Second place award of 2019 RMDS data science competition (2019)
Galileo circle scholarship, University of Arizona (2018)
Best group presentation award, DOE ARM summer training and science applications, Oklahoma (2015)
Tian, J., Dong, X., Xi, B., and Feng, Z. (2020), Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains. J. Hydrometeor., 21, 317–334, https://doi.org/10.1175/JHM-D-19-0176.1
Tian, J., Dong, X., Xi, B., Williams, C. R., and Wu, P. (2019), Estimation of liquid water path below the melting layer in stratiform precipitation systems using radar measurements during MC3E, Atmos. Meas. Tech., 12, 3743–3759, https://doi.org/10.5194/amt-12-3743-2019.
Tian, J., Dong, X., Xi, B., Minnis, P., Smith, W. L., Jr, Sun-Mack, S., … Wang, J.(2018), Comparisons of ice water path in deep convective systems among ground-based, GOES, and CERES-MODIS retrievals. Journal of Geophysical Research: Atmospheres, 123, 1708–1723. https://doi.org/10.1002/2017JD027498
Tian, J., Dong, X., Xi, B., Wang, J., Homeyer, C. R., McFarquhar, G. M., and Fan, J. (2016), Retrievals of ice cloud microphysical properties of deep convective systems using radar measurements, Journal of Geophysical Research: Atmosphere., 121,10 ,820–10,839, https://doi.org/10.1002/2015JD024686
Tian, J. and Wu, P. (2019) Prediction of tropical cyclone intensity change using advance machine learning techniques, 2019 RMDS data science competition 2nd-place winner report.