A new framework for evaluating dust emission model development using dichotomous satellite observations of dust emission
Dust models are essential for understanding the impact of mineral dust on Earth’s systems, human health, and global economies, but dust emission modelling has large uncertainties. Satellite observations of dust emission point sources (DPS) provide a valuable dichotomous inventory of regional dust emissions. We develop a framework for evaluating dust emission model performance using existing DPS data before routine calibration of dust models. To illustrate this framework’s utility and arising insights, we evaluated the albedo-based dust emission model (AEM) with its areal (MODIS 500 m) estimates of soil surface wind friction velocity (us*) and common, poorly constrained grain-scale entrainment threshold (u*ts) adjusted by a function of soil moisture (H). The AEM simulations are reduced to its frequency of occurrence, P(us* > u*tsH). The spatio-temporal variability in observed dust emission frequency is described by the collation of nine existing DPS datasets. Observed dust emission occurs rarely, even in North Africa and the Middle East, where DPS frequency averages 1.8 %, (~7 days y− 1), indicating extreme, large wind speed events. The AEM coincided with observed dust emission ~71.4 %, but simulated dust emission ~27.4 % when no dust emission was observed, while dust emission occurrence was over-estimated by up to 2 orders of magnitude. For estimates to match observations, results showed that grain-scale u*ts needed restricted sediment supply and compatibility with areal us*. Failure to predict dust emission during observed events, was due to us* being too small because reanalysis winds (ERA5-Land) were averaged across 11 km pixels, and inconsistent with us* across 0.5 km pixels representing local maxima. Assumed infinite sediment supply caused the AEM to simulate dust emission whenever P(us*>u*tsH), producing false positives when wind speeds were large. The dust emission model scales of existing parameterisations need harmonising and a new parameterisation for u*ts is required to restrict sediment supply over space and time.
Funding
USA National Science Foundation (EAR-1853853)
Collaborative Research: NSFGEO-NERC: Aeolian dust responses to regional ecosystem change
Natural Environment Research Council
Find out more...History
School
- Social Sciences and Humanities
Department
- Geography and Environment
Published in
Science of The Total EnvironmentVolume
912Publisher
ElsevierVersion
- VoR (Version of Record)
Rights holder
© The AuthorsPublisher statement
This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2023-12-07Publication date
2023-12-13Copyright date
2023ISSN
0048-9697eISSN
1879-1026Publisher version
Language
- en