current deficiencies in model frameworks, physics, and dynamics while avoiding a plethora of poorly validated models that are not compatible or easily implemented in operational settings because of their complexity and the number and type of input parameters needed, (2) advancing air chemistry models and better coupling with weather models to improve predictions of particulates and other harmful atmospheric pollutants, and (3) implementing end-to-end physical social models with appropriate feedbacks and error characterization.
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Urban Meteorology: Forecasting, Monitoring, and Meeting Users' Needs . Washington, DC: The National Academies Press,
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