B.P. Reen, K.J. Schmehl, G.S. Young, J.A. Lee, Sue Ellen Haupt and D.R. Stauffer, 2014
Uncertainty in Contaminant Concentration Fields Resulting from Atmospheric Boundary Layer Depth Uncertainty
Journal of Applied Meteorology and Climatology. 53, 2610-2626
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
relevant model physics and the numerical methods used to diagnose ABL depth.
New analysis methods are used to analyze ensemble output within an ABL-depth
relative framework. Uncertainty due to ABL depth calculation methodology is
investigated via a four-member mini-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.