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Elizabeth E. Ebert and William A. Gallus Jr.

1. Introduction As the spatial and temporal resolution of forecasts from numerical weather prediction (NWP) models grows increasingly finer, there is a need for spatial verification approaches that adequately reflect the quality of these forecasts without overpenalizing errors at the grid scale. Many new spatial verification strategies have been proposed, including neighborhood or fuzzy verification, scale decomposition, features-based verification, and field deformation approaches [for reviews

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Eric Gilleland, David Ahijevych, Barbara G. Brown, Barbara Casati, and Elizabeth E. Ebert

1. Introduction Small-scale variability in high-resolution weather forecasts presents a challenging problem for verifying forecast performance. Traditional verification scores provide incomplete information about the quality of a forecast because they only make comparisons on a point-to-point basis with no regard to spatial information [ Baldwin and Kain (2006) ; Casati et al. (2008) ; see Wilks (2005) and Jolliffe and Stephenson (2003) for more on traditional verification scores]. For

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