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Regional and Seasonal Biases in Convection-Allowing Model Forecasts of Near-Surface Temperature and Moisture
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2023
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Source: Wea. Forecasting, 38, 2415–2426
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Journal Title:Weather and Forecasting
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Description:This study investigates regional, seasonal biases in convection-allowing model forecasts of near-surface temperature and dewpoint in areas of particular importance to forecasts of severe local storms. One method compares model forecasts with objective analyses of observed conditions in the inflow sectors of reported tornadoes. A second method captures a broader sample of environments, comparing model forecasts with surface observations under certain warm-sector criteria. Both methods reveal a cold bias across all models tested in Southeast U.S. cool-season warm sectors. This is an operationally important bias given the thermodynamic sensitivity of instability-limited severe weather that is common in the Southeast cool season. There is not a clear bias across models in the Great Plains warm season, but instead more varied behavior with differing model physics.
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Source:Wea. Forecasting, 38, 2415–2426
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Rights Information:Other
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Compliance:Submitted
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