Ozone ensemble forecasts: 1. A new ensemble design

[1] A new Ozone Ensemble Forecast System (OEFS) is tested as a technique to improve the accuracy of real-time photochemical air quality modeling. The performance of 12 different forecasts along with their ensemble mean is tested against the observations during 11–15 August 2004, over five monitoring stations in the Lower Fraser Valley, British Columbia, Canada, a population center in a complex coastal mountain setting. The 12 ensemble members are obtained by driving the U.S. Environmental Protection Agency (EPA) Models-3/Community Multiscale Air Quality Model (CMAQ) with two mesoscale meteorological models, each run at two resolutions (12- and 4-km): the Mesoscale Compressible Community (MC2) model and the Penn State/NCAR mesoscale (MM5) model. Moreover, CMAQ is run for three emission scenarios: a control run, a run with 50% more NOx emissions, and a run with 50% fewer. For the locations and days used to test this new OEFS, the ensemble mean is the best forecast if ranked using correlation, gross error, and root mean square error and has average performance when evaluated with the unpaired peak prediction accuracy. Ensemble averaging removes part of the unpredictable components of the physical and chemical processes involved in the ozone fate, resulting in a more skilful forecast when compared to any deterministic ensemble member. There is not one of the 12 individual forecasts that clearly outperforms the others on the basis of the four statistical parameters considered here. A lagged-averaged OEFS is also tested as follows. The 12-member OEFS is expanded to an 18-member OEFS by adding the second day from the six 12-km “yesterday” forecasts to the “today” ensemble forecast. The 18-member ensemble does not improve the ensemble mean forecast skill. Neither correlation nor a relationship between ensemble spread and forecast error is evident.

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

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

[3]  Eugenia Kalnay,et al.  Ensemble Forecasting at NMC: The Generation of Perturbations , 1993 .

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

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

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

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

[8]  D. Stensrud,et al.  Evaluation of a Short-Range Multimodel Ensemble System , 2001 .

[9]  J. Salmond,et al.  Secondary ozone maxima in a very stable nocturnal boundary layer: observations from the Lower Fraser Valley, BC , 2002 .

[10]  E. Kalnay,et al.  Ensemble Forecasting at NCEP and the Breeding Method , 1997 .

[11]  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 .

[12]  F. Girardi,et al.  The field campaigns of the European Tracer Experiment (ETEX): overview and results , 1998 .

[13]  C. Willmott.  ON THE VALIDATION OF MODELS , 1981 .

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

[15]  R. Vingarzan.  A review of surface ozone background levels and trends , 2004 .

[16]  M. Brauer,et al.  Personal and fixed-site ozone measurements with a passive sampler. , 1995, Journal of the Air & Waste Management Association.

[17]  D. Steyn,et al.  Overview of tropospheric ozone in the Lower Fraser Valley, and the Pacific '93 field study , 1997 .

[18]  William F. Ryan,et al.  A Real-Time Eulerian Photochemical Model Forecast System: Overview and Initial Ozone Forecast Performance in the Northeast U.S. Corridor , 2004 .

[19]  K. Droegemeier,et al.  Objective Verification of the SAMEX ’98 Ensemble Forecasts , 2001 .

[20]  R. J. Yamartino,et al.  The CALGRID mesoscale photochemical grid model—I. Model formulation , 1992 .

[21]  M. C. Dodge,et al.  A photochemical kinetics mechanism for urban and regional scale computer modeling , 1989 .

[22]  M. Desgagné,et al.  The Canadian MC2: A Semi-Lagrangian, Semi-Implicit Wideband Atmospheric Model Suited for Finescale Process Studies and Simulation , 1997 .

[23]  E. Lorenz.  Deterministic nonperiodic flow , 1963 .

[24]  C. Leith.  Theoretical Skill of Monte Carlo Forecasts , 1974 .

[25]  A Citizen’s Guide to Air Pollution , 2003 .

[26]  Carlie J. Coats,et al.  High Performance Algorithms In The Sparse Matrix Operator Kernel Emissions (smoke) Modeling System , 1996 .

[27]  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 .

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

[29]  Ross N. Hoffman,et al.  Lagged average forecasting, an alternative to Monte Carlo forecasting , 1983 .

[30]  J. Lundgren,et al.  Tropospheric layering of ozone in regions of urbanized complex and/or coastal terrain: a review , 2000 .

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

[32]  G. Grell,et al.  A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5) , 1994 .

[33]  Julius Chang,et al.  On the performance of numerical solvers for a chemistry submodel in three‐dimensional air quality models: 1. Box model simulations , 2001 .

[34]  A. Martilli,et al.  A Numerical Study of Recirculation Processes in the Lower Fraser Valley (British Columbia, Canada) , 2007 .

[35]  B. Lamb,et al.  Intercomparison of the community multiscale air quality model and CALGRID using process analysis. , 2005, Environmental science & technology.

[36]  K. Taylor.  Summarizing multiple aspects of model performance in a single diagram , 2001 .

[37]  Brian K. Lamb,et al.  A Numerical Daily Air Quality Forecast System for The Pacific Northwest , 2004 .

[38]  Ross N. Hoffman,et al.  Medium Range Lagged Average Forecasts , 1988 .

[39]  Stephen J. Thomas,et al.  An Ensemble Analysis of Forecast Errors Related to Floating Point Performance , 2002 .

[40]  Ian G. McKendry,et al.  Synoptic Circulation and Summertime Ground-Level Ozone Concentrations at Vancouver, British Columbia , 1994 .

[41]  B. Ainslie.  A photochemical model based on a scaling analysis of ozone photochemistry , 2004 .

[42]  F. Molteni,et al.  The ECMWF Ensemble Prediction System: Methodology and validation , 1996 .

[43]  Robin L. Dennis,et al.  NARSTO critical review of photochemical models and modeling , 2000 .