Articles | Volume 16, issue 3
https://doi.org/10.5194/gmd-16-1009-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-1009-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
09 Feb 2023
Development and technical paper |
| 09 Feb 2023
| 09 Feb 2023
Application of a satellite-retrieved sheltering parameterization (v1.0) for dust event simulation with WRF-Chem v4.1
Sandra L. LeGrand
CORRESPONDING AUTHOR
U.S. Army Engineer Research and Development Center, Geospatial Research Laboratory, Alexandria, Virginia, USA
Department of Geography, University of California, Los Angeles, California, USA
Theodore W. Letcher
U.S. Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire, USA
Gregory S. Okin
Department of Geography, University of California, Los Angeles, California, USA
Nicholas P. Webb
USDA-ARS Jornada Experimental Range, Las Cruces, New Mexico, USA
Alex R. Gallagher
U.S. Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire, USA
Saroj Dhital
USDA-ARS Jornada Experimental Range, Las Cruces, New Mexico, USA
Taylor S. Hodgdon
U.S. Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire, USA
Nancy P. Ziegler
U.S. Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire, USA
Michelle L. Michaels
U.S. Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire, USA
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Pei Zhang, Brandon L. Edwards, John A. Gillies, George Nikolich, Andrew Trautz, Brandi Wheeler, and Nancy P. Ziegler
EGUsphere, https://doi.org/10.5194/egusphere-2026-1635, https://doi.org/10.5194/egusphere-2026-1635, 2026
This preprint is open for discussion and under review for Earth Surface Dynamics (ESurf).
Short summary
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Plants help protect drylands from wind erosion, but wind can accelerate along plant sides, increasing erosion risk. We measured ground-level wind forces around a shrub over two years and found stronger spatial variability than previously reported, with substantial changes over time. Wind effects along plant sides did not depend on wind speed but varied with plant growth stage. Including these patterns can improve predictions of erosion and dust emission.
Clarissa Baldo, Servanne Chevaillier, Sophie Nowak, Gael Noyalet, Sandra Lafon, Claudia Di Biagio, Amelie Chaput, James King, Mathieu Cazaunau, Edouard Pangui, Jean-Francois Doussin, Remi Stanus, Nadine Mattielli, Heleen C. Vos, Gregory S. Okin, Brigitte Language, Stuart Piketh, Karine Desboeufs, Akinori Ito, Silvia Becagli, Laurie Barrier, Stephane Jacquemound, and Paola Formenti
EGUsphere, https://doi.org/10.5194/egusphere-2026-1532, https://doi.org/10.5194/egusphere-2026-1532, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
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Our results show that crustal element ratios and clay contents distinguish dust aerosols from arid western coastal areas and humid eastern inland regions in Southern Africa. This dust contains key micronutrients that can become bioaccessible during atmospheric transport to nearby and remote marine ecosystems. It is also enriched in carbonates and K-feldspar, serving as a source of cloud condensation and ice nuclei, with potential implications ranging from regional to sub-hemispheric scales.
Claudia Di Biagio, Elisa Bru, Avila Orta, Servanne Chevaillier, Clarissa Baldo, Antonin Bergé, Mathieu Cazaunau, Sandra Lafon, Sophie Nowak, Edouard Pangui, Meinrat O. Andreae, Pavla Dagsson-Waldhauserova, Kebonyethata Dintwe, Konrad Kandler, James S. King, Amelie Chaput, Gregory S. Okin, Stuart Piketh, Thuraya Saeed, David Seibert, Zongbo Shi, Earle Williams, Pasquale Sellitto, and Paola Formenti
Atmos. Chem. Phys., 26, 1079–1091, https://doi.org/10.5194/acp-26-1079-2026, https://doi.org/10.5194/acp-26-1079-2026, 2026
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Spectroscopy measurements show that the absorbance of dust in the far-infrared up to 25 µm is comparable in intensity to that in the mid-infrared (3–15 µm) suggesting possible relevance for its direct radiative effect. Absorption signatures differ between Icelandic and low/mid-latitude dust due to differences in mineralogical composition. Spectral differences could be used to characterise the mineralogy and trace the origin of airborne dust based on infrared remote sensing observations.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
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Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Theodore Letcher, Julie Parno, Zoe Courville, Lauren Farnsworth, and Jason Olivier
The Cryosphere, 16, 4343–4361, https://doi.org/10.5194/tc-16-4343-2022, https://doi.org/10.5194/tc-16-4343-2022, 2022
Short summary
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We present a radiative transfer model that uses ray tracing to determine optical properties from computer-generated 3D renderings of snow resolved at the microscale and to simulate snow spectral reflection and transmission for visible and near-infrared light. We expand ray-tracing techniques applied to sub-1 cm3 snow samples to model an entire snowpack column. The model is able to reproduce known snow surface optical properties, and simulations compare well against field observations.
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
Short summary
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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.
Huilin Huang, Yongkang Xue, Ye Liu, Fang Li, and Gregory S. Okin
Geosci. Model Dev., 14, 7639–7657, https://doi.org/10.5194/gmd-14-7639-2021, https://doi.org/10.5194/gmd-14-7639-2021, 2021
Short summary
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This study applies a fire-coupled dynamic vegetation model to quantify fire impact at monthly to annual scales. We find fire reduces grass cover by 4–8 % annually for widespread areas in south African savanna and reduces tree cover by 1 % at the periphery of tropical Congolese rainforest. The grass cover reduction peaks at the beginning of the rainy season, which quickly diminishes before the next fire season. In contrast, the reduction of tree cover is irreversible within one growing season.
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
Short summary
Short summary
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.
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Short summary
Ground cover affects dust emissions by reducing wind flow over the immediate soil surface. This study reviews a method for estimating ground cover effects on wind erosion from satellite-detected terrain shadows. We conducted a case study for a US dust event using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Adding the shadow-based method for ground cover effects markedly improved simulated results and may lead to better dust modeling outcomes in vegetated drylands.
Ground cover affects dust emissions by reducing wind flow over the immediate soil surface. This...
