The NOAA Warn-on-Forecast program aims to develop convection—allowing ensemble numerical weather prediction systems that will enable longer warning lead times for tornadoes, flash floods, damaging wind and hail, and other thunderstorm hazards. The optimal design of these ensembles is largely determined by the intrinsic and practical predictability limits of convective storms, for two reasons. First, knowledge of the primary sensitivities of storm evolution is needed to prioritize improvements to ensemble prediction systems. For example, if sub-kilometer model grid spacing is required to reliably predict tornado potential, this suggests that computational resources should be preferentially allocated toward finer model grids versus, e.g., larger ensembles. Second, knowledge of the predictability limits of storms will help prevent wasteful resource allocation in ensemble systems. For example, if current observational and model limitations render storm track forecasts highly uncertain after 2 hours, this suggests that forecast periods >2 hours be sacrificed in favor of, e.g., more frequent forecast updates. Thorough understanding of the predictability of storms is also needed to objectively calibrate and subjectively interpret ensemble forecast output.
Comprehensive investigation of storm predictability requires both idealized experiments, which allow individual sources of forecast error to be explored, as well as real case studies, which better represent contemporary observational and modeling limitations. Translating the findings of predictability studies to the design of Warn-on-Forecast systems is itself a large undertaking, in part because of the additional degrees of freedom provided by multi-resolution ensembles. The latter use different grid spacings for the analysis updates, the forecast cycles, and/or the longer-range forecasts initialized at the end of each data assimilation period. This strategy presents a promising way to further optimize tradeoffs between forecast accuracy and forecast lead time.
Research proposals are invited on any aspect of the predictability of organized convection and/or the design and testing of multi-resolution convection-allowing ensembles.
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Potvin, C. K., and M. L. Flora, 2015: Sensitivity of idealized supercell simulations to horizontal grid spacing: Implications for Warn-On-Forecast. Mon. Wea. Rev., 143, 2998-3024.
Stensrud, D. J., L. J. Wicker, M. Xue, D. T. Dawson II, N. Yussouf, D. M. Wheatley, T. E. Thompson, N. A. Snook, T. M. Smith, A. D. Schenkman, C. K. Potvin, E. R. Mansell, T. Lei, K. M. Kuhlman, Y. Jung, T. A. Jones, J. Gao, M. C. Coniglio, H. E. Brooks, and K. A. Brewster, 2013: Progress and challenges with Warn-on-Forecast. Atmos. Res., 123, 2-16.
Predictability; Prediction; Convection; Assimilation; Ensemble; Tornado; Warning; Storm; Forecast;