Ensemble-based data assimilation and targeted observation of a chemical tracer in a sea breeze model

Atmospheric Environment

Volumn 41, Issue 14, 2007, Pages 3082-3094

  Stuart, Amy L ^a   Aksoy, Altug ^b   Zhang, Fuqing ^c   Nielsen Gammon, John W ^c  

^a UNIVERSITY OF SOUTH FLORIDA   (United States)

^b NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^c TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Adaptive observations; Air quality modeling; Data assimilation; Ensemble modeling

Indexed keywords

DATA REDUCTION; ERROR ANALYSIS; MATHEMATICAL MODELS; NUMERICAL METHODS; OCEANOGRAPHY; WEATHER FORECASTING;

ADAPTIVE OBSERVATIONS; AIR QUALITY MODELING; DATA ASSIMILATION; ENSEMBLE MODELING;

RADIOACTIVE TRACERS;

TRACER;

AIR QUALITY; ATMOSPHERIC FORCING; ATMOSPHERIC TRANSPORT; DATA ASSIMILATION; ENSEMBLE FORECASTING; ERROR ANALYSIS; KALMAN FILTER; LAND BREEZE; NUMERICAL MODEL; OBSERVATIONAL METHOD; SEA BREEZE; TRACER; TWO-DIMENSIONAL MODELING; UNCERTAINTY ANALYSIS;

ARTICLE; CONCENTRATION (PARAMETERS); DYNAMICS; FORECASTING; MEASUREMENT ERROR; METEOROLOGY; MODEL; PRIORITY JOURNAL; SIMULATION;

EID: 33947416571     PISSN: 13522310     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosenv.2006.11.046     Document Type: Article

References (34)

1. Aksoy A., Zhang F., Nielsen-Gammon J.W., and Epifanio C. Ensemble-based data assimilation for thermally forced circulations. Journal of Geophysical Research 110 (2005) D16105 10.1029/2004JD005718
2. Aksoy A., Zhang F., and Nielsen-Gammon J.W. Ensemble-based simultaneous state and parameter estimation in a two-dimensional sea breeze model. Monthly Weather Review 134 (2006) 2951-2970
3. Asselin R. Frequency filter for time integrations. Monthly Weather Review 100 (1972) 487-490
4. Banta R.M., Senff C.J., Nielsen-Gammon J., Darby L.S., Ryerson T.B., Alvarez R.J., Sandberg S.P., Williams E.J., and Trainer M. A bad air day in Houston. Bulletin of the American Meteorological Society 86 5 (2005) 657-669
5. Bao J.-W., Michelson S.A., Mckeen S.A., and Grell G.A. Meteorological evaluation of weather-chemistry forecasting model using observations from the TEXAS AQS 2000 field experiment. Journal of Geophysical Research 110 (2005) 21105 10.1029/2004JD005024
6. Bergin M.S., Noblet G.S., Petrini K., Dhieux J.R., Milford J.B., and Harley R.A. Formal uncertainty analysis of a Lagranian photochemical air pollution model. Environmental Science and Technology 33 7 (1999) 1116-1126
7. Berliner L.M., Lu Z.-Q., and Snyder C. Statistical design for adaptive weather observations. Journal of Atmospheric Sciences 56 (1999) 2536-2552
8. Boybeyi Z., Raman S., and Zannetti P. Numerical investigation of the possible role of local meteorology in Bhopal gas accident. Atmospheric Environment 24 4 (1995) 479-496
9. Chang M.E., Hartley D.E., Cardelino C., Haas-Laursen D., and Change W.L. On using inverse methods for resolving emissions with large spatial in homogeneities. Journal of Geophysical Research 102 (1997) 16023-16036
10. Dabberdt W.F., and Miller E. Uncertainty, ensembles and air quality dispersion modeling: applications and challenges. Atmospheric Environment 34 27 (2000) 4667-4673
11. Daescu D.N., and Carmichael G.R. An adjoint sensitivity method for the adaptive location of the observations in air quality modeling. Journal of the Atmospheric Sciences 60 (2003) 434-450
12. Elbern H., Schmidt H., Talagrand O., and Ebel A. 4-D variational data assimilation with an adjoint air quality model for emission analysis. Environmental Modelling and Software 15 (2000) 539-548
13. Emanuel K.A., and Langland R. FASTEX adaptive observations workshop. Bulletin of the American Meteorological Society 79 (1998) 1915-1919
14. Emanuel K.A., et al. Report of the first prospectus development team of the US Weather Research Program to NOAA and NSF. Bulletin of the American Meteorological Society 76 (1995) 1194-1208
15. Evensen G. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dynamics 53 (2003) 343-367
16. Gaspari G., and Cohn S.E. Construction of correlation functions in two and three dimensions. Quarterly Journal of the Royal Meteorological Society 125 (1999) 723-757
17. Hamill T.M., and Snyder C. Using improved background-error covariances from an ensemble Kalman filter for adaptive observations. Monthly Weather Review 130 (2002) 1552-1572
18. Hanea R.G., Velders G.J.M., and Heemink A. Data assimilation of ground-level ozone in Europe with a Kalman filter and chemistry transport model. Journal of Geophysical Research 109 (2004) D10302 10.1029/2003JD004283
19. Heemink A.W., and Segers A.J. Modeling and prediction of environmental data in space and time using Kalman filtering. Stochastic Environmental Research and Risk Assessment 16 (2002) 240-255
20. Houtekamer P.L., and Mitchell H.L. A sequential ensemble Kalman filter for atmospheric data assimilation. Monthly Weather Review 129 (2001) 123-137
21. Kalnay E. Atmospheric Modeling, Data Assimilation and Predictability (2003), Cambridge University Press, New York
22. Lorenz E.N. Deterministic nonperiodic flow. Journal of the Atmospheric Sciences 20 (1963) 130-141
23. Lorenz E.N., and Emanuel K.A. Optimal sites for supplementary observations: simulation with a small model. Journal of the Atmospheric Sciences 55 (1998) 399-414
24. Mendoza-Dominguez A., and Russell A.G. Estimation of emission adjustments from the application of four-dimensional data assimilation to photochemical air quality modeling. Atmospheric Environment 35 (2001) 2879-2894
25. Navon I.M. Practical and theoretical aspects of adjoint parameter estimation and identifiability in meteorology and oceanography. Dynamics of Atmosphere and Oceans 27 (1998) 55-79
26. Morss R.E., Emanuel K.A., and Snyder C. Observational strategies for improving numerical weather prediction. Journal of the Atmospheric Science 58 (2001) 210-232
27. Sax T., and Isakov V. A case study for assessing uncertainty in local-scale regulatory air quality modeling applications. Atmospheric Environment 37 25 (2003) 3481-3489
28. Seigneur C. Air pollution: current challenges and future opportunities. A.I.C.h.E. Journal 54 2 (2005) 356-364
29. Seinfeld J.H. Air pollution: a half century of progress. A.I.C.h.E. Journal 50 6 (2004) 1096-1108
30. Snyder C., and Zhang F. Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Monthly Weather Review 131 (2003) 1663-1677
31. Stuart, A.L., Jain, S., Libicki, S.B., 1996. The use of long-term meteorological information to predict impact probabilities resulting from toxic chemical releases. In: Proceedings of the International Topical Meeting of Probabilistic Safety Assessment. American Nuclear Society, October.
32. Tippett M.K., Anderson J.L., Bishop C.H., M Hamill T., and Whitaker J.S. Ensemble square root filters. Monthly Weather Review 131 (2003) 1485-1490
33. Whitaker J.S., and Hamill T.M. Ensemble data assimilation without perturbed observations. Monthly Weather Review 130 (2002) 1913-1924
34. Zhang F., Bei N., Nielsen-Gammon J.W., Li G., Zhang R., Stuart A., and Aksoy A. Impacts of meteorological uncertainties on ozone pollution predictability estimated through meteorological and photochemical ensemble forecasts. Journal of Geophysical Research. (2006) (in press)