Directional Biases in Back Trajectories Caused by Model and Input Data

References

• Ashbaugh, L.L.; Malm, W.C.; Sadeh, W.Z. A Residence Time Probability Analysis of Sulfur Concentrations at Grand Canyon National Park. Atmos. Env. 1985, 19, 1263-1270.
   Google Scholar
• Poirot, R.L.; Wishinski, P.R. Visibility, Sulfate and Air Mass History Associated With the Summertime Aerosol in Northern Vermont; Atmos. Env. 1986, 20, 1457-1469.
   Google Scholar
• Miller, J.E.; Mantis, H.T. An Objective Method of Forecasting Visibility; Bull. Am. Meteor. Soc. 1948, 29, 237-250.
   Google Scholar
• Green, M.C.; Pai, P.; Ashbaugh, L.; Farber, R.J. Evaluation of Wind Fields Used in Grand Canyon Visibility Transport Commission Analyses: J. Air & Waste Manage Assoc. 2000, 50, 809-817.
   Google Scholar
• Stohl, A. Computation, Accuracy and Applications of Trajectories: A Review and Bibliography; Atmos. Env. 1998, 32, 947-966.
   Google Scholar
• Schichtel, B.A.; Gebhart, K.A.; Barna, M.G.; Malm, W.C.; Day, D.; Kreidenweis, S.; Green, M. Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study Results: Air Quality Data and Source Attribution Analyses Results from the National Park Service /Cooperative Institute for Research in the Atmosphere; Final Report, July 2004; available at http://vista.cira.colostate.edu/improve/Studies/BRAVO/reports/FinalReport/bravofinalreport_CIRA.htm (accessed October 6, 2005).
   Google Scholar
• Pitchford, M.L.; Tombach, I.H.; Barna, M.G.; Gebhart, K.A.; Green, M.C.; Knipping, E.; Kumar, N.; Malm, W.C.; Pun, B.; Schichtel, B.A.; Seigneur, C. Big Bend Regional Aerosol and Visibility Observational Study (BRAVO) Study. Official Report of the sponsoring agencies: U.S. Environmental Protection Agency, National Park Service, Texas Commission on Environmental Quality, EPRI, and National Oceanic and Atmospheric Administration. 2004; available at http://vista.cira.colostate.edu/improve/Studies/BRAVO/reports/FinalReport/bravofinalreport.htm (accessed October 6, 2005).
   Google Scholar
• Schichtel, B.A.; Pitchford, M.; Gebhart, K.A.; Malm, W.C.; Barna, M.G.; Knipping, E.M.; Tombach, I.H. Reconciliation and Interpretation of Big Bend National Park’s Particulate Sulfur Source Apportionment: Results from the BRAVO Study. Part I; J. Air & Waste Manage. Assoc. 2005, 55, 1709-1725.
   Google Scholar
• Pitchford, M.L.; Schichtel, B.A.; Gebhart, K.A.; Barna, M.G.; Malm, W.C.; Tombach, I.H.; Knipping, E.M. Reconciliation and Interpretation of the Big Bend National Park’s Particulate Light Extinction Sul-fate Source Apportionment: Results from the BRAVO Study. Part II; J. Air & Waste Manage. Assoc. 2005, 55, 1726-1732.
   Google Scholar
• Barna, M.G.; Gebhart, K.A.; Schichtel, B.A.; Malm, W.C. Modeling Regional Sulfate during the BRAVO Study: 1. Base Emissions Simulation and Performance Evaluation; Atmos. Env. In review.
   Google Scholar
• Barna, M.G.; Schichtel, B.A.; Gebhart, K.A.; Malm, W.C. Modeling Regional Sulfate during the BRAVO Study: 2. Emission Sensitivity Simulations and Source Apportionment; Atmos. Env. Submitted for publication.
   Google Scholar
• Bresch, J.F.; Reiter, E.R.; Klitch, M.A.; Iyer, H.K.; Malm, W.C.; Gebhart, K.A. Origins of Sulfur-Laden Air at National Parks in the Continental United States. In Proceeding of the Transactions of the Air Pollution Control Association Specialty Conference: Visibility Protection—Research & Policy Aspects; Bhardwaja, P.S., Ed.; 1986; pp 695-708.
   Google Scholar
• Malm, W.C.; Gebhart, K.A.; Henry, R.C. An Investigation of the Dominant Source Regions of Fine Sulfur in the Western United States and Their Areas of Influence; Atmos. Env. 1990, 24a, 3047-3060.
   Google Scholar
• Gebhart, K.A.; Malm, W.C.; Flores, M. A Preliminary Look at Source-Receptor Relationships in the Texas-Mexico Border Area; J. Air & Waste Manag. Assoc. 2000, 50, 858-868.
   Google Scholar
• Gebhart, K.A.; Kreidenweis, S.; Malm, W.C. Back-Trajectory Analyses of Fine Particulate Matter Measured at Big Bend National Park in the Historical Database and the 1996 Scoping Study; Sci. Tot. Env. 2001, 276, 185-204.
   Google Scholar
• Heffter, J.L. Air Resources Laboratory Atmospheric Transport and Diffusion Model (ARL-ATAD), National Oceanic and Atmospheric Administration, Technical Memo, ERL-ARL-81; National Oceanic and Atmospheric Administration: Washington, DC, 1980.
   Google Scholar
• Draxler, R.R.; Hess, G.D. An Overview of the HYSPLIT_4 Modeling System for Trajectories, Dispersion, and Deposition; Aust. Meteo. Mag. 1998, 47, 295-308.
   Google Scholar
• READY (Real-Time Environmental Applications and Display System); NOAA Air Resources Laboratory; available at http://www.arl.noaa.gov/ready/hysplit4.html (accessed October 6, 2005).
   Google Scholar
• Schichtel, B.A.; Husar, R.B. Regional Simulation of Atmospheric Pollutants with the CAPITA Monte Carlo Model; J. Air & Waste Manag. Assoc. 1997, 47, 331-343.
   Google Scholar
• Schwartz, B.E.; Govett, M.A Hydrostatically Consistent North American Radiosonde Data Base at the Forecast Systems Laboratory, 1946-Present; NOAA Technical Memorandum ERL FSL-4; National Oceanic and Atmospheric Administration/Environmental Research Laboratories/Forecast Systems Laboratory: Boulder, CO, 1992.
   Google Scholar
• Govett, M. National Oceanic and Atmospheric Administration-Forecast Systems Laboratory, Radiosonde Database Access; available at http://raob.fsl.noaa.gov (accessed October 6, 2005).
   Google Scholar
• Grell, G.A.; Dudhia, J.; Stauffer, D.R. A Description of the Fifth Generation Penn State/National Center for Atmospheric Research Mesoscale Model (MM5); NCAR Technical Note (TN-398-STR); National Center for Atmospheric: Boulder, CO, 1994.
   Google Scholar
• Seaman, N.L.; Stauffer, D.R. Final Report to EPRI Contract EP-P3883/C1886 for MM5 Modeling in Support of the Big Bend Regional Aerosol and Visibility Observation Study (BRAVO); The Pennsylvania State University for Electrical Power Research Institute: Palo Alto, CA; Available at http://vista.cira.colostate.edu/improve/Studies/BRAVO/reports/FinalReport/BRAVO/A9_Seaman2003MM5Modeling.pdf (accessed October 6, 2005).
   Google Scholar
• Alapaty, K.; Seaman, N.L.; Niyogi, D.S.; Hanna, A.F. Assimilating Surface Data to Improve Accuracy of Atmospheric Boundary Layer Simulations; J. Appl. Meteo. 2001, 40, 2068-2082.
   Google Scholar
• Kain, J.S.; Fritsch, J.M.A. One-Dimensional Entraining/Detraining Plume Model and Its Application in Convective Parameterization; J. Atmos. Sci. 1990, 47, 2784-2802.
   Google Scholar
• Dudhia, J. Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Mode; J. Atmos. Sci. 1989, 46, 3077-3107.
   Google Scholar
• Shafran, P.C.; Seaman, N.L.; Gayno, G.A. Evaluation of Numerical Predictions of Boundary-Layer Structure During the Lake Michigan Ozone Study (LMOS); J. Appl. Meteor.2000, 39, 412-426.
   Google Scholar
• Zhang, D.L.; Anthes, R.A.A. High-Resolution Model of the Planetary Boundary Layer-Sensitivity Tests and Comparisons with SESAME-79 Data; J. Appl. Meteor. 1982, 21, 1594-1609.
   Google Scholar
• Black, T.L. The New NMC Mesoscale Eta Model: Description and Forecast Examples; Wea. Forecasting, 1994, 9, 265-278.
   Google Scholar
• Parrish, D.; Purser, J.; Rogers, E.; Lin, Y. The Regional 3D Variational Analysis for the Eta Model; In Proceedings of the 11th Conference on Numerical Weather Prediction; American Meteorological Society: Norfolk, VA, 1996; pp 454-455.
   Google Scholar
• Zapotocny, T.H.; Nieman, S.J.; Menzel, W.P.; Nelson, J.P. III; Jung, J.A.; Rogers, E.; Parrish, D.F.; DIMego, G.J.; Timothy, M.B.; Schmit, J.A Case Study of the Sensitivity of the Eta Data Assimilation System; Wea. Forecasting, 2000, 15, 603-621.
   Google Scholar
• Zapotocny, T.H.; Menzel, W.P.; Nelson, J.P. III; Jung, J.A. An Impact Study of Five Remotely Sensed and Five in Situ Data Types in the Eta Data Assimilation System; Wea. Forecasting, 2002, 17, 263-285.
   Google Scholar
• Kanamitsu, M. Description of the NMC Global Data Assimilation and Forecast System; Wea. Forecasting, 1989, 4, 335-342.
   Google Scholar
• Derber, J.C.; Parrish, D.F.; Lord, S.J. The New Global Operational Analysis System at the National Meteorological Center; Wea. Forecasting, 1991, 6, 538-547.
   Google Scholar
• Parrish, D.F.; Derber, J.C. The National Meteorological Center’s Spectral Statistical Interpolation Analysis System; Mon. Wea. Rev. 1992, 120, 1747-1766.
   Google Scholar
• Sela, J.G. Spectral Modeling at the National Meteorological Center; Mon. Wea. Rev. 1980, 108, 1279-1292.
   Google Scholar
• Petersen, R.A.; Stackpole, J.D. Overview of the NMC Production Suite; Wea. Forecasting, 1989, 4, 313-322.
   Google Scholar
• Stunder, B.J.B. NCEP Model Output—FNL Archive Data; National Climatic Data Center (NCDC) Report TD-6141; National Climatic Data Center: Washington, DC, 1997.
   Google Scholar
• Seibert, P.; Frank, A. Source-Receptor Matrix Calculation with a Lagrangian Particle Dispersion Model in Backward Mode; Atmos. Chem. Phys. Discuss. 2003, 3, 4516-4548.
   Google Scholar
• Desiato, F.; Anfossi, D.; Castelli, S.T.; Ferrero, E.; Tinarelli, G. The Role of Wind Field, Mixing Height and Horizontal Diffusivity Investigated through Two Lagrangian Particle Models; Atmos. Env. 1998, 32, 4157-4165.
   Google Scholar
• Zannetti, P. Air Pollution Modeling; Computational Mechanics Publications: Southhampton Boston, MA, 1990.
   Google Scholar
• Pitchford, M.; Pitchford, A. Analysis of Regional Visibility in the Southwest Using Principal Component and Back Trajectory Techniques; Atmos. Env. 1985, 19, 1301-1316.
   Google Scholar
• Iyer, H.K.; Malm, W.C.; Ahlbrandt, R.A. A Mass Balance Method for Estimating the Fractional Contribution from Various Sources to a Receptor Site; In Transactions: Visibility Protection: Research and Policy Aspects; Bhardwaja, P.S., Ed.; Air Pollution Control Association: Grand Teton National Park, WY, Pittsburgh, PA, 1986; pp 861-869.
   Google Scholar
• Gebhart, K.A; Schichtel, B.A.; Barna, M.G. Source Apportionment of Sulfate and Unique Tracers at Big Bend National Park Using a Back-Trajectory Based Receptor Model and Measurements from the BRAVO Study; Presented at the Air & Waste Management Association’s 96th Annual Meeting & Exhibition, San Diego, CA, June 2003.
   Google Scholar
• Belsley, D.A.; Kuh, E.; R.E. Welsch, R.E. Regression Diagnostics-Identifying Influential Data and Sources of Collinearity; John Wiley & Sons: New York, NY, 1980; pp 92-93.
   Google Scholar
• Kahl, J.D.; Harris, J.M.; Herbert, G.A. Intercomparison of Three Long-Range Trajectory Models Applied to Arctic Haze. Tellus, 1989, 41B, 524-536.
   Google Scholar