Open AccessQuantifying Uncertainties of Ground‐Level Ozone Within WRF‐Chem Simulations in the Mid‐Atlantic Region of the United States as a Response to Variability
Author(s) -
Thomas Andrew,
Huff Amy K.,
Hu XiaoMing,
Zhang Fuqing
Publication year - 2019
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1029/2018ms001457
Subject(s) - weather research and forecasting model , predictability , environmental science , air quality index , ozone , ground level ozone , mean squared error , ground level , climatology , meteorology , sensitivity (control systems) , root mean square , planetary boundary layer , propagation of uncertainty , atmospheric sciences , atmospheric research , boundary layer , mathematics , physics , statistics , geology , thermodynamics , architectural engineering , ground floor , quantum mechanics , electronic engineering , engineering
Understanding forecast uncertainties and error growth dynamics is a prerequisite for improving dynamical prediction of meteorology and air quality. While predictability of meteorology has been investigated over the past few decades, the uncertainties in air quality simulations are less well known. This study explores the uncertainties in predicting ground‐level ozone (O 3 ) in the Mid‐Atlantic region of the United States during June 2016 through a series of simulations using WRF‐Chem, focusing on the sensitivity to the meteorological initial and boundary conditions (IC/BCs), emissions inventory (EI), and planetary boundary layer (PBL) scheme. The average uncertainty of ground‐level maximum 8‐hr average O 3 mixing ratio (MD8‐O 3 ) was most sensitive to uncertainties in the IC/BCs, while uncertainty in the EI was of secondary importance, and was least sensitive was to the use of different PBL schemes. Updating the NO emissions in the EI had the greatest influence on the accuracy, with an estimated decrease of 0.59 ppbv/year in the root‐mean‐square error and an average decrease of 0.63 ppbv/year in the values of modeled MD8‐O 3 . Our study suggests using perturbations in IC/BCs may lead to a more dispersive ensemble of O 3 prediction than using different PBL schemes and/or different EI. However, considering the combined uncertainties from all three sources examined are still smaller than the averaged root‐mean‐square errors of predicted O 3 against observations, there are apparent other sources of uncertainties not studied that need to be considered in future ensemble predictions of O 3 .