The Met. Office global three-dimensional variational data assimilation scheme

被引:381
作者
Lorenc, AC [1 ]
Ballard, SP [1 ]
Bell, RS [1 ]
Ingleby, NB [1 ]
Andrews, PLF [1 ]
Barker, DM [1 ]
Bray, JR [1 ]
Clayton, AM [1 ]
Dalby, T [1 ]
Li, D [1 ]
Payne, TJ [1 ]
Saunders, FW [1 ]
机构
[1] Meteorol Off, Bracknell RG12 2SZ, Berks, England
关键词
numerical weather prediction; variational data assimilation;
D O I
10.1002/qj.49712657002
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The Met. Office has developed a Variational assimilation for its Unified Model forecast system, which contains a grid-point model that is run operationally in global, mesoscale, and stratospheric configurations. Key characteristics of the design are: a development path from three-dimensional to four-dimensional variational assimilation; global and limited-area configurations; variational analysis of perturbations; and a carefully designed, well conditioned background term. The background term is implemented using a sequence of Variable transforms to independent balanced and unbalanced variables, to vertical modes, and to spectral coefficients. The coefficients used are based on statistics from differences of one- and two-day forecasts valid at the same time. The covariance model represents many of the features seen in the covariances of forecast differences. The three-dimensional Variational data assimilation (3D-Var) system was implemented in the operational global forecast system on 29 March 1999. In parallel trials, the 3D-Var system gave a 2.7% improvement in a composite skill score (verified against observations and weighted according to the importance of each field).
引用
收藏
页码:2991 / 3012
页数:22
相关论文
共 29 条
[1]   USE OF CLOUD-CLEARED RADIANCES IN 3-DIMENSIONAL 4-DIMENSIONAL VARIATIONAL DATA ASSIMILATION [J].
ANDERSSON, E ;
PAILLEUX, J ;
THEPAUT, JN ;
EYRE, JR ;
MCNALLY, AP ;
KELLY, GA ;
COURTIER, P .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 1994, 120 (517) :627-653
[2]  
Bloom SC, 1996, MON WEATHER REV, V124, P1256, DOI 10.1175/1520-0493(1996)124<1256:DAUIAU>2.0.CO
[3]  
2
[4]  
BOER GJ, 1983, J ATMOS SCI, V40, P154, DOI 10.1175/1520-0469(1983)040<0154:HAITOT>2.0.CO
[5]  
2
[6]   A STRATEGY FOR OPERATIONAL IMPLEMENTATION OF 4D-VAR, USING AN INCREMENTAL APPROACH [J].
COURTIER, P ;
THEPAUT, JN ;
HOLLINGSWORTH, A .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 1994, 120 (519) :1367-1387
[7]   IMPORTANT LITERATURE ON THE USE OF ADJOINT, VARIATIONAL-METHODS AND THE KALMAN FILTER IN METEOROLOGY [J].
COURTIER, P ;
DERBER, J ;
ERRICO, R ;
LOUIS, JF ;
VUKICEVIC, T .
TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY, 1993, 45A (05) :342-357
[8]   Data assimilation in the presence of forecast bias [J].
Dee, DP ;
Da Silva, AM .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 1998, 124 (545) :269-295
[9]  
Derber J, 1999, TELLUS A, V51, P195, DOI 10.1034/j.1600-0870.1999.t01-2-00003.x
[10]  
Desroziers G, 1997, MON WEATHER REV, V125, P3030, DOI 10.1175/1520-0493(1997)125<3030:ACCFDA>2.0.CO