Southern high-latitude ensemble data assimilation in the Antarctic Mesoscale Prediction System

Monthly Weather Review

Volumn 133, Issue 12, 2005, Pages 3431-3449

  Barker, D M ^a  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC PRESSURE; ATMOSPHERIC TEMPERATURE; BOUNDARY CONDITIONS; ERROR ANALYSIS; ERROR STATISTICS; MATHEMATICAL MODELS; PERTURBATION TECHNIQUES; WEATHER FORECASTING; WIND;

ANTARCTIC MESOSCALE PREDICTION SYSTEM (AMPS); ENSEMBLE DATA ASSIMILATION SYSTEMS; ENSEMBLE SQUARE ROOT FILTER (ENSRF); FORECAST ERROR COVARIANCE; NUMERICAL WEATHER PREDICTION (NWP) MODEL;

CLIMATOLOGY;

DATA ASSIMILATION; MESOSCALE METEOROLOGY; WEATHER FORECASTING;

ANTARCTICA;

EID: 31344446619     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/MWR3042.1     Document Type: Article

References (38)

1. Anderson, J., 2001: An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Rev., 129, 2884-2903.
2. Barker, D. M., W. Huang, Y.-R. Guo, and A. Bourgeois, 2003: A three-dimensional variational (3DVAR) data assimilation system for use with MM5. NCAR Tech Note NCAR/TN-453+STR, 68 pp. [Available from UCAR Communications, P.O. Box 3000, Boulder, CO 80307.]
3. Barker, D. M., W. Huang, Y.-R. Guo, and Q. N. Xiao, 2004: A three-dimensional (3DVAR) data assimilation system for use with MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897-914.
4. Bishop, C. H., B. J. Etherton, and S. J. Majumdar, 2001: Adaptive sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical aspects. Mon. Wea. Rev., 129, 420-436.
5. Bromwich, D. H., R. I. Cullather, and R. W. Grumbane, 1999: An assessment of the NCEP operational global spectral model forecasts and analyses for Antarctica during FROST. Wea. Forecasting, 14, 835-850.
6. Bromwich, D. H., J. J. Cassano, T. Klein, G. Heinemann, K. M. Hines, K. Steffen, and J. E. Box, 2001: Mesoscale modeling of katabatic winds over Greenland with the Polar MM5. Mon. Wea. Rev., 129, 2290-2309.
7. Burgers, G., P. J. van Leeuwen, and G. Evensen, 1998: Analysis scheme in the ensemble Kalman filter. Mon. Wea. Rev., 126, 1719-1724.
8. Cohn, S., A. da Silva, J. Guo, M. Sienkiewicz, and D. Lamich, 1998: Assessing the effects of data selection with the DAO Physical-Space Statistical Analysis System. Mon. Wea. Rev., 126, 2913-2926.
9. Daley, R., and E. Barker, 2001: NAVDAS: Formulation and diagnostics. Mon. Wea. Rev., 129, 869-883.
10. Desroziers, G., 1997: A coordinate change for data assimilation in spherical geometry of frontal structures. Mon. Wea. Rev., 125, 3030-3039.
11. Desroziers, G., and S. Ivanov, 2001: Diagnosis and adaptive tuning of observation-error parameters in a variational assimilation. Quart. J. Roy. Meteor. Soc., 127, 1433-1452.
12. Dudhia, J., 1993: A nonhydrostatic version of the Penn State/NCAR Mesoscale Model: Validation tests and simulations of an Atlantic cyclone and cold front. Mon. Wea. Rev., 121, 1493-1513.
13. Evensen, G., 1994: Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99 (C5), 10 143-10 162.
14. Gaspari, G., and S.E., Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125, 723-757.
15. Hamill, T. M., J. S. Whitaker, and C. Snyder, 2001: Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129, 2776-2790.
16. Hayden, C. M., and R. J. Purser, 1995: Recursive filter objective analysis of meteorological fields: Applications to NESDIS operational processing. J. Appl. Meteor., 34, 3-15.
17. Hollingsworth, A., and P. Lönnberg, 1986: The statistical structure of short-range forecast errors as determined from radiosonde data. Part I: The wind field. Tellus, 38A, 111-136.
18. Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126, 796-811.
19. Houtekamer, P. L., and H. L. Mitchell, 2001: A sequential ensemble Kalman filter for atmospheric data assimilation. Mort. Wea. Rev., 129, 123-137.
20. Ingleby, N. B., 2001: The statistical structure of forecast errors and its representation in the Met. Office global 3-D variational data assimilation scheme. Quart. J. Roy. Meteor. Soc., 127, 209-232.
21. Kalman, R., and R. Bucy, 1961: New results in linear prediction and filtering theory. Trans. AMSE J. Basic Eng., 83D, 95-108.
22. Key, J. R., D. Santek, C. S. Velden, N. Bormann, J.-N. Thepaut, L. P. Riishojgaard, Y. Zhu, and W. P. Menzel, 2003: Cloud-drift and water vapor winds from MODIS. IEEE Trans. Geosci. Remote Sens., 41, 482-492.
23. Lorenc, A. C., 2003: The potential of the ensemble Kalman filter for NWP - A comparison with 4D-Var. Quart. J. Roy. Meteor. Soc., 129, 3183-3204.
24. Lorenc, A. C., and Coauthors, 2000: The Met. Office global three-dimensional variational data assimilation scheme. Quart. J. Roy. Meteor. Soc., 1-26, 2991-3012.
25. Lutz, H. J., W. L. Smith, and E. Raschke, 1990: A note on the improvement of TOVS temperature retrievals above the Antarctic snow and ice fields. J. Geophys. Res., 95, 11 747-11 754.
26. Mitchell, H. L., P. L. Houtekamer, and G. Pellerin, 2002: Ensemble size, balance, and model-error representation in an ensemble Kalman filter. Mon. Wea. Rev., 130, 2791-2808.
27. Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center's Spectral Statistical Interpolation analysis system. Mon. Wea. Rev., 120, 1747-1763.
28. Powers, J. G., A. J. Monaghan, A. M. Cayette, D. H. Bromwich, Y.-H. Kuo, and K. W. Manning, 2003: Real-time mesoscale modeling over Antarctica: The Antarctic Mesoscale Prediction System. Bull. Amer. Meteor. Soc., 84, 1533-1545.
29. Purser, R. J., W.-S. Wu, D. F. Parrish, and N. M. Roberts, 2003: Numerical aspects of the application of recursive filters to variational statistical analysis. Part II: Spatially inhomogeneous and anisotropic general covariances. Mon. Wea. Rev., 131, 1536-1548.
30. Rabier, F., J. N. Thépaut, and P. Courtier, 1998a: Extended assimilation and forecast experiments with a four-dimensional variational assimilation system. Quart. J. Roy. Meteor. Soc., 12A, 1861-1887.
31. Rabier, F., A. McNally, E. Andersson, P. Courtier, P. Undén, J. Eyre, A. Hollingsworth, and F. Bouttier, 1998b: The ECMWF implementation of three-dimensional variational assimilation (3D-Var): Structure functions. Quart. J. Roy. Meteor. Soc., 12A, 1809-1829.
32. Rabier, F., H. Järvinnen, E. Klinker, J.-F. Mahfouf, and A. Simmons, 2000: The ECMWF operational implementation of four-dimensional variational assimilation. I: Experimental results with simplified physics. Quart. J. Roy. Meteor. Soc., 126, 1143-1170.
33. Simmons, A. J., and A. Hollingsworth, 2002: Some aspects of the improvement in skill of numerical weather prediction. Quart. J. Roy. Meteor. Soc., 128, 647-678.
34. Tippett, M. K., J. L. Anderson, C. H. Bishop, T. M. Hamill, and J. S. Whittaker, 2003: Ensemble square root filters. Mon. Wea. Rev., 131, 1485-1490.
35. Turner, J., S. Leonard, G. J. Marshall, M. Pook, L. Cowled, R. Jardine, S. Pendlebury, and N. Adams, 1999: An assessment of operational Antarctic analyses based on data from the FROST project. Wea. Forecasting, 14, 817-834.
36. Whitaker, J. S., and T. M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913-1924.
37. Wu, W.-S., R. J. Purser, and D. F. Parrish, 2002: Three-dimensional variational analysis with spatially inohomogeneous covariances. Mon. Wea. Rev., 130, 2905-2916.
38. Zou, X., F. Vandenberghe, M. Pondeca, and Y.-H. Kuo, 1997: Introduction to adjoint techniques and the MM5 adjoint modeling system. NCAR Tech. Note NCAR/TN-435+STR, 110 pp. [Available from UCAR Communications, P.O. Box 3000, Boulder, CO 80307.]