资源环境科技发展态势分析平台

This study examines the influence of insolation and cloud retrieval products from the Geostationary Operational Environmental Satellite (GOES) system on biogenic emission estimates and ozone simulations in Texas. Compared to surface pyranometer observations, satellite-retrieved insolation and photosynthetically active radiation (PAR) values tend to systematically correct the overestimation of downwelling shortwave radiation in the Weather Research and Forecasting (WRF) model. The correlation coefficient increases from 0.93 to 0.97, and the normalized mean error decreases from 36% to 21%. The isoprene and monoterpene emissions estimated by the Model of Emissions of Gases and Aerosols from Nature are on average 20% and 5% less, respectively, when PAR from the direct satellite retrieval is used rather than the control WRF run. The reduction in biogenic emission rates using satellite PAR reduced the predicted maximum daily 8h ozone concentration by up to 5.3ppbV over the Dallas-Fort Worth (DFW) region on some days. However, episode average ozone response is less sensitive, with a 0.6ppbV decrease near DFW and 0.3ppbV increase over East Texas. The systematic overestimation of isoprene concentrations in a WRF control case is partially corrected by using satellite PAR, which observes more clouds than are simulated by WRF. Further, assimilation of GOES-derived cloud fields in WRF improved CAMx model performance for ground-level ozone over Texas. Additionally, it was found that using satellite PAR improved the model's ability to replicate the spatial pattern of satellite-derived formaldehyde columns and aircraft-observed vertical profiles of isoprene.

Plain Language Summary Models have long struggled to accurately estimate emissions of hydrocarbons from vegetation. Those emissions strongly influence concentrations of pollutants such as ozone and particulate matter. Errors in modeling of cloudiness and solar radiation may contribute to errors in estimates of biogenic emissions, which vary with the intensity of sunlight reaching vegetation. This study applies satellite retrievals of sunlight and cloudiness to adjust model estimates of hydrocarbon emissions from vegetation in a modeling episode over Texas. It then tests how those adjustments influence estimates of ozone, particulate matter, and formaldehyde. Pollutant measurements from satellites, aircraft, and ground-based monitors are used to evaluate model results.