Uncertainty in contaminant concentration fields resulting from atmospheric boundary layer depth uncertainty

Brian P. Reen, Kerrie J. Schmehl, George Spencer Young, Jared A. Lee, Sue Ellen Haupt, David R. Stauffer

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Abstract

The relationship between atmospheric boundary layer (ABL) depth uncertainty and uncertainty in atmospheric transport and dispersion (ATD) simulations is investigated by examining profiles of predicted concentrations of a contaminant. Because ensembles are an important method for quantifying uncertainty in ATD simulations, this work focuses on the utilization and analysis of ensemble members' ABL structures for ATD simulations. A 12-member physics ensemble of meteorological model simulations drives a 12-member explicit ensemble of ATD simulations. The relationship between ABL depth and plume depth is investigated using ensemble members, which vary both the relevantmodel physics and the numericalmethods used to diagnoseABLdepth. New analysis methods are used to analyze ensemble output within an ABL-depth relative framework.Uncertainty due toABL depth calculation methodology is investigated via a four-membermini-ensemble.When subjected to a continuous tracer release, concentration variability among the ensemble members is largest near the ABL top during the daytime, apparently because of uncertainty in ABL depth. This persists to the second day of the simulation for the 4-member diagnosis mini-ensemble, which varies only the ABL depth, but for the 12-member physics ensemble the concentration variability is large throughout the daytime ABL. This suggests that the increased within-ABL concentration variability on the second day is due to larger differences among the ensemble members' predicted meteorological conditions rather than being solely due to differences in the ABL depth diagnosis methods. This work demonstrates new analysis methods for the relationship between ABL depth and plume depth within an ensemble framework and provides motivation for directly including ABL depth uncertainty from a meteorological model into an ATD model.

Original languageEnglish (US)
Pages (from-to)2610-2626
Number of pages17
JournalJournal of Applied Meteorology and Climatology
Volume53
Issue number11
DOIs
StatePublished - Jan 1 2014

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All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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