Ensemble-based simultaneous state and parameter estimation for treatment of mesoscale model error: A real-data study

Geophysical Research Letters

Volumn 37, Issue 8, 2010, Pages

  Hu, Xiao Ming ^a   Zhang, Fuqing ^a   Nielsen Gammon, John W ^b  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENSEMBLE KALMAN FILTER; GREATER HOUSTON AREA; MESOSCALE MODEL; MODEL ERRORS; MODEL SENSITIVITY; NEAR-SURFACE; PROGNOSTIC VARIABLES; SIMULTANEOUS STATE AND PARAMETER ESTIMATION; STATE VECTOR; TWO PARAMETER; WIND PROFILER; WIND PROFILES;

AIR QUALITY; ATMOSPHERIC BOUNDARY LAYER; BOUNDARY LAYER FLOW; COMPUTER SIMULATION; METAL ANALYSIS; RAIN; TROPOSPHERE; WEATHER FORECASTING;

PARAMETER ESTIMATION;

ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; BOUNDARY LAYER; KALMAN FILTER; MESOSCALE METEOROLOGY; MODEL TEST; PARAMETERIZATION;

HOUSTON; TEXAS; UNITED STATES;

EID: 77951984842     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2010GL043017     Document Type: Article

References (26)

1. Aksoy, A., F. Zhang, and J. W. Nielsen-Gammon (2006a), Ensemble-based simultaneous state and parameter estimation with MM5, Geophys. Res. Lett, 33, L12801, doi:10.1029/2006GL026186. (Pubitemid 44687727)
2. Aksoy, A., F. Zhang, and J. W. Nielsen-Gammon (2006b), Ensemble-based simultaneous state and parameter estimation in a two-dimensional sea-breeze model, Mon. Weather Rev., 134, 2951-2970, doi:10.1175/ MWR3224.1. (Pubitemid 44649932)
3. Annan, J. D., J. C. Hargreaves, N. R. Edwards, and R. Marsh (2005a), Parameter estimation in an intermediate complexity earth system model using an ensemble Kalman filter, Ocean Modell., 8, 135-154, doi:1.0.1016/j.ocemod.2003. 12.004.
4. Annan,J.D.,J.D.Lunt,J.C.Hargreaces,andP.J.Valdes(2005b), Param-eterestimationinanatmosphericGCMusingtheensembleKalmanfilter, NonlinearProcessesGeophys.,12,363-371.(Pubitemid40518138)
5. Evensen, G. (1994), Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res., 99, 10, 143-10, 162, doi:10.1029/94JC00572.
6. Evensen, G. (2003), The ensemble Kalman filter: Theoretical formulation and practical implementation, Ocean Dyn., 53, 343-367, doi:10.1007/ s10236-003-0036-39
7. Gaspari,G.,andS.E.Cohn(1999), Constructionofcorrelationfunctionsintwoandthreedimensions,Q.J.R.Meteorol.Soc., 125,723-757,doi:10.1002/qj.49712555417.(Pubitemid29247364)
8. Hacker, J. P., and C. Snyder (2005), Ensemble Kalman filter assimilation of fixed screen-height observations in a parameterized PBL, Mon. Weather Rev., 133, 3260-3275, doi:10.1175/MWR3022.1.
9. Hamill, T. M. (2006), Ensemble-based atmospheric data assimilation, in Predictability of Weather and Climate, edited by T. Palmer and R. Hagedorn, chap. 6, pp. 124-156, Cambridge Univ. Press, Cambridge, U. K.
10. Hansen, J. A. (2002), Accounting for model error in ensemble-based state estimation and forecasting, Mon. Weather Rev., 130, 2373-2391, doi:10.1175/1520-0493(2002)130<2373:AFMEIE>2.0.CO;2.
11. Hansen, J., and C. Penland (2007), On stochastic parameter estimation. using data assimilation, Physica D, 230, 88-98, doi:10.1016/j.physd.2006. 11.006. (Pubitemid 46776910)
12. Hu, X.-M., J. W. Nielsen-Gammon, and F. Zhang (2010), Evaluation of three planetary boundary layer schemes in the WRF model, J. Appl. Meteorol. Climatol., in press.
13. Kondrashov, D., C.-J. Sun, and M. Ghil (2008), Data assimilation for a coupled ocean-atmosphere model. Part II: Parameter estimation, Mon. Weather Rev., 136, 5062-5076, doi:10.1175/2008MWR2544.1.
14. Meng, Z., and F. Zhang (2007), Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part II: Imperfect model experiments, Mon. Weather Rev., 135, 1403-1423, doi:.10.1175/ MWR3352.1.
15. Nielsen-Gammon, J. W., X.-M. Hu, F. Zhang, and J. E. Pleim (2010), Evaluation of planetary boundary layer scheme sensitivities for the purpose of parameter estimation. Mon. Weather Rev., in press.
16. Parrish, D. D., et al. (2009), Overview of the Second Texas Air Quality Study (TexAQS II) and the Gulf of Mexico Atmospheric Composition and Climate Study (GoMaACCS), J. Geophys. Res., 114, D00F13, doi:10.1029/2009JD011842.
17. Pleim, J. E. (2007a), A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: Model description and testing, J. Appl. Meteorol. Climatol, 46,1383-1395, doi:10.1175/JAM2539.1.
18. Pleim, J. E. (2007b), A combined local and nonlocal closure model for the atmospheric boundary layer. Part II: Application and evaluation in a mesoscale meteorological model, J. Appl. Meteorol. Climatol., 46, 1396-1409, doi:10.1175/JAM2534.1. (Pubitemid 350001964)
19. Rappenglück, B., R. Perna, S. Zhong, and G. A. Morris (2008), An analysis of the vertical structure of the atmosphere and the upper-level meteorology and their impact on surface ozone levels in Houston, Texas, J. Geophys. Res., 113, D17315, doi:10.1029/2007JD009745.
20. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers (2005), A description of the advanced research WRF version 2, Tech. Note NCAR/TN-468+STR, Natl. Cent. for Atmos. Res., Boulder, Colo.
21. Stuart, A. L., A. Aksoy, F. Zhang, and J. W. Nielsen-Gammon (2007), Ensemble-based data assimilation and targeted observation of a chem-ical tracer in a sea breeze model, Atmos. Environ., 41, 3082-3094, doi: 10.1016/j.atmosenv. 2006.11.046.
22. Tong, M., and M. Xue (2008), Simultaneous estimation of microphysical parameters and atmospheric state with simulated radar data and ensemble square root Kalman filter. Part II: Parameter estimation experiments, Mon. Weather Rev., 136, 1649-1668, doi: 10.1175/2007MWR2071.1. (Pubitemid 351819019)
23. Wilczak, J. M., I. Djalalova, S. McKeen, L. Bianco, J.-W. Bao, G. Grell, S. Peckham, R. Mathur, J. McQueen, and P. Lee (2009), Analysis of regional meteorology and surface ozone during the TexAQS II field pro-gram and an evaluation of the NMM-CMAQ and WRF-Chem air quality models, J. Geophys. Res., 114, D00F14, doi:10.1029/2008JD011675.
24. Zhang, F., and C. Snyder (2007), Ensemble-based data assimilation, Bull. Am. Meteorol. Soc., 88, 565-568, doi:10.1175/BAMS-88-4-565.
25. Zhang, F., C. Snyder, and J. Sun (2004), Tests of an ensemble Kalman filter for convective-scale data assimilation: Impact of initial estimate and observations, Mon. Weather Rev., 132, 1238-1253, doi: 10.1175/1520-0493(2004) 132<1238:IOIEAO>2.0.CO;2. (Pubitemid 38673074)
26. Zhang, F., Y. Weng, J. A. Sippel, Z. Meng, and C. H. Bishop (2009), Cloud-resolving hurricane initialization and prediction through assimila-tion of Doppler radar observations with an ensemble Kalman filter: Humberto (2007), Mon. Weather Rev., 137, 2105-2125, doi:10.1175/ 2009MWR2645.1.