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Sean M. Wile, Joshua P. Hacker, and Kenneth H. Chilcoat

anemometer-height observations contain potentially useful information for both forecasters and NWP model initialization. Surface observation networks could conceivably be designed to improve fog forecasts in regions particularly susceptible. At the heart of the network design is an understanding of numerical forecast sensitivity to initial-condition analysis perturbations that result from assimilating proposed hypothetical observations. One candidate method for quantifying forecast sensitivity to

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Jeffrey D. Massey, W. James Steenburgh, Jason C. Knievel, and William Y. Y. Cheng

1. Introduction Accurate temperature forecasts by numerical weather prediction (NWP) models are critical for the protection of life and property, economic and operational activities, and routine day-to-day planning. Temperature forecasts not only affect near-surface (2 m) conditions, but also atmospheric stability, planetary boundary layer (PBL) heights, near-surface winds, and precipitation type. Large systematic temperature errors from the Weather Research and Forecasting (WRF) Model are

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