dc.contributor.author
Hennen, Mark
dc.contributor.author
Chappell, Adrian
dc.contributor.author
Webb, Nicholas P.
dc.contributor.author
Schepanski, Kerstin
dc.contributor.author
Baddock, Matthew C.
dc.contributor.author
Eckardt, Frank D.
dc.contributor.author
Kandakji, Tarek
dc.contributor.author
Lee, Jeffrey A.
dc.contributor.author
Nobakht, Mohamad
dc.contributor.author
Holdt, Johanna von
dc.date.accessioned
2024-03-21T12:06:39Z
dc.date.available
2024-03-21T12:06:39Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/42962
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-42676
dc.description.abstract
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 (u(s*)) 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(u(s*) > u(*ts)H). 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 %, (similar to 7 days y(-1)), indicating extreme, large wind speed events. The AEM coincided with observed dust emission similar to 71.4 %, but simulated dust emission similar to 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 u(s*). Failure to predict dust emission during observed events, was due to u(s*) being too small because reanalysis winds (ERA5-Land) were averaged across 11 km pixels, and inconsistent with u(s*)across 0.5 km pixels representing local maxima. Assumed infinite sediment supply caused the AEM to simulate dust emission whenever P(u(s*)>u(*ts)H), 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.
en
dc.format.extent
16 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject.ddc
500 Naturwissenschaften und Mathematik::550 Geowissenschaften, Geologie::550 Geowissenschaften
dc.title
A new framework for evaluating dust emission model development using dichotomous satellite observations of dust emission
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
169237
dcterms.bibliographicCitation.doi
10.1016/j.scitotenv.2023.169237
dcterms.bibliographicCitation.journaltitle
Science of The Total Environment
dcterms.bibliographicCitation.volume
912
dcterms.bibliographicCitation.url
https://doi.org/10.1016/j.scitotenv.2023.169237
refubium.affiliation
Geowissenschaften
refubium.affiliation.other
Institut für Meteorologie
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1879-1026
refubium.resourceType.provider
WoS-Alert