Characterising the background errors for the boundary-layer capping inversion

Australian Meteorological and Oceanographic Journal

Volumn 59, Issue SPECIAL ISSUE, 2010, Pages 17-24

  Fowler, Alison M ^a   Bannister, Ross N ^a   Eyre, John ^b  

^a UNIVERSITY OF READING   (United Kingdom)

^b MET OFFICE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BOUNDARY LAYER; COVARIANCE ANALYSIS; DATA ASSIMILATION; ENSEMBLE FORECASTING; ERROR ANALYSIS; TEMPERATURE PROFILE; VERTICAL PROFILE;

EID: 80054971104     PISSN: 1836716X     EISSN: None     Source Type: Journal    
DOI: 10.22499/2.5901.004     Document Type: Article

References (18)

1. Andersson, E. and Järvinen, H. 1999. Variational quality control. Q. Jl R. Met. Soc., 125, 697-722. (Pubitemid 29240030)
2. Bannister, R. N. 2008. A review of forecast error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast error covariances. Q. Jl R. Met. Soc., 134, 1951-70.
3. Beck, A. and Ehrendorfer, M. 2005. Singular-vector-based covariance propagation in a quasigeostrophic assimilation system. Mon. Weath. Rev., 133, 1295-1310. (Pubitemid 40829953)
4. Bowler, N. E., Arribas, A., Mylne, K. R., Robertson, K. B. and Beare, S. E. 2008. The MOGREPS short-range ensemble prediction system. Q. Jl R. Met. Soc., 134, 703-22.
5. Dee, D. P. and da Silva, A. M. 1998. Data assimilation in the presence of forecast bias. Q. Jl R. Met. Soc., 124, 269-95. (Pubitemid 128614310)
6. Evensen, G. 1994. Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 94(C5), 10143-62.
7. Hamill, T. M., Mullen, S. L., Snyder, C., Toth, Z. and Baumhefner, D. P. 2000. Ensemble forecasting in the short to medium range: a report from a workshop. Bull. Am. Met. Soc., 81, 2653-64.
8. Hamill, T. M., Whitaker, J. S. and Snyder, C. 2001. Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Weath. Rev., 129, 2776-90. (Pubitemid 33079980)
9. Hoffman, R. N., Liu, Z., Louis, J.-F. and Grassoti, C. 1995. Distortion representation of forecast errors. Mon. Weath. Rev., 123, 2758-70.
10. Houtekamer, P. L. and Mitchell, H. L. 2001. A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Weath. Rev., 129, 123-37. (Pubitemid 32180439)
11. Houtekamer, P. L., Lefaivre, L., Derome, J., Ritchie, H. and Mitchell, H. L. 1996. A system simulation approach to ensemble prediction. Mon. Weath. Rev., 124, 1225-42. (Pubitemid 126551850)
12. Jacobson, M. Z. 2002. Atmospheric pollution. Cambridge University Press. Cambridge, 160-5.
13. Lorenc, A. C. 1986. Analysis methods for numerical weather prediction. Q. Jl R. Met. Soc., 112, 1177-94.
14. Lorenc, A. C. 2003. The potential of the ensemble Kalman filter for NWP-a comparison with 4d-Var. Q. Jl R. Met. Soc., 129, 3183-203. (Pubitemid 38034055)
15. Milionis, A. E. and Davies, T. D. 1992: A five year climatology of elevated inversions at Emsby (UK). Int. J. Climatol., 12, 205-15.
16. Parrish, D. F. and Derber, J. C. 1992. The National Meteorological Center's spectral statistical interpolation analysis system. Mon. Weath. Rev., 120, 1747-63. (Pubitemid 23375504)
17. Ravela, S., Emanuel, K. and McLaughlin, D. 2007. Data assimilation by field alignment. Physica D, 230, 127-45. (Pubitemid 46783922)
18. Stull, R. B. 1988. An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, Dordrecht.