Satellite soil moisture data assimilation impacts on ozone dry deposition modeling: sensitivity to dry deposition parameterizations

Ozone dry deposition is a major ozone sink. Realistically representing this process in models is important for accurately simulating ozone concentrations and exceedances, as well as assessing ozone impacts on human and ecosystem health. In this work, soil moisture data from NASAs Soil Moisture Active Passive mission are assimilated into a coupled regional-scale modeling system covering the southeastern US based on two different dry deposition schemes (i.e., the Wesely and "dynamic" schemes, in the latter of which the dry deposition parameterization is coupled with photosynthesis and vegetation dynamics). It is demonstrated that, when the "dynamic" scheme is applied, the modeled dry deposition velocities and ozone fluxes are overall larger and more sensitive to soil moisture data assimilation. It is also found that the choice of soil moisture factor controlling stomatal resistance (i.e., the beta factor) scheme affects strongly the quantitative results. Satellite and satellite-derived vegetation, latent/sensible heat fluxes and gross primary productivity products, as well as proxies of gross primary productivity such as satellite-derived solar-induced chlorophyll fluorescence and aircraft carbonyl sulfide data, are also used to help assess the land surface model performance and indirectly indicate the usefulness of soil moisture data assimilation for improving the modeled flux variables. This study is an extended work of Huang et al. (2021, https://doi.org/10.5194/acp-21-11013-2021), with major updates in the applied land surface model, irrigation and CH (i.e., surface exchange coefficient for heat) schemes. Results from the updated modeling system are compared with those from the Huang et al. (2021) work, based on which the implications for health and agricultural impact assessments are discussed.