Jeremy Gibbs


Data Assimilation & Modeling Team (DAMT)

Job Title:Research Scientist


Email:Email hidden; Javascript is required.

Phone:(405) 325-3792


Jeremy uses theory and computers to study atmospheric boundary-layer flows, including turbulence modeling, land-surface modeling, parameterization of boundary-layer and surface-layer interactions, and multi-scale numerical weather prediction. He is currently working on projects to improve atmospheric models in the areas of scale-aware boundary-layer physics, heterogeneous boundary and surface layers, fire weather, tornado dynamics, and other storm-scale phenomena.

Degree (Ph.D, M.S, B.A, etc.) Major Subject University or College Name Year (YYYY) (optional)
Ph.D. Meteorology University of Oklahoma 2012
M.S. Meteorology University of Oklahoma 2008
B.S. Meteorology University of Oklahoma 2006
Research Interests
  • atmospheric boundary layer
  • turbulence
  • computational fluid dynamics
  • numerical methods
  • numerical weather prediction
Professional Activities
  • NSSL Representative, OAR EEO Advisory Committee
  • Member, NCAR CISL High-Performance Computing Allocations Panel
  • Member, NCAR Common Community Physics Package (CCPP) code management committee
  • Member, NCAR High-Performance Computing User Group
  • Co-Leader, Boundary Layer Integrated Sensing and Simulation (BLISS) group
  • Co-Chair, NSSL Outreach Committee and ex officio NDIST participant
Honors & Awards
Award Name Year
NOAA Research EEO Diversity Award for Exemplary Service 2022
School of Meteorology Douglas Lilly Award for best peer-reviewed publication 2012
School of Meteorology Outstanding Teaching Assistant Award 2009
Selected Publications
  • Labriola, J. D., J. A. Gibbs, L. J. Wicker, 2023: A method for generating a quasi-linear convective system suitable for observing system simulation experiments. Geoscientific Model Development, 16, 6, 1779–1799, doi:10.5194/gmd-16-1779-2023
  • Gibbs, J. A., R. Stoll, S. Salesky, 2023: Inclination Angles of Turbulent Structures in Stably Stratified Boundary Layers. Boundary-Layer Meteorology, 186, 27–41, doi:10.1007/s10546-0
  • Moody, M. J., J. A. Gibbs, S. Krueger, D. Mallia, E. R. Pardyjak, A. K. Kochanski, B. N. Bailey, R. Stoll, 2022: QES-Fire: a dynamically coupled fast-response wildfire model. International Journal of Wildland Fire, 31, 3, 306–325, doi:10.1071/WF21057
  • Bozorgmehr, B., P. Willemsen, J. A. Gibbs, R. Stoll, J. J. Kim, E. R. Pardyjak, 2021: Utilizing dynamic parallelism in CUDA to accelerate a 3D red-black successive over relaxation wind-field solver. Environmental Modelling & Software, 137, 104958, doi:10.1016/j.envsoft.2021.104958
  • Stoll, R., J. A. Gibbs, S. S. Salesky, W. Anderson, M. Calaf, 2020: Large-Eddy Simulation of the Atmospheric Boundary Layer. Boundary-Layer Meteorol, 177, 541–581, doi:10.1007/s10546-020-00556-3
  • Gibbs, J. A., E. Fedorovich, 2020: On the evaluation of the proportionality coefficient between the turbulence temperature spectrum and structure parameter. Journal of the Atmospheric Sciences, 77, 2761–2763, doi:10.1175/JAS-D-19-0344.1
  • Gibbs, J. A., E. Fedorovich, 2020: Structure Functions and Structure Parameters of Velocity Fluctuations in Numerically Simulated Atmospheric Convective Boundary Layer Flows. Journal of the Atmospheric Sciences, 77, 3619–3630, doi:10.1175/JAS-D-20-0038.1
  • Potvin, C. K., P. S. Skinner, K. A. Hoogewind, M. C. Coniglio, J. A. Gibbs, A. J. Clark, M. L. Flora, A. E. Reinhart, J. R. Carley, E. N. Smith, 2020: Assessing Systematic Impacts of PBL Schemes on Storm Evolution in the NOAA Warn-on-Forecast System. Monthly Weather Review, 148, 2567–2590, doi:10.1175/MWR-D-19-0389.1
  • McFarquhar, G. M., E. Smith, E. A. Pillar-Little, K. Brewster, P. B. Chilson, T. R. Lee, S. Waugh, N. Yussouf, X. Wang, M. Xue, G. de Boer, J. A. Gibbs, C. Fiebrich, B. Baker, J. Brotzge, F. Carr, H. Christophersen, M. Fengler, P. Hall, T. Hock, A. Houston, R. Huck, J. Jacob, R. Palmer, P. K. Quinn, M. Wagner, Y. Zhang, D. Hawk, 2020: Current and Future Uses of UAS for Improved Forecasts/Warnings and Scientific Studies. Bulletin of the American Meteorological Society, 101, E1322–E1328, doi:10.1175/BAMS-D-20-0015.1
  • Smith, E. N., J. G. Gebauer, P. M. Klein, E. Fedorovich, and J. A. Gibbs, 2019: The Great Plains Low-Level Jet during PECAN: Observed and Simulated Characteristics. Mon. Wea. Rev., 147, 1845–1869, doi:10.1175/MWR-D-18-0293.1.
  • Smith, E. N., J. A. Gibbs, E. Fedorovich, and P. M. Klein, 2018: WRF Model Study of the Great Plains Low-Level Jet: Effects of Grid Spacing and Boundary Layer Parameterization. J. Appl. Meteor. Climatol., 57, 2375–2397, doi:
  • van Heerwaarden, C. C., van Stratum, B. J. H., Heus, T., J. A. Gibbs, Fedorovich, E., and Mellado, J. P., 2017: MicroHH 1.0: a computational fluid dynamics code for direct numerical simulation and large-eddy simulation of atmospheric boundary layer flows, Geosci. Model Dev., 10, 3145–3165, doi:10.5194/gmd-10-3145-2017
  • Fedorovich, E., J. A. Gibbs, and A. Shapiro, 2017: Numerical Study of Nocturnal Low-Level Jets over Gently Sloping Terrain. J. Atmos. Sci., 74, 2813–2834, doi:10.1175/JAS-D-17-0013.1
  • Gibbs, J. A. and Fedorovich, E., 2016: Sensitivity of turbulence statistics in the lower portion of a numerically simulated stable boundary layer to parameters of the Deardorff subgrid turbulence model. Q.J.R. Meteorol. Soc., 142: 2205-2213, doi:10.1002/qj.2818
  • Gibbs, J. A., E. Fedorovich, B. Maronga, C. Wainwright, and M. Dröse, 2016: Comparison of Direct and Spectral Methods for Evaluation of the Temperature Structure Parameter in Numerically Simulated Convective Boundary Layer Flows. Mon. Wea. Rev., 144, 2205–2214, doi:10.1175/MWR-D-15-0390.1
  • Bonin, T.A., Goines, D.C., Scott, A.K., C. Wainwright, J. A. Gibbs, and P.B. Chilson, 2015: Measurements of the Temperature Structure-Function Parameters with a Small Unmanned Aerial System Compared with a Sodar. Boundary-Layer Meteorol 155, 417–434, doi:10.1007/s10546-015-0009-9
  • Shapiro, A., Fedorovich, E., and J. A. Gibbs: An analytical verification test for numerically simulated convective flow above a thermally heterogeneous surface, Geosci. Model Dev., 8, 1809–1819, doi: 10.5194/gmd-8-1809-2015
  • Wainwright, C.E., Bonin, T.A., Chilson, P.B., J. A. Gibbs, E. Fedorovich, and R.D. Palmer, 2015: Methods for Evaluating the Temperature Structure-Function Parameter Using Unmanned Aerial Systems and Large-Eddy Simulation. Boundary-Layer Meteorol. 155, 189–208, doi: 10.1007/s10546-014-0001-9
  • Gibbs, J. A., Fedorovich, E. & Shapiro, A., 2015: Revisiting Surface Heat-Flux and Temperature Boundary Conditions in Models of Stably Stratified Boundary-Layer Flows. Boundary-Layer Meteorol. 154, 171–187, doi: 10.1007/s10546-014-9970-y
  • Gibbs, J. A. and E. Fedorovich, 2014: Effects of Temporal Discretization on Turbulence Statistics and Spectra in Numerically Simulated Convective Boundary Layers. Boundary-Layer Meteorol. 153, 19–41,
  • Wainwright, C. E., P. M. Stepanian, P. B. Chilson, R. D. Palmer, E. Fedorovich, and J. A. Gibbs, 2014: A Time Series Sodar Simulator Based on Large-Eddy Simulation. J. Atmos. Oceanic Technol., 31, 876–889, doi: 10.1175/JTECH-D-13-00161.1
  • Gibbs, J. A. and E. Fedorovich, 2014: Comparison of Convective Boundary Layer Velocity Spectra Retrieved from Large- Eddy-Simulation and Weather Research and Forecasting Model Data. J. Appl. Meteor. Climatol., 53, 377–394, doi:10.1175/JAMC-D-13-033.1
  • Gibbs, J. A., E. Fedorovich, and A. M. J. van Eijk, 2011: Evaluating Weather Research and Forecasting (WRF) Model Predictions of Turbulent Flow Parameters in a Dry Convective Boundary Layer. J. Appl. Meteor. Climatol., 50, 2429–2444, doi: 10.1175/2011JAMC2661.1