Rui Mei is a postdoctoral research associate in the Computational Earth Science group at ORNL. Since joining ORNL in Mar 2012, he has been working on two projects: “A hierarchical regional modeling framework for decadal-scale hydro-climate predictions and impact assessments”, which focuses on developing the capacity of regional hydro-climate modeling and predictions for climate change impact assessment at ORNL, and “Development of frameworks for robust regional climate modeling”, which seeks to develop frameworks for robust regional climate modeling and improve understanding of factors (i.e., dynamical core, resolution, downscaling framework) contributing to modeling uncertainties.
Rui received his degrees in Environmental Engineering: B.S. from Tsinghua University in China in 2006, M.S. and Ph.D. from University of Connecticut in USA in 2008 and 2012 respectively. His graduate research focuses on land-atmosphere interaction. During his M.S. study, he examined the impact of different logging scenarios on climate in the Amazon region using the CAM3-CLM3 model. Later for his Ph.D., he investigated the land (soil moisture)-atmosphere coupling strength over the U.S. during summer with observations (CPC-VIC), reanalysis data (NARR and CFSR) and numerical models (CAM-CLM and RegCM) with several approaches (including a conditioned correlation approach and the GLACE approaches). In addition, he has contributed to several other research lines including modeling the impact of hydraulic redistribution on vegetation distribution and examining the impact of vegetation dynamics on long-term climate variability in the Amazon, and predicting future changes of climate extremes in East and South Asia.
Rui has broad research interests including: land surface and earth system modeling, land-atmosphere interactions; climate predictions and downscaling, climate changes and variability; hydrological cycle, surface and subsurface hydrology.