Elucidating hidden and enduring weaknesses in dust emission modeling

Authors: CHAPPELL, ADRIAN - Cardiff University; Webb, Nicholas - Nick; HENNEN, MARK - Cardiff University; ZENDER, CHARLES - University Of California; CIAIS, PHILIPPE - Laboratoire Des Sciences Du Climat Et De L'Environnement (LSCE); SCHEPANSKI, KERSTIN - Freie University; EDWARDS, BRANDON - New Mexico State University; ZIEGLER, NANCY - Us Army Research Institute Of Environmental Medicine; BALKANSKI, YVES - Laboratoire Des Sciences Du Climat Et De L'Environnement (LSCE); TONG, DANIEL - George Mason University; LEYS, JOHN - Australian National University; HEIDENREICH, STEPHAN - Nsw Office Of Environment And Heritage; HYNES, ROBERT - Nsw Office Of Environment And Heritage; FUCHS, DAVID - Nsw Office Of Environment And Heritage; ZENG, ZHENZHONG - Central South University; BADDOCK, MATTHEW - Loughborough University; LEE, JEFFREY - Texas Tech University; KANDAKJI, TAREK - Yale University

Submitted to: Journal of Geophysical Research Atmospheres
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/13/2023
Publication Date: 9/16/2023
Citation: Chappell, A., Webb, N.P., Hennen, M., Zender, C.S., Ciais, P., Schepanski, K., Edwards, B.L., Ziegler, N.P., Balkanski, Y., Tong, D., Leys, J.F., Heidenreich, S., Hynes, R., Fuchs, D., Zeng, Z., Baddock, M.C., Lee, J.A., Kandakji, T. 2023. Elucidating hidden and enduring weaknesses in dust emission modeling. Journal of Geophysical Research Atmospheres. 128(17). Article e2023JD038584. https://doi.org/10.1029/2023JD038584.
DOI: https://doi.org/10.1029/2023JD038584

Interpretive Summary: Mineral dust influences Earth's systems, and understanding its impacts relies on numerical models which include large uncertainties. We compared measurements of dust optical depth (DOD) frequency of occurrence (probability) and satellite observed dust emission frequency from point sources (DPS) across North America. We found up to 2 orders of magnitude difference between DOD probability and DPS probability. Compared with DPS probability, we found an exemplar traditional dust emission model (TEM) and the albedo-based dust emission model (AEM) both overestimated dust emission probability by up to 1 order of magnitude with statistically significant relations, suitable for calibration. Relative to the AEM calibrated to DPS, the exemplar TEM overestimated large dust emission over vast vegetated areas and produced considerable false change in dust emission. Tuning dust cycle models to DOD has very likely hidden, for more than two decades, these TEM weaknesses with implications for our understanding of Earth's systems. Considerable potential exists for new insights of dust-climate in Earth System Models by using AEM with prognostic albedo.

Technical Abstract: Large-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.