2017 - Jingwan Li
2014 – 2017
Jingwan was one of our own undergraduates who started with Ashish, Fiona and Jason Evans (from the CCRC) on estimating changes to IFDs in future climates using high resolution RCM simulations. She has developed one of the coolest RCM IFD bias correction approaches out there - taking into account the bias in rainfall amounts (nothing unusual about this) as well as the bias in sampling different types of extremes (such as convective versus non-convective - this being the main innovation as RCMs are pretty bad on this front.
Her PhD consisted of the following papers:
- Li, J., J. Evans, F. Johnson, and A. Sharma (2017), A comparison of methods for estimating climate change impact on design rainfall using a high-resolution RCM, Journal of Hydrology, 547, 413-427, doi:10.1016/j.jhydrol.2017.02.019.
- Li, J., F. Johnson, J. Evans, and A. Sharma (2017), A comparison of methods to estimate future sub-daily design rainfall, Advances in Water Resources, 110, 215-227, doi:10.1016/j.advwatres.2017.10.020.
- Li, J., A. Sharma, J. Evans, and F. Johnson (2016), Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach, Journal of Hydrology, doi:10.1016/j.jhydrol.2016.04.070.
- Li, J., A. Sharma, F. Johnson, and J. Evans (2015), Evaluating the effect of climate change on areal reduction factors using regional climate model projections, Journal of Hydrology, 528, 419-434, doi:10.1016/j.jhydrol.2015.06.067.