David J. Stensrud

David J. Stensrud

  • Professor of Meteorology
620 Walker Building
The Pennsylvania State University
Department of Meteorology
University Park, PA 16802-5013
Email: david.stensrud@psu.edu
Phone: (814) 865-0478

Education:

  1. Ph.D., 1992, The Pennsylvania State University, Meteorology
  2. M.S., 1985, The Pennsylvania State University, Meteorology

Biography:

Website:

You can learn more about my research and teaching at https://sites.psu.edu/davidstensrud

Research Interests:

Dr. Stensrud is well known for his studies on ensemble forecasting, mesoscale and convective-scale data assimilation, severe weather, convective-scale predictability, and the North American monsoon.  He has authored more than 150 peer-reviewed publications and a textbook entitled Parameterization Schemes: Keys to Understanding Numerical Weather Models

Ensembles are groups of numerical weather prediction model forecasts valid over the same time period.  Each forecast starts from a slightly different initial condition and may use a different model configuration to account for model error.  When you analyze the resulting forecasts you can calculate probabilities for the occurrence of various weather events and, using observations from past events, you can calibrate the ensemble and obtain reliable forecast probabilities.  Many questions remain regarding how best to develop ensemble initial conditions, calibration, and the use of ensembles in human forecasting.  Dr. Stensrud is currently exploring the use of convective-scale ensembles as a tool for severe weather prediction.

Data assimilation is the process by which we integrate different types of observations together to form a three-dimensional description of the atmosphere at a given point in time.  Data assimilation thus provides the initial conditions that numerical weather prediction models use to start their forecasts.  Integrating different observations and observation types together is not easy.  Every observation has error and yet every observation is precious, as observations cost time and resources to provide, so we find dynamically consistent ways to relate observations to conditions at nearby locations so that each observation is used most effectively.  Dr. Stensrud is most interested in data assimilation for convective-scale models of thunderstorms.

Severe weather in the United States typically refers to tornadoes, large hail and damaging winds, although tropical cyclones and flash floods also are considered severe in other countries.  These types of events threaten life and property and can develop very quickly.  Dr. Stensrud has studied the physical processes that produce damaging windstorms called derechos, helped develop a climatology of heavy rainfall events over the United States, and evaluated surface data to define cold pool characteristics.  He is currently involved in studying how urban areas influence severe thunderstorms and how convective systems influence their surrounding environment.

Predictability is the degree to which a correct forecast of future atmospheric state can be made.  Questions of predictability are important to address, since it is important to know what atmospheric features we can predict well and which we cannot.  Dr. Stensrud studies the predictability of convective-scale phenomena, such as thunderstorms and convective lines.

The North American monsoon is the seasonal wind shift that occurs over southwestern North America and is accompanied by a pronounced increase in rainfall.  The monsoon is centered over western Mexico and typically starts in July and lasts into October.  Monsoon convection alters the hemispheric large-scale weather pattern and is influenced by tropical easterly waves that form over Africa. The monsoon represents a natural laboratory for the interactions between mesoscale features, such as gulf surges and outflow boundaries, and large-scale circulation patterns.  Dr. Stensrud is studying the upscale influences of deep convection on warm season circulation patterns.

Selected Service Activities

Chair, Storm-scale Radar Data Assimilation Workshop, Norman, Oklahoma, October 2011
Member, NOAA/NWS Functional Weather Radar Requirements Integrated Working Team, 2012-2013
Guest Editor, Advances in Meteorology, Special Issue on “Storm-scale data assimilation and NWP”, 2013
Commissioner, Scientific and Technological Activities Commission, American Meteorological Society, 2016-2017

Selected Publications

Stensrud, D. J., M. Xue, L. J. Wicker, K. E. Kelleher, M. P. Foster, J. T. Schaefer, R. S. Schneider, 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.

Yussouf, N., E. R. Mansell, L. J. Wicker, D. M. Wheatley, and D. J. Stensrud, 2013:  The ensemble Kalman filter analyses and forecasts of the 8 May 2003 Oklahoma City tornadic supercell thunderstorm using single and double moment microphysics.  Mon. Wea. Rev., 141, 3388-3412.

Stensrud, D. J., 2013:  Upscale effects of deep convection during the North American monsoon.  J. Atmos. Sci., 70, 2681-2695.

Banghoff, J. R., D. J. Stensrud, and M. R. Kumjian, 2018: Convective boundary layer depth estimation from S-band dual-polarization radar.  J. Atmos. Oceanic Technol., 35, 1723-1733. 

Zhang, Y., D. J. Stensrud, and F. Zhang, 2019: Simultaneous assimilation of radar and all-sky satellite infrared radiance observations for convection-allowing ensemble analysis and prediction of severe thunderstorms.  Mon. Wea. Rev., 147, 4389-4409. 

Banghoff, J. R., J. D. Sorber, D. J. Stensrud, G. S. Young, and M. R. Kumjian, 2020: A 10-year warm-season climatology of horizontal convective rolls and cellular convection in central Oklahoma.  Mon. Wea. Rev., 148, 21-42. 

Eure, K. C., P. D. Mykolajtchuk, Y. Zhang, D. J. Stensrud, F. Zhang, S. J. Greybush, and M. R. Kumjian, 2023:  Simultaneous assimilation of planetary boundary layer observations from radar and all-sky satellite observations to improve forecasts of convection intiation.  Mon. Wea. Rev., 151, 795-813, https://doi.org/10.1175/MWR-D-22-0188.1

Mykolajtchuk, P.D., K. C. Eure, D. J. Stensrud, Y. Zhang, S. J. Greybush, and M. R. Kumjian, 2023:  Diagnosing factors leading to an incorrect supercell thunderstorm forecast.  Wea. Forecasting, 38, 1935-1951, https://doi.org/10.1175/WAF-D-23-0010.1.