Convective Weather - Aviation

Improving short-term forecasting of storm hazards affecting aviation

Convective storms can have a significant impact on the global, regional and local scale.  Our understanding of how convective storms form, grow, organize, move, and dissipate remains a scientific challenge that researchers are attacking by means of field programs, data analysis, and high-resolution modeling.  Short-term forecasting (0-8 hours) of thunderstorms is a particular focus for applied research on convective storms.

Program Goals

The research and development of the Convective Weather Program are geared towards very short-term forecasting of high-impact weather.  The objective is to enhance existing and facilitate new capabilities of monitoring (i.e., analysis), nowcasting (under two hours), and forecasting (two hours and beyond) weather-related conditions that pose a hazard or threat to, or otherwise impact, human safety, transportation on land, water, and in the air, and infrastructure.

The program strives to advance a basic understanding of dynamic, thermodynamic, and microphysical processes related to severe weather, including the initiation of storms and their subsequent evolution, by focusing on observations, data assimilation, numerical modeling, forecasting, and diagnostic evaluation.  Understanding weather sensitivity of aviation and integration of short-term weather prediction with specific stakeholder applications (i.e., decision support guidance) is a high priority.


High-resolution, short-term forecasts of thunderstorms provide critical information for a wide range of users, including the aviation community, ground transportation, urban emergency and water resources management groups, recreation facilities, construction industries, and the military, that assists them to safely and efficiently deploy resources.  However, achieving reliable and accurate convective weather forecasts remains a scientific challenge due to uncertainty in grasping initial conditions, shortcomings in model physics and computational capabilities, and limitations of our understanding of how nature works.  The forecast skill of observation-driven expert systems decreases rapidly with increasing lead-time, while numerical weather prediction models exhibit a limited forecast ability within the first few hours after initialization primarily due to spin-up problems.  Furthermore, forecast methodology and display systems have to be tuned to the needs of different users—for example, a line of severe convective storms predicted in the wrong place may be perceived as a bad forecast from a water resources manager (e.g., dam operator), yet the same forecast might be quite good for an en-route air traffic control manager.



  • Short Term Explicit Prediction (STEP)



  • MIT/LL Aviation Weather


  • NOAA Earth System Research Laboratory (ESRL)


  • NOAA National Severe Storms Laboratory (NSSL)


  • NOAA National Weather Service (NWS)


  • NOAA/NWS Aviation Weather Center (AWC)


  • NASA Short-term Prediction Research and Transition (SPoRT) Center


Search through all publications in NCAR's OpenSky Library.

Publications in Refereed Journals

Cai, H., W.-C. Lee, T. M. Weckwerth, C. Flamant, and H. V. Murphey, 2006:  Observations of the 11 June dryline during IHOP 2002—A null case for convection initiationMonthly Weather Review, 134(1), 336 – 354. 

Crook, N. A., and J. B. Klemp, 2000:  Lifting by convergence linesJournal of the Atmospheric Sciences, 57(6), 873 – 890. 

Crook, N. A., and J. Sun, 2002:  Assimilating radar, surface, and profiler data for the Sydney 2000 forecast demonstration projectJournal of Atmospheric and Oceanic Technology, 19(6), 888 – 898. 

Crook, N. A., and J. Sun, 2004:  Analysis and forecasting of the low-level wind during the Sydney 2000 forecast demonstration projectWeather and Forecasting, 19(1), 151 – 167. 

Dixon, M., and G. Wiener, 1993:  TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting—A radar-based methodologyJournal of Atmospheric and Oceanic Technology, 10(6), 785 – 797. 

Fox, N. I., R. Webb, J. Bally, M. W. Sleigh, C. E. Pierce, D. M. L. Sills, P. I. Joe, J. Wilson, and C. G. Collier, 2004:  The impact of advanced nowcasting systems on severe weather warning during the Sydney 2000 Forecast Demonstration Project: 3 November 2000Weather and Forecasting, 19(1), 97 – 114. 

Fritsch, J. M., R. A. Houze Jr., R. Adler, H. Bluestein, L. Bosart, J. Brown, F. Carr, C. Davis, R. H. Johnson, N. Junker, Y.-H. Kuo, S. Rutledge, J. Smith, Z. Toth, J. W. Wilson, E. Zipser, and D. Zrnic, 1998:  Quantitative precipitation forecasting: Report of the eighth Prospectus Development Team, U.S. Weather Research ProgramBulletin of the American Meteorological Society, 79(2), 285 – 299. 

Keenan, T., P. Joe, J. Wilson, C. Collier, B. Golding, D. Burgess, P. May, C. Pierce, J. Bally, A. Crook, A. Seed, D. Sills, L. Berry, R. Potts, I. Bell, N. Fox, E. Ebert, M. Eilts, K. O'Loughlin, R. Webb, R. Carbone, K. Browning, R. Roberts, and C. Mueller, 2003:  The Sydney 2000 World Weather Research Programme Forecast Demonstration Project: Overview and current statusBulletin of the American Meteorological Society, 84(8), 1041 – 1054. 

May, P. T., T. D. Keenan, R. Potts, J. W. Wilson, R. Webb, A. Treloar, E. Spark, S. Lawrence, E. Ebert, J. Bally, and P. Joe, 2004:  The Sydney 2000 Olympic Games Forecast Demonstration Project: Forecasting, observing network infrastructure, and data processing issuesWeather and Forecasting, 19(1), 115 – 130. 

Mueller, C., T. Saxen, R. Roberts, J. Wilson, T. Betancourt, S. Dettling, N. Oien, and J. Yee, 2003:  NCAR Auto-Nowcast systemWeather and Forecasting, 18(4), 545 – 561. 

Pierce, C. E., E. Ebert, A. W. Seed, M. Sleigh, C. G. Collier, N. I. Fox, N. Donaldson, J. W. Wilson, R. Roberts, and C. K. Mueller, 2004:  The nowcasting of precipitation during Sydney 2000: An appraisal of the QPF algorithmsWeather and Forecasting, 19(1), 7 – 21. 

Roberts, R. D., and S. Rutledge, 2003:  Nowcasting storm initiation and growth using GOES-8 and WSR-88D dataWeather and Forecasting, 18(4), 562 – 584. 

Roberts, R. D., D. Burgess, and M. Meister, 2006:  Developing tools for nowcasting storm severityWeather and Forecasting, 21(4), 540 – 558. 

Saxen, T. R., Cynthia K. Mueller, Thomas T. Warner, Matthias Steiner, Edward E. Ellison, Eric W. Hatfield, Terri L. Betancourt, Susan M. Dettling, and Niles A. Oien, 2008: The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part IV: The White Sands Missile Range Auto-Nowcast System. Journal of Applied Meteorology and Climatology, 47(4), 1123–1139.

Sharif, H. O., D. Yates, R. Roberts, and C. Mueller, 2006:  The use of an automated nowcasting system to forecast flash floods in an urban watershedJournal of Hydrometeorology, 7(1), 190 – 202. 

Sills, D. M. L., J. W. Wilson, P. I. Joe, D. W. Burgess, R. M. Webb, and N. I. Fox, 2004:  The 3 November tornadic event during Sydney 2000: Storm evolution and the role of low-level boundariesWeather and Forecasting, 19(1), 22 – 42. 

Sun, J., and N. A. Crook, 1997:  Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experimentsJournal of the Atmospheric Sciences, 54(12), 1642 – 1661. 

Sun, J., and N. A. Crook, 1998:  Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective stormJournal of the Atmospheric Sciences, 55(5), 835 – 852. 

Sun, J., and N. A. Crook, 2001:  Real-time low-level wind and temperature analysis using single WSR-88D dataWeather and Forecasting, 16(1), 117 – 132. 

Warner, T. T., E. A. Brandes, J. Sun, D. N. Yates, and C. K. Mueller, 2000:  Prediction of a flash flood in complex terrain. Part I: A comparison of rainfall estimates from radar, and very short range rainfall simulations from a dynamic model and an automated algorithmic systemJournal of Applied Meteorology, 39(6), 797 – 814. 

Wilson, J. W., N. A. Crook, C. K. Mueller, J. Sun, and M. Dixon, 1998:  Nowcasting thunderstorms: A status reportBulletin of the American Meteorological Society, 79(10), 2079 – 2099. 

Wilson, J. W., R. E. Carbone, J. D. Tuttle, and T. D. Keenan, 2001:  Tropical island convection in the absence of significant topography. Part II: nowcasting storm evolutionMonthly Weather Review, 129(7), 1637 – 1655. 

Wilson, J. W., E. E. Ebert, T. R. Saxen, R. D. Roberts, C. K. Mueller, M. Sleigh, C. E. Pierce, and A. Seed, 2004:  Sydney 2000 Forecast Demonstration Project: Convective storm nowcastingWeather and Forecasting, 19(1), 131 – 150. 

Xiao, Q., Y.-H. Kuo, J. Sun, W.-C. Lee, D. M. Barker, and E. Lim, 2007:  An approach of radar reflectivity data assimilation and its assessment with the inland QPF of Typhoon Rusa (2002) at landfallJournal of Applied Meteorology and Climate, 46(1), 14 – 22. 

Yates, D. N., T. T. Warner, and G. H. Leavesley, 2000:  Prediction of a flash flood in complex terrain. Part II: A comparison of flood discharge simulations using rainfall input from radar, a dynamic model, and an automated algorithmic systemJournal of Applied Meteorology, 39(6), 815 – 825.

Convective Weather - Aviation