Elucidating Hidden and Enduring Weaknesses in Dust Emission Modeling

Author:

Chappell Adrian1ORCID,Webb Nicholas P.2,Hennen Mark3,Zender Charles S.4ORCID,Ciais Philippe56ORCID,Schepanski Kerstin7ORCID,Edwards Brandon L.2ORCID,Ziegler Nancy P.8ORCID,Balkanski Yves5ORCID,Tong Daniel9ORCID,Leys John F.1011ORCID,Heidenreich Stephan10,Hynes Robert10,Fuchs David10ORCID,Zeng Zhenzhong12ORCID,Baddock Matthew C.13ORCID,Lee Jeffrey A.14ORCID,Kandakji Tarek15ORCID

Affiliation:

1. School of Earth and Environmental Sciences Cardiff University Cardiff UK

2. USDA‐ARS Jornada Experimental Range Las Cruces NM USA

3. Catapult Satellite Services Oxford UK

4. Department of Earth System Science University of California Irvine CA USA

5. Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UPSACLAY Gif‐sur‐Yvette France

6. The Cyprus Institute Climate and Atmosphere Research Center (CARE‐C) Nicosia Cyprus

7. Institute of Meteorology Freie Universität Berlin Berlin Germany

8. Cold Regions Research and Engineering Laboratory (CRREL) US Army Engineer Research and Development Center Hanover NH USA

9. Department of Atmospheric, Oceanic and Earth Sciences George Mason University Fairfax VA USA

10. Department of Planning, Industry and Environment Sydney NSW Australia

11. The Fenner School of Environment and Society, Australian National University Acton ACT Australia

12. School of Environmental Science and Engineering, South University of Science and Technology of China Shenzhen China

13. Geography and Environment Loughborough University Loughborough UK

14. Department of Geosciences Texas Tech University Lubbock TX USA

15. Centre for Earth Observation Yale University New Haven CT USA

Abstract

AbstractLarge‐scale classical dust cycle models, developed more than two decades ago, assume for simplicity that the Earth's land surface is devoid of vegetation, reduce dust emission estimates using a vegetation cover complement, and calibrate estimates to observed atmospheric dust optical depth (DOD). Consequently, these models are expected to be valid for use with dust‐climate projections in Earth System Models. We reveal little spatial relation between DOD frequency and satellite observed dust emission from point sources (DPS) and a difference of up to 2 orders of magnitude. We compared DPS data to an exemplar traditional dust emission model (TEM) and the albedo‐based dust emission model (AEM) which represents aerodynamic roughness over space and time. Both models overestimated dust emission probability but showed strong spatial relations to DPS, suitable for calibration. Relative to the AEM calibrated to the DPS, the TEM overestimated large dust emission over vast vegetated areas and produced considerable false change in dust emission. It is difficult to avoid the conclusion that calibrating dust cycle models to DOD has hidden for more than two decades, these TEM modeling weaknesses. The AEM overcomes these weaknesses without using masks or vegetation cover data. Considerable potential therefore exists for ESMs driven by prognostic albedo, to reveal new insights of aerosol effects on, and responses to, contemporary and environmental change projections.

Funder

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geophysics

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