments operating at infrared wavelengths, such as IASI (infrared atmospheric sounder interferometer), use regionally dependent refractive indices rather than generic values. Our observations also suggest that the refractive index of dust in the LW does not change as a result of the loss of coarse particles by gravitational settling, so that constant values of n and k could be assumed close to sources and following transport.

The whole dataset of the dust complex refractive indices presented in this paper is made available to the scientific community in the Supplement.

Short summary
Modeling the interaction of dust with long-wave (LW) radiation is still a challenge due to the scarcity of information on their refractive index. In this paper, we present a unique dataset of dust refractive indices obtained from in situ measurements in a large smog chamber. Our results show that the dust LW refractive index varies strongly from source to source due to particle composition changes. We recommend taking this variability into account in climate and remote sensing applications.
Final-revised paper