Preprints
https://doi.org/10.5194/acp-2022-719
https://doi.org/10.5194/acp-2022-719
 
24 Oct 2022
24 Oct 2022
Status: this preprint is currently under review for the journal ACP.

A new process-based and scale-respecting desert dust emission scheme for global climate models – Part I: description and evaluation against inverse modeling emissions

Danny M. Leung1, Jasper F. Kok1, Longlei Li2, Gregory S. Okin3, Catherine Prigent4, Martina Klose5, Carlos Pérez Garcia-Pando6,7, Laurent Menut8, Natalie M. Mahowald2, David M. Lawrence9, and Marcelo Chamecki1 Danny M. Leung et al.
  • 1Department of Atmospheric and Oceanic Sciences, University of California – Los Angeles, Los Angeles, California, USA
  • 2Department of Earth and Atmospheric Sciences, Cornell University, Ithica, New York, USA
  • 3Department of Geography, University of California – Los Angeles, Los Angeles, California, USA
  • 4Sorbonne Université, Observatoire de Paris, Université PSL, CNRS, LERMA, Paris, France
  • 5Institute of Meteorology and Climate Research (IMK-TRO), Department Troposphere Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
  • 6Barcelona Supercomputing Center (BSC), Barcelona, Spain
  • 7Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
  • 8Laboratoire de Météorologie Dynamique, École Polytechnique, Institut Polytechnique de Paris, Ecole Normale Supérieure, Sorbonne Université, CNRS, Palaiseau, France
  • 9Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA

Abstract. Desert dust accounts for most of the atmosphere’s aerosol burden by mass and produces numerous important impacts on the Earth system. However, current global climate models (GCMs) and land surface models (LSMs) struggle to accurately represent key dust emission processes, in part because of inadequate representations of soil particle sizes that affect the dust emission threshold, surface roughness elements that absorb wind momentum, and boundary-layer characteristics that control wind fluctuations. Furthermore, because dust emission is driven by small-scale (~1 km or smaller) processes, simulating the global cycle of desert dust in GCMs with coarse horizontal resolutions (~100 km) presents a fundamental challenge. This representation problem is exacerbated by dust emission fluxes scaling nonlinearly with wind speed above a threshold wind speed that is sensitive to land surface characteristics. Here, we address these fundamental problems underlying the simulation of dust emissions in GCMs and LSMs by developing improved descriptions of (1) the effect of soil texture on the dust emission threshold, (2) the effects of non-erodible roughness elements (both rocks and green vegetation) on the surface wind stress, and (3) the effects of boundary-layer turbulence on driving intermittent dust emissions. We then use the resulting revised dust emission parameterization to simulate global dust emissions in a standalone model forced by reanalysis meteorology and land surface fields. We further propose (4) a simple methodology to scale up high-resolution gridded dust emissions to the coarse resolution of GCMs. The resulting dust emission simulation shows substantially improved agreement against regional dust emissions observationally constrained by inverse modeling. We thus find that our revised dust emission parameterization can substantially improve dust emission simulations in GCMs and LSMs.

Danny M. Leung et al.

Status: open (until 23 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Danny M. Leung et al.

Danny M. Leung et al.

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Short summary
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.
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