Satellite soil moisture data assimilation impacts on modeling weather variables and ozone in the southeastern US-part I: an overview

This study evaluates the impact of satellite soil moisture (SM) data assimilation (DA) on regional weather and ozone (O3) modeling over the southeastern US during the summer. Satellite SM data are assimilated into the Noah land surface model using an ensemble Kalman filter approach within National Aeronautics and Space Administration’s Land Information System framework, which is semicoupled with the Weather Research and Forecasting model with online Chemistry (WRF-Chem, 15 standard version 3.9.1.1). The DA impacts on the model performance of SM, weather states and energy fluxes show strong spatiotemporal variability. Dense vegetation and water use from human activities unaccounted for in the modeling system are among the factors impacting the effectiveness of the DA. The daytime surface O3 responses to the DA can largely be explained by the temperature-driven changes in biogenic emissions of volatile organic compounds and soil nitric oxide, chemical reaction rates, as well as dry deposition velocities. On a near-biweekly timescale, the DA modified the mean daytime and daily 20 maximum 8 h-average surface O3 by up to 2-3 ppbv, with the maximum impacts occurring in areas where daytime surface air temperature most strongly (i.e., by ~2 K) responded to the DA. The DA impacted WRF-Chem upper tropospheric O3 (e.g., for its daytime-mean, by up to 1-1.5 ppbv) partially via altering the transport of O3 and its precursors from other places as well as in-situ chemical production of O3 from lightning and other emissions. Case studies during airborne field campaigns suggest that the DA improved the model treatment of convective transport and/or lightning production. In the cases that the DA 25 improved the modeled SM, weather fields and some O3-related processes, its influences on the model’s O3 performance at various altitudes are not always as desirable, due to the uncertainty in the model’s key chemical inputs (e.g., anthropogenic emissions), as well as the shortcomings in model parameterizations (e.g., chemical mechanism, natural emission, photolysis and deposition schemes) and the model representation of stratosphere-troposphere exchanges. This study also shows that, WRF-Chem upper tropospheric O3 response to the DA has comparable magnitudes with its response to the estimated US 30 anthropogenic emission changes within two years. As reductions in anthropogenic emissions in North America would benefit the mitigation of O3 pollution in its downwind regions, this analysis highlights the important role of SM in quantifying air pollutants’ source-receptor relationships between the US and its downwind areas. It also emphasizes that using up-to-date Deleted: SM Deleted: SM 35 Deleted: WRF-Chem Deleted: Many factors may have impacted the effectiveness of the SM DA, including Deleted: used, such as irrigation, as well as dense vegetation and complex terrain discussed in detail in a previous study. 40 Deleted: WRF-Chem weather fields due to the SM DA modified various model processes critical to its surface O3 fields, such as Deleted: isoprene Deleted: emissions, photochemical reactions Deleted: . 45 Deleted: SM Deleted: SM Deleted: It is shown