Evaluation of WRF-Chem aeolian dust emission and land surface models over the dust belt.

Aeolian dust is a key component of the Earth system, influencing biogeochemical cycle, cloud microphysics, and the radiative energy budget and atmospheric dynamics, while also degrading air quality around major source regions. Large uncertainties persist in simulating atmospheric dust emission and transport, arising from the complex coupling between surface properties, boundary-layer processes, and atmospheric forcing. 

Previous efforts to evaluate the dust modelling performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) have mostly relied on short-term or region-specific case studies, typically focused on individual dust outbreaks or restricted geographical domains.
In this study, we present a comprehensive, year-long evaluation of WRF-Chem (v4.7.1) over the dust belt spanning North Africa, the Middle East, and Central Asia. We evaluate an ensemble of six simulations using three widely applied dust emission schemes (GOCART, AFWA, and UoC) combined with two advanced land surface models (LSM): Noah-MP and CLM4. The ensemble model output is assessed against multiple observation and reanalysis datasets, including AERONET aerosol optical depth (AOD), the MODIS-derived MIDAS dust optical depth product, and ERA5-Land surface fields of soil moisture and wind speed, which control dust emission fluxes. 

Our analysis shows that land-surface representation exerts a strong influence on dust emission magnitude and spatial distribution, with Noah-MP yielding systematically higher agreement with observed meteorology and AOD. Among the dust emission schemes, AFWA performs most consistently, while UoC04 exhibits lower precision. Empirical scaling factors are derived for each dust emissions–LSM pairing.To our knowledge this is the first year-round, multi-scheme assessment of WRF-Chem dust performance, offering guidance for improved dust forecasting and climate applications.