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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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    Removal of Systematic Model Bias on a Model Grid 

    Source: Weather and Forecasting:;2008:;volume( 023 ):;issue: 003:;page 438
    Author(s): Mass, Clifford F.; Baars, Jeffrey; Wedam, Garrett; Grimit, Eric; Steed, Richard
    Publisher: American Meteorological Society
    Abstract: Virtually all numerical forecast models possess systematic biases. Although attempts to reduce such biases at individual stations using simple statistical corrections have met with some success, there is an acute need for ...
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    Locally Calibrated Probabilistic Temperature Forecasting Using Geostatistical Model Averaging and Local Bayesian Model Averaging 

    Source: Monthly Weather Review:;2011:;volume( 139 ):;issue: 008:;page 2630
    Author(s): Kleiber, William; Raftery, Adrian E.; Baars, Jeffrey; Gneiting, Tilmann; Mass, Clifford F.; Grimit, Eric
    Publisher: American Meteorological Society
    Abstract: he authors introduce two ways to produce locally calibrated grid-based probabilistic forecasts of temperature. Both start from the Global Bayesian model averaging (Global BMA) statistical postprocessing method, which has ...
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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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    Wind Ramp Events Validation in NWP Forecast Models during the Second Wind Forecast Improvement Project (WFIP2) Using the Ramp Tool and Metric (RT&M) 

    Source: Weather and Forecasting:;2020:;volume( 035 ):;issue: 006:;page 2407
    Author(s): Djalalova, Irina V.;Bianco, Laura;Akish, Elena;Wilczak, James M.;Olson, Joseph B.;Kenyon, Jaymes S.;Berg, Larry K.;Choukulkar, Aditya;Coulter, Richard;Fernando, Harinda J. S.;Grimit, Eric;Krishnamurthy, Raghavendra;Lundquist, Julie K.;Muradyan, Paytsar;Tu
    Publisher: American Meteorological Society
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    Regional Environmental Prediction Over the Pacific Northwest 

    Source: Bulletin of the American Meteorological Society:;2003:;volume( 084 ):;issue: 010:;page 1353
    Author(s): Mass, Clifford F.; Albright, Mark; Ovens, David; Steed, Richard; MacIver, Mark; Grimit, Eric; Eckel, Tony; Lamb, Brian; Vaughan, Joseph; Westrick, Kenneth; Storck, Pascal; Colman, Brad; Hill, Chris; Maykut, Naydene; Gilroy, Mike; Ferguson, Sue A.; Yetter, Joseph; Sierchio, John M.; Bowman, Clint; Stender, Richard; Wilson, Robert; Brown, William
    Publisher: American Meteorological Society
    Abstract: This paper examines the potential of regional environmental prediction by focusing on the local forecasting effort in the Pacific Northwest. A consortium of federal, state, and local agencies have funded the development ...
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