Reader TTS

ABSTRACT Airborne mineral dust particles can act as natural seeds for cirrus clouds in the upper troposphere. However, the atmospheric abundance of dust is unconstrained in cirrus-forming

regions, hampering our ability to predict these radiatively important clouds. Here we present global-scale measurements of dust aerosol abundance in the upper troposphere and incorporate

these into a detailed cirrus-formation model. We show that dust aerosol initiates cirrus clouds throughout the extra-tropics in all seasons and dominates cirrus formation in the Northern

Hemisphere (75–93% of clouds seasonally). Using a global transport model with improved dust treatment, we also explore which of Earth’s deserts are the largest contributors of dust aerosol

to cirrus-forming regions. We find that the meteorological environment downstream of each emission region modulates dust atmospheric lifetime and transport efficiency to the upper

troposphere so that source contributions are disproportionate to emissions. Our findings establish the critical role of dust in Earth’s climate system through the formation of cirrus clouds.

Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS OPTIONS Access through your institution Access Nature and 54

other Nature Portfolio journals Get Nature+, our best-value online-access subscription $29.99 / 30 days cancel any time Learn more Subscribe to this journal Receive 12 print issues and

online access $259.00 per year only $21.58 per issue Learn more Buy this article * Purchase on SpringerLink * Instant access to full article PDF Buy now Prices may be subject to local taxes

which are calculated during checkout ADDITIONAL ACCESS OPTIONS: * Log in * Learn about institutional subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY

OTHERS ANNUAL CYCLE OBSERVATIONS OF AEROSOLS CAPABLE OF ICE FORMATION IN CENTRAL ARCTIC CLOUDS Article Open access 20 June 2022 INCREASING ARCTIC DUST SUPPRESSES THE REDUCTION OF ICE

NUCLEATION IN THE ARCTIC LOWER TROPOSPHERE BY WARMING Article Open access 01 November 2024 THE DOMINANT ROLE OF AEROSOL’S CCN EFFECT IN CLOUD GLACIATION Article Open access 26 March 2025

DATA AVAILABILITY In situ data and model output for this study are publically available at https://doi.org/10.3334/ORNLDAAC/2006. ATom aircraft data are publically available at

https://doi.org/10.3334/ORNLDAAC/1925. CODE AVAILABILITY Code for the CESM model is publically available at http://www.cesm.ucar.edu/models/cesm1.0/. Code for the GEOS model is publically

available at https://gmao.gsfc.nasa.gov/GEOS_systems/. REFERENCES * Boucher, O. et al. in _Climate Change 2013: The Physical Science Basis_ (eds Stocker, T. F. et al.) Ch. 7 and 8 (IPCC,

Cambridge Univ. Press, 2013). * Cziczo, D. J. et al. Clarifying the dominant sources and mechanisms of cirrus cloud formation. _Science_ 340, 1320–1324 (2013). Article  Google Scholar  *

Twohy, C. H. Measurements of Saharan dust in convective clouds over the tropical eastern Atlantic Ocean. _J. Atmos. Sci._ 72, 75–81 (2015). Article  Google Scholar  * Kanji, Z. A. et al.

Overview of ice nucleating particles. _Meteorol. Monogr._ 58, 1.1–1.33 (2017). Article  Google Scholar  * Lohmann, U. & Gasparini, B. A cirrus cloud climate dial? _Science_ 357, 248–249

(2017). Article  Google Scholar  * Knippertz, P. & Stuut, J.-B. W. (eds) _Mineral Dust_ (Springer, 2014). * Huneeus, N. et al. Global dust model intercomparison in AeroCom phase I.

_Atmos. Chem. Phys._ 11, 7781–7816 (2011). Article  Google Scholar  * Kok, J. F. et al. Smaller desert dust cooling effect estimated from analysis of dust size and abundance. _Nat. Geosci._

10, 274–278 (2017). Article  Google Scholar  * Cakmur, R. V. et al. Constraining the magnitude of the global dust cycle by minimizing the difference between a model and observations. _J.

Geophys. Res. Atmos._ 111, D06207 (2006). Article  Google Scholar  * Yu, H. et al. Quantification of trans-Atlantic dust transport from seven-year (2007–2013) record of CALIPSO lidar

measurements. _Remote Sens. Environ._ 159, 232–249 (2015). Article  Google Scholar  * Koffi, B. et al. Evaluation of the aerosol vertical distribution in global aerosol models through

comparison against CALIOP measurements: AeroCom phase II results. _J. Geophys. Res. Atmos._ 121, 7254–7283 (2016). Article  Google Scholar  * Pruppacher, H. R. & Klett, J. D.

_Microphysics of Clouds and Precipitation_ (Springer, 2010). * Kipling, Z. et al. Constraints on aerosol processes in climate models from vertically-resolved aircraft observations of black

carbon. _Atmos. Chem. Phys._ 13, 5969–5986 (2013). Article  Google Scholar  * Sayer, A. M. et al. Satellite Ocean Aerosol Retrieval (SOAR) algorithm extension to S‐NPP VIIRS as part of the

‘Deep Blue’ aerosol project. _J. Geophys. Res. Atmos._ 123, 380–400 (2018). Article  Google Scholar  * Shi, Y. et al. A critical examination of spatial biases between MODIS and MISR aerosol

products—application for potential AERONET deployment. _Atmos. Meas. Tech._ 4, 2823–2836 (2011). Article  Google Scholar  * Winker, D. M. et al. The global 3-D distribution of tropospheric

aerosols as characterized by CALIOP. _Atmos. Chem. Phys._ 13, 3345–3361 (2013). Article  Google Scholar  * Froyd, K. D. et al. A new method to quantify mineral dust and other aerosol species

from aircraft platforms using single-particle mass spectrometry. _Atmos. Meas. Tech._ 12, 6209–6239 (2019). Article  Google Scholar  * Bullard, J. E. et al. High-latitude dust in the Earth

system. _Rev. Geophys._ 54, 447–485 (2016). Article  Google Scholar  * Yu, P. et al. Evaluations of tropospheric aerosol properties simulated by the Community Earth System Model with a

sectional aerosol microphysics scheme. _J. Adv. Model. Earth Syst._ 7, 865–914 (2015). Article  Google Scholar  * Colarco, P., da Silva, A., Chin, M. & Diehl, T. Online simulations of

global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth. _J. Geophys. Res._ 115, D14207 (2010). Article  Google Scholar  *

Yu, P. et al. Efficient in-cloud removal of aerosols by deep convection. _Geophys. Res. Lett._ 46, 1061–1069 (2019). Article  Google Scholar  * Schill, G. P. et al. Widespread biomass

burning smoke throughout the remote troposphere. _Nat. Geosci._ 13, 422–427 (2020). Article  Google Scholar  * Formenti, P. et al. Regional variability of the composition of mineral dust

from western Africa: results from the AMMA SOP0/DABEX and DODO field campaigns. _J. Geophys. Res. Atmos._ 113, D00C13 (2008). Article  Google Scholar  * Lieke, K. et al. Particle chemical

properties in the vertical column based on aircraft observations in the vicinity of Cape Verde Islands. _Tellus B Chem. Phys. Meteorol._ 63, 497–511 (2011). Article  Google Scholar  *

Weinzierl, B. et al. The Saharan aerosol long-range transport and aerosol–cloud-interaction experiment: overview and selected highlights. _Bull. Am. Meteorol. Soc._ 98, 1427–1451 (2017).

Article  Google Scholar  * Ryder, C. L. et al. Coarse-mode mineral dust size distributions, composition and optical properties from AER-D aircraft measurements over the tropical eastern

Atlantic. _Atmos. Chem. Phys._ 18, 17225–17257 (2018). Article  Google Scholar  * Price, H. C. et al. Atmospheric ice-nucleating particles in the dusty tropical Atlantic. _J. Geophys. Res.

Atmos._ 123, 2175–2193 (2018). Article  Google Scholar  * Wiacek, A., Peter, T. & Lohmann, U. The potential influence of Asian and African mineral dust on ice, mixed-phase and liquid

water clouds. _Atmos. Chem. Phys._ 10, 8649–8667 (2010). Article  Google Scholar  * Tsai, F., Chen, G. T.-J., Liu, T.-H., Lin, W.-D. & Tu, J.-Y. Characterizing the transport pathways of

Asian dust. _J. Geophys. Res._ 113, D17311 (2008). Article  Google Scholar  * Xu, C., Ma, Y., Yang, K. & You, C. Tibetan Plateau impacts on global dust transport in the upper

troposphere. _J. Clim._ 31, 4745–4756 (2018). Article  Google Scholar  * Ma, J. et al. Modeling the aerosol chemical composition of the tropopause over the Tibetan Plateau during the Asian

summer monsoon. _Atmos. Chem. Phys._ 19, 11587–11612 (2019). Article  Google Scholar  * Mahowald, N. M. Anthropocene changes in desert area: sensitivity to climate model predictions.

_Geophys. Res. Lett._ 34, L18817 (2007). Article  Google Scholar  * Kok, J. F., Ward, D. S., Mahowald, N. M. & Evan, A. T. Global and regional importance of the direct dust-climate

feedback. _Nat. Commun._ 9, 241 (2018). Article  Google Scholar  * Chin, M. et al. Multi-decadal aerosol variations from 1980 to 2009: a perspective from observations and a global model.

_Atmos. Chem. Phys._ 14, 3657–3690 (2014). Article  Google Scholar  * Gettelman, A. et al. Global simulations of ice nucleation and ice supersaturation with an improved cloud scheme in the

Community Atmosphere Model. _J. Geophys. Res._ 115, D18216 (2010). Article  Google Scholar  * Kuebbeler, M., Lohmann, U., Hendricks, J. & Kärcher, B. Dust ice nuclei effects on cirrus

clouds. _Atmos. Chem. Phys._ 14, 3027–3046 (2014). Article  Google Scholar  * Krämer, M. et al. A microphysics guide to cirrus—part 2: climatologies of clouds and humidity from observations.

_Atmos. Chem. Phys._ 20, 12569–12608 (2020). Article  Google Scholar  * Ullrich, R. et al. A new ice nucleation active site parameterization for desert dust and soot. _J. Atmos. Sci._ 74,

699–717 (2017). Article  Google Scholar  * Mitchell, D. L., Rasch, P., Ivanova, D., McFarquhar, G. & Nousiainen, T. Impact of small ice crystal assumptions on ice sedimentation rates in

cirrus clouds and GCM simulations. _Geophys. Res. Lett._ 35, L09806 (2008). Article  Google Scholar  * Sanderson, B. M., Piani, C., Ingram, W. J., Stone, D. A. & Allen, M. R. Towards

constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations. _Clim. Dyn._ 30, 175–190 (2008). Article  Google Scholar  *

Jensen, E. J. et al. Heterogeneous ice nucleation in the tropical tropopause layer. _J. Geophys. Res. Atmos._ 123, 12210–12227 (2018). Article  Google Scholar  * Mace, G. G. et al. A

description of hydrometeor layer occurrence statistics derived from the first year of merged Cloudsat and CALIPSO data. _J. Geophys. Res. Atmos._ 114, D00A26 (2009). Article  Google Scholar

  * Petzold, A. et al. Upper tropospheric water vapour and its interaction with cirrus clouds as seen from IAGOS long-term routine: in situ observations. _Faraday Discuss._ 200, 229–249

(2017). Article  Google Scholar  * Haag, W. et al. Freezing thresholds and cirrus cloud formation mechanisms inferred from in situ measurements of relative humidity. _Atmos. Chem. Phys._ 3,

1791–1806 (2003). Article  Google Scholar  * Gettelman, A., Fetzer, E. J., Eldering, A. & Irion, F. W. The global distribution of supersaturation in the upper troposphere from the

Atmospheric Infrared Sounder. _J. Clim._ 19, 6089–6103 (2006). Article  Google Scholar  * Mitchell, D. L., Garnier, A., Pelon, J. & Erfani, E. CALIPSO (IIR–CALIOP) retrievals of cirrus

cloud ice-particle concentrations. _Atmos. Chem. Phys._ 18, 17325–17354 (2018). Article  Google Scholar  * Sourdeval, O. et al. Ice crystal number concentration estimates from lidar-radar

satellite remote sensing—part 1: method and evaluation. _Atmos. Chem. Phys._ 18, 14327–14350 (2018). Article  Google Scholar  * Kahn, B. H., Gettelman, A., Fetzer, E. J., Eldering, A. &

Liang, C. K. Cloudy and clear-sky relative humidity in the upper troposphere observed by the A-train. _J. Geophys. Res. Atmos._ 114, D00H02 (2009). Article  Google Scholar  * Diao, M.,

Zondlo, M. A., Heymsfield, A. J. & Beaton, S. P. Hemispheric comparison of cirrus cloud evolution using in situ measurements in HIAPER pole-to-pole observations. _Geophys. Res. Lett._

41, 4090–4099 (2014). Article  Google Scholar  * Wofsy, S. C. et al. _ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols_ (ORNL DAAC, 2018); https://doi.org/10.3334/ornldaac/1581

* Liu, J. et al. Spatial and temporal representativeness of ATom transects using GEOS-5 and GMI-CTM simulations. In _98th Ann. Meeting_ _Amer. Meteor. Soc._ 5B.2 (2018). * Brock, C. A. et

al. Aerosol size distributions during the Atmospheric Tomography Mission (ATom): methods, uncertainties, and data products. _Atmos. Meas. Tech._ 12, 3081–3099 (2019). Article  Google Scholar

  * Williamson, C. et al. Fast time response measurements of particle size distributions in the 3–60 nm size range with the nucleation mode aerosol size spectrometer. _Atmos. Meas. Tech._

11, 3491–3509 (2018). Article  Google Scholar  * Kupc, A., Williamson, C., Wagner, N. L., Richardson, M. & Brock, C. A. Modification, calibration, and performance of the Ultra-High

Sensitivity Aerosol Spectrometer for particle size distribution and volatility measurements during the Atmospheric Tomography Mission (ATom) airborne campaign. _Atmos. Meas. Tech._ 11,

369–383 (2018). Article  Google Scholar  * McNaughton, C. S. et al. Results from the DC-8 inlet characterization experiment (DICE): airborne versus surface sampling of mineral dust and sea

salt aerosols. _Aerosol Sci. Technol._ 41, 136–159 (2007). Article  Google Scholar  * Thomson, D. S., Schein, M. E. & Murphy, D. M. Particle Analysis by Laser Mass Spectrometry WB-57F

instrument overview. _Aerosol Sci. Technol._ 33, 153–169 (2000). Article  Google Scholar  * Murphy, D. M. et al. Single-particle mass spectrometry of tropospheric aerosol particles. _J.

Geophys. Res. Atmos._ 111, D23S3 (2006). Article  Google Scholar  * Murphy, D. M., Middlebrook, A. M. & Warshawsky, M. Cluster analysis of data from the Particle Analysis by Laser Mass

Spectrometry (PALMS) instrument. _Aerosol Sci. Technol._ 37, 382–391 (2003). Article  Google Scholar  * Diskin, G. S., Podolske, J. R., Sachse, G. W. & Slate, T. A. Open-path airborne

tunable diode laser hygrometer. _Proc. SPIE_ 4817, 196 (2002). Article  Google Scholar  * Podolske, J. R. Calibration and data retrieval algorithms for the NASA Langley/Ames Diode Laser

Hygrometer for the NASA Transport and Chemical Evolution Over the Pacific (TRACE-P) mission. _J. Geophys. Res._ 108, 8792 (2003). Article  Google Scholar  * Rollins, A. W. et al. Evaluation

of UT/LS hygrometer accuracy by intercomparison during the NASA MACPEX mission. _J. Geophys. Res. Atmos._ 119, 1915–1935 (2014). Article  Google Scholar  * Chan, K. R., Dean-Day, J., Bowen,

S. W. & Bui, T. P. Turbulence measurements by the DC-8 Meteorological Measurement System. _Geophys. Res. Lett._ 25, 1355–1358 (1998). Article  Google Scholar  * Bardeen, C. G., Toon, O.

B., Jensen, E. J., Marsh, D. R. & Harvey, V. L. Numerical simulations of the three-dimensional distribution of meteoric dust in the mesosphere and upper stratosphere. _J. Geophys. Res._

113, D17202 (2008). Article  Google Scholar  * Toon, O. B., Turco, R. P., Westphal, D., Malone, R. & Liu, M. A multidimensional model for aerosols: description of computational analogs.

_J. Atmos. Sci._ 45, 2123–2144 (1988). Article  Google Scholar  * Ginoux, P. et al. Sources and distributions of dust aerosols simulated with the GOCART model. _J. Geophys. Res. Atmos._ 106,

20255–20273 (2001). Article  Google Scholar  * Su, L. & Toon, O. B. Numerical simulations of Asian dust storms using a coupled climate–aerosol microphysical model. _J. Geophys. Res._

114, D14202 (2009). Article  Google Scholar  * Gillette, D. A. & Passi, R. Modeling dust emission caused by wind erosion. _J. Geophys. Res. Atmos._ 93, 14233–14242 (1988). Article 

Google Scholar  * Creamean, J. M. et al. Colorado air quality impacted by long-range-transported aerosol: a set of case studies during the 2015 Pacific Northwest fires. _Atmos. Chem. Phys._

16, 12329–12345 (2016). Article  Google Scholar  * Tobo, Y. et al. Glacially sourced dust as a potentially significant source of ice nucleating particles. _Nat. Geosci._ 12, 253–258 (2019).

Article  Google Scholar  * Zhang, G. J. & McFarlane, N. A. Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian climate centre general

circulation model. _Atmos. Ocean_ 33, 407–446 (1995). Article  Google Scholar  * Wang, H. et al. Sensitivity of remote aerosol distributions to representation of cloud–aerosol interactions

in a global climate model. _Geosci. Model Dev._ 6, 765–782 (2013). Article  Google Scholar  * Grell, G. A. & Freitas, S. R. A scale and aerosol aware stochastic convective

parameterization for weather and air quality modeling. _Atmos. Chem. Phys._ 14, 5233–5250 (2014). Article  Google Scholar  * Chin, M. et al. Tropospheric aerosol optical thickness from the

GOCART model and comparisons with satellite and sun photometer measurements. _J. Atmos. Sci._ 59, 461–483 (2002). Article  Google Scholar  * Bian, H. et al. Investigation of global

particulate nitrate from the AeroCom phase III experiment. _Atmos. Chem. Phys._ 17, 12911–12940 (2017). Article  Google Scholar  * Rienecker, M. M. et al. _The GEOS‐5 Data Assimilation

System: Documentation of Versions 5.0.1 and 5.1.0, and 5.2.0_ (NASA, 2008). * Bowman, K. P. Large-scale isentropic mixing properties of the Antarctic polar vortex from analyzed winds. _J.

Geophys. Res. Atmos._ 98, 23013–23027 (1993). Article  Google Scholar  * Bowman, K. P. & Carrie, G. D. The mean-meridional transport circulation of the troposphere in an idealized GCM.

_J. Atmos. Sci._ 59, 1502–1514 (2002). Article  Google Scholar  * Spichtinger, P. & Gierens, K. M. Modelling of cirrus clouds—part 1b: structuring cirrus clouds by dynamics. _Atmos.

Chem. Phys._ 9, 707–719 (2009). Article  Google Scholar  * Jensen, E. J., Pfister, L. & Bui, T. P. Physical processes controlling ice concentrations in cold cirrus near the tropical

tropopause. _Geophys. Res. Atmos._ 117, D111205 (2012). Article  Google Scholar  * Murphy, D. M. Rare temperature histories and cirrus ice number density in a parcel and a one-dimensional

model. _Atmos. Chem. Phys._ 14, 13013–13022 (2014). Article  Google Scholar  * Jensen, E. J. et al. Physical processes controlling ice concentrations in synoptically forced, midlatitude

cirrus. _J. Geophys. Res. Atmos._ 118, 5348–5360 (2013). Article  Google Scholar  * Jensen, E. & Pfister, L. Transport and freeze-drying in the tropical tropopause layer. _J. Geophys.

Res._ 109, D02207 (2004). Google Scholar  * Koop, T., Luo, B., Tsias, A. & Peter, T. Water activity as the determinant for homogeneous ice nucleation in aqueous solutions. _Nature_ 406,

611–614 (2000). Article  Google Scholar  * DeMott, P. J. Quantitative descriptions of ice formation mechanisms of silver iodide-type aerosols. _Atmos. Res._ 38, 63–99 (1995). Article  Google

Scholar  * Cziczo, D. J. et al. Deactivation of ice nuclei due to atmospherically relevant surface coatings. _Environ. Res. Lett._ 4, 044013 (2009). Article  Google Scholar  * Sullivan, R.

C. et al. Irreversible loss of ice nucleation active sites in mineral dust particles caused by sulphuric acid condensation. _Atmos. Chem. Phys._ 10, 11471–11487 (2010). Article  Google

Scholar  * DeMott, P. J., Rogers, D. C. & Kreidenweis, S. M. The susceptibility of ice formation in upper tropospheric clouds to insoluble aerosol components. _J. Geophys. Res. Atmos._

102, 19575–19584 (1997). Article  Google Scholar  * Kärcher, B., Hendricks, J. & Lohmann, U. Physically based parameterization of cirrus cloud formation for use in global atmospheric

models. _J. Geophys. Res._ 111, D01205 (2006). Google Scholar  * Podglajen, A., Hertzog, A., Plougonven, R. & Legras, B. Lagrangian temperature and vertical velocity fluctuations due to

gravity waves in the lower stratosphere. _Geophys. Res. Lett._ 43, 3543–3553 (2016). Article  Google Scholar  * Schoeberl, M. R. et al. Gravity wave spectra in the lower stratosphere

diagnosed from project loon balloon trajectories. _J. Geophys. Res. Atmos._ 122, 8517–8524 (2017). Article  Google Scholar  Download references ACKNOWLEDGEMENTS We thank M. Dollner and B.

Weinzierl for cloud particle measurements to exclude cloudy flight segments; M. Richardson, F. Erdesz and D. Thomson for technical support; and D. Cziczo for valuable input. The ATom mission

was supported by NASA’s Earth System Science Pathfinder Program EVS-2 funding. Participation in the ATom mission by K.D.F., G.P.S., C.J.W., C.A.B., D.M.M. and E.R. was supported by NOAA

climate funding and NASA award NNH15AB12I. P.Y. was supported by the second Tibetan Plateau Scientific Expedition and Research Program (STEP, 2019QZKK0604). The CESM project is supported

partly by the National Science Foundation. A.K. was supported by the Austrian Science Fund’s Erwin Schrodinger Fellowship J-3613. GEOS development in the Global Modeling and Assimilation

Office is funded by NASA’s Modeling, Analysis and Prediction (MAP) program. Resources supporting GEOS were provided by the NASA High-End Computing (HEC) Program through the NASA Center for

Climate Simulation (NCCS) at Goddard Space Flight Center. H.B. was supported by NASA award NNX17AG31G. P.R.C. was supported by the MAP-funded Chemistry-Climate Modeling (CCM) project

(600-17-6985). AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Chemical Sciences Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA Karl D. Froyd, Pengfei Yu, 

Gregory P. Schill, Charles A. Brock, Agnieszka Kupc, Christina J. Williamson, Eric J. Jensen, Eric Ray, Karen H. Rosenlof & Daniel M. Murphy * Cooperative Institute for Research in

Environmental Sciences, University of Colorado, Boulder, CO, USA Karl D. Froyd, Pengfei Yu, Gregory P. Schill, Christina J. Williamson, Eric J. Jensen & Eric Ray * Institute for

Environment and Climate Research, Jinan University, Guangzhou, China Pengfei Yu * Faculty of Physics, Aerosol Physics and Environmental Physics, University of Vienna, Vienna, Austria

Agnieszka Kupc * NASA Goddard Space Flight Center, Greenbelt, MD, USA Huisheng Bian, Anton S. Darmenov & Peter R. Colarco * University of Maryland at Baltimore County, Baltimore County,

MD, USA Huisheng Bian * NASA Langley Research Center, Hampton, VA, USA Glenn S. Diskin * NASA Ames Research Center, Moffett Field, CA, USA ThaoPaul Bui Authors * Karl D. Froyd View author

publications You can also search for this author inPubMed Google Scholar * Pengfei Yu View author publications You can also search for this author inPubMed Google Scholar * Gregory P. Schill

View author publications You can also search for this author inPubMed Google Scholar * Charles A. Brock View author publications You can also search for this author inPubMed Google Scholar

* Agnieszka Kupc View author publications You can also search for this author inPubMed Google Scholar * Christina J. Williamson View author publications You can also search for this author

inPubMed Google Scholar * Eric J. Jensen View author publications You can also search for this author inPubMed Google Scholar * Eric Ray View author publications You can also search for this

author inPubMed Google Scholar * Karen H. Rosenlof View author publications You can also search for this author inPubMed Google Scholar * Huisheng Bian View author publications You can also

search for this author inPubMed Google Scholar * Anton S. Darmenov View author publications You can also search for this author inPubMed Google Scholar * Peter R. Colarco View author

publications You can also search for this author inPubMed Google Scholar * Glenn S. Diskin View author publications You can also search for this author inPubMed Google Scholar * ThaoPaul Bui

View author publications You can also search for this author inPubMed Google Scholar * Daniel M. Murphy View author publications You can also search for this author inPubMed Google Scholar

CONTRIBUTIONS K.D.F. wrote the paper with contributions from all authors. K.D.F., G.P.S., C.A.B., A.K., C.J.W., D.M.M., G.S.D. and T.B. collected airborne data. P.Y. and K.H.R. provided

CESM/CARMA model results. H.B., A.S.D. and P.R.C. provided GEOS model results. E.R. provided forward trajectory results. E.J.J. provided cirrus model results. CORRESPONDING AUTHOR

Correspondence to Karl D. Froyd. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Geoscience_ thanks Amato

Evan, Trude Storelvmo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Tom Richardson, in collaboration with the _Nature

Geoscience_ team. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Discussion, Figs. 1–13 and Table 1. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE

Froyd, K.D., Yu, P., Schill, G.P. _et al._ Dominant role of mineral dust in cirrus cloud formation revealed by global-scale measurements. _Nat. Geosci._ 15, 177–183 (2022).

https://doi.org/10.1038/s41561-022-00901-w Download citation * Received: 25 November 2020 * Accepted: 12 January 2022 * Published: 24 February 2022 * Issue Date: March 2022 * DOI:

https://doi.org/10.1038/s41561-022-00901-w SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not

currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative