Mark D. Risser
Welcome to my personal website!
I am a Research Scientist in the Climate Division at the Lawrence Berkeley National Laboratory. I received my Ph.D. in Statistics from the Ohio State University in 2015. My thesis advisor was Catherine Calder.
My primary goal as a statistician is to use data science, Bayesian modeling, and computational tools to identify and quantify climate change. My research focuses on statistical climatology, extreme value analysis, Gaussian processes, and Bayesian modeling.
Here is a link to my Google Scholar page.
Recent news
June, 2024: our paper titled Leveraging extremal dependence to characterize the 2021 Pacific Northwest heatwave led by Dr. Likun Zhang was published in Journal of Agricultural, Biological and Environmental Statistics
May, 2024: our paper titled Is bias correction in dynamical downscaling defensible? was published in Geophysical Research Letters
May, 2024: our paper titled Understanding the Cascade: Removing GCM biases improves dynamically downscaled climate projections led by Dr. Stefan Rahimi was published in Geophysical Research Letters
March, 2024: our paper titled Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent over the Rocky Mountains led by Dr. Shiheng Duan was published in Water Resources Research
March, 2024: our paper titled On the uncertainty of long-period return values of extreme daily precipitation led by Dr. Michael Wehner was published in Frontiers in Climate
February, 2024: our paper titled A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes led by Dr. Marcus Noack was published in APL Machine Learning
February, 2024: our paper titled Anthropogenic aerosols mask increases in US rainfall by greenhouse gases was published in Nature Communications
August, 2022: began advising Dr. Joshua North as a Postdoctoral Fellow in the CASCADE Scientific Focus Area at LBNL.