The EMIT Mission Information Yield for Mineral Dust Radiative Forcing

The net direct radiative effect of mineral dust is a large uncertainty in global radiative forcing. To address this challenge, NASA's Earth Mineral dust source InvesTigation (EMIT) will map the surface mineralogy of Earth's desert dust source regions, constraining the composition of mineral dust aerosol for use in Earth system models (ESMs). This mission foreshadows multiple future global spectroscopic investigations for which coupling with ESMs will play a critical role. Planning such experiments requires a methodology for assessing the impact of uncertain remote observations on ESM accuracy. We design and implement an end-to-end simulation of the EMIT mission, leveraging Bayesian statistical methods and Monte Carlo sampling to analyze uncertainties in the retrieval and processing of EMIT data products. Special focus is placed on those uncertainties caused by atmospheric water vapor and aerosol loading conditions likely to be encountered by EMIT. We apply these results to a single-column configuration of the Community Earth System Model (CESM), revealing the potential impact of EMIT observations on radiative forcing estimates. We show that EMIT data stand to significantly reduce uncertainty in estimates of the dust direct radiative forcing attributable to uncertainties in surface mineralogies that are input to ESMs, and that the information gain for radiative forcing comes predominantly from better constraining iron oxides, which dominate the shortwave radiative effects of aerosol dust.