Monitoring the observation impact on the short-range forecast

Quarterly Journal of the Royal Meteorological Society

Volumn 135, Issue 638, 2009, Pages 239-250

  Cardinali, Carla ^a  

^a EUROPEAN CENTRE FOR MEDIUM RANGE WEATHER FORECASTS   (United Kingdom)

Author keywords

Adjoint system; Data assimilation; Observations impact

Indexed keywords

ADJOINT SYSTEM; ASSIMILATION SYSTEM; CONTROL EXPERIMENTS; DATA ASSIMILATION; DATA ASSIMILATION SYSTEMS; DATA IMPACT; DATA QUALITY; DIAGNOSTIC TOOLS; FIELD VARIABILITY; FORECAST ERRORS; FORECAST SENSITIVITY; OBSERVATION DATA; OBSERVATIONS IMPACT; OBSERVING SYSTEM EXPERIMENTS; POOR PERFORMANCE; SUBOPTIMALITY;

ATMOSPHERICS; DATA PROCESSING; EXPERIMENTS; WEATHER SATELLITES;

FORECASTING;

ADJOINT METHOD; CLIMATE PREDICTION; DATA ASSIMILATION; MONITORING; PERFORMANCE ASSESSMENT; SENSITIVITY ANALYSIS; WEATHER FORECASTING;

EID: 67649427472     PISSN: 00359009     EISSN: None     Source Type: Journal    
DOI: 10.1002/qj.366     Document Type: Article

References (35)

1. Ackley MH, Chadwick RB, Cogan J, Crosiar C, Eaton FD, Gage KS, Gossard EE, Lucci R, Merceret FJ, Neff WD, Ralph FM, Strauch RG, van de Kamp D, Weber BL, White AB. 1998. 'U.S. wind profilers: A review.' Technical Report FCM-R14-1998, US DoC/NOAA/OFCM, Washington, DC.
2. Baker NL, Daley R. 2000. Observation and background adjoint sensitivity in the adaptive observation-targeting problem. Q. J. R. Meteorol. Soc. 126: 1431-1454.
3. Bouttier F, Kelly G. 2001. Observing-system experiments in the ECMWF 4D-Var data assimilation system. Q. J. R. Meteorol. Soc. 127: 1469-1488.
4. Cardinali C, Buizza R. 2004. 'Observation sensitivity to the analysis and the forecast: A case study during ATreC targeting campaign.' Proceedings of the first THORPEX international science symposium, 6-10 December 2004, Montreal, Canada. WMO/TD-1237, WWRP/THORPEX No. 6.
5. Cardinali C, Pezzulli S, Andersson E. 2004. Influence-matrix diagnostic of a data assimilation system. Q. J. R. Meteorol. Soc. 130: 2767-2786.
6. Chapnik B, Desroziers G, Rabier F, Talagrand O. 2004. Properties and first application of an error-statistics tuning method in variational assimilation. Q. J. R. Meteorol. Soc. 130: 2253-2275.
7. Chapnik B, Desroziers G, Rabier F, Talagrand O. 2006. Diagnosis and tuning of observational error in a quasi-operational data assimilation setting. Q. J. R. Meteorol. Soc. 132: 543-565.
8. Courtier P, Andersson E, Heckley W, Pailleux J, Vasiljevic D, Hamrud M, Hollingsworth A, Rabier F, Fisher M. 1998: The ECMWF implementation of three-dimension variational assimilation (3D-Var). I: Formulation. Q. J. R. Meteorol. Soc. 124: 1783-1807.
9. Daescu DN. 2008. On the sensitivity equations of four-dimensional variational (4D-Var) data assimilation. Mon. Weather Rev. 136: 3050-3065.
10. Desroziers G, Ivanov S. 2001. Diagnosis and adaptive tuning of observation-error parameters in a variational assimilation. Q. J. R. Meteorol. Soc. 127: 1433-1452.
11. English S, Saunders R, Candy B, Forsythe M, Collard A. 2004. 'Met Office satellite data OSEs.' Pp. 146-156 in Proc. Third WMO workshop on the impact of various observing systems on numerical weather prediction, Alpbach, Austria. WMO/TD-1228, Geneva.
12. Errico RM. 2007. Interpretations of an adjoint-derived observational impact measure. Tellus 59A: 273-276.
13. Fisher M. 2003. 'Estimation of entropy reduction and degrees of freedom for signal for large variational analysis systems.' ECMWF Tech. Memo. 397, pp. 18.
14. Gelaro R, Buizza R, Palmer TN, Klinker E. 1998; Sensitivity analysis of forecast errors and the construction of optimal perturbations using singular vectors. J. Atmos. Sci. 55: 1012-1037.
15. Healy SB, Thépaut J-N. 2006. Assimilation experiments with CHAMP GPS radio occultation measurements. Q. J. R Meteorol. Soc. 132: 605-623.
16. Janisková M, Mahfouf J-F, Morcrette J-J, Chevallier F. 2002. Linearized radiation and cloud schemes in the ECMWF model: Development and evaluation. Q. J. R. Meteorol. Soc. 128: 1505-1527.
17. Kelly G, Thépaut J-N. 2007. 'Evaluation of the impact of the space component of the Global Observation System through Observing System Experiments. Pp. 16-28 in ECMWF Newsletter 113, Autumn.
18. Langland RH, Baker NL. 2004. Estimation of observation impact using the NRL atmospheric variational data assimilation adjoint system. Tellus 56A: 189-201.
19. Lopez P, Moreau E. 2005. A convection scheme for data assimilation: Description and initial tests. Q. J. R. Meteorol. Soc. 131: 409-436.
20. Lord S, Zapotocny T, Jung J. 2004. 'Observing system experiments with NCEP's global forecast system.' Pp. 56-62 in Third WMO workshop on the impact of various observing systems on numerical weather prediction, Alpbach, Austria. WMO/TD-1228, Geneva.
21. Lorenc AC. 1986. Analysis methods for numerical weather prediction. Q. J. R. Meteorol, Soc. 112: 1177-1194.
22. Morneau J, Pellerin S, Laroche S, Tanguay M. 2006. 'Estimation of adjoint sensitivity gradients in observation space using the dual (PSAS) formulation of the Environment Canada operational 4D-Var.' Pp. 162-163 in Proc. Second THORPEX international science symposium, 4-8 December 2006, Landshut, Germany. WMO/TD No. 1355, WWRP/THORPEX No. 7.
23. Purser RJ, Huang H-L. 1993. Estimating effective data density in a satellite retrieval or an objective analysis. J. Appl. Meteorol. 32: 1092-1107.
24. Rabier F, Courtier P. 1992. Four-dimensional assimilation in the presence of baroclinic instability. Q. J. R. Meteorol. Soc. 118: 649-672.
25. Rabier F, Klinker E, Courtier P, Hollingsworth A. 1996. Sensitivity of forecast errors to initial conditions. Q. J. R. Meteorol Soc. 122: 121-150.
26. Rabier F, Järvinen H, Klinker E, Mahfouf J-F, Simmons A. 2000. The ECMWF operational implementation of four-dimensional variational assimilation. I: Experimental results with simplified physics. Q. J. R. Meteorol. Soc. 126: 1143-1170.
27. Talagrand O. 1997. Assimilation of observations, an introduction. J. Meteorol. Soc. Jpn 75: 191-209.
28. Talagrand O. 1999. 'A posteriori evaluation and verification of the analysis and assimilation algorithms.' Pp. 17-28 in Proc. ECMWF workshop on diagnosis of data assimilation systems, 2-4 November 1998. ECMWF, Reading, UK.
29. Talagrand O. 2002. 'A posteriori validation of assimilation algorithms. In Data assimilation for the Earth system, NATO Advanced Study. Institute Series, Swinbank R, Shutyaev V, Lahoz WA (eds). Kluwer.
30. Tompkins AM, Janisková -M. 2004. A cloud scheme for data assimilation: Description and initial tests. Q. J. R. Meteorol. Soc. 130: 2495-2517.
31. Uppala SM, Kållberg PW, Simmons AJ, Andrae U, da Costa Bechtold V, Fiorino M., Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Hólm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, McNally AP, Mahfouf J-F, Morcrette J-J, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J. 2005. The ERA-40 re-analysis. Q. J. R. Meteorol. Soc. 131: 2961-3012.
32. van der Vorst HA. 2003. Iterative Krylov methods for large linear systems. Cambridge University Press.
33. Wilczak JM, Strauch RG, Ralph FM, Weber BL, Merritt DA, Jordan JR, Wolfe DE, Lewis LK, Wuertz DB, Gaynor JE, McLaughlin SA, Rogers RR, Riddle AC, Dye TS. 1995. Contamination of wind profiler data by migrating birds: Characteristics of corrupted data and potential solutions. J. Atmos. Oceanic Technol. 12: 449-467.
34. Xu L, Langland R, Baker N, Rosmond T. 2006. 'Development and testing of the adjoint of NAVDAS-AR.' Seventh international workshop on adjoint applications in dynamic meteorology, 8-13 October 2006, Obergurgl, Austria.
35. Zhu Y, Gelaro R. 2008. Observation sensitivity calculations using the adjoint of the Gridpoint Statistical Interpolation (GSI) analysis system. Mon. Weather Rev. 136: 335-351.