• xliang@umd.edu
  • University of Maryland, College Park


Dr. Liang’s research focuses on the development and application of the integrated Earth modeling, which incorporates global general circulation models, mesoscale multi-nested regional climate models, state-of-the-art air quality models, comprehensive emissions inventory models, advanced terrestrial hydrology models, water quality models, and dynamic ecosystem models.

Dr. Liang’s expertise is in the areas of climate dynamics, with the focus on numerical modeling and physical understanding of land-ocean-atmosphere and convection-cloud-radiation interactions, seasonal climate predictions, future climate change projections and environmental consequences (terrestrial hydrology, ecosystem dynamics, air quality, water quality). He has published over 100 peer-reviewed journal articles and led interdisciplinary research projects funded by United States Environmental Protection Agency, National Oceanic and Atmospheric Administration, United States Department of Agriculture, National Science Foundation, National Aeronautics and Space Administration, and United States Department of Energy.

Current Research

[1] Developing improved representations of physical processes and integrated global and regional models to advance numerical simulations of the Earth climate system. In particular, the Climate-Weather Research Forecasting model (CWRF, http://cwrf.umd.edu) along with the Cloud-Aerosol-Radiation ensemble modeling system (CAR, http://car.umd.edu) developed under his leadership provides an unprecedented pathway for tackling major roadblocks in predicting weather and climate variations as well as assessing environmental consequences (terrestrial hydrology, ecosystem dynamics, air quality, water quality) at regional-local scales.

[2] Applying these models to improve seasonal-interannual climate prediction and future climate change projection, focusing on precipitation and terrestrial hydrology, land-ocean-atmosphere and convection-cloud-radiation interactions.

[3] Diagnosing model simulations and observations to understand key physical processes and mechanisms for climate variation and change.


[126]    **Ling, T., M. Xu, X.-Z. Liang, J.X.L. Wang, and Y. Noh, 2015: A multi-level ocean mixed layer model resolving the diurnal cycle: development and validation. J. Adv. Model. Earth Syst. (accepted).

[125]     **Gan, Y., X.-Z. Liang, Q. Duan, H.I. Choi, Y. Dai, and H. Wu, 2014: Stepwise sensitivity analysis from qualitative to quantitative: application to the terrestrial hydrological modeling of a conjunctive surface-subsurface process (CSSP) land surface model. J. Adv. Model. Earth Syst., 10.1002/2014MS000406.

[124]     Chen, L., X.-Z. Liang, D. DeWitt, A.N. Samel, and J.X.L. Wang, 2015: Seasonal prediction of U.S. precipitation and temperature by the nested CWRF-ECHAM system. Climate Dynamics, DOI 10.1007/s00382-015-2619-9.

[123]     Liu, S., J.X.L. Wang, X.-Z. Liang, V. Morris, and S.S. Fine, 2015: A hybrid approach to improve U.S. seasonal climate outlook skills at the regional scale. Climate Dynamics, DOI 10.1007/s00382-015-2594-1.

[122]     *He, H., X.-Z. Liang, H. Lei, and D.J. Wuebbles, 2014: Attribution of future U.S. ozone pollution to regional emissions, long-range transport, climate change, and model deficiency. Atmos. Chem. Phys. Disc.

[121]     **Qiao, F., and X.-Z. Liang, 2015: Effects of cumulus parameterizations on predictions of summer flood in the Central United States. Climate Dynamics, 45, 727-744, DOI: 10.1007/s00382-014-2301-7.

[120]     Shafiee-Jood, M., X. Cai, L. Chen, X.-Z. Liang, and P. Kumar, 2014: Assessing the value of seasonal climate forecast information through an end-to-end forecasting framework: Application to U.S. 2012 drought in central Illinois. Water Resources Research (accepted).

[119]     Xu, M., X.-Z. Liang, A. Samel, and W. Gao, 2014: MODIS consistent vegetation parameter specifications and their impacts on regional climate simulations. J. Climate (accepted).

[118]     Lei, H., D.J. Wuebbles, X.-Z. Liang, Z. Tao, S. Olsen, R. Artz, X. Ren, and M. Cohen, 2014: Projections of atmospheric mercury levels and their effect on air quality in the United States. Atmos. Chem. Phys., 14, 783-795.

[117]     *Liu, S., X.-Z. Liang, W. Gao, and T.J. Stohlgren, 2013: Regional climate model downscaling may improve prediction of alien plant species distribution. Frontiers of Earth Sciences, 1-15, DOI 10.1007/s11707-014-0457-4.

[116]    Barsugli, J.J., G. Guentchev, R.M. Horton, A. Wood, L.O. Mearns, X.-Z. Liang, J.A. Winkler, K. Dixon, K. Hayhoe, R.B. Rood, L. Goddard, A. Ray, L. Buja, and C. Ammann, 2013: “The Practitioner’s dilemma” – How to assess the credibility of downscaled climate projections? EOS, 94, 424-425.

[115]     **Lei, H., X.-Z. Liang, D.J. Wuebbles, Z. Tao, and S. Olsen, 2013: Model analyses of atmospheric mercury: Present air quality and effects of transpacific transport on the United States. Atmos. Chem. Phys., 13, 10807-10825.

[114]     *Zhang, F., X.-Z. Liang, J. Li, and Q.-C. Zeng, 2013: Dominant roles of subgrid-scale cloud structures in model diversity of cloud radiative effects. J. Geophys. Res., 118, 7733-7749, DOI: 10.1002/jgrd.50604.

[113]     Liang, X.-Z., and F. Zhang, 2013: The Cloud-Aerosol-Radiation (CAR) ensemble modeling system. Atmos. Chem. Phys., 13, 8335-8364, doi:10.5194/acp-13-8335-2013.

[112]     Li, J., K. von Salzen, Y. Peng, H. Zhang, and X.-Z. Liang, 2013: Evaluation of black carbon semi-direct radiative effect in a climate model. J. Geophys. Res., 118, 1-14, doi:10.1002/jgrd.50327

[111]    *Zhang, F., X.-Z. Liang, Q.-C. Zeng, Y. Gu, and S. Su, 2013: Cloud-Aerosol-Radiation (CAR) ensemble modeling system: Overall accuracy and efficiency. Adv. Atmos. Sci., 30, 955-973.

[110]     Hejazi, M.I., X. Cai, X. Yuan, X.-Z. Liang, and P. Kumar, 2013: Incorporating short-term forecasts from a regional climate model in an irrigation scheduling optimization problem. Journal of Water Resources Planning and Management, 10.1061/(ASCE)WR.1943-5452.0000365.

[109]     Choi, H.I., X.-Z. Liang, and P. Kumar, 2013: A conjunctive surface-subsurface flow representation for mesoscale land surface models. J. Hydrometeorology, 14, 1421-1442.

[108]     **Chen, Q., X.-Z. Liang, M. Xu, T. Lin, and J.X.L. Wang, 2013: Improvement of cloud radiative forcing and its impact on weather forecasts. Open Atmospheric Science Journal, 7, 1-13, DOI: 10.2174/1874282301307010001.

[107]     *Zhu, J., and X.-Z. Liang, 2013: Impacts of the Bermuda high on regional climate and air quality over the United States. J. Climate, 26, 1018-1032. doi:10.1175/JCLI-D-12-00168.1.

[106]     *Liu, S., W. Gao, and X.-Z. Liang, 2012: Regional climate model downscaling projection of China future climate change. Climate Dynamics, 41, 1871-1884, doi:10.1007/s00382-012-1632-5.

[105]     **Lei, H., D.J. Wuebbles, and X.-Z. Liang, 2012: Domestic versus international contributions on 2050 ozone air quality: How much is convertible by regional control? Atmospheric Environment, 68, 315-325, doi:10.1016/j.atmosenv.2012.12.002.

[104]     **Lei, H., D.J. Wuebbles, and X.-Z. Liang, 2012: Projected risk of high ozone episodes in 2050. Atmospheric Environment, 59, 567-577.

[103]     Post, E.S., A. Grambsch, C.P. Weaver, P. Morefield, J. Huang, L.-Y. Leung, C. Nolte, P. Adams, X.-Z. Liang, J.-H. Zhu, and H. Mahoney, 2012: Variation in estimated health impacts of climate change via ambient ozone concentration changes due to modeling choices and assumptions. Environmental Health Perspectives, 120(11), 1559-64, doi: 10.1289/ehp.1104271.

[102]     Liang, X.-Z., M. Xu, W. Gao, K.R. Reddy, K.E. Kunkel, D.L. Schmoldt, and A.N. Samel, 2012: A distributed cotton growth model developed from GOSSYM and its parameter determination. Agronomy Journal, 104, 661-674.

[101]     Liang, X.-Z., M. Xu, W. Gao, K.R. Reddy, K.E. Kunkel, D.L. Schmoldt, and A.N. Samel, 2012: Physical modeling of U.S. cotton yields and climate stresses during 1979 to 2005. Agronomy Journal, 104, 675-683.

[100]     Liang, X.-Z., M. Xu, X. Yuan, T. Ling, H.I. Choi, F. Zhang, L. Chen, S. Liu, S. Su, F. Qiao, Y. He, J.X.L. Wang, K.E. Kunkel, W. Gao, E. Joseph, V. Morris, T.-W. Yu, J. Dudhia, and J. Michalakes, 2012: Regional Climate-Weather Research and Forecasting Model (CWRF). Bull. Amer. Meteor. Soc., 93, 1363-1387. [Featured in the cover page of the BAMS 2012 September issue]

[99]       Yuan, X., X.-Z. Liang, and E.F. Wood, 2012: WRF ensemble downscaling seasonal forecasts of China winter precipitation during 1982-2008. Climate Dynamics, 39, 2041-2058. DOI: 10.1007/s00382-011-1241-8.