A new process-based and scale-respecting dust emission scheme for global climate models

Desert dust is an important aerosol component that produces large uncertainties in assessments of Earth’s radiative budget and global climate change. However, current global climate model (GCM) simulations show that modeled dust poorly captures the observed dust in both spatial and temporal variability, which inhibits accurate assessments of aerosol radiative effects. Furthermore, dust emission is a local-scale process that varies on scales less than 1–10 km and thus current GCMs with typical grid-scale of > 100 km inherently have difficulties capturing dust spatial distribution and its sensitivity to local-scale meteorological variability. To tackle these problems, we develop a new dust emission scheme for GCMs that includes several more physical aeolian processes, and use the Community Earth System Model version 2.1 (CESM2.1) as a case study. First, we account for the dissipation of surface wind momentum by surface roughness elements included plants and rocks, which reduce the wind momentum exerted on the bare soil surface over deserts. The roughness of plants is a function of time-varying leaf area index (LAI), improving the sensitivity of the modeled emissions to climate and land use/land cover (LULC) changes. Second, we account for the effects of soil particle size distribution (PSD) on dust emission threshold by implementing a realistic soil median diameter inferred from a compilation of soil PSD observations. Third, we account for intermittent dust emissions induced by boundary-layer turbulence using a recently proposed saltation parameterization, which further couples dust with boundary-layer dynamics. With more aeolian processes, CESM2 dust emission matches better in spatial variability, seasonality, and dust activation frequency when compared against dust satellite retrievals. Modeled dust aerosol optical depth (DAOD) also shows better agreement in both spatial and temporal correlations with satellite-derived and ground-based AOD. Fourth, in addition to improving the description of aeolian processes, we conduct dust emission simulations across multiple grid resolutions and show that the high-resolution simulations generally produce a better dust spatial distribution. We then generate a map of correction factors to dust emissions for the coarse-gridded simulations to reduce the scale-dependency of dust emission parameterizations, and results indicate further improved agreement with dust observations for coarse-gridded CESM2. Our results suggest that including more physical processes into climate models can lessen bias, improve simulation results, and eliminate the use of empirical source functions. Therefore, our dust emission scheme could improve assessments of dust impacts on the Earth system and future climate changes.