Simulating the effects of chronic ozone exposure on hydrometeorology and crop productivity using a fully coupled crop, meteorology and air quality modeling system

摘要

In this study, the Noah-Multiparameterization with Crop land surface model in the Weather Research and Forecasting (WRF) with Chemistry (WRF/Chem) model is modified to include the effects of chronic ozone exposure (COE) on plant conductance and photosynthesis (PCP) found from field experiments. Based on the modified WRF/Chem, the effects of COE on regional hydrometeorology and crop productivity have been investigated over the central United States. Our results indicate that the model in its current configuration can reproduce the rainfall and temperature patterns of the observations and reanalysis data, although it overestimates rainfall. The model underestimates daily maximum 8-hour average ozone concentrations by 4–7?ppb compared with ozone observations from the Clean Air Status and Trend Network. The experimental tests on the effects of COE include setting different thresholds of ambient ozone concentrations ([O3]) and using linear regressions to quantify PCP against the COE. Compared with the WRF/Chem control run (i.e., without considering the effects of COE), the modified model at different experimental setups consistently improves the simulated estimates of rainfall and temperatures. The simulations in June, July, August, and September of 2009–2014 show that, over crop lands, surface [O3] decrease latent heat fluxes (LH) by 9 to 11?W/m2, increase surface air temperatures (T2) by 0.6 to 0.7?°C with the daily maximum temperature increasing up to 1?°C, and decrease rainfall by 0.15 to 0.21?mm per day by mostly reducing convective rainfall. Additionally, surface [O3] decrease crop yields by 18–23%, decrease Gross Primary Productivity (GPP) by 30%–38% in a domain average and up to 50% in some areas, and decrease crop yields by 30–45%, all of which highly depends on the precise experimental setup, especially the [O3] threshold. The mechanism producing these results is also discussed. Employing this modified WRF/Chem model in any high [O3] region can more precisely elucidate the interactions of vegetation, meteorology, chemistry/emissions, and crop productivity.