Impacts of meteorological uncertainties on ozone pollution predictability estimated through meteorological and photochemical ensemble forecasts

[1] This study explores the sensitivity of ozone predictions from photochemical grid point simulations to small meteorological initial perturbations that are realistic in structure and evolution. Through both meteorological and photochemical ensemble forecasts with the Penn State/NCAR mesoscale model MM5 and the EPA Community Multiscale Air Quality (CMAQ) Model-3, the 24-hour ensemble mean of meteorological conditions and the ozone concentrations compared fairly well against the observations for a highozone event that occurred on 30 August during the Texas Air Quality Study of 2000 (TexAQS2000). Moreover, it was also found that there were dramatic uncertainties in the ozone prediction in Houston and surrounding areas due to initial meteorological uncertainties for this event. The high uncertainties in the ozone prediction in Houston and surrounding areas due to small initial wind and temperature uncertainties clearly demonstrated the importance of accurate representation of meteorological conditions for the Houston ozone prediction and the need for probabilistic evaluation and forecasting for air pollution, especially those supported by regulating agencies.

[1]  D. Byun Science algorithms of the EPA Models-3 community multi-scale air quality (CMAQ) modeling system , 1999 .

[2]  Christopher K. Wikle,et al.  Atmospheric Modeling, Data Assimilation, and Predictability , 2005, Technometrics.

[3]  A. Yegnan,et al.  Uncertainty analysis in air dispersion modeling , 2002, Environ. Model. Softw..

[4]  V. Mallet,et al.  Uncertainty in a chemistry-transport model due to physical parameterizations and numerical approximations: An ensemble approach applied to ozone modeling , 2006 .

[5]  Torben Mikkelsen,et al.  Ensemble dispersion forecasting—Part II: application and evaluation , 2004 .

[6]  Youhua Tang,et al.  A simple method to improve ensemble‐based ozone forecasts , 2005 .

[7]  Fuqing Zhang,et al.  Ensemble‐based data assimilation for thermally forced circulations , 2005 .

[8]  P. Hess,et al.  Industrial emissions cause extreme urban ozone diurnal variability. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Nancy J. Brown,et al.  Evaluating Uncertainties in Regional Photochemical Air Quality Modeling , 2003 .

[10]  H. Christopher Frey,et al.  Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain , 2001 .

[11]  Thomas T. Warner,et al.  Ensemble Simulations with Coupled Atmospheric Dynamic and Dispersion Models: Illustrating Uncertainties in Dosage Simulations , 2002 .

[12]  M. Sofiev,et al.  Ensemble dispersion forecasting—Part I: concept, approach and indicators , 2004 .

[13]  G. Grell,et al.  Meteorological evaluation of a weather‐chemistry forecasting model using observations from the TEXAS AQS 2000 field experiment , 2005 .

[14]  John N. McHenry,et al.  Evaluating the performance of regional-scale photochemical modeling systems: Part I—meteorological predictions , 2001 .

[15]  H. Pan,et al.  Nonlocal Boundary Layer Vertical Diffusion in a Medium-Range Forecast Model , 1996 .

[16]  Tete,et al.  SUMMARY AND DISCUSSION , 1972 .

[17]  Fuqing Zhang,et al.  Ensemble-based simultaneous state and parameter estimation in a two-dimensional sea-breeze model , 2006 .

[18]  Walter F. Dabberdt,et al.  Uncertainty, ensembles and air quality dispersion modeling: applications and challenges , 2000 .

[19]  Rohit Mathur,et al.  Assessment of an ensemble of seven real-time ozone forecasts over eastern North America during the summer of 2004 , 2005 .

[20]  J. Simpson Sea Breeze and Local Winds , 1994 .

[21]  Luca Delle Monache,et al.  Ozone ensemble forecasts: 1. A new ensemble design , 2006 .

[22]  Richard Rotunno,et al.  On the Linear Theory of the Land and Sea Breeze , 1983 .

[23]  Altug Aksoy,et al.  Mesoscale ensemble-based data assimilation and parameter estimation , 2005 .

[24]  M. Estoque,et al.  The Sea Breeze as a Function of the Prevailing Synoptic Situation , 1962 .

[25]  E. Atlas,et al.  Signatures of terminal alkene oxidation in airborne formaldehyde measurements during TexAQS 2000 , 2003 .

[26]  L. Delle Monache,et al.  An ensemble air-quality forecast over western Europe during an ozone episode , 2003 .

[27]  E. Atlas,et al.  Effect of petrochemical industrial emissions of reactive alkenes and NOx on tropospheric ozone formation in Houston, Texas , 2003 .

[28]  D. B. Turner,et al.  Relating error bounds for maximum concentration estimates to diffusion meteorology uncertainty , 1987 .

[29]  E. Williams,et al.  A BAD AIR DAY IN HOUSTON , 2005 .

[30]  Laurent Menut,et al.  Adjoint modeling for atmospheric pollution process sensitivity at regional scale , 2003 .

[31]  Richard T. McNider,et al.  Mesoscale model performance with assimilation of wind profiler data: Sensitivity to assimilation parameters and network configuration , 2007 .

[32]  Anne Grete Straume,et al.  A More Extensive Investigation of the Use of Ensemble Forecasts for Dispersion Model Evaluation , 2001 .

[33]  Crystal Zuzek BAD AIR DAY? , 2008, Science.

[34]  G. Grell Prognostic evaluation of assumptions used by cumulus parameterizations , 1993 .

[35]  Luca Delle Monache,et al.  Ozone ensemble forecasts: 2. A Kalman filter predictor bias correction , 2006 .

[36]  M. Bergin,et al.  Formal Uncertainty Analysis of a Lagrangian Photochemical Air Pollution Model , 1999 .

[37]  J. Dudhia A Nonhydrostatic Version of the Penn State–NCAR Mesoscale Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front , 1993 .

[38]  H Slaper,et al.  Can the confidence in long range atmospheric transport models be increased? The pan-european experience of ensemble. , 2004, Radiation protection dosimetry.

[39]  Matthias Beekmann,et al.  Monte Carlo uncertainty analysis of a regional‐scale transport chemistry model constrained by measurements from the Atmospheric Pollution Over the Paris Area (ESQUIF) campaign , 2003 .

[40]  L. Darby Cluster Analysis of Surface Winds in Houston, Texas, and the Impact of Wind Patterns on Ozone , 2005 .

[41]  Hans Peter Schmid,et al.  Meteorological Research Needs for Improved Air Quality Forecasting Report of the 11th Prospectus Development Team of the U.S. Weather Research Program , 2004 .