Climate and Space Sciences and Engineering
CSRB 1541AClimate & Space Research Building University of Michigan 2455 Hayward Street Ann Arbor, MI 48109-2143
Cloud microphysics & macrophysics; Atmospheric radiation; Remote sensing; Climate simulation.
Publications in English:
1. 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. J. Climate, 32, 4409–4430, https://doi.org/10.1175/JCLI-D-18-0789.1.
2. Michibata, T., Suzuki, K., Ogura, T., and Jing, X.: Incorporation of inline warm rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation, Geosci. Model Dev., 12, 4297–4307, https://doi.org/10.5194/gmd-12- 4297-2019, 2019. 3
3. Stephens G. L., M. Christensen, T. Andrews, J. Haywood, F. Malavelle, K. Suzuki, X. Jing, M. Lebsock, J. L. Li, H. Takahshi, and O. Sy, 2019. Cloud Physics from Space, Q. J. Royal Meteorol. Soc., https://doi.org/10.1002/qj.3589.
4. Maloney, E.D., A. Gettelman, Y. Ming, J.D. Neelin, D. Barrie, A. Mariotti, C. Chen, D.R. Coleman, Y. Kuo, B. Singh, H. Annamalai, A. Berg, J.F. Booth, S.J. Camargo, A. Dai, A. Gonzalez, J. Hafner, X. Jiang, X. Jing, D. Kim, A. Kumar, Y. Moon, C.M. Naud, A.H. Sobel, K. Suzuki, F. Wang, J. Wang, A.A. Wing, X. Xu, and M. Zhao, 2019: Process-Oriented Evaluation of Climate and Weather Forecasting Models. Bull. Amer. Meteor. Soc., 100, 1665- 1686, https://doi.org/10.1175/BAMS-D-18-0042.1.
5. Jing X., and K. Suzuki, 2018. The impact of process-based warm rain constraints on the aerosol indirect effect. Geophys. Res. Lett., 45, 10,729–10,737, https://doi.org/10.1029/2018GL079956.
6. Jing X., H. Zhang, M. Satoh, and S. Zhao, 2018. Improving Representation of Tropical Cloud Overlap in GCMs Based on Cloud-Resolving Model Data. J. Meteor. Res., 32(2), 233-245, https://doi.org/10.1007/s13351-018-7095-9.
7. 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, J. Geophys. Res., 122, 11,806-11,824, https://doi.org/10.1002/2017JD027310. (Featured by J. Geophys. Res. atmosphere)
8. Zhao S., H. Zhang, Z. Wang, and X. Jing, 2017. Simulating the Effects of Anthropogenic Aerosols on Terrestrial Aridity Using an Aerosol–Climate Coupled Model. J. Climate, 30, 7451–7463, https://doi.org/10.1175/JCLI-D-16-0407.1.
9. Zhang F., K. Wu, P. Liu, X. Jing, and J. Li, 2017. Accounting for Gaussian quadrature in four-stream radiative transfer algorithms, J. Quantitative Spectroscopy and Radiative Transfer, 192, 1–13, https://doi.org/10.1016/j.jqsrt.2017.01.040.
10. Tang W., K.Yang, J. Qin, X. Niu, C. Lin, and X. Jing, 2017. A revisit to decadal change of aerosol optical depth and its impact on global radiation over China, Atmospheric Environment, 150, 106–115, https://doi.org/10.1016/j.atmosenv.2016.11.043.
11. Jing X., H. Zhang, J. Peng, J. Li, and H. Barker, 2016. Cloud Overlapping parameter Obtained from CloudSat/CALIPSO Dataset and Its Application in AGCM with McICA Scheme. Atmospheric Research, 170: 52–65, https://doi.org/10.1016/j.atmosres.2015.11.007.
12. Zhang H. and X. Jing* (corresponding author), 2016. Advances in Studies on Cloud Overlap and Its Radiative Transfer in Climate Models. J. Meteor. Res., 30, 156–168, https://doi.org/10.1007/s13351-016-5164-5.
13. Zhang H., Z. Wang, F. Zhang, and X. Jing, 2015. Impact of four-stream radiative transfer algorithm on aerosol direct radiative effect and forcing. Int. J. Climatol., 35: 4318–4328, https://doi.org/10.1002/joc.4289.
14. Zhang H., X. Jing, and J. Li, 2014. Application and evaluation of a new radiation code under McICA scheme in BCC_AGCM2.0.1. Geosci. Model Dev. 7(3): 737– 4 754, https://doi.org/10.5194/gmd-7-737-2014.
15. Jing X. and H. Zhang, 2013. Application and evaluation of McICA scheme in BCC_AGCM2.0.1. AIP Conference Proceedings, 1531, 756–759, https://doi.org/10.1063/1.4804880.
16. Wang Z., H. Zhang, J. Li, X. Jing, and P. Lu, 2013. Radiative forcing and climate response due to the presence of black carbon in cloud droplets, J. Geophys. Res. Atmos., 118, 3662–3675, https://doi.org/10.1002/jgrd.50312.
17. Wang Z., H. Zhang, X. Jing, X. Wei, 2013. Effect of non-spherical dust aerosol on its direct radiative forcing, Atmospheric Research, 120–121, 112–126.
18. Zhang H., J. Peng, X. Jing, and J. Li, 2013. The features of cloud overlapping in Eastern Asia and their effect on cloud radiative forcing. Sci. China Earth Sci. 56: 737–747, https://doi.org/10.1007/s11430-012-4489-x.
19. Lu P., H. Zhang, and X. Jing, 2012. The effects of different HITRAN versions on calculated long-wave radiation and uncertainty evaluation. Acta Meteorol. Sin. 26: 389–398, https://doi.org/10.1007/s13351-012-0310-1.
Selected publications in Chinese:
20. Zhang H., P. Lu, X. Jing, 2015. Application of Two-Four Stream Spherical Harmonic Expansion Approximation in a Global Climate Model. Chinese Journal of Atmospheric Sciences (in Chinese), 39(1): 137–144, https://doi.org/10.3878/j.issn.1006-9895.1404.13316.
21. Jing X., H. Zhang, 2012. Application and Evaluation of McICA Cloud-Radiation Framework in the AGCM of the National Climate Center. Chinese Journal of Atmospheric Sciences (in Chinese), 36(5): 945–958, https://doi.org/10.3878/j.issn.1006-9895.2012.11155.
22. Zhang H., X. Jing, 2010. Effect of cloud overlap assumptions in climate models on modeled earth-atmosphere radiative fields. Chinese Journal of Atmospheric Sciences (in Chinese), 34(3): 520–532, http://doi.org/10.3878/j.issn.1006- 9895.2010.03.06.
23. Jing X., H. Zhang, P. Guo, 2009. A Study of the Effect of Sub-grid Cloud Structure on Global Radiation in Climate Models. Acta Meteorologica Sinica (in Chinese), 67(6): 1058–1068, https://doi.org/10.11676/qxxb2009.102.