37
Views
3
CrossRef citations to date
0
Altmetric
Original Articles

Using an adjoint model to improve an optimum interpolation-based data-assimilation system

, &
Pages 161-176 | Received 12 Jun 1996, Accepted 16 Sep 1996, Published online: 15 Dec 2016

References

  • Bengsson, L. 1980. On the use of a time sequence of surface pressures in four-dimensional data assimilation. Tellus, 30, 189–497.
  • Courtier, P., Thépaut, J. N. and Hollingsworth, A. 1994. A strategy for operational implementation of 4D-Var, using an incremental approach. Q. J. R. Meteorol. Soc. 120, 1367–1387.
  • Eliassen, A. 1954. Provisional report on calculation of spatial covariance and autocorrelation of the pressure field. Report 5. Videnskaps-Akademiet, Institut for Vaer och Klimaforskning (Norwegian Academy of Sciences, Institute of Weather and Climate Research), Oslo, Norway.
  • Errico, R. M. and Vukicevic, T. 1992. Sensitivity analysis using an adjoint of the PSU-NCAR Mesoscale Model. Mon. Wea. Re v. 120, 1644–1660.
  • Gandin, L. 1963. Objective analysis of meteorological fields. Leningrad: Gidromet; English translation Jerusalem: Israel Program for Scientific Translations, 1965.
  • Gustafsson, N. 1990. Sensitivity of limited area model data assimilation to lateral boundary condition fields. Tellus 42A, 109–115.
  • Gustafsson, N. 1991. The HIRLAM model. Proceedings of the ECMWF Seminar on Numerical methods in atmospheric models, 9-13 September 1991, Vol. II, pp. 115–146. Available from the European Centre for Medium Range Weather Forecasting, Shinfield Park, Reading, Berks. RG2 9AX, UK.
  • Gustafsson, N. 1993. HIRLAM 2 final report. HIRLAM Tech. Rep. 9, 129 pp. Available from SMHI, S-601 76 Norrkoping, Sweden.
  • Gustafsson, N. and Huang, X.-Y. 1996. Sensitivity experiments with the spectral HIRLAM and its adjoint. Tellus 48A, 501–517.
  • Hall, C. 1987. A common verification scheme for limited area models. EWGLAM Newsletter 15, 144–147.
  • Hollingsworth, A. and Lönnberg, P. 1986. The statistical structure of short-range forecast errors as determined from radiosonde data. Part I: The wind field. Tellus 38A, 111–136.
  • Huang, X.-Y., Cederskov, A. and Källén, E. 1994. A comparison between digital filtering initialization and nonlinear normal mode initialization in a data assimilation system. Mon. Wea. Re v. 122, 1001–1015.
  • Källén, E. (Ed.). 1996. HIRLAM documentation manual. System 2.5. Available from SMHI, S-601 76 Norrkoping, Sweden.
  • Le Dimet, F. and Talagrand, O. 1986. Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus 38A, 97–110.
  • Lewis, J. and Derber, J. 1985. The use of adjoint equations to solve a variational adjustment problem with advective constraints. Tellus 37A, 309–327.
  • Lorene, A. 1981. A global three-dimensional multivariate statistical interpolation scheme. Mon. Wea. Re v. 109, 701–721.
  • Lorenc, A. and Hammon, O. 1988. Objective quality control of observations using Bayesian methods. Theory and practical implementation. Quart. J. Roy. Meteor. Soc. 114, 515–543.
  • Machenhauer, B. 1988. HIRLAM final report. HIRLAM Tech. Rep. 9, 116 pp. Available from DMI, DK-2100 Copenhagen Ø, Denmark.
  • 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.
  • Thépaut, 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.
  • Zupanski, M. 1993. Regional four-dimensional variational data assimilation in a quasi-operational forecasting environment. Mon. Wea. Re v. 121, 2396–2408.