An Improved Dust Emission Modeling With Multiple Endmember Spectral Mixture Analysis

Abstract

Abstract Traditional dust emission schemes typically rely on photosynthetic vegetation (PV) alone when parameterizing key surface properties. Here, we integrate five endmembers from the multiple endmember spectral mixture analysis (MESMA), namely PV, non‐photosynthetic vegetation, bare soil, dark surface, and ice/snow (IS), into a well‐established dust emission scheme to simultaneously constrain surface roughness and the erodible fraction, avoiding the common reliance on PV alone as in traditional dust emission schemes. By evaluating three severe dust events in East Asia in 2021, 2023, and 2024, the MESMA‐constrained configurations reduce total dust emissions by 22.2%–49.7% and show substantially improved agreement with station observations. By enabling a physically realistic characterization of dryland surface heterogeneity through multiple endmembers, this approach substantially alleviates the systematic overestimation that is typical when using PV‐based parameterizations.