Variational data assimilation in the tropics using precipitation data. Part II: 3D model

Monthly Weather Review

Volumn 124, Issue 11, 1996, Pages 2545-2561

  Tsuyuki, Tadashi ^a,b  

^a FLORIDA STATE UNIVERSITY   (United States)

^b JAPAN METEOROLOGICAL AGENCY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0000760135     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/1520-0493(1996)124<2545:VDAITT>2.0.CO;2     Document Type: Article

References (45)

1. Adler, R. F., and A. J. Negri, 1988: A satellite infrared technique to estimate tropical convective and stratiform rainfall. J. Appl. Meteor., 27, 30-51.
2. Andersson, E., J. Pailleux, J.-N. Thépaut, J. R. Eyre, A. P. McNally, G. A. Kelly, and P. Courtier, 1994: Use of cloud-clear radiances in three/four-dimensional variational data assimilation. Quart. J. Roy. Meteor. Soc., 120, 627-653.
3. Aonashi, K., 1993: An initialization method to incorporate precipitation data into a mesoscale numerical weather prediction model. J. Meteor. Soc. Japan, 71, 393-406.
4. Chang, S. W., and T. R. Holt, 1994: Impact of SSM/I rainfall rate on numerical prediction of cyclones. Mon. Wea. Rev., 122, 151-164.
5. Courtier, P., 1993: Introduction to numerical weather prediction data assimilation methods. Proc. ECMWF Seminar on Developments in the Use of Satellite Data in Numerical Weather Prediction, Reading, United Kingdom, ECMWF, 189-207.
6. _, and O. Talagrand, 1990: Variational assimilation of meteorological observations with the direct and adjoint shallow-water equations. Tellus, 42A, 531-549.
7. _, J.-N. Thépaut, and A. Hollingsworth, 1994: A strategy for operational implementation of 4D-Var, using an incremental approach. Quart. J. Roy. Meteor. Soc., 120, 1367-1387.
8. Daley, R., C. Girard, J. Henderson, and I. Simmonds, 1976: Short-term forecasting with a multi-level spectral primitive model. Part I - Model formulation. Atmosphere, 14, 98-116.
9. Davidson, N. E., and K. Puri, 1992: Tropical prediction using dynamical nudging, satellite-defined convective heat sources, and a cyclone bogus. Mon. Wea. Rev., 120, 2501-2522.
10. Derber, J. C., 1989: A variational continuous assimilation technique. Mon. Wea. Rev., 117, 2437-2446.
11. Gill, P. E., W. Murray, and M. H. Wright, 1981: Practical Optimization. Academic Press, 401 pp.
12. Gustafsson, N., 1992: Use of a digital filter as weak constraint in variational data assimilation. Proc. ECMWF Workshop on Variational Assimilation with Special Emphasis on Three-Dimensional Aspects, Reading, United Kingdom, ECMWF, 327-338.
13. Heckley, W. A., A. G. Kelly, and M. Tiedtke, 1990: On the use of satellite-derived heating rates for data assimilation within the tropics. Mon. Wea. Rev., 118, 1743-1757.
14. Kanamitsu, M., 1985: A study of the predictability of the ECMWF operational forecast model in the tropics. J. Meteor. Soc. Japan, 63, 779-804.
15. Kasahara, A., A. P. Mizzi, and L. J. Donner, 1994: Diabatic initialization for improvement in the tropical analysis of divergence and moisture using satellite radiometric imagery data. Tellus, 46A, 242-264.
16. Krishnamurti, T. N., K. Ingles, S. Cocke, R. Pasch, and T. Kitade, 1984: Details of low latitude medium-range numerical weather prediction using a global spectral model II. Effect of orography and physical initialization. J. Meteor. Soc. Japan, 62, 613-649.
17. _, H. S. Bedi, W. Heckley, and K. Ingles, 1988: Reduction of the spinup time for evaporation and precipitation in a spectral model. Mon. Wea. Rev., 116, 907-920.
18. _, J. Xue, H. S. Bedi, K. Ingles, and D. Oosterhof, 1991: Physical initialization for numerical weather prediction over the tropics. Tellus, 43AB, 53-81.
19. _, H. S. Bedi, and K. Ingles, 1993: Physical Initialization using SSM/I rain rates. Tellus, 45A, 247-269.
20. _, G. Rohaly, and H. S. Bedi, 1994: On the improvement of precipitation forecast skill from physical initialization. Tellus, 46A, 598-614.
21. Kummerow, C., and L. Giglio, 1994: A passive technique for estimating rainfall and vertical structure information from space. Part I: Algorithm description. J. Appl. Meteor., 33, 3-18.
22. _, and _, 1994: A passive technique for estimating rainfall and vertical structure information from space. Part II: Applications to SSM/I data. J. Appl. Meteor., 33, 19-34.
23. Liu, D. C., and J. Nocedal, 1989: On the limited memory BFGS method for large scale optimization. Mathematical Programming, 45, 503-528.
24. Liu, G., and J. A. Curry, 1992: Retrieval of precipitation from satellite microwave measurement using both emission and scattering. J. Geophys. Res., 97, 9959-9974.
25. Lynch, P., and X.-Y. Huang, 1992: Initialization of the HIRLAM model using a digital filter. Mon. Wea. Rev., 120, 1019-1034.
26. Manobianco, J., S. Koch, V. M. Karyampudi, and A. J. Negri, 1994: The impact of assimilating satellite-derived precipitation rates on numerical simulations of the ERICA IOP 4 cyclone. Mon. Wea. Rev., 122, 341-365.
27. Navon, I. M., X. Zou, J. C. Derber, and J. Sela, 1992: Variational data assimilation with an adiabatic version of the NMC spectral model. Mon. Wea. Rev., 120, 1433-1446.
28. Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center's spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747-1763.
29. Pasch, P. J., 1983: On the onset of the planetary scale monsoon. Ph.D. thesis, The Florida State University, 220 pp.
30. Puri, K., and M. J. Miller, 1990: The use of satellite data in the specification of convective heating for diabatic initialization and moisture adjustment in numerical weather prediction. Mon. Wea. Rev., 118, 67-93.
31. Thépaut, J.-N., and P. Courtier, 1991: Four-dimensional variational data assimilation using the adjoint of a multilevel primitive-equation model. Quart. J. Roy. Meteor. Soc., 117, 1225-1254.
32. _, D. Vasiljevic, P. Courtier, and J. Pailleux, 1993a: Variational assimilation of conventional meteorological observations with a multilevel primitive-equation model. Quart. J. Roy. Meteor. Soc., 119, 153-186.
33. _, R. N. Hoffman, and P. Courtier, 1993b: Interactions of dynamics and observations in a four-dimensional variational assimilation. Mon. Wea. Rev., 121, 3393-3414.
34. Tsuyuki, T., 1996: Variational data assimilation in the tropics using precipitation data. Part I: Column model. Meteor. Atmos. Phys., in press.
35. Vukicević, T., and R. M. Errico, 1993: Linearization and adjoint of parameterized moist diabatic processes. Tellus, 45A, 493-510.
36. Wang, Z., 1993: Variational data assimilation with 2-D shallow water equations and 3-D FSU global spectral models. Ph.D. thesis, The Florida State University, 232 pp.
37. Yang, W., I. M. Navon, and P. Courtier, 1996: A new Hessian preconditioning method applied to variational data assimilation experiments using NASA general circulation model. Mon. Wea. Rev., 124, 1000-1017.
38. Zou, X., I. M. Navon, and F. X. Le Dimet, 1992: Incomplete observations and control of gravity waves in variational data assimilation. Tellus, 44A, 273-296.
39. _, _, and J. Sela, 1993a: Control of gravitational oscillations in variational data assimilation. Mon. Wea. Rev., 121, 272-289.
40. _, _, and _, 1993b: Variational data assimilation with moist threshold processes using the NMC spectral model. Tellus, 45A, 370-387.
41. _, _, M. Berger, K. H. Phua, T. Schlick, and F. X. Le Dimet, 1993c: Numerical experience with limited-memory quasi-Newton and truncated Newton methods. SIAM J. Optimization, 3, 582-608.
42. Zupanski, D., 1993: The effects of discontinuities in the Betts-Miller cumulus convection scheme on four-dimensional variational data assimilation. Tellus, 45A, 511-524.
43. _, and F. Mesinger, 1995: Four-dimensional variational assimilation of precipitation data. Mon. Wea. Rev., 123, 1112-1127.
44. Zupanski, M., 1993a: Regional four-dimensional variational data assimilation in a quasi-operational forecasting environment. Mon. Wea. Rev., 121, 2396-2408.
45. _, 1993b: A preconditioning algorithm for large-scale minimization problems. Tellus, 45A, 478-492.