A Theoretical Model for Predicting Visibility During Dust Events

A physically based framework is developed to predict horizontal visibility during dust events by linking surface wind erosion, dust emission, near-surface dust concentration, and visibility. An analytical concentration–visibility relationship is derived using a heuristic closure condition. Dust concentration is further related to wind forcing through saltation-controlled dust emission and steady-state mass conservation, while a moment-balance entrainment model incorporates median particle size and soil cohesion into the threshold friction velocity. The concentration–visibility relationship is evaluated using observations from three published studies and captures the overall variation in the combined dataset with R2 = 0.62. Under the same calibration conditions, the proposed relationship achieved the highest R2 among all formulations examined, indicating that its functional form more effectively captures the nonlinear dependence of visibility on dust concentration in the combined dataset. By linking surface erodibility and aerodynamic forcing to atmospheric dust loading and visibility, the framework provides a physically based approach for dust-event visibility prediction. Further evaluation of the complete model chain requires synchronized observations of surface properties, particle entrainment, dust emission, concentration, and visibility.

Authors

Institutions

Publication Details

Journal
Atmosphere
Published
2026-09-16
DOI
https://doi.org/10.3390/atmos17090902
Primary Topic
Aeolian processes and effects
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

A Theoretical Model for Predicting Visibility During Dust Events

Weiguang Tian, Jun Lü, Jin Li, Yang Meng et al.
Atmosphere
Aeolian processes and effects
article

A Theoretical Model for Predicting Visibility During Dust Events

Weiguang Tian, Jun Lü, Jin Li, Yang Meng, Xiaoqian Ma
article en

Abstract

A physically based framework is developed to predict horizontal visibility during dust events by linking surface wind erosion, dust emission, near-surface dust concentration, and visibility. An analytical concentration–visibility relationship is derived using a heuristic closure condition. Dust concentration is further related to wind forcing through saltation-controlled dust emission and steady-state mass conservation, while a moment-balance entrainment model incorporates median particle size and soil cohesion into the threshold friction velocity. The concentration–visibility relationship is evaluated using observations from three published studies and captures the overall variation in the combined dataset with R2 = 0.62. Under the same calibration conditions, the proposed relationship achieved the highest R2 among all formulations examined, indicating that its functional form more effectively captures the nonlinear dependence of visibility on dust concentration in the combined dataset. By linking surface erodibility and aerodynamic forcing to atmospheric dust loading and visibility, the framework provides a physically based approach for dust-event visibility prediction. Further evaluation of the complete model chain requires synchronized observations of surface properties, particle entrainment, dust emission, concentration, and visibility.

AtmosphereVol. 17(9)
Universitätsklinikum Erlangen (DE), Lanzhou University (CN)
Life in Land
Openalex Percentile: Top 12%
Aeolian processes and effects
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.