Ensemble singular vectors as additive inflation in the Local Ensemble Transform Kalman Filter (LETKF) framework with a global NWP model

被引:1
作者
Shin, Seoleun [1 ]
Kang, Ji-Sun [2 ]
Yang, Shu-Chih [3 ]
Kalnay, Eugenia [4 ]
机构
[1] Korea Inst Atmospher Predict Syst, Syst Configurat Team, Seoul, South Korea
[2] Korea Inst Sci & Technol Informat, Supercomp Serv Ctr, Daejeon, South Korea
[3] Natl Cent Univ Taiwan, Dept Atmospher Sci, Jhongli, Taiwan
[4] Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA
关键词
atmospheric global model; ensemble data assimilation; ensemble singular vectors; local ensemble transform Kalman filter; numerical weather prediction; DATA ASSIMILATION; EQUATIONS; ERRORS;
D O I
10.1002/qj.3429
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
We test an ensemble data assimilation system using the four-dimensional Local Ensemble Transform Kalman Filter (4D-LETKF) for a global numerical weather prediction (NWP) model with unstructured grids on the cubed-sphere. It is challenging to selectively represent structures of dynamically growing errors in background states under system uncertainties such as sampling and model errors. We compute Ensemble Singular Vectors (ESVs) in an attempt to capture fast-growing errors on the subspace spanned by ensemble perturbations, and use them as additive inflation to enlarge the covariance in the area where errors are flow-dependently growing. The performance of the 4D-LETKF system with ESVs is evaluated in real data assimilation, as well as Observing System Simulation Experiments (OSSEs). We find that leading ESVs help to capture fast-growing errors effectively, especially when model errors are present, and that the use of ESVs as additive inflation significantly improves the performance of the 4D-LETKF.
引用
收藏
页码:258 / 272
页数:15
相关论文
共 34 条
[1]  
Bishop CH, 1999, J ATMOS SCI, V56, P1748, DOI 10.1175/1520-0469(1999)056<1748:ETAAO>2.0.CO
[2]  
2
[3]   Use of the breeding technique to estimate the structure of the analysis "errors of the day" [J].
Corazza, M ;
Kalnay, E ;
Patil, DJ ;
Yang, SC ;
Morss, R ;
Cai, M ;
Szunyogh, I ;
Hunt, BR ;
Yorke, JA .
NONLINEAR PROCESSES IN GEOPHYSICS, 2003, 10 (03) :233-243
[4]   The ERA-Interim reanalysis: configuration and performance of the data assimilation system [J].
Dee, D. P. ;
Uppala, S. M. ;
Simmons, A. J. ;
Berrisford, P. ;
Poli, P. ;
Kobayashi, S. ;
Andrae, U. ;
Balmaseda, M. A. ;
Balsamo, G. ;
Bauer, P. ;
Bechtold, P. ;
Beljaars, A. C. M. ;
van de Berg, L. ;
Bidlot, J. ;
Bormann, N. ;
Delsol, C. ;
Dragani, R. ;
Fuentes, M. ;
Geer, A. J. ;
Haimberger, L. ;
Healy, S. B. ;
Hersbach, H. ;
Holm, E. V. ;
Isaksen, L. ;
Kallberg, P. ;
Koehler, M. ;
Matricardi, M. ;
McNally, A. P. ;
Monge-Sanz, B. M. ;
Morcrette, J. -J. ;
Park, B. -K. ;
Peubey, C. ;
de Rosnay, P. ;
Tavolato, C. ;
Thepaut, J. -N. ;
Vitart, F. .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2011, 137 (656) :553-597
[5]   CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model [J].
Dennis, John M. ;
Edwards, Jim ;
Evans, Katherine J. ;
Guba, Oksana ;
Lauritzen, Peter H. ;
Mirin, Arthur A. ;
St-Cyr, Amik ;
Taylor, Mark A. ;
Worley, Patrick H. .
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 2012, 26 (01) :74-89
[6]  
Enomoto T., 2006, P 3 WORKSH MECH CLIM, P40
[7]   Simple Sensitivity Analysis Using Ensemble Forecasts [J].
Enomoto, Takeshi ;
Yamane, Shozo ;
Ohfuchi, Wataru .
JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN, 2015, 93 (02) :199-213
[8]  
Environmental Modeling Center, 2003, 442 NCEP EMC GLOB CL
[9]   AMIP Simulation with the CAM4 Spectral Element Dynamical Core [J].
Evans, K. J. ;
Lauritzen, P. H. ;
Mishra, S. K. ;
Neale, R. B. ;
Taylor, M. A. ;
Tribbia, J. J. .
JOURNAL OF CLIMATE, 2013, 26 (03) :689-709
[10]   Accounting for the error due to unresolved scales in ensemble data assimilation: A comparison of different approaches [J].
Hamill, TM ;
Whitaker, JS .
MONTHLY WEATHER REVIEW, 2005, 133 (11) :3132-3147