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    Measuring the Ensemble Spread–Error Relationship with a Probabilistic Approach: Stochastic Ensemble Results 

    Source: Monthly Weather Review:;2007:;volume( 135 ):;issue: 001:;page 203
    Author(s): Grimit, Eric P.; Mass, Clifford F.
    Publisher: American Meteorological Society
    Abstract: One widely accepted measure of the utility of ensemble prediction systems is the relationship between ensemble spread and deterministic forecast accuracy. Unfortunately, this relationship is often characterized by spread?error ...
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    Initial Results of a Mesoscale Short-Range Ensemble Forecasting System over the Pacific Northwest 

    Source: Weather and Forecasting:;2002:;volume( 017 ):;issue: 002:;page 192
    Author(s): Grimit, Eric P.; Mass, Clifford F.
    Publisher: American Meteorological Society
    Abstract: Motivated by the promising results of global-scale ensemble forecasting, a number of groups have attempted mesoscale, short-range ensemble forecasting (SREF), focusing mainly over the eastern half of the United States. To ...
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    Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction 

    Source: Monthly Weather Review:;2009:;volume( 138 ):;issue: 005:;page 1811
    Author(s): Bao, Le; Gneiting, Tilmann; Grimit, Eric P.; Guttorp, Peter; Raftery, Adrian E.
    Publisher: American Meteorological Society
    Abstract: Wind direction is an angular variable, as opposed to weather quantities such as temperature, quantitative precipitation, or wind speed, which are linear variables. Consequently, traditional model output statistics and ...
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