Contact Information
Biography
Dr. Zhuo Wang's research interests are primarily in the fields of tropical meteorology and climate dynamics, including tropical cyclones, intraseasonal variability, tropical-extratropical interaction, subseasonal to seasonal prediction and predictability. The research objective is to better understand the fundamental dynamics and physics governing atmospheric motions and to improve the prediction skills.
Education
- Ph.D. Meteorology, University of Hawaii, 2004
- M.S. Meteorology, University of Hawaii, 2000
- B.S. Atmospheric Sciences, Nanjing University, 1997
Additional Campus Affiliations
Professor, Center for Global Studies
Recent Publications
Miller, D. E., Wang, Z., Li, B., Harnos, D. S., & Ford, T. (2021). Skillful subseasonal prediction of U.S. Extreme warm days and standardized precipitation index in boreal summer. Journal of Climate, 34(14), 5887-5898. https://doi.org/10.1175/JCLI-D-20-0878.1
YAN, ZIYU., GE, XUYANG., WANG, ZHUO., WU, CHUN. CHIEH., & PENG, MELINDA. (2021). Understanding the impacts of upper-tropospheric cold low on typhoon jongdari (2018) using piecewise potential vorticity inversion. Monthly Weather Review, 149(5), 1499-1515. https://doi.org/10.1175/MWR-D-20-0271.1
Zhang, G., Murakami, H., Cooke, W. F., Wang, Z., Jia, L., Lu, F., Yang, X., Delworth, T. L., Wittenberg, A. T., Harrison, M. J., Bushuk, M., McHugh, C., Johnson, N. C., Kapnick, S. B., Tseng, K. C., & Zhang, L. (2021). Seasonal predictability of baroclinic wave activity. npj Climate and Atmospheric Science, 4(1), [50]. https://doi.org/10.1038/s41612-021-00209-3
Zhou, W., Guan, K., Peng, B., Wang, Z., Fu, R., Li, B., Ainsworth, E. A., DeLucia, E., Zhao, L., & Chen, Z. (2021). A generic risk assessment framework to evaluate historical and future climate-induced risk for rainfed corn and soybean yield in the U.S. Midwest. Weather and Climate Extremes, 33, [100369]. https://doi.org/10.1016/j.wace.2021.100369
Chang, C. C., & Wang, Z. (2020). Multiyear hybrid prediction of Atlantic tropical cyclone activity and the predictability sources. Journal of Climate, 33(6), 2263-2279. https://doi.org/10.1175/JCLI-D-19-0475.1
