Numerical simulations of a nighttime-generated Tibetan Plateau vortex (TPV) are conducted using the advanced Weather Research and Forecasting (WRF) Model. It is found that the nighttime TPV forms as a result of the merging of convections. Although the WRF Model can reproduce the genesis of the nighttime TPV well, colder and drier biases in the lower atmosphere and drier biases in the upper atmosphere are still presented, thus degrading the simulation performance. Intercomparisons among the experiments indicate that the simulations are more sensitive to land surface schemes than to cloud microphysics schemes. The development of convection is more favorable when daytime surface diabatic heating is vigorous. Surface diabatic heating during daytime plays a dominant role in the development of daytime convection and the genesis of nighttime TPV. Further diagnosis of the PV budget reveals that the obvious increase in PV in the lower atmosphere is associated with the evidently strengthened cyclonic vorticity during TPV genesis. This could be attributed to the increased vertical component of net cross-boundary PV fluxes during the merging of convections as well as the significant positive contribution of diabatic heating effects in the lower atmosphere. Therefore, strong daytime surface diabatic heating, which is essential to convection development, could provide a favorable condition for nighttime TPV genesis. Overall results illuminate the complicated process of TPV genesis.

Accurate forecast and simulation of near-surface wind is a great challenge for numerical weather prediction models due to the significant transient and intermittent nature of near-surface wind. Based on the analyses of the impact of assimilating in situ and Advanced Tiros Operational Vertical Sounder (ATOVS) satellite radiance data on the simulation of near-surface wind during a severe wind event, using the new generation mesoscale Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system, the dynamic downscaling of near-surface wind is further investigated by coupling the microscale California Meteorological (CALMET) model with the WRF and its 3DVAR system. Results indicate that assimilating in situ and ATOVS radiance observations strengthens the airflow across the Alataw valley and triggers the downward transport of momentum from the upper atmosphere in the downstream area of the valley in the initial conditions, thus improving near-surface wind simulations. Further investigations indicate that the CALMET model provides more refined microtopographic structures than the WRF model in the vicinity of the wind towers. Although using the CALMET model achieves the best simulation of near-surface wind through dynamic downscaling of the output from the WRF and its 3DVAR assimilation, the simulation improvements of near-surface wind speed are mainly within 1m s⁻¹. Specifically, the mean improvement proportions of near-surface wind speed are 64.8 for the whole simulation period, 58.7 for the severe wind period, 68.3 for the severe wind decay period, and 75.4 for the weak wind period. The observed near-surface wind directions in the weak wind conditions are better simulated in the coupled model with CALMET downscaling than in the WRF and its 3DVAR system. It is concluded that the simulation improvements of CALMET downscaling are distinct when near-surface winds are weak, and the downscaling effects are mainly manifested in the simulation of near-surface wind directions.

Accurate prediction of near-surface wind based on numerical weather prediction models is essential to promote efficient wind energy harvesting. In this study, the performances of different Boundary Layer (BL) schemes in Weather Research and Forecasting model on the simulation of near-surface wind over complex terrain are investigated. Results indicate that, 1) the observed mean wind speed, its standard deviation and wind power density are evidently larger in Spring (seasonal shift period) than that in other season, with the maximum in April 2008; 2) YSU scheme produces overall higher prediction accuracy of near-surface wind speed, wind power density and ideal energy production than the other schemes, such as MYJ, MYNN, and QNSE, and thus could be regarded as the optimal BL scheme in the research region and the period; 3) further investigations on the simulation results with the YSU scheme suggest that, the simulation of near-surface stability is closely related to the simulation of near-surface wind, however, YSU scheme cannot correctly reflect the daily variation of observed stability in the near-surface layer, which could be the key factor that results in the large simulation errors of near-surface wind, especially during the day-night alternation periods. Overall results imply that using an optimal BL scheme is an effective approach for improving the wind resource utilization and wind power prediction.