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The higher the numerical resolution, the more accurate the calculations become.  A high spatial resolution also enables a better representation of topographical fields (mountains, coasts, islands) and the effects they have both on local weather and the large-scale flow.  It also produces a more accurate description of horizontal and vertical structures, which facilitates better assimilation of observations.  However, the smallest atmospheric features that can be resolved by models using the Reduced Gaussian Octahedral grid (HRES* and ENS) have wavelengths four to six times the nominal grid point distance.  Such small atmospheric systems have a predictability of relatively few hours but their representation is important for energy exchanges between different atmospheric scales.  Increasing the resolution (i.e. making grid point spacing smaller) benefits the analyses and forecasts of both large-scale systems (such as large-scale blocking "omega" anticyclones, and "cut-off lows") and the small-scale systems often associated with severe weather.  The ability to accurately forecast the formation of large-scale blocking “omega” anticyclones and “cut-off lows” depends crucially on sufficient effective resolution.  To capture mesoscale phenomena a resolution of at least ~1km is required.

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Fig2.1.5: Rainfall forecasts run for the same period (24hr rainfall to T+69 verifying at 06UTC 6 Dec 2015) at several resolutions.    Resolutions: 80km , 36 km (used by system 5 seasonal and extended ranges (day 16-46), 18km, 9km (used by HRES* and ensembleENS) , 5km (a possible future resolution).

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