The EMIT mission information yield for mineral dust radiative forcing

The influence of mineral dust is one of the largest uncertainties in global radiative forcing. To address this challenge, NASA’s Earth Mineral dust source InvesTigation (EMIT) will map the mineralogy of Earth’s mineral dust forming regions, constraining the composition of mineral dust and reducing uncertainty 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. In this study, we design and implement an end-to-end simulation of EMIT 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 NCAR Community Earth System Model (CESM), revealing the impact of EMIT observations on radiative forcing estimates. We find that EMIT data products stand to significantly reduce uncertainty in estimates of the dust radiative forcing due to uncertainties in surface mineralogies that are input to Earth system models, and that the information gain for radiative forcing closely tracks that for iron oxides, which dominate the radiative effects of aerosol dust.