Qingyu Wang is a PhD student at the University of Oklahoma. She works with Dr. Sean Crowell on CO2 flux and transport and helps evaluate a coupled mesoscale atmospheric and biospheric Model (WRF-VPRM) by Dr. Xiao-Ming Hu. She attained her bachelor’s degree at Nanjing University, China in 2016, where she participated in research on Observation of Particle Structures and Variations inside Precipitation System by Using C-band Dual-Polarimetric Radar Data. In 2019, she earned her MS at OU, working on Atmospheric Variations in Column Integrated CO 2 over the U.S.
Characterization of the critical mechanisms that underpin land-surface processes is fundamental in quantifying and distinguishing the interactions and feedbacks between the planetary boundary layer (PBL), the land surface, and the subsurface layer under different soil-vegetation system conditions. The estimation of surface energy fluxes, especially sensible heat flux (H) and latent heat flux (LE), are considered as strongly related to vegetation photosynthesis, PBL turbulence, and atmospheric convection. We optimize the six most sensitive parameters with a 10-day simulation (April 2 – 11, 2016) in Noah-Multiparameterization Land Surface Model (Noah-MP LSM) at Southern Great Plains (SGP) using Bayesian optimization. The implementation of Noah-MP in the single-column weather research and forecasting (WRF) model and the application of Bayesian optimization essentially reduce the computational cost. Noah-MP with optimized parameters increases (decreases) the H (LE), which was underestimated (overestimated) by Noah-MP with original parameters compared to flux tower observations (AmeriFlux). The estimation of state variables, including 2-meter temperature, 2-m specific humidity, and 10-m wind speed, are also improved with optimized parameters. The optimized parameters also result in better simulations of H and LE on longer time scales (April and May) and another year (2017) at SGP, whereas not necessarily improve other rainfed cropland site (e.g., US-Ne3). In response to the change of surface energy fluxes and state variables, the vertical rectifier effects of CO2 are enhanced – ~2.5 ppm at night and ~1.5 ppm in the daytime, suggesting adjusting soil parameters and/or surface energy flux strength can enhance or diminish diurnal vertical rectifier effect.