-
Title
Staff Scientist -
Email
zhang40@llnl.gov -
Phone
(925) 424-4573 -
Organization
Not Available
Research Interests
- Climate model development and validation
- Earth system model post-processing and evaluation tools
- Cloud microphysics and dynamics
Ph.D., Meteorology, Penn State University, 2012
B.S., Atmospheric Sciences, Nanjing Institute of Meteorology, 2007
Tang, S., Gleckler, P., Xie, S., Lee, J., Ahn, M. S., Covey, C., & Zhang, C. (2021). Evaluating the Diurnal and Semidiurnal Cycle of Precipitation in CMIP6 Models Using Satellite-and Ground-Based Observations. Journal of Climate, 34(8), 3189-3210.
Zhang, C., Xie, S., Tao, C., Tang, S., Emmenegger, T., Neelin, J. D., ... & Shaheen, Z. (2020). The ARM Data- Oriented Metrics and Diagnostics Package for Climate Models: A New Tool for Evaluating Climate Models with Field Data. Bulletin of the American Meteorological Society, 101(10), E1619-E1627.
Golaz, J. C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q., Wolfe, J. D., ... & Zhu, Q. (2019). The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution. Journal of Advances in Modeling Earth Systems, 11(7), 2089-2129.
Phillips, T. J., Bonfils, C. J., & Zhang, C. (2019). Model consensus projections of US regional hydroclimates under greenhouse warming. Environmental Research Letters, 14(1), 014005.
Zhang, C., Xie, S., Klein, S. A., Ma, H. Y., Tang, S., Van Weverberg, K., ... & Petch, J. (2018). CAUSES: Diagnosis of the summertime warm bias in CMIP5 climate models at the ARM Southern Great Plains site. Journal of Geophysical Research: Atmospheres, 123(6), 2968-2992.
Van Weverberg, K., Morcrette, C. J., Petch, J., Klein, S. A., Ma, H. Y., Zhang, C., ... & Thieman, M. M. (2018). CAUSES: Attribution of surface radiation biases in NWP and climate models near the US Southern Great Plains. Journal of Geophysical Research: Atmospheres, 123(7), 3612-3644.
Morcrette, C. J., Van Weverberg, K., Ma, H. Y., Ahlgrimm, M., Bazile, E., Berg, L. K., .. ., Zhang, C. & Petch, J. (2018). Introduction to CAUSES: Description of weather and climate models and their near-surface temperature errors in 5 day hindcasts near the Southern Great Plains. Journal of Geophysical Research: Atmospheres, 123(5), 2655-2683.
Ma, H. Y., Klein, S. A., Xie, S., Zhang, C., Tang, S., Tang, Q., ... & Wang, Y. C. (2018). CAUSES: On the role of surface energy budget errors to the warm surface air temperature error over the Central United States. Journal of Geophysical Research: Atmospheres, 123(5), 2888-2909.
Kim, S., Ames, S., Lee, J., Zhang, C., Wilson, A. C., & Williams, D. (2017, November). Resolution reconstruction of climate data with pixel recursive model. In 2017 IEEE International Conference on Data Mining Workshops (ICDMW) (pp. 313-321). IEEE.
Kim, S., Ames, S., Lee, J., Zhang, C., Wilson, A. C., & Williams, D. (2017). Massive scale deep learning for detecting extreme climate events. Climate Informatics.
Zhang, C., & Harrington, J. Y. (2015). The effects of surface kinetics on crystal growth and homogeneous freezing in parcel simulations of cirrus. Journal of the Atmospheric Sciences, 72(8), 2929-2946.
Zhang, C., Wang, M., Morrison, H., Somerville, R. C., Zhang, K., Liu, X., & Li, J. L. F. (2014). Investigating ice nucleation in cirrus clouds with an aerosol-enabled multiscale modeling framework. Journal of Advances in Modeling Earth Systems, 6(4), 998-1015.
Zhang, C., & Harrington, J. Y. (2014). Including surface kinetic effects in simple models of ice vapor diffusion. Journal of the Atmospheric Sciences, 71(1), 372-390.