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Impact of inherent meteorology uncertainty on air quality model predictions
Author(s) -
Gilliam Robert C.,
Hogrefe Christian,
Godowitch James M.,
Napelenok Sergey,
Mathur Rohit,
Rao S. Trivikrama
Publication year - 2015
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd023674
Subject(s) - cmaq , weather research and forecasting model , air quality index , meteorology , environmental science , data assimilation , ensemble forecasting , range (aeronautics) , wind speed , air pollution , model output statistics , atmospheric sciences , climatology , geography , engineering , chemistry , organic chemistry , geology , aerospace engineering
It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is important to understand how uncertainties in these inputs affect the simulated concentrations. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. Most studies explore this uncertainty by running different meteorological models or the same model with different physics options and in some cases combinations of different meteorological and air quality models. While these have been shown to be useful techniques in some cases, we present a technique that leverages the initial condition perturbations of a weather forecast ensemble, namely, the Short‐Range Ensemble Forecast system to drive the four‐dimensional data assimilation in the Weather Research and Forecasting (WRF)‐Community Multiscale Air Quality (CMAQ) model with a key focus being the response of ozone chemistry and transport. Results confirm that a sizable spread in WRF solutions, including common weather variables of temperature, wind, boundary layer depth, clouds, and radiation, can cause a relatively large range of ozone‐mixing ratios. Pollutant transport can be altered by hundreds of kilometers over several days. Ozone‐mixing ratios of the ensemble can vary as much as 10–20 ppb or 20–30% in areas that typically have higher pollution levels.