Multi-spectral sensitivity studies for the retrieval of tropospheric and lowermost tropospheric ozone from simulated clear-sky GEO-CAPE measurements

One of the important science requirements of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission is to be able to measure ozone with two degrees of freedom in the troposphere and sensitivity in the lowest 2 km (lowermost troposphere, LMT), in order to characterize air quality and boundary layer transport of pollution. Currently available remote sensing techniques utilize backscattered solar ultraviolet (UV) radiances or thermal infrared (TIR) emissions to perform ozone retrievals. However, in the TIR, measurement sensitivity to the LMT requires high thermal contrast between the Earth's surface and the near-surface (tens to hundreds of meters above surface) atmosphere, while in the UV, the measurement sensitivity to the LMT is low because of Rayleigh scattering. In this paper, we explore the feasibility of using multi-spectral intensity measurements in the UV, visible (VIS), mid infrared (MIR) and TIR, and polarization measurements in the UV/VIS, to improve tropospheric and lowermost tropospheric ozone retrievals.Simulations for 16 cloud and aerosol free atmospheric profiles spanning a range of ozone mixing ratios indicate that adding VIS measurements to UV measurements significantly enhances the sensitivity to lowermost tropospheric ozone, but only makes a slight improvement to the total degrees of freedom for signal (DFS). On the other hand, the combination of UV and TIR significantly improves the total DFS as well as the lowermost tropospheric DFS.The analysis presented here is a necessary and important first step for defining spectral regions that can meet the GEO-CAPE measurement requirements, and subsequently, the requirements for instrumentation. In this work, the principle of multi-spectral retrievals has been extended from previously published literature and we show that the UV + VIS, UV + TIR and UV + VIS + TIR combinations have the potential to meet the GEO-CAPE measurement requirements for tropospheric ozone. Our analysis includes errors from water and surface properties; further analysis is needed to include temperature, additional gas interferents, clouds, aerosols and more realistic surface properties. These simulations must be run on a much larger dataset, followed by OSSEs (Observing System Simulation Experiments), where simulated retrievals are assimilated into chemical-transport models, to quantitatively assess the impact of the proposed measurements for constraining the spatiotemporal distribution of ozone in the LMT for basic science studies and applications such as air quality forecasts.