Xianwen Jing

Xianwen Jing

Associate Professor

Welcome to GoART!


GoART (Group of Applied Radiative Transfer) is a small group of people led by Prof. Xianwen Jing, aiming at enhancing the application of radiative transfer tools in various areas, such as climate models, solar energy, and remote sensing. Our research topics include developing parameterization methods for better atmospheric radiative transfer simulations, investigating processes that interact with radiative transfer (e.g., aerosol-cloud-radiation interaction, surface reflection), and solving practical problems associated with solar energy harvest.

News

  • New paper published: Kong, Chenxi, Xianwen Jing, Xiaorui Niu, and Jing Jing. 2025. "Implications of Spaceborne High-Resolution Solar Spectral Irradiance Observation for the Assessment of Surface Solar Energy in China". Energies, 18(5): 1221. https://doi.org/10.3390/en18051221 (Mar 2, 2025)
  • NASA reported our paper: . New NASA Data Sheds (Sun) Light on Climate Models (May 15, 2021)
  • New paper published: Jing, X., Xianglei Huang, Xiuhong Chen, Dong L. Wu, Peter Pilewskie, Odele Coddington, Erik Richard, 2021. Direct influence of solar spectral irradiance on the high-latitude surface climate. Journal of Climate, 34(10), 4145-4158, https://doi.org/10.1175/JCLI-D-20-0743.1 (Mar 29, 2021)
  • Highlighted young scientist: Xianwen Jing got highlighted on the newsletter of the Scientific Committee on Solar-Terrestrial Physics (SCOSTEP). PDF (Jan 26, 2021)

Selected Publications

  • Kong, C., Jing X., Niu X., and Jing J. 2025. Implications of Spaceborne High-Resolution Solar Spectral Irradiance Observation for the Assessment of Surface Solar Energy in China. Energies, 18(5): 1221. https://doi.org/10.3390/en18051221
  • Jing, X., Xianglei Huang, Xiuhong Chen, Dong L. Wu, Peter Pilewskie, Odele Coddington, Erik Richard, 2021. Direct influence of solar spectral irradiance on the high-latitude surface climate. Journal of Climate, 34(10), 4145-4158, https://doi.org/10.1175/JCLI-D-20-0743.1. (NASA News Reported)
  • Jing, X., K. Suzuki, and T. Michibata, 2019. The Key Role of Warm Rain Parameterization in Determining the Aerosol Indirect Effect in a Global Climate Model. Journal of Climate, 32, 4409–4430, https://doi.org/10.1175/JCLI-D-18-0789.1.
  • Jing, X., and Suzuki, K., 2018, The impact of process-based warm rain constraints on the aerosol indirect effect. Geophysical Research Letters, 45, 10,729–10,737. https://doi.org/10.1029/2018GL079956.
  • Jing, X., H. Zhang, M. Satoh, S. Zhao, 2018, Improving Representation of Tropical Cloud Overlap in GCMs Based on Cloud-Resolving Model Data. Journal of Meteorological Research, 32(2), https://doi.org/10.1007/s13351-018-7095-9.
  • Jing, X., K. Suzuki, H. Guo, D. Goto, T. Ogura, T. Koshiro, and J. Mülmenstädt, 2017, A multi-model study on warm precipitation biases in global models compared to satellite observations, Journal of Geophysical Research: Atmosphere, 122, 11,806-11,824, https://doi.org/10.1002/2017JD027310. ( Featured on JGR: Atmosphere)