- NSSL/FRDD Rm 4368, 120 David L. Boren Boulevard, Norman, OK 73072
- Lastest Update:
- March 26th, 2014
- Nonhydrostatic atmospheric model development (particularily numerical methods used to solve the compressible Euler equations)
- The use of ensemble Kalman filter data assimilation techniques for storm-scale analysis and prediction
- Dynamics and predictability of severe storms and tornadogenesis
- Radar and other in situ observations of supercell thunderstorms
As part of that work, I am interested in a number of related scientific problems....
I have a broad set of research interests which generally are focused on numerical analysis, simulation, and forecasts of severe convection and tornadoes. My original research interests in supercells and tornadoes can be traced back to nearly my high school days in the late 1970s. While obtaining my undergraduate and Master's degrees at University of Oklahoma in the 1980s, I became an avid storm chaser and eventually was fortunate enough to be able to work on some of the first in situ deployments of instruments near severe storms with my mentors: Howie Bluestein (OU) and later Don Burgess and Bob Davies-Jones (NSSL). I got the modeling bug while doing my work with Dr. Tzvi Gal-Chen on satellite temperature assimilation for my Master's degree, and was fortunate enough to be able to work on a Ph.D. with Dr. Bob Wilhelmson at the University of Illinois on numerical simulations of tornadogenesis. This work was facilitated by the newly formed NSF computing center, the National Center for Supercomputing Applications, where I became very involved with the newly developing paradigm of "computational science" that is now ubiquitous across most scientific disciplines. During most of the 1990s I was a professor of Atmospheric Sciences at Texas A&M University. In 1999 I was very fortunate to be able to return to my meteorological roots here in Norman as a scientist at the National Severe Storms Lab. My work today continues to focus on severe storms and tornadoes. I very much believe (and history I think demonstrates this clearly) that increasing our scientific understanding of these phenomena directly leads to better forecasts and warnings for the public.
Current Research Interests and Associated Publications
Dynamics of severe storms and tornadoes
Dahl, J., M. D. Parker and L. J. Wicker, 2014: The roles of ambient and storm-generated vorticity in the development of near-ground rotation in a simulated supercell. J. Atmos. Sci., In press. DOI: JAS-D-13-0123.1
Dawson II, D. T., E. R. Mansell, Y. Jungsun, L. J. Wicker, M. R. Kumjian, and M. Xue 2014: Low- level Zdr Signatures in Supercell Forward Flanks: The Role of Size Sorting and Melting Hail. J. Atmos. Sci., 276-299. http://dx.doi.org/10.1175/JAS-D-13-0118.1
Wandishin, M., D. Stensrud, S. Mullen, and L. J. Wicker, 2009: On the predictability of mesoscale convective systems: Three-dimensional simulations. Mon. Wea. Rev., 138, 863-885. DOI: 10.1175/2009MWR2961.1.
Observation and analyses of supercells and tornadoes
Potvin, C. K., L.J. Wicker, D. Betten, M. I. Biggerstaff, and A. Shapiro, 2013: Comparison between storm-scale dual-Doppler and EnKF wind analyses: The 29-30 May 2004 Geary, Oklahoma, supercell thunderstorm. Mon. Wea. Rev., 141, 1612-1628, DOI: http://dx.doi.org/10.1175/MWR-D-12-00308.1.
Skinner, P. S., C. C. Weiss, J. L. Schroeder, L. J. Wicker, and M. I. Biggerstaff, 2011: Observations of the surface boundary structure within the 23 May, 2007 Perryton, Texas supercell. Mon. Wea. Rev. In press. PDF available here.
French, M., H. B. Bluestein, D. C. Dowell, L. J. Wicker, M. R. Kramer, and A. L. Pazmany, 2008: An example of the use of mobile, Doppler radar data in tornado verification. Wea. Forecasting., 24, 884-891.
French, M., H. B. Bluestein, D. C. Dowell, L. J. Wicker, M. R. Kramer, and A. L. Pazmany, 2008: High-resolution, mobile, Doppler observations of cyclic mesocyclogenesis in a supercell. Mon. Wea. Rev., 136, 4997–5016. DOI: 10.1175/2008MWR2407.1.
Recent papers on the development of data assimilation methods for convective storms
Dawson II, D. T., L. J. Wicker, E. R. Mansell, and M. Xue 2013: Low-level Polarimetric Radar Signatures in EnKF Analyses and Forecasts of the 8 May 2003 Oklahoma City Tornadic Supercell: Impact of Multi-moment Microphysics and Comparisons with Observations. Advances In Meteorology, Article ID 818394, 13 pp., http://dx.doi.org/10.1155/2013/818394
Dawson II, Daniel T., L. Wicker, E. R. Mansell, and R. L. Tanamachi, 2011: Impact from the environmental wind profile on ensemble forecasts of the 4 May 2007 Greensburg tornado and its associated mesoscyclones. Mon. Wea. Rev., In press. PDF available here.
Dowell, D. C., L. J. Wicker, and C. Snyder, 2011: Ensemble Kalman filter assimilation of radar observations of the 8 May 2003 Oklahoma City supercell: Influences of reflectivity observations on storm-scale analyses. Mon. Wea. Rev., 139 272–294. PDF available here.
Dowell, D. C., and L. J. Wicker, 2009: Additive noise for storm-scale ensemble forecasting and data assimilation. J. Atmos. Ocea. Tech., 26 911-927. DOI: 10.1175/2008JTECHA1156.1.
Stensrud, D., M. Xue, L. J. Wicker, K. E. Kelleher, M. P. Foster, J. T. Schaefer, R. S. Schneider4, S. G. Benjamin, S. S. Weygandt, J. T. Ferree, and J. P. Tuell, 2009: Convective-scale Warn on Forecast: A Vision for 2020. Bull. Amer. Meteor. Soc., 90 1487-1499. DOI: 10.1175/2009BAMS2795.1.
Numerical methods for nonhydrostatic models
Wicker, L. J., 2009: A two-step Adams-Bashforth-Moulton split-explicit integrator for compressible atmospheric models. Mon. Wea. Rev., 137 3588-3595. DOI: 10.1175/2009MWR2838.1
Wicker, L. J., and W. C. Skamarock, 2002: Time-splitting methods for elastic models using forward time schemes. Mon. Wea. Rev., 130, 2088–2097.
Wicker, L. J., and W. C. Skamarock, 1998: A time splitting scheme for the elastic equations incorporating second-order Runge-Kutta time differencing. Mon. Wea. Rev., 126, 1992–1999.
To search my complete list of recent publications, please see NSSL's Publications Search.
Louis J. Wicker (.pdf, last updated 9 May 2014)
Using Git and Dropbox
Python in computational science
Reproducible research in computational science
Randy LeVeque: Wave propagation software, computational science, and reproducible research (.pdf, 412 kB)