Nathan Lenssen

Teaching Assistant Professor, Applied Mathematics and Statistics

Nathan Lenssen

Contact

Engineering Annex 103
303-384-2520
lenssen@mines.edu

Dr. Nathan Lenssen is an Assistant Teaching Professor in Applied Mathematics and Statistics at Colorado School of Mines and a Project Scientist at the National Center of Atmospheric Research (NCAR). He received his PhD in Earth and Environmental Sciences and MA in Statistics from Columbia University. As an instructor, Nathan develops data science and climate science curricula with a focus on project-based learning and using statistics to better ask and answer questions about the world. His research aims are to better understand variability, predictability, and change of the climate system, while accounting for uncertainty in observational data and biases in dynamical climate models.  He develops statistical and dynamical models as well as the computational methods needed to apply these models to extremely large datasets.

Education

  • B.A. in Mathematics and Physics, Claremont McKenna College
  • M.A. in Statistics, Columbia University
  • Ph.D. in Earth and Environmental Sciences, Columbia University

Research Areas

  • Statistical prediction of dynamical systems
  • Spatial statistics for geoscience applications
  • Large-scale atmospheric and oceanic dynamics
  • Impacts of climate change on natural and human systems

Current Courses

  • Math 324: Statistical Modeling
  • Math 334: Introduction to Probability
  • Math 335: Introduction to Mathematical Statistics

Publication

Complete list of publications here.

  • Lenssen, N., DiNezio, P., Goddard, L., et al. (2024). Strong El Niño events lead to robust multi‐year ENSO predictability. Geophysical Research Letters, 51(12), e2023GL106988. [link]
  • Schwarzwald, K., & Lenssen, N. (2022). The importance of internal climate variability in climate impact projections. Proceedings of the National Academy of Sciences, 119(42), e2208095119. [link]
  • Lenssen, N., Goddard, L., & Mason, S. (2020). Seasonal forecast skill of ENSO teleconnection maps. Weather and Forecasting, 35(6), 2387-2406. [link]
  • Lenssen, N., Schmidt, G. A., Hansen, et al. (2019). Improvements in the GISTEMP uncertainty model. Journal of Geophysical Research: Atmospheres, 124(12), 6307-6326. [link]