Sensitivity experiments with the spectral HIRLAM and its adjoint

Tellus, Series A: Dynamic Meteorology and Oceanography

Volumn 48, Issue 4, 1996, Pages 501-517

  Gustafsson, Nils ^a   Huang, Xiang Yu ^b  

^a SWEDISH METEOROLOGICAL AND HYDROLOGICAL INSTITUTE   (Sweden)

^b DANISH METEOROLOGICAL INSTITUTE   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

4D MODEL; ADJOINT METHOD; BAROCLINIC SYSTEM; HIRLAM; RESOLUTION; WEATHER FORECASTING;

EID: 0030424341     PISSN: 02806495     EISSN: None     Source Type: Journal    
DOI: 10.1034/j.1600-0870.1996.t01-3-00002.x     Document Type: Article

References (19)

1. Errico, R. M. and Vukicevic, T. 1992. Sensitivity analysis using an adjoint of the PSU-NCAR mesoscale model. Mon. Wea. Rev. 120, 1644-1660.
2. Gustafsson, N. 1990. Sensitivity of limited area model data assimilation to lateral boundary condition fields. Tellus 42A, 109-115.
3. Gustafsson, N. 1991. The HIRLAM model. Proceedings of the ECMWF Seminar on Numerical methods in atmospheric models, 9-13 September, 1991; available from the European Centre for Medium Range Weather Forecasting, Shinfield Park, Reading, England.
4. Gustafsson, N. 1993. HIRLAM 2 final report. HIRLAM Tech. Rep. 9, 126 pp., available from SMHI, S-601 76 Norrköping, Sweden.
5. Gustafsson, N., Lönnberg, P. and Pailleux, J. 1995. Data assimilation for high resolution limited area models. J. Meteorol. Soc. Japan, in press.
6. Gustafsson, N. and Salmond, D. 1994. A parallel spectral HIRLAM with the data parallel programming model and with message passing. A comparison. In "Coming of Age", Proceedings of the 6th ECMWF Workshop on the use of Parallel processors in meteorology. Reading, UK, 21-25 November, 1994. World Scientific Publishing Co., 32-48.
7. Hall, C. 1987. A common verification scheme for limited area models. EWGLAM Newsletter 15, 144-147.
8. Haugen, J.-E. and Machenhauer, B. 1993. A spectral Limited-Area Model Formulation with time-dependent boundary conditions applied to the shallow-water equations. Mon. Wea. Rev. 121, 2618-2630.
9. Huang, X.-Y. 1996. Initialization of cloud water content in a data assimilation system. Mon. Wea. Rev. 124, 478-486.
10. Ide, K., Bennet, A. F., Courtier, P., Ghil, M. and Lorenc, A. C. 1995. Unified Notation for data assimilation: Operational, Sequential and Variational. J. Meteorol. Soc. Japan, in press.
11. Kållberg, P. (ed.) 1989. The HIRLAM level-1 system. Documentation Manual. Available from SMHI, S-601 76 Norrköping, Sweden.
12. Källen, E. and Huang, X.-Y. 1988. The influence of isolated observations on short-range numerical weather forecasts. Tellus 40A, 324-336.
13. Le Dimet, F. X. and Talagrand, O. 1986. Variational algorithms for analysis and assimilation of meteorological observations: Theoretical aspects. Tellus 38A, 97-110.
14. Lewis, J. M. and Derber, J. C. 1985. The use of adjoint equations to solve a variational adjustment problem with advective constraints. Tellus 37A, 309-322.
15. Machenhauer, B. 1988. HIRLAM final report. HIRLAM Tech. Rep. 5, 116 pp., available from DMI, Lyngbyvej 100, DK-2100 Copenhagen Ø, Denmark.
16. Navon, I. M., Zou, X., Derber, J. and Sela, J. 1992. Variational Data Assimilation with an Adiabatic Version of the NMC Spectral Model. Mon. Wea. Rev. 120, 1433-1446.
17. Rabier, F., Klinker, E., Courtier, P. and Hollingsworth, A. 1996. Sensitivity of two-day forecast errors over the Northern Hemisphere to initial conditions. Q. J. R. Meteorol. Soc. 122, 121-150.
18. Radnoti, G. 1995. Comments on: "A spectral limited-area formulation with time-dependent boundary conditions applied to the shallow-water equations". Mon. Wea. Rev. 123, 3122-3123.
19. Thepaut, J.-N. and Courtier, P. 1991. Four-dimensional variational data assimilation using the adjoint of a multilevel primitive-equation model. Q. J. R. Meteorol. Soc. 117, 1225-1254.