Articles | Volume 24, issue 20
https://doi.org/10.5194/acp-24-11451-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-11451-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Bernd Heinold
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Kerstin Schepanski
Institute of Meteorology, Freie Universität Berlin, Berlin, Germany
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Agnesh Panta, Konrad Kandler, Kerstin Schepanski, Andres Alastuey, Pavla Dagsson Waldhauserova, Sylvain Dupont, Melanie Eknayan, Cristina González-Flórez, Adolfo González-Romero, Martina Klose, Mara Montag, Xavier Querol, Jesús Yus-Díez, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 25, 10457–10478, https://doi.org/10.5194/acp-25-10457-2025, https://doi.org/10.5194/acp-25-10457-2025, 2025
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Iceland is among the most active dust source areas in the world. Dust properties are influenced by particle size, mineralogy, shape, and mixing state. This work characterizes freshly emitted individual aerosol particles of Icelandic dust using electron microscopy. Our study provides insights into critical particle-specific information and will contribute to better constraining climate models that consider mineralogical variations in their representation of the dust cycle.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Julian Hofer, Moritz Haarig, Ulla Wandinger, Bernd Heinold, Ina Tegen, Matthias Faust, Holger Baars, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Atmos. Chem. Phys., 25, 9737–9764, https://doi.org/10.5194/acp-25-9737-2025, https://doi.org/10.5194/acp-25-9737-2025, 2025
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This study investigates how hematite in Sahara dust affects how dust particles interact with radiation. Using lidar data from Cabo Verde (2021–2022) and hematite content from atmospheric model simulations, the results show that a higher hematite fraction leads to a decrease in the particle backscattering coefficients in a spectrally different way. These findings can improve the representation of mineral dust in climate models, particularly regarding their radiative effect.
Anisbel Leon-Marcos, Moritz Zeising, Manuela van Pinxteren, Sebastian Zeppenfeld, Astrid Bracher, Elena Barbaro, Anja Engel, Matteo Feltracco, Ina Tegen, and Bernd Heinold
Geosci. Model Dev., 18, 4183–4213, https://doi.org/10.5194/gmd-18-4183-2025, https://doi.org/10.5194/gmd-18-4183-2025, 2025
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This study represents the primary marine organic aerosol (PMOA) emissions, focusing on their sea–atmosphere transfer. Using the FESOM2.1–REcoM3 model, concentrations of key organic biomolecules were estimated and integrated into the ECHAM6.3–HAM2.3 aerosol–climate model. Results highlight the influence of marine biological activity and surface winds on PMOA emissions, with reasonably good agreement with observations improving aerosol representation in the southern oceans.
Anisbel Leon-Marcos, Manuela van Pinxteren, Sebastian Zeppenfeld, Moritz Zeising, Astrid Bracher, Laurent Oziel, Ina Tegen, and Bernd Heinold
EGUsphere, https://doi.org/10.5194/egusphere-2025-2829, https://doi.org/10.5194/egusphere-2025-2829, 2025
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This study links modelled ocean surface concentrations of key marine organic groups with the aerosol-climate model ECHAM-HAM to quantify species-resolved primary marine organic aerosol emissions from 1990 to 2019. Results show strong seasonality, driven by productivity and summer sea ice loss. Emissions and burdens increased over time with more frequent positive anomalies in the last decade, revealing an overall upward trend with regional differences across the Arctic and aerosol species.
Andreas Walbröl, Janosch Michaelis, Sebastian Becker, Henning Dorff, Kerstin Ebell, Irina Gorodetskaya, Bernd Heinold, Benjamin Kirbus, Melanie Lauer, Nina Maherndl, Marion Maturilli, Johanna Mayer, Hanno Müller, Roel A. J. Neggers, Fiona M. Paulus, Johannes Röttenbacher, Janna E. Rückert, Imke Schirmacher, Nils Slättberg, André Ehrlich, Manfred Wendisch, and Susanne Crewell
Atmos. Chem. Phys., 24, 8007–8029, https://doi.org/10.5194/acp-24-8007-2024, https://doi.org/10.5194/acp-24-8007-2024, 2024
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To support the interpretation of the data collected during the HALO-(AC)3 campaign, which took place in the North Atlantic sector of the Arctic from 7 March to 12 April 2022, we analyze how unusual the weather and sea ice conditions were with respect to the long-term climatology. From observations and ERA5 reanalysis, we found record-breaking warm air intrusions and a large variety of marine cold air outbreaks. Sea ice concentration was mostly within the climatological interquartile range.
Cyrille Flamant, Jean-Pierre Chaboureau, Marco Gaetani, Kerstin Schepanski, and Paola Formenti
Atmos. Chem. Phys., 24, 4265–4288, https://doi.org/10.5194/acp-24-4265-2024, https://doi.org/10.5194/acp-24-4265-2024, 2024
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In the austral dry season, the atmospheric composition over southern Africa is dominated by biomass burning aerosols and terrigenous aerosols (so-called mineral dust). This study suggests that the radiative effect of biomass burning aerosols needs to be taken into account to properly forecast dust emissions in Namibia.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Michael Weger and Bernd Heinold
Atmos. Chem. Phys., 23, 13769–13790, https://doi.org/10.5194/acp-23-13769-2023, https://doi.org/10.5194/acp-23-13769-2023, 2023
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This study investigates the effects of complex terrain on air pollution trapping using a numerical model which simulates the dispersion of emissions under real meteorological conditions. The additionally simulated aerosol age allows us to distinguish areas that accumulate aerosol over time from areas that are more influenced by fresh emissions. The Dresden Basin, a widened section of the Elbe Valley in eastern Germany, is selected as the target area in a case study to demonstrate the concept.
Suvarna Fadnavis, Bernd Heinold, T. P. Sabin, Anne Kubin, Katty Huang, Alexandru Rap, and Rolf Müller
Atmos. Chem. Phys., 23, 10439–10449, https://doi.org/10.5194/acp-23-10439-2023, https://doi.org/10.5194/acp-23-10439-2023, 2023
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The influence of the COVID-19 lockdown on the Himalayas caused increases in snow cover and a decrease in runoff, ultimately leading to an enhanced snow water equivalent. Our findings highlight that, out of the two processes causing a retreat of Himalayan glaciers – (1) slow response to global climate change and (2) fast response to local air pollution – a policy action on the latter is more likely to be within the reach of possible policy action to help billions of people in southern Asia.
Fabian Senf, Bernd Heinold, Anne Kubin, Jason Müller, Roland Schrödner, and Ina Tegen
Atmos. Chem. Phys., 23, 8939–8958, https://doi.org/10.5194/acp-23-8939-2023, https://doi.org/10.5194/acp-23-8939-2023, 2023
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Wildfire smoke is a significant source of airborne atmospheric particles that can absorb sunlight. Extreme fires in particular, such as those during the 2019–2020 Australian wildfire season (Black Summer fires), can considerably affect our climate system. In the present study, we investigate the various effects of Australian smoke using a global climate model to clarify how the Earth's atmosphere, including its circulation systems, adjusted to the extraordinary amount of Australian smoke.
Bernd Heinold, Holger Baars, Boris Barja, Matthew Christensen, Anne Kubin, Kevin Ohneiser, Kerstin Schepanski, Nick Schutgens, Fabian Senf, Roland Schrödner, Diego Villanueva, and Ina Tegen
Atmos. Chem. Phys., 22, 9969–9985, https://doi.org/10.5194/acp-22-9969-2022, https://doi.org/10.5194/acp-22-9969-2022, 2022
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The extreme 2019–2020 Australian wildfires produced massive smoke plumes lofted into the lower stratosphere by pyrocumulonimbus convection. Most climate models do not adequately simulate the injection height of such intense fires. By combining aerosol-climate modeling with prescribed pyroconvective smoke injection and lidar observations, this study shows the importance of the representation of the most extreme wildfire events for estimating the atmospheric energy budget.
Michael Weger, Holger Baars, Henriette Gebauer, Maik Merkel, Alfred Wiedensohler, and Bernd Heinold
Geosci. Model Dev., 15, 3315–3345, https://doi.org/10.5194/gmd-15-3315-2022, https://doi.org/10.5194/gmd-15-3315-2022, 2022
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Numerical models are an important tool to assess the air quality in cities,
as they can provide near-continouos data in time and space. In this paper,
air pollution for an entire city is simulated at a high spatial resolution of 40 m.
At this spatial scale, the effects of buildings on the atmosphere,
like channeling or blocking of the air flow, are directly represented by diffuse obstacles in the used model CAIRDIO. For model validation, measurements from air-monitoring sites are used.
Mark Hennen, Adrian Chappell, Nicholas Webb, Kerstin Schepanski, Matthew Baddock, Frank Eckardt, Tarek Kandakji, Jeff Lee, Mohamad Nobakht, and Johanna von Holdt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-423, https://doi.org/10.5194/gmd-2021-423, 2022
Revised manuscript not accepted
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We use 90,000 dust point source observations (DPS), identified in satellite imagery across 9 global dryland environments to develop a novel dust emission model performance assessment. We evaluate the albedo-based dust emission model (AEM), which agrees with dust emission observations, or lack of emission 71 % of the time. Modelled dust occurs 27 % of the time with no observation, caused mostly by the incorrect assumption of infinite sediment supply and lack of dynamic dust entrainment thresholds.
Adrian Chappell, Nicholas Webb, Mark Hennen, Charles Zender, Philippe Ciais, Kerstin Schepanski, Brandon Edwards, Nancy Ziegler, Sandra Jones, Yves Balkanski, Daniel Tong, John Leys, Stephan Heidenreich, Robert Hynes, David Fuchs, Zhenzhong Zeng, Marie Ekström, Matthew Baddock, Jeffrey Lee, and Tarek Kandakji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-337, https://doi.org/10.5194/gmd-2021-337, 2021
Revised manuscript not accepted
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Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Our results indicate that tuning dust emission models to dust in the atmosphere has hidden dust emission modelling weaknesses and its poor performance. Our new approach will reduce uncertainty and driven by prognostic albedo improve Earth System Models of aerosol effects on future environmental change.
Tobias Peter Bauer, Peter Holtermann, Bernd Heinold, Hagen Radtke, Oswald Knoth, and Knut Klingbeil
Geosci. Model Dev., 14, 4843–4863, https://doi.org/10.5194/gmd-14-4843-2021, https://doi.org/10.5194/gmd-14-4843-2021, 2021
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We present the coupled atmosphere–ocean model system ICONGETM. The added value and potential of using the latest coupling technologies are discussed in detail. An exchange grid handles the different coastlines from the unstructured atmosphere and the structured ocean grids. Due to a high level of automated processing, ICONGETM requires only minimal user input. The application to a coastal upwelling scenario demonstrates significantly improved model results compared to uncoupled simulations.
Matthias Faust, Ralf Wolke, Steffen Münch, Roger Funk, and Kerstin Schepanski
Geosci. Model Dev., 14, 2205–2220, https://doi.org/10.5194/gmd-14-2205-2021, https://doi.org/10.5194/gmd-14-2205-2021, 2021
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Trajectory dispersion models are powerful and intuitive tools for tracing air pollution through the atmosphere. But the turbulent nature of the atmospheric boundary layer makes it challenging to provide accurate predictions near the surface. To overcome this, we propose an approach using wind and turbulence information at high temporal resolution. Finally, we demonstrate the strength of our approach in a case study on dust emissions from agriculture.
Michael Weger, Oswald Knoth, and Bernd Heinold
Geosci. Model Dev., 14, 1469–1492, https://doi.org/10.5194/gmd-14-1469-2021, https://doi.org/10.5194/gmd-14-1469-2021, 2021
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A new numerical air-quality transport model for cities is presented, in which buildings are described diffusively. The used diffusive-obstacles approach helps to reduce the computational costs for high-resolution simulations as the grid spacing can be more coarse than in traditional approaches. The research which led to this model development was primarily motivated by the need for a computationally feasible downscaling tool for urban wind and pollution fields from meteorological model output.
Sophie Vandenbussche, Sieglinde Callewaert, Kerstin Schepanski, and Martine De Mazière
Atmos. Chem. Phys., 20, 15127–15146, https://doi.org/10.5194/acp-20-15127-2020, https://doi.org/10.5194/acp-20-15127-2020, 2020
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Mineral dust aerosols blown mostly from desert areas are a key player in the climate system. We use a new desert dust aerosol low-altitude concentration data set as well as additional information on the surface state and low-altitude winds to infer desert dust emission and source maps over North Africa. With 9 years of data, we observe a full seasonal cycle of dust emissions, differentiating morning and afternoon/evening emissions and providing a first glance at long-term changes.
Christof G. Beer, Johannes Hendricks, Mattia Righi, Bernd Heinold, Ina Tegen, Silke Groß, Daniel Sauer, Adrian Walser, and Bernadett Weinzierl
Geosci. Model Dev., 13, 4287–4303, https://doi.org/10.5194/gmd-13-4287-2020, https://doi.org/10.5194/gmd-13-4287-2020, 2020
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Mineral dust aerosol plays an important role in the climate system. Previously, dust emissions have often been represented in global models by prescribed monthly-mean emission fields representative of a specific year. We now apply an online calculation of wind-driven dust emissions. This results in an improved agreement with observations, due to a better representation of the highly variable dust emissions. Increasing the model resolution led to an additional performance gain.
Cited articles
Adebiyi, A. A., Huang, Y., Samset, B. H., and Kok, J. F.: Observations suggest that North African dust absorbs less solar radiation than models estimate, Communications Earth & Environment, 4, 168, https://doi.org/10.1038/s43247-023-00825-2, 2023. a
Alamirew, N. K., Todd, M. C., Ryder, C. L., Marsham, J. H., and Wang, Y.: The early summertime Saharan heat low: sensitivity of the radiation budget and atmospheric heating to water vapour and dust aerosol, Atmos. Chem. Phys., 18, 1241–1262, https://doi.org/10.5194/acp-18-1241-2018, 2018. a
Albani, S., Mahowald, N. M., Perry, A. T., Scanza, R. A., Zender, C. S., Heavens, N. G., Maggi, V., Kok, J. F., and Otto-Bliesner, B. L.: Improved dust representation in the Community Atmosphere Model, J. Adv. Model. Earth Sy., 6, 541–570, https://doi.org/10.1002/2013MS000279, 2014. a, b, c, d, e, f
Alizadeh-Choubari, O., Zawar-Reza, P., and Sturman, A.: The “wind of 120 days” and dust storm activity over the Sistan Basin, Atmos. Res., 143, 328–341, https://doi.org/10.1016/j.atmosres.2014.02.001, 2014. a
Argaman, E., Singer, A., and Tsoar, H.: Erodibility of some crust forming soils/sediments from the Southern Aral Sea Basin as determined in a wind tunnel, Earth Surf. Proc. Land., 31, 47–63, https://doi.org/10.1002/esp.1230, 2006. a, b, c
Banks, J. R., Brindley, H. E., Flamant, C., Garay, M. J., Hsu, N. C., Kalashnikova, O. V., Klüser, L., and Sayer, A. M.: Intercomparison of satellite dust retrieval products over the west African Sahara during the Fennec campaign in June 2011, Remote Sens. Environ., 136, 99–116, https://doi.org/10.1016/j.rse.2013.05.003, 2013. a
Banks, J. R., Brindley, H. E., Hobby, M., and Marsham, J. H.: The daytime cycle in dust aerosol direct radiative effects observed in the central Sahara during the Fennec campaign in June 2011, J. Geophys. Res.-Atmos., 119, 13861–13876, https://doi.org/10.1002/2014JD022077, 2014. a
Banks, J. R., Heinold, B., and Schepanski, K.: Impacts of the desiccation of the Aral Sea on the Central Asian dust life-cycle, J. Geophys. Res.-Atmos., 127, e2022JD036618, https://doi.org/10.1029/2022JD036618, 2022. a
Banks, J. R., Heinold, B., and Schepanski, K.: Dataset associated with Banks et al.: “Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia”, Zenodo [data set], https://doi.org/10.5281/zenodo.11503923, 2023a. a
Banks, J. R., Heinold, B., and Schepanski, K.: Python code associated with Banks et al.: “Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia”, Zenodo [code], https://doi.org/10.5281/zenodo.10160848, 2023b. a
Breckle, S.-W. and Wucherer, W.: The Aralkum, a Man-Made Desert on the Desiccated Floor of the Aral Sea (Central Asia): General Introduction and Aims of the Book, in: Aralkum – a Man-Made Desert: The Desiccated Floor of the Aral Sea (Central Asia), Chap. 1, edited by: Breckle, S.-W., Wucherer, W., Dimeyeva, L. A., and Ogar, N. P., Springer, 1–9, https://doi.org/10.1007/978-3-642-21117-1_1, 2012. a
Brindley, H. E. and Russell, J. E.: An assessment of Saharan dust loading and the corresponding cloud-free longwave direct radiative effect from geostationary satellite observations, J. Geophys. Res., 114, D23201, https://doi.org/10.1029/2008JD011635, 2009. a
DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D., Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: Predicting global atmospheric ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci. USA, 107, 11217–11222, https://doi.org/10.1073/pnas.0910818107, 2010. a
Deutscher Wetterdienst: PArallel MOdel data REtrieve from Oracle databases (PAMORE), DWD [data set], https://www.dwd.de/DE/leistungen/pamore/pamore.html, last access: 10 October 2024. a
Di Biagio, C., Balkanski, Y., Albani, S., Boucher, O., and Formenti, P.: Direct radiative effect by mineral dust aerosols constrained by new microphysical and spectral optical data, Geophys. Res. Lett., 47, e2019GL086186, https://doi.org/10.1029/2019GL086186, 2020. a
Didan, K.: MYD13C2 MODIS/Aqua Vegetation Indices Monthly L3 Global 0.05Deg CMG V006, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MYD13C2.006, 2015. a, b
Doelling, D. R., Loeb, N. G., Keyes, D. F., Nordeen, M. L., Morstad, D., Nguyen, C., Wielicki, B. A., Young, D. F., and Sun, M.: Geostationary Enhanced Temporal Interpolation for CERES Flux Products, J. Atmos. Ocean. Tech., 30, 1072–1090, https://doi.org/10.1175/JTECH-D-12-00136.1, 2013. a
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I.: Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations, J. Atmos. Sci., 59, 590–608, https://doi.org/10.1175/1520-0469(2002)059<0590:VOAAOP>2.0.CO;2, 2002. a, b
Fomba, K. W., Müller, K., Hofer, J., Makhmudov, A. N., Althausen, D., Nazarov, B. I., Abdullaev, S. F., and Herrmann, H.: Variations of the aerosol chemical composition during Asian dust storm at Dushanbe, Tajikistan, E3S Web Conf., 99, 03007, https://doi.org/10.1051/e3sconf/20199903007, 2019. a
Global Facility for Disaster Risk Reduction and Recovery: Weather, Climate and Water in Central Asia: A Guide to Hydrometeorological Services in the Region, https://www.gfdrr.org/en/weather-climate-and-water-central-asia-guide-hydrometeorological-services-region (last access: 10 October 2024), 2019. a
Global Surface Water: Global Surface Water, European Commission's Joint Research Centre [data set], https://global-surface-water.appspot.com/download (last access: 10 October 2024), 2016. a
Groll, M., Opp, C., and Aslanov, I.: Spatial and temporal distribution of the dust deposition in Central Asia – results from a long term monitoring program, Aeolian Res., 9, 49–62, https://doi.org/10.1016/j.aeolia.2012.08.002, 2013. a
Hall, D. K. and Riggs, G. A.: MODIS/Aqua Snow Cover 8-Day L3 Global 0.05Deg CMG. (MYD10C2, Version 6), NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado USA [data set], https://doi.org/10.5067/MODIS/MYD10C2.006, 2016. a, b
Hamzehpour, N., Marcolli, C., Pashai, S., Klumpp, K., and Peter, T.: Measurement report: The Urmia playa as a source of airborne dust and ice-nucleating particles – Part 1: Correlation between soils and airborne samples, Atmos. Chem. Phys., 22, 14905–14930, https://doi.org/10.5194/acp-22-14905-2022, 2022. a
Haywood, J. M., Francis, P., Osborne, S., Glew, M., Loeb, N., Highwood, E., Tanré, D., Myhre, G., Formenti, P., and Hirst, E.: Radiative properties and direct radiative effect of Saharan dust measured by the C-130 aircraft during SHADE: 1. Solar spectrum, J. Geophys. Res., 108, 8577, https://doi.org/10.1029/2002JD002687, 2003. a
Haywood, J. M., Allan, R. P., Culverwell, I., Slingo, T., Milton, S., Edwards, J., and Clerbaux, N.: Can desert dust explain the outgoing longwave radiation anomaly over the Sahara during July 2003?, J. Geophys. Res., 110, D05105, https://doi.org/10.1029/2004JD005232, 2005. a
Heinold, B., Tegen, I., Schepanski, K., Tesche, M., Essenborn, M., Freudenthaler, V., Gross, S., Kandler, K., Knippertz, P., Müller, D., Schladitz, A., Toledano, C., Weinzierl, B., Ansmann, A., Althausen, D., Müller, T., Petzold, A., and Wiedensohler, A.: Regional modelling of Saharan dust and biomass-burning smoke. Part 1: Model description and evaluation, Tellus B, 63, 781–799, https://doi.org/10.1111/j.1600-0889.2011.00570.x, 2011. a
Hengl, T., de Jesus, J. M., Heuvelink, G. B. M., Gonzalez, M. R., Kilibarda, M., Blagotic, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and Kempen, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLoS ONE, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017. a
Hofer, J., Ansmann, A., Althausen, D., Engelmann, R., Baars, H., Fomba, K. W., Wandinger, U., Abdullaev, S. F., and Makhmudov, A. N.: Optical properties of Central Asian aerosol relevant for spaceborne lidar applications and aerosol typing at 355 and 532 nm, Atmos. Chem. Phys., 20, 9265–9280, https://doi.org/10.5194/acp-20-9265-2020, 2020. a, b
Hsu, N. C., Herman, J. R., and Weaver, C.: Determination of radiative forcing of Saharan dust using combined TOMS and ERBE data, J. Geophys. Res., 105, 20649–20661, https://doi.org/10.1029/2000JD900150, 2000. a
Indoitu, R., Kozhoridze, G., Batyrbaeva, M., Vitkovskaya, I., Orlovsky, N., Blumberg, D., and Orlovsky, L.: Dust emission and environmental changes in the dried bottom of the Aral Sea, Aeolian Res., 17, 101–115, https://doi.org/10.1016/j.aeolia.2015.02.004, 2015. a
Kok, J. F., Ridley, D. A., Zhou, Q., Miller, R. L., Zhao, C., Heald, C. L., Ward, D. S., Albani, S., and Haustein, K.: Smaller desert dust cooling effect estimated from analysis of dust size and abundance, Nat. Geosci., 10, 274–278, https://doi.org/10.1038/NGEO2912, 2017. a
Li, L. and Sokolik, I. N.: The Dust Direct Radiative Impact and Its Sensitivity to the Land Surface State and Key Minerals in the WRF-Chem-DuMo Model: A Case Study of Dust Storms in Central Asia, J. Geophys. Res.-Atmos., 123, 4564–4582, https://doi.org/10.1029/2017JD027667, 2018. a, b
Loeb, N. G., Priestley, K. J., Kratz, D. P., Geier, E. B., Green, R. N., Wielicki, B. A., O'Rawe Hinton, P., and Nola, S. K.: Determination of Unfiltered Radiances from the Clouds and the Earth's Radiant Energy System Instrument, J. Appl. Meteorol., 40, 822–835, https://doi.org/10.1175/1520-0450(2001)040<0822:DOURFT>2.0.CO;2, 2001. a
Loeb, N. G., Manalo-Smith, N., Su, W., Shankar, M., and Thomas, S.: CERES Top-of-Atmosphere Earth Radiation Budget Climate Data Record: Accounting for in-Orbit Changes in Instrument Calibration, Remote Sens.-Basel, 8, 182., https://doi.org/10.3390/rs8030182, 2016. a
Löw, F., Navratil, P., Kotte, K., Schöler, H. F., and Bubenzer, O.: Remote-sensing-based analysis of landscape change in the desiccated seabed of the Aral Sea – a potential tool for assessing the hazard degree of dust and salt storms, Environ. Monit. Assess., 185, 8303–8319, https://doi.org/10.1007/s10661-013-3174-7, 2013. a
Marticorena, B. and Bergametti, G.: Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme, J. Geophys. Res., 100, 16415–16430, 1995. a
Meier, J., Tegen, I., Heinold, B., and Wolke, R.: Direct and semi-direct radiative effects of absorbing aerosols in Europe: Results from a regional model, Geophys. Res. Lett., 39, L09802, https://doi.org/10.1029/2012GL050994, 2012. a
Meloni, D., di Sarra, A., Brogniez, G., Denjean, C., De Silvestri, L., Di Iorio, T., Formenti, P., Gómez-Amo, J. L., Gröbner, J., Kouremeti, N., Liuzzi, G., Mallet, M., Pace, G., and Sferlazzo, D. M.: Determining the infrared radiative effects of Saharan dust: a radiative transfer modelling study based on vertically resolved measurements at Lampedusa, Atmos. Chem. Phys., 18, 4377–4401, https://doi.org/10.5194/acp-18-4377-2018, 2018. a
Micklin, P.: The past, present, and future Aral Sea, Lakes & Reservoirs: Research and Management, 15, 193–213, https://doi.org/10.1111/j.1440-1770.2010.00437.x, 2010. a
Mie, G.: Beiträge zur Optik trüber Medien speziell kolloidaler Metallösungen, Ann. Phys., 330, 377–445, https://doi.org/10.1002/andp.19083300302, 1908. a
Miinalainen, T., Kokkola, H., Lehtinen, K. E. J., and Kühn, T.: Comparing the Radiative Forcings of the Anthropogenic Aerosol Emissions From Chile and Mexico, J. Geophys. Res.-Atmos., 126, e2020JD033364, https://doi.org/10.1029/2020JD033364, 2021. a
Miller, R. L.: Adjustment to Radiative Forcing in a Simple Coupled Ocean-Atmosphere Model, J. Climate, 25, 7802–7821, https://doi.org/10.1175/JCLI-D-11-00119.1, 2012. a
Miller, R. L., Knippertz, P., Pérez García-Pando, C., Perlwitz, J. P., and Tegen, I.: Impact of Dust Radiative Forcing upon Climate, in: Mineral Dust: A Key Player in the Earth System, edited by: Knippertz, P. and Stuut, J.-B. W., Springer Netherlands, Dordrecht, 327–357, ISBN 978-94-017-8978-3, https://doi.org/10.1007/978-94-017-8978-3_13, 2014. a
NASA/LARC/SD/ASDC: CERES Time-Interpolated TOA Fluxes, Clouds and Aerosols Daily Aqua Edition4A, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/AQUA/CERES/SSF1DEGDAY_L3.004A, 2015. a
Nobakht, M., Shahgedanova, M., and White, K.: New Inventory of Dust Emission Sources in Central Asia and Northwestern China Derived From MODIS Imagery Using Dust Enhancement Technique, J. Geophys. Res.-Atmos., 126, e2020JD033382, https://doi.org/10.1029/2020JD033382, 2021. a
O'Hara, S. L., Wiggs, G. F. S., Mamedov, B., Davidson, G., and Hubbard, R. B.: Exposure to airborne dust contaminated with pesticide in the Aral Sea region, Lancet, 355, 627–628, https://doi.org/10.1016/S0140-6736(99)04753-4, 2000. a
Orlovsky, L., Orlovsky, N., and Durdyev, A.: Dust storms in Turkmenistan, J. Arid Environ., 60, 83–97, https://doi.org/10.1016/j.jaridenv.2004.02.008, 2005. a
Osipov, S., Stenchikov, G., Brindley, H., and Banks, J.: Diurnal cycle of the dust instantaneous direct radiative forcing over the Arabian Peninsula, Atmos. Chem. Phys., 15, 9537–9553, https://doi.org/10.5194/acp-15-9537-2015, 2015. a
Pekel, J.-F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, Nature, 540, 418–422, https://doi.org/10.1038/nature20584, 2016. a
Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., and Rossiter, D.: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty, SOIL, 7, 217–240, https://doi.org/10.5194/soil-7-217-2021, 2021. a
Prigent, C., Jiménez, C., and Catherinot, J.: Comparison of satellite microwave backscattering (ASCAT) and visible/near-infrared reflectances (PARASOL) for the estimation of aeolian aerodynamic roughness length in arid and semi-arid regions, Atmos. Meas. Tech., 5, 2703–2712, https://doi.org/10.5194/amt-5-2703-2012, 2012. a
Ritter, B. and Geleyn, J.-F.: A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations, Mon. Weather Rev., 120, 303–325, https://doi.org/10.1175/1520-0493(1992)120<0303:ACRSFN>2.0.CO;2, 1992. a
Ryder, C. L., Highwood, E. J., Rosenberg, P. D., Trembath, J., Brooke, J. K., Bart, M., Dean, A., Crosier, J., Dorsey, J., Brindley, H., Banks, J., Marsham, J. H., McQuaid, J. B., Sodemann, H., and Washington, R.: Optical properties of Saharan dust aerosol and contribution from the coarse mode as measured during the Fennec 2011 aircraft campaign, Atmos. Chem. Phys., 13, 303–325, https://doi.org/10.5194/acp-13-303-2013, 2013. a
Scanza, R. A., Mahowald, N., Ghan, S., Zender, C. S., Kok, J. F., Liu, X., Zhang, Y., and Albani, S.: Modeling dust as component minerals in the Community Atmosphere Model: development of framework and impact on radiative forcing, Atmos. Chem. Phys., 15, 537–561, https://doi.org/10.5194/acp-15-537-2015, 2015. a, b, c, d, e
Schättler, U., Doms, G., and Schraff, C.: A description of the nonhydrostatic regional COSMO-model, Part VII: User's guide, Tech. rep., Deutscher Wetterdienst, Offenbach, Germany, http://www.cosmo-model.org/ (last access: 10 October 2024), 2014. a
Sinyuk, A., Torres, O., and Dubovik, O.: Combined use of satellite and surface observations to infer the imaginary part of refractive index of Saharan dust, Geophys. Res. Lett., 30, 1081, https://doi.org/10.1029/2002GL016189, 2003. a, b
Sokolik, I. N. and Toon, O. B.: Incorporation of mineralogical composition into models of the radiative properties of mineral aerosol from UV to IR wavelengths, J. Geophys. Res., 104, 9423–9444, https://doi.org/10.1029/1998JD200048, 1999. a, b
Sotoudeheian, S., Salim, R., and Arhami, M.: Impact of Middle Eastern dust sources on PM10 in Iran: Highlighting the impact of Tigris-Euphrates basin sources and Lake Urmia desiccation, J. Geophys. Res.-Atmos., 121, 14018–14034, https://doi.org/10.1002/2016JD025119, 2016. a
Stjern, C. W., Forster, P. M., Jia, H., Jouan, C., Kasoar, M. R., Myhre, G., Olivié, D., Quaas, J., Samset, B. H., Sand, M., Takemura, T., Voulgarakis, A., and Wells, C. D.: The Time Scales of Climate Responses to Carbon Dioxide and Aerosols, J. Climate, 36, 3537–3551, https://doi.org/10.1175/JCLI-D-22-0513.1, 2023. a, b
Tan, I., Storelvmo, T., and Zelinka, M. D.: Observational constraints on mixed-phase clouds imply higher climate sensitivity, Science, 352, 224–227, https://doi.org/10.1126/science.aad5300, 2016. a
Tegen, I., Bierwirth, E., Heinold, B., Helmert, J., and Wendisch, M.: Effect of measured surface albedo on modeled Saharan dust solar radiative forcing, J. Geophys. Res., 115, D24312, https://doi.org/10.1029/2009JD013764, 2010. a
Volz, F. E.: Infrared Optical Constants of Ammonium Sulfate, Sahara Dust, Volcanic Pumice, and Flyash, Appl. Optics, 12, 564–568, https://doi.org/10.1364/AO.12.000564, 1973. a
Wang, W., Samat, A., Abuduwaili, J., Ge, Y., De Maeyer, P., and Van de Voorde, T.: Temporal characterization of sand and dust storm activity and its climatic and terrestrial drivers in the Aral Sea region, Atmos. Res., 275, 106242, https://doi.org/10.1016/j.atmosres.2022.106242, 2022. a
Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee, R. B., Smith, G. L., and Cooper, J. E.: Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment, B. Am. Meteorol. Soc., 77, 853–868, https://doi.org/10.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2, 1996. a
Wiggs, G. F. S., O'Hara, S. L., Wegerdt, J., van der Meers, J., Small, I., and Hubbard, R.: The dynamics and characteristics of aeolian dust in dryland Central Asia: possible impacts on human exposure and respiratory health in the Aral Sea basin, Geogr. J., 169, 142–157, https://doi.org/10.1111/1475-4959.04976, 2003. a
Wolke, R., Schröder, W., Schrödner, R., and Renner, E.: Influence of grid resolution and meteorological forcing on simulated European air quality: A sensitivity study with the modeling system COSMO-MUSCAT, Atmos. Environ., 53, 110–130, https://doi.org/10.1016/j.atmosenv.2012.02.085, 2012. a
Xi, X.: On the geomorphic, meteorological, and hydroclimatic drivers of the unusual 2018 early summer salt dust storms in Central Asia, J. Geophys. Res.-Atmos., 128, e2022JD038089, https://doi.org/10.1029/2022JD038089, 2023. a, b
Zhang, X.-X., Claiborn, C., Lei, J.-Q., Vaughan, J., Wu, S.-X., Li, S.-Y., Liu, L.-Y., Wang, Z.-F., Wang, Y.-D., Huang, S.-Y., and Zhou, J.: Aeolian dust in Central Asia: Spatial distribution and temporal variability, Atmos. Environ., 238, 117734, https://doi.org/10.1016/j.atmosenv.2020.117734, 2020. a
Short summary
The Aralkum is a new desert in Central Asia formed by the desiccation of the Aral Sea. This has created a source of atmospheric dust, with implications for the balance of solar and thermal radiation. Simulating these effects using a dust transport model, we find that Aralkum dust adds radiative cooling effects to the surface and atmosphere on average but also adds heating events. Increases in surface pressure due to Aralkum dust strengthen the Siberian High and weaken the summer Asian heat low.
The Aralkum is a new desert in Central Asia formed by the desiccation of the Aral Sea. This has...
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