Assimilating ambiguous QuikScat scatterometer observations in <small>HIRLAM</small> 3-D-Var at the Norwegian Meteorological Institute

Frank Thomas Tveter

doi:10.1111/j.1600-0870.2006.00155.x

Assimilating ambiguous QuikScat scatterometer observations in HIRLAM 3-D-Var at the Norwegian Meteorological Institute

Author:

Frank Thomas Tveter

Norwegian Meteorological Institute, PO Box 43 Blindern, N-0313 Oslo, NO

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Abstract

The Norwegian Meteorological Institute has implemented ambiguous QuikScat observations in the HIRLAM threedimensional variational data assimilation system, by approximating the method that will achieve the best mean squared error verification results according to the Bayesian decision theory. A four-month long impact study of this implementation during the 2003/2004 winter showed that assimilating QuikScat observations had a small positive effect on the average mean sea level pressure forecasting skill.

How to Cite: Tveter, F.T., 2006. Assimilating ambiguous QuikScat scatterometer observations in HIRLAM 3-D-Var at the Norwegian Meteorological Institute. Tellus A: Dynamic Meteorology and Oceanography, 58(1), pp.59–68. DOI: http://doi.org/10.1111/j.1600-0870.2006.00155.x

Accepted on 28 Jul 2005 Submitted on 3 Sep 2004

References

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Atlas , R. , Hoffman , R. N. , Leidner , S. M. , Sienlciewicz , J. , Yu , T.-W. and co-authors 2001 . The effects of marine winds from scatterometer data on weather analysis and forecasting . Bull. Am. MeteoroL Soc . 82 , 1965 – 1990 .

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de Vries , J. 2004 . QuikSCAT data processor user manual v1.3b. KNMI, NWPSAF-KN-UD-001 02/2004. Available at http://www.knmi.n1/scatterometer/sw_proc/pda

Gustafsson , N. , Berre , L. , Hörnquist , S. , Huang , X.-Y. , Lindskog , M. and co-authors 2001 . Three-dimensional variational data assimilation for a limited area model, Part I: General formulation and the background error constraint . Tellus 53A , 425 – 4146 .

Liu , W. T. 2002 . Progress in scatterometer application . J. Oceanogr 58 , 121 – 136 .

Ingleby , B. and Lorene , A. 1993 . Bayesian quality control using mul-tivariate normal distributions . Q. J. R. MeteoroL Soc . 119 , 1195 – 1225 .

Isaksen , L. and Janssen , P. A. E. M. 2004 . Impact of ERS scatterometer winds in ECMWF’s assimilation system . Q. J. R. MeteoroL Soc . 130 , 1793 – 1814 .

Lorene , A. C. 1986 . Analysis methods for numerical weather prediction . Q. J. R. MeteoroL Soc . 112 , 1177 – 1194 .

Lorene , A. C. 1988 . Optimal nonlinear objective analysis . Q. J. R. MeteoroL Soc . 114 , 205 – 240 .

Portabella , M. and Stoffelen , A. 2004 . A probabilistic approach for SeaWinds data assimilation . Q. J. R. MeteoroL Soc . 130 , 127 – 159 .

Rice , J. A. 1995 . Mathematical Statistics and Data Analysis 2nd Edition , Duxbury Press , California , 584 pp .

Stoffelen , A. and Anderson , D. 1997 . Ambiguity removal and assim-ilation of scatterometer data . Q. J. R. MeteoroL Soc . 123 , 491 – 518 .

Und´en , R , Rontu , L. , Järvinen , H. , Lynch , D. , Calvo , J. and co-authors 2002 . HIRLAM-5 Scientific Documentation. Available at http://hirlam.knmi.n1

Vedel , H. and Huang , X.-Y. 2004 . Impact of ground based GPS data on NWP forecasts . J. MeteoroL Soc. Japan 82 , 459 – 472 .

[CIT0001] Andersson , E. and Järvinen , H. 1999 . Variational Quality Control . Q. J. R. MeteoroL Soc . 125 , 697 – 722 .

[CIT0002] Atlas , R. , Hoffman , R. N. , Leidner , S. M. , Sienlciewicz , J. , Yu , T.-W. and co-authors 2001 . The effects of marine winds from scatterometer data on weather analysis and forecasting . Bull. Am. MeteoroL Soc . 82 , 1965 – 1990 .

[CIT0003] Courtier , P. , Thepaut , J.-N. and Hollingsworth , A. 1994 . A strategy for operational implementation of 4-D-Var, using an incremental ap-proach . Q. J. R. MeteoroL Soc . 120 , 1367 – 1388 .

[CIT0004] de Vries , J. 2004 . QuikSCAT data processor user manual v1.3b. KNMI, NWPSAF-KN-UD-001 02/2004. Available at http://www.knmi.n1/scatterometer/sw_proc/pda

[CIT0005] Gustafsson , N. , Berre , L. , Hörnquist , S. , Huang , X.-Y. , Lindskog , M. and co-authors 2001 . Three-dimensional variational data assimilation for a limited area model, Part I: General formulation and the background error constraint . Tellus 53A , 425 – 4146 .

[CIT0006] Liu , W. T. 2002 . Progress in scatterometer application . J. Oceanogr 58 , 121 – 136 .

[CIT0007] Ingleby , B. and Lorene , A. 1993 . Bayesian quality control using mul-tivariate normal distributions . Q. J. R. MeteoroL Soc . 119 , 1195 – 1225 .

[CIT0008] Isaksen , L. and Janssen , P. A. E. M. 2004 . Impact of ERS scatterometer winds in ECMWF’s assimilation system . Q. J. R. MeteoroL Soc . 130 , 1793 – 1814 .

[CIT0009] Lorene , A. C. 1986 . Analysis methods for numerical weather prediction . Q. J. R. MeteoroL Soc . 112 , 1177 – 1194 .

[CIT0010] Lorene , A. C. 1988 . Optimal nonlinear objective analysis . Q. J. R. MeteoroL Soc . 114 , 205 – 240 .

[CIT0011] Portabella , M. and Stoffelen , A. 2004 . A probabilistic approach for SeaWinds data assimilation . Q. J. R. MeteoroL Soc . 130 , 127 – 159 .

[CIT0012] Rice , J. A. 1995 . Mathematical Statistics and Data Analysis 2nd Edition , Duxbury Press , California , 584 pp .

[CIT0013] Stoffelen , A. and Anderson , D. 1997 . Ambiguity removal and assim-ilation of scatterometer data . Q. J. R. MeteoroL Soc . 123 , 491 – 518 .

[CIT0014] Und´en , R , Rontu , L. , Järvinen , H. , Lynch , D. , Calvo , J. and co-authors 2002 . HIRLAM-5 Scientific Documentation. Available at http://hirlam.knmi.n1

[CIT0015] Vedel , H. and Huang , X.-Y. 2004 . Impact of ground based GPS data on NWP forecasts . J. MeteoroL Soc. Japan 82 , 459 – 472 .

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