Matthew Norman

  • Program Years: 2008-2011
  • Academic Institution: North Carolina State University
  • Field of Study: Atmospheric Sciences
  • Academic Advisor: Fredrick Semazzi
  • Practicum(s):
    Oak Ridge National Laboratory (2009)
  • Degree(s):
    Ph.D. Atmospheric Sciences, North Carolina State University, 2011
    M.S. Atmospheric Sciences, North Carolina State University, 2008
    B.S. Meteorology, North Carolina State University, 2006
    B.S. Computer Science, North Carolina State University, 2006

Current Status

  • Status: Computational Climate Scientist, Oak Ridge National Lab, Oak Ridge Leadership Computing Facility
  • Research Area: Computational Climate Science
  • Personal URL:


[1] Katherine J Evans, Richard K Archibald, David J Gardner, Matthew R Norman, Mark A Taylor, Carol S Woodward, and Patrick H Worley. Performance analysis of fully explicit and fully implicit solvers within a spectral element shallow-water atmosphere model. The International Journal of High Performance Computing Applications, 33(2):268-284, 2019.

[2] Walter M Hannah, Christopher R Jones, Benjamin R Hillman, Matthew R Norman, David C Bader, Mark A Taylor, LR Leung, Michael S Pritchard, Mark D Branson, Guangxing Lin, et al. Initial results from the super-parameterized e3sm. Journal of Advances in Modeling Earth Systems, 12(1), 2020.

[3] Joseph H Kennedy, Andrew R Bennett, Katherine J Evans, Stephen Price, Matthew Hoffman, William H Lipscomb, Jeremy Fyke, Lauren Vargo, Adrianna Boghozian, Matthew Norman, et al. Livvkit: An extensible, python-based, land ice verification and validation toolkit for ice sheet models. Journal of Advances in Modeling Earth Systems, 9(2):854-869, 2017.

[4] Lixiang Luo, Tjerk P Straatsma, LE Aguilar Suarez, Ria Broer, Dmytro Bykov, Eduardo F D'Azevedo, Shirin S Faraji, Kalyana C Gottiparthi, Coen De Graaf, J Austin Harris, et al. Pre-exascale accelerated application development: The ornl summit experience. IBM Journal of Research and Development, 64(3/4):11-1, 2020.

[5] Salil Mahajan, Katherine J Evans, Joseph H Kennedy, Min Xu, and Matthew R Norman. A multivariate approach to ensure statistical reproducibility of climate model simulations. In Proceedings of the Platform for Advanced Scientific Computing Conference, pages 1-10, 2019.

[6] Salil Mahajan, Abigail L Gaddis, Katherine J Evans, and Matthew R Norman. Exploring an ensemble-based approach to atmospheric climate modeling and testing at scale. Procedia Computer Science, 108(C), 2017.

[7] Matthew Norman, Jeffrey Larkin, Aaron Vose, and Katherine Evans. A case study of cuda fortran and openacc for an atmospheric climate kernel. Journal of computational science, 9:1-6, 2015.

[8] Matthew R Norman. Algorithmic improvements for schemes using the ader time discretization. Journal of Computational Physics, 243:176-178, 2013.

[9] Matthew R Norman. Targeting atmospheric simulation algorithms for large, distributed-memory, gpu-accelerated computers. In GPU Solutions to Multi-scale Problems in Science and Engineering, pages 271-282. Springer, Berlin, Heidelberg, 2013.

[10] Matthew R Norman. A weno-limited, ader-dt, finite-volume scheme for efficient, robust, and communication-avoiding multi-dimensional transport. Journal of Computational Physics, 274:1-18, 2014.

[11] Matthew R Norman. Arbitrarily high-order-accurate, hermite weno limited, boundary-averaged multi-moment constrained finite-volume (ba-mcv) schemes for 1-d transport. Procedia Computer Science, 51:2688-2697, 2015.

[12] Matthew R Norman. Developing a large time step, robust, and low communication multi-moment pde integration scheme for exascale applications. Procedia Computer Science, 51:1848-1857, 2015.

[13] Matthew R Norman. Hermite weno limiting for multi-moment finite-volume methods using the ader-dt time discretization for 1-d systems of conservation laws. Journal of Computational Physics, 282:381-396, 2015.

[14] Matthew R Norman and Hal Finkel. Multi-moment ader-taylor methods for systems of conservation laws with source terms in one dimension. Journal of Computational Physics, 231(20):6622-6642, 2012.

[15] Matthew R Norman, Azamat Mametjanov, and Mark Taylor. Exascale programming approaches for accelerated climate modeling for energy. In Exascale Scientific Applications, pages 187-206. Chapman and Hall/CRC, 2017.

[16] Matthew R Norman and Ramachandran D Nair. Inherently conservative nonpolynomial-based remapping schemes: Application to semi-lagrangian transport. Monthly Weather Review, 136(12):5044-5061, 2008.

[17] Matthew R Norman and Ramachandran D Nair. A positive-definite, weno-limited, high-order finite volume solver for 2-d transport on the cubed sphere using an ader time discretization. Journal of Advances in Modeling Earth Systems, 10(7):1587-1612, 2018.

[18] Matthew R Norman, Ramachandran D Nair, and Fredrick HM Semazzi. A low communication and large time step explicit finite-volume solver for non-hydrostatic atmospheric dynamics. Journal of Computational Physics, 230(4):1567-1584, 2011.

[19] Matthew R Norman, Fredrick HM Semazzi, and Ramachandran D Nair. Conservative cascade interpolation on the sphere: An intercomparison of various non-oscillatory reconstructions. Quarterly Journal of the Royal Meteorological Society: A journal of the atmospheric sciences, applied meteorology and physical oceanography, 135(640):795-805, 2009.

[20] Matthew Ross Norman. Investigation of higher-order accuracy for a conservative semi-lagrangian discretization of the atmospheric dynamical equations. 2008.

[21] Matthew Ross Norman et al. Characteristics-based methods for efficient parallel integration of the atmospheric dynamical equations. 2010.

[22] Anikesh Pal, Salil Mahajan, and Matthew R Norman. Using deep neural networks as cost-effective surrogate models for super-parameterized e3sm radiative transfer. Geophysical Research Letters, 46(11):6069-6079, 2019.

[23] Fredrick HM SEMAZZI, Jeffrey S Scroggs, George A Pouliot, Analemma Leia Mckee-Burrows, Matthew NORMAN, Vikram POOJARY, and Yu-Ming TSAI. On the accuracy of semi-lagrangian numerical simulation of internal gravity wave motion in the atmosphere. Journal of the Meteorological Society of Japan. Ser. II, 83(5):851-869, 2005.

[24] Paul A Ullrich and Matthew R Norman. The flux-form semi-lagrangian spectral element (ff-slse) method for tracer transport. Quarterly Journal of the Royal Meteorological Society, 140(680):1069-1085, 2014.


*Departmental Honors, NCSU, Marine, Earth, & Atmospheric Sciences, 2006.
*Magna Cum Laude, B.S. in Meteorology, NCSU, 2006.
*Magna Cum Laude, B.S. in Computer Science, NCSU, 2006.