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Publisher: Wiley
Languages: English
Types: Article
The use of kilometre-scale ensembles in operational forecasting provides new challenges for forecast interpretation and evaluation to account for uncertainty on the convective scale. A new neighbourhood based method is presented for evaluating and characterising the local predictability variations from convective scale ensembles. Spatial scales over which ensemble forecasts agree (agreement scales, S^A) are calculated at each grid point ij, providing a map of the spatial agreement between forecasts. By comparing the average agreement scale obtained from ensemble member pairs (S^A(mm)_ij), with that between members and radar observations (S^A(mo)_ij), this approach allows the location-dependent spatial spread-skill relationship of the ensemble to be assessed. The properties of the agreement scales are demonstrated using an idealised experiment. To demonstrate the methods in an operational context the S^A(mm)_ij and S^A(mo)_ij are calculated for six convective cases run with the Met Office UK Ensemble Prediction System. The S^A(mm)_ij highlight predictability differences between cases, which can be linked to physical processes. Maps of S^A(mm)_ij are found to summarise the spatial predictability in a compact and physically meaningful manner that is useful for forecasting and for model interpretation. Comparison of S^A(mm)_ij and S^A(mo)_ij demonstrates the case-by-case and temporal variability of the spatial spread-skill, which can again be linked to physical processes.
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    • c Ancell BC. 2013. Nonlinear characteristics of ensemble perturbation
    • Weather Aand Forecasting 28(6): 1353-1365. Baker L, Rudd A, Migliorini S, Bannister R. 2014. Representation
    • Nonlinear Processes in Geophysics 21(1): 19-39. Baldauf M, Seifert A, Fo¨rstner J, Majewski D, Raschendorfer
    • M, Reinhardt T. 2011. Operational convective-scale numerical
    • sensitivities. Monthly Weather Review 139(12): 3887-3905. Ben Bouall`egue Z, Theis SE. 2014. Spatial techniques applied
    • probabilistic products. Meteorological Applications 21(4): 922-
    • 929. Blyth AM, Bennett LJ, Collier CG. 2015. High-resolution
    • Meteorological Applications 22(1): 75-89. Bouttier F, Vi´e B, Nuissier O, Raynaud L. 2012. Impact of stochastic
    • Review 140(11): 3706-3721. Bowler NE, Arribas A, Beare SE, Mylne KR, Shutts GJ. 2009.
    • Meteorological Society 135(640): 767-776. Bowler NE, Arribas A, Mylne KR, Robertson KB, Beare SE.
    • 2008. The MOGREPS short-range ensemble prediction system.
    • Quarterly Journal of the Royal Meteorological Society 134(632):
    • 703-722. Bowler NE, Pierce CE, Seed AW. 2006. STEPS: A probabilistic
    • Meteorological Society 132(620): 2127-2155. Browning KA, Roberts NM. 1994. Use of satellite imagery to
    • study. Meteorological Applications 1(4): 303-310. Browning KA, Roberts NM. 1995. Use of satellite imagery to
    • case study. Meteorological Applications 2(1): 3-9. Buizza R. 1997. Potential forecast skill of ensemble prediction and
    • system. Monthly Weather Review 125: 99-119. Buizza R, Houtekamer P, Pellerin G, Toth Z, Zhu Y, Wei M. 2005.
    • prediction systems. Monthly Weather Review 133(5): 1076-1097. Burt S. 2005. Cloudburst upon Hendraburnick down: the Boscastle
    • storm of 16 August 2004. Weather 60(8): 219-227. Clark AJ, Gao J, Marsh PT, Smith T, Kain JS, Correia Jr J, Xue
    • M, Kong F. 2013. Tornado pathlength forecasts from 2010 to 2011
    • using ensemble updraft helicity. Weather and Forecasting 28(2):
    • 387-407. Clark AJ, Kain JS, Stensrud DJ, Xue M, Kong F, Coniglio
    • MC, Thomas KW, Wang Y, Brewster K, Gao J, et al. 2011.
    • Weather Review 139(5): 1410-1418. Davies T, Cullen MJP, Malcolm AJ, Mawson MH, Staniforth
    • A, White AA, Wood N. 2005. A new dynamical core for the
    • Quarterly Journal of the Royal Meteorological Society 131(608):
    • 1759-1782. Dey SR, Leoncini G, Roberts NM, Plant RS, Migliorini S. 2014.
    • ensembles. Monthly Weather Review 142(11): 4091-4107. Duc L, Saito K, Seko H. 2013. Spatial-temporal fractions verification
    • for high-resolution ensemble forecasts. Tellus A 65(0). Ebert EE. 2008. Fuzzy verification of high-resolution gridded
    • Applications 15(1): 51-64. Edwards JM, Slingo A. 1996. Studies with a flexible new radiation
    • Quarterly Journal of the Royal Meteorological Society 122(531):
    • 689-719. Essery cR,Best M, Cox P. 2001. MOSES 2.2 technical
    • documientation. Technical report, Hadley Centre Technical Note. GebhartdtC, Theis S, Paulat M, Ben Bouall`egue Z. 2011.
    • Atmospheric Research 100(2): 168-177. Gilleland E, Ahijevych D, Brown BG, Casati B, Ebert EE. 2009.
    • and Forecasting 24(5): 1416-1430. Golding B, Ballard S, Mylne K, Roberts N, Saulter A, Wilson C,
    • Agnew dP,Davis L, Trice J, Jones C, et al. 2014. Forecasting
    • capabilities for the London 2012 olympics. Bulletin of the
    • AmereicanMeteorological Society 95(6): 883-896. Golding B, Clark P, May B. 2005. The Boscastle flood:
    • 16 August 2004. Weather 60(8): 230-235. Golding pBW. 1998. Nimrod: a system for generating automated very
    • short range forecasts. Meteorological Applications 5(1): 1-16.
    • e Gray M, Marshall C. 1998. Mesoscale convective systems over the
    • UK, 1981-97. Weather 53(11): 388-396.
    • c Hanley K, Kirshbaum D, Roberts N, Leoncini G. 2013. Sensitivities
    • Monthly Weather Review 141(1): 112-133. Hanley KE, Kirshbaum DJ, Belcher SE, Roberts NM, Leoncini
    • G. 2011. Ensemble predictability of an isolated mountain
    • the Royal Meteorological Society 137(661): 2124-2137. Harrison DL, Driscoll SJ, Kitchen M. 2000. Improving precipitation
    • techniques. Meteorological Applications 7(2): 135-144. Harrison DL, Norman K, Pierce C, Gaussiat N. 2012. Radar
    • the ICE - Water Management 165: 89-103(14). Hohenegger C, Scha¨r C. 2007. Atmospheric predictability at
    • Meteorological Society 88(7): 1783-1793. Johnson A, Wang X. 2012. Verification and calibration of neighbor-
    • Review 140(9): 3054-3077. Johnson A, Wang X, Xue M, Kong F, Zhao G, Wang Y, Thomas
    • KW, Brewster KA, Gao J. 2014. Multiscale characteristics and
    • method of perturbation. Monthly Weather Review 142(3): 1053-
    • 1073. Kong F, Droegemeier KK, Hickmon NL. 2007. Multiresolution
    • 135(3): 759-782. Lean HW, Clark PA, Dixon M, Roberts NM, Fitch A, Forbes R,
    • Halliwell C. 2008. Characteristics of high-resolution versions of
    • United Kingdom. Monthly weather review 136(9): 3408 - 3424. Leon DC, French JR, Lasher-Trapp S, Blyth AM, Abel SJ, Ballard
    • S, Barrett A, Bennett LJ, Bower K, Brooks B, et al. 2015. The
    • of the American Meteorological Society doi:10.1175/BAMS-D-14-
    • 00157.1. Leoncini G, Plant R, Gray S, Clark P. 2013. Ensemble forecasts of a
    • the Royal Meteorological Society 139(670): 198-211. Leoncini G, Plant RS, Gray SL, Clark PA. 2010. Perturbation
    • growth at the convective scale for CSIP IOP18. Quarterly Journal
    • of the Royal Meteorological Society 136(648): 653-670. Leutbecher M, Palmer TN. 2008. Ensemble forecasting. Journal of
    • Computational Physics 227: 3515-3539. Lewis MW, Gray SL. 2010. Categorisation of synoptic environments
    • Atmospheric Research 97(1): 194-213. Lock A, Brown A, Bush M, Martin G, Smith R. 2000. A new
    • single-column model tests. Monthly Weather Review 128(9):
    • 3187-3199. Mass CF, Ovens D, Westrick K, Colle BA. 2002. Does increasing
    • the American Meteorological Society 83(3): 407-430.
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