Dr. Yongjie Huang (黄永杰) currently works at the Center for Analysis and Prediction of Storms (CAPS), University of Oklahoma. His primary research interests include,
Huang, Y., Wu, W., McFarquhar, G. M., Wang, X., Morrison, H., Ryzhkov, A., Hu, Y., Wolde, M., Nguyen, C., Schwarzenboeck, A., Milbrandt, J., Korolev, A. V., and Heckman, I., 2020: Microphysical Processes Producing High Ice Water Contents (HIWCs) in Tropical Convective Clouds during the HAIC-HIWC Field Campaign: Evaluation of Simulations Using Bulk Microphysical Schemes. Atmos. Chem. Phys. Discuss., in review. https://doi.org/10.5194/acp-2020-1045. Download
Phased-array radar (PAR) technology offers the flexibility of sampling the storm and clear-air regions with different update times. As such, the radial velocity from clear-air regions, typically with lower signal-to-noise ratio, can be measured more accurately. Observing system simulation experiments (OSSEs) are conducted to explore the potential value of assimilating clear-air radial velocity observations to improve numerical prediction of supercell thunderstorms. Results show that assimilating environmental clear-air radial velocity can reduce wind errors in the near-storm environment and within the precipitation region. Improvements in the forecast are seen at different stages, especially for the forecast after 30 min. After assimilating clear-air radial velocity observations, the probabilities of updraft helicity and precipitation within the corresponding swaths of the truth simulation increase up to 30–40%. The more accurate track forecast, stronger vertical motion, and better-maintained supercell can be attributed to the better analysis and prediction of the mean environmental winds and linear and nonlinear dynamic forces. Consequently, assimilating clear-air radial velocity produces accurate storm structure (rotating updrafts), updraft size and storm track, and improves the surface accumulated precipitation forecast. These results highlight the potential of assimilating clear-air radial velocity observations to improve numerical weather prediction (NWP) forecasts of supercell thunderstorms (Huang et al., 2020).
Huang, Y., X. Wang, C. Kerr, A. Mahre, T. Yu and D. Bodine, 2020: Impact of assimilating future clear-air radial velocity observations from phased array radar on a supercell thunderstorm forecast: An observing system simulation experiment study. Monthly Weather Review, 148 (9), 3825–3845. https://doi.org/10.1175/MWR-D-19-0391.1. Download
"On May 7, 2017, an extreme rainstorm dumped 20 inches of rain on Guangzhou, China, most of it falling in just six hours.
The record-breaking rainfall inundated the populous city along the Pearl River in southern China requiring thousands to be evacuated and causing devastating damage.
That day, weather forecasters had predicted only moderate showers.
To understand the driving forces that caused the predicted showers to instead become a deluge, scientists at NCAR ran a very large eddy simulation with the Weather Research and Forecasting model (WRF-LES). This model allows scientists to simulate the interactions between the complex urban environment and that atmosphere at extremely fine scales.
The scientists -- Yongjie Huang, Yubao Liu, Yuewei Liu, and Jason Knievel -- were able to successfully simulate the intense period of rainfall over the city in the model, which could help improve weather forecasts of such events in the future. They also found that the urban area itself affected the timing and location of the storm and helped concentrate the rainfall. Learn more about the study in the JGR Atmospheres (Huang et al., 2019a)." Facebook Twitter Instagram
Further, budget analyses are used to investigate what structure can generate the extreme hourly rainfall of 184.4 mm during this severe local storm (Huang et al., 2019b).
Besides, cloud microphysics sensitivity experiments and microphysics budgets are conducted to investigate how the interaction between dynamics and
microphysics influences the storm development, convection propagation and surface precipitation. Results show that: The latent heating from the
water vapor condensation dominates the convection initiation and storm development. The latent cooling from the
rain water evaporation dominates the cold pool intensity and distribution, which influences the storm moving and subsequent convection propagation,
and finally the intensity and distribution of surface precipitation (Huang et al., 2020).
School of Meteorology
University of Oklahoma
Room 5310, 120 David L. Boren Blvd.
Norman, OK 73072