- PhD -- The Pennsylvania State University (1990)
- MS -- The Pennsylvania State University (1984)
- BS -- The Pennsylvania State University (1981)
Prof. Stauffer has more than 29 years of experience in meteorological research and development, numerical weather prediction (NWP), data assimilation, and software development and management. He is a principal developer of the Penn State University/National Center for Atmospheric Research MM5 Modeling System, and he is a contributing developer of the Weather Research and Forecast (WRF) model in the areas of data assimilation and model physics. He is widely recognized for his expertise in building customized, state-of-the-science, mesoscale modeling and data assimilation systems for military-defense, energy and aviation concerns, as well as basic research in model development, atmospheric processes, air quality and probabilistic weather / atmospheric transport and dispersion.
Dr. Stauffer leads his Penn State team of four M.S. level and five Ph.D level research faculty, and his graduate students, in projects ranging from basic and applied research to development of operationally fielded NWP systems. He is the Principal Investigator (PI) and team leader on many large multi-institutional multi-disciplinary research teams (e.g., for U.S. Army via Smiths Detection, U.S. Department of Defense (DoD) /Defense Threat Reduction Agency (DTRA) and Air Force Technical Applications Center (AFTAC) via L-3 Titan, U.S. Marine Corps via Smiths Detection), and others with Penn State as lead, including DTRA, Army Research Office, U.S. Environmental Protection Agency, Coordinating Research Council, Bay Area Air Quality Management District and National Science Foundation. These projects involve high-resolution mesoscale modeling and observations, advanced parameterizations for land-surface, boundary layer and cloud microphysics, large eddy simulation, air quality, ensemble modeling / transport and dispersion modeling and advanced four-dimensional data assimilation (FDDA).
He is currently leading several DoD / DTRA projects spanning basic research topics to operational reachback. The objective of his ongoing DTRA basic research program is to understand and predict the structure and variability of the stable boundary layer (SBL) in order to improve predictions of transport and dispersion of airborne toxic materials released in accidents or WMDs. It is a high-resolution modeling and field measurement program, with additional special instrumentation funded by the Army Research Office through the Defense University Research Instrumentation Program (DURIP). This SBL study focuses on the interactions of complex terrain, gravity driven currents, low-level jets and elevated turbulence, internal gravity waves, and other processes that result in submeso wind and temperature fluctuations in the SBL, and their related AT&D effects in the complex terrain over central PA. Special instruments include an expanded network of tower and surface measurements as well as acoustic SODARS for detailed vertical profile measurements within the lowest few hundred meters. Daily realtime WRF mathematical modeling is being performed at horizontal grid resolutions of about 400 m, and 10 vertical layers in the lowest 50 m above ground level, and this is at least 10 times finer resolution than that being used in the operational weather model products shown for example on TV weathercasts.
Other DTRA projects include development of the WRF FDDA system and next-generation data assimilation systems, uncertainty quantification, high-resolution meteorological modeling and probabilistic weather for AT&D, and development and upgrades to DTRA’s in-house mesoscale modeling system supporting worldwide events such as the Torino Winter Olympics, Beijing Summer Olympics, Vancouver Winter Olympics, and national events such as Super Bowls, etc.
Dr. Stauffer and his team also perform ensemble modeling and AT&D research and development using WRF for the Air Force Technical Applications Center (AFTAC), for nuclear treaty monitoring and nuclear event detection. AFTAC provides national authorities quality technical measurements to monitor nuclear treaty compliance, and this research is aimed at bounding inherent errors when forecasting effluent released from nuclear detonations.
Teamed with Smiths Detection, he directed the design, coding and testing of the Army’s Meteorological Measuring Set – Profiler (MMS-P) nowcasting system, an automated computerized weather forecast and post-processing system that runs in the back of specially equipped Humvees to provide detailed meteorological information to the Field Artillery. The MMS-P, used worldwide and in the battlefields of Iraq and Afghanistan, was fielded by the Army in early 2005 and the full production cycle of 108 units was completed in May 2010 (see http://live.psu.edu/story/47311
). He also worked with Smiths Detection to develop two prototypes of another mobile nowcast-forecast system specifically designed for the U.S. Marines (NEXGEN METMFR).
Prof. Stauffer was a charter member of the Weather Research and Forecasting (WRF) Model Science Board, and he is also a member of several WRF Working Groups, including the Model Physics Working Group and Ensemble Forecasting Working Group (see http://wrf-model.org).
Areas of Expertise:
Mesoscale meteorology and numerical weather prediction (NWP), four-dimensional data assimilation (e.g., nudging, adjoint methods, variational methods, ensemble Kalman filters and hybrid methods), physical parameterizations and coupled models (e.g., boundary layer, land-surface, parameterized versus explicit convection), probabilistic weather and model ensembles, and process studies (e.g., boundary layer and land-surface processes, meteorological modeling for air-quality and transport and dispersion applications, shallow and deep convection, terrain-forced circulations, coastal-zone meteorology, cold-air damming, tropical cyclones).
Selected publications:Stauffer, D.R., 2011: Uncertainty in Environmental NWP Modeling. Handbook of Environmental Fluid Dynamics
, Harindra Joseph S. Fernando, Ed., Taylor &Francis Books, Inc., in press.
Seaman, N.L., B.J. Gaudet, D.R. Stauffer, L. Mahrt, S. Richardson, J.R. Zielonka, and J.C. Wyngaard, 2011: Numerical prediction of sub-mesoscale flow in the nocturnal stable boundary layer over complex terrain, submitted to Mon. Wea. Rev., 138:
Lei, L., D.R. Stauffer, S.E. Haupt, and G. Young, 2011: A hybrid ensemble Kalman filter approach to data assimilation. Part I: Application in the Lorenz system, submitted to Tellus
, 48 pp.
Lei, L., D.R. Stauffer, and A. Deng, 2011: A hybrid ensemble Kalman filter approach to data assimilation. Part II: Application in a shallow water model, submitted to Tellus
, 52 pp.
Kolczynski, W.C., D.R. Stauffer, S.E. Haupt, N.S. Altman and A. Deng, 2010: Investigation of Linear Variance Calibration for spread-error relationship using a stochastic model, accepted with minor revisions in Mon. Wea. Rev.
Mahrt, L., S. Richardson, N. Seaman and D. Stauffer, 2010: Interaction between drainage flows, the valley cold pool and submeso motions, Tellus, 62:
Peltier, L.J., S.E. Haupt, J.C. Wyngaard, D.R. Stauffer, A. Deng, J.A. Lee, K.J. Long, and A.J. Annunzio, 2010: Parameterizing mesoscale wind uncertainty for dispersion modeling, J. Appl. Meteor. Climatol., 49
Reen, B. P. and D. R. Stauffer, 2010: Data assimilation strategies in the Planetary Boundary Layer, Bound.-Layer Meteor., 137
Hanna, S., B. Reen, E. Hendrick, L. Santos, D. Stauffer, A. Deng, J. McQueen, M. Tsidulko, Z. Janjic, D. Jovic, and R. I. Sykes, 2010: Comparison of observed, MM5 and WRF-NMM model-simulated, and HPAC-assumed boundary-layer meteorological variables for three days during the IHOP field experiment, Bound.-Layer Meteorol. , 134
Kolczynski, Jr.,W.C., D.R. Stauffer, S.E. Haupt, and A. Deng, 2009: Ensemble variance calibration for representing meteorological uncertainty for atmospheric transport and dispersion modeling, J. Appl Meteor. Climatol., 48
Lee, J.A., L.J. Peltier, S.E. Haupt, J.C. Wyngaard, D.R. Stauffer, and A. Deng, 2009: Improving SCIPUFF dispersion forecasts with NWP ensembles, J. Appl. Meteor. Climatol., 48
Stauffer, D.R., B.J. Gaudet, N.L. Seaman, J.C. Wyngaard, L. Mahrt and S. Richardson, 2009: Sub-kilometer numerical predictions in the nocturnal stable boundary layer, 23rd Conference on Weather Analysis and Forecasting (WAF) /19th Conference on Numerical Weather Prediction (NWP)
, Omaha, NE, Jun 1-5, 8 pp.
Stauffer, D.R., G.K. Hunter, A. Deng, J.R. Zielonka, K. Dedrick, C. Broadwater, A. Grose, C. Pavloski, and J. Toffler, 2009: Realtime high-resolution mesoscale modeling for the Defense Threat Reduction Agency, 23rd Conference on WAF/19th Conference on NWP
, Omaha, NE, Jun 1-5, 10 pp.
Deng, A., D.R. Stauffer, B. Gaudet, J. Dudhia, C. Bruyere, W. Wu, F. Vandenberghe, Y. Liu, and A. Bourgeois, 2009: Update on WRF-ARW end-to-end multi-scale FDDA system, Preprint, WRF Users’ Workshop
, Boulder, CO, June 23-26.
Reen, B.P., D. Tyndall, G.S. Young, and D.R. Stauffer, 2009: Idealized simulations of circulations forced by land surface heterogeneity, 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction
, Omaha, NE, Jun 1-5, 8 pp.
Lei, L. and D.R. Stauffer, 2009: A hybrid ensemble Kalman filter approach to data assimilation in a two-dimensional shallow water model, 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction
, Omaha, NE, Jun 1-5, 7 pp.
Stauffer, D.R., A. Deng, G.K. Hunter, A.M. Gibbs, A.R. Zielonka, K. Tinklepaugh, and J. Dobek, 2007: NWP goes to war ..., Preprints, 22nd Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction
, June 25-29, Park City, UT, 13 pp.
Stauffer, D.R., G.K. Hunter, A. Deng, J.R. Zielonka, K. Tinklepaugh, P. Hayes and C. Kiley, 2007: On the role of atmospheric data assimilation and model resolution on model forecast accuracy for the Torino Winter Olympics, Preprints, 22nd Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction
, June 25-29, Park City, UT, 7 pp.
Deng, A. and D.R. Stauffer, 2006: On improving 4-km mesoscale model simulations. J. Appl. Meteor., 45
Schroeder, A.J., D.R. Stauffer, N.L. Seaman, A. Deng, A.M. Gibbs, G.K. Hunter and G.S. Young, 2006: Unleashing an automated mobile weather prediction system, summary of Schroeder et al. 2006 from Mon. Wea. Rev. , and an update sidebar on the battlefield system written by Prof. Stauffer and appearing in Papers of Note, Bull. Amer. Meteor. Soc.
, July 2006, 878-880.
Schroeder, A.J., D.R. Stauffer, N.L. Seaman, A. Deng, A.M. Gibbs, G.K. Hunter and G.S. Young, 2006: Evaluation of a high-resolution, rapidly relocatable meteorological nowcasting and prediction system. Mon. Wea. Rev., 134
Reen, B.P., D.R. Stauffer, K.J. Davis and A.R. Desai, A.R., 2006: A case study on the effects of heterogeneous soil moisture on mesoscale boundary layer structure in the southern Great Plains, USA. Part II: Mesoscale modeling, Bound. Layer Meteorol. , 120
Desai, A.R., K.J. Davis, C.J. Senff, S. Ismail, E.V. Browell, D.R. Stauffer. and B.P. Reen, 2006: A case study on the effects of heterogeneous soil moisture on mesoscale boundary layer structure in the southern Great Plains, USA. Part I: Simple prognostic model. Bound.-Layer Meteorol. , 119
Deng, A., N.L. Seaman, G.K. Hunter and D.R. Stauffer, 2004: Evaluation of interregional transport using the MM5-SCIPUFF system. J. Appl. Meteor. , 43
Otte, T.L. N.L. Seaman and D.R. Stauffer, 2001: A heuristic study on the importance of anisotropic error distributions in data assimilation. Mon. Wea. Rev. , 129
Lynn, B.H., D.R. Stauffer, P.J. Wetzel, W.K. Tao and co-authors, 2001: Improved simulation of Florida summertime convection using the PLACE land-surface model and a 1.5-order turbulence parameterization coupled to the Penn State/NCAR mesoscale model. Mon. Wea. Rev. , 129
Leidner, S.M., D.R. Stauffer and N.L. Seaman, 2001: Improving California coastal zone numerical weather prediction by dynamic initialization of the marine layer. Mon. Wea. Rev. , 129
Tanrikulu, S., D.R. Stauffer, N.L. Seaman, and A.J. Ranzieri, 2000: A field-coherence technique for meteorological field-program design for air-quality studies. Part II: Evalulation in the San Joaquin Valley. J. Appl. Meteor. , 39
Stauffer, D.R., N.L. Seaman, G.K. Hunter, S.M. Leidner, A.M. Lario-Gibbs and S. Tanrikulu, 2000: A field-coherence technique for meteorological field-program design for air-quality studies. Part I: Description and interpretation. J. Appl. Meteor., 39
Grell, G.A., J. Dudhia and D.R. Stauffer, 1995: A description of the fifth-generation Penn State/NCAR mesoscale model (MM5). NCAR Tech. Note, NCAR/TN-398+STR, 122 pp.
Seaman, N.L., D.R. Stauffer and A.M. Lario-Gibbs, 1995: A multi-scale four-dimensional data assimilation system applied in the San Joaquin Valley during SARMAP. Part I: Modeling design and basic performance characteristics. J. Appl. Meteor. , 34
Stauffer, D.R. and N.L. Seaman, 1994: Multiscale four-dimensional data assimilation. J. Appl. Meteor. , 33
Stauffer, D.R., and J.-W. Bao, 1993: Optimal determination of nudging coefficients using the adjoint equations. Tellus, 45A
Stauffer, D.R., N.L. Seaman, T.T. Warner and A.M. Lario, 1993: Application of an atmospheric simulation model to diagnose air pollution transport in the Grand Canyon region of Arizona. Chemical Engineering Communications, 121
Warner, T. T., Y.-H Kuo, J.D. Doyle, J. Dudhia, D.R. Stauffer and N.L. Seaman, 1992: Nonhydrostatic, mesobeta-scale, real-data simulations with the Penn State University/ National Center for Atmospheric Research mesocale model. Meteor. Atmos. Phys., 49
Stauffer, D.R., N. L. Seaman and F. S. Binkowski, 1991: Use of four-dimensional data assimilation in a limited-area mesoscale model. Part II: effects of data assimilation within the planetary boundary layer. Mon. Wea. Rev., 119
Stauffer, D.R. and N.L. Seaman, 1990: Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I: Experiments with synoptic-scale data. Mon. Wea. Rev., 118
Stauffer, D.R. and T.T. Warner, 1987: A numerical study of Appalachian cold-air damming and coastal frontogenesis. Mon. Wea. Rev., 115, 799-821.