Affiliation: College of Arts and Sciences, Curriculum in Environment and Ecology
Ingesting MODIS satellite derived leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and albedo into the Pleim-Xiu (PX) land surface model (LSM) in the combined meteorology and air quality modeling system WRF/CMAQ, composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ), adds realism to the system especially for vegetation fractional coverage in western drylands because the PX LSM intentionally exaggerates vegetation coverage in these sparsely vegetated areas for more effective soil moisture nudging for surface temperature and water vapor mixing ratio estimations. Initial simulations with realistic MODIS vegetation show mixed results with greater error and bias in daytime temperature and greater high bias for ozone concentrations but reduced error and bias in moisture over the western arid regions. Incorporating yearlong MODIS input into an updated WRF/CMAQ with recent improvements in vegetation, soil, and boundary layer processes results in improved 2 m temperature (T) and mixing ratio (Q), 10 m wind speed, and surface ozone simulations across the U.S. WRF/CMAQ 12km domain compared to the initial simulations. Yearlong MODIS input helps reduce bias of the 2 m Q estimation during the growing season from April to September. Improvements follow the green up in the southeast from April and move towards the west and north through August. A coupled photosynthesis-stomatal conductance model with two-big leaf canopy scaling (PX PSN) is developed for the PX LSM in a diagnostic box model. The PX PSN shows distinct advantages in simulating latent heat over landscapes with short vegetation such as grassland and cropland. The advanced approach performs exceptionally well in simulating ozone deposition velocity and flux while the current PX approach significantly overestimates.