Singular vector structure and evolution of a recurving tropical cyclone

Monthly Weather Review

Volumn 137, Issue 2, 2009, Pages 505-524

  Kim, Hyun Mee ^a   Jung, Byoung Joo ^a  

^a Yonsei University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ADJOINT MODELS; BAROCLINICITY; DEVELOPMENT STAGES; EXTRATROPICAL CYCLONES; EXTRATROPICAL TRANSITION; LANCZOS ALGORITHM; LOWER TROPOSPHERE; MESOSCALE MODEL; MIDLATITUDES; PENNSYLVANIA STATE UNIVERSITY; SINGULAR VECTORS; TOTAL ENERGY SINGULAR VECTORS; TROPICAL CYCLONE; TROUGH REGION; VERTICAL STRUCTURES;

HURRICANES; TROPICS;

STORMS;

ALGORITHM; ATMOSPHERIC MODELING; BAROCLINIC MODE; FRONTOGENESIS; MESOSCALE METEOROLOGY; MIDLATITUDE ENVIRONMENT; TROPICAL CYCLONE; TROPOSPHERE; TYPHOON;

EID: 68249154985     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/2008MWR2643.1     Document Type: Article

References (39)

1. Badger, J., and B. J. Hoskins, 2001: Simple initial value problems and mechanisms for baroclinic growth. J. Atmos. Sci., 58, 38-49.
2. Baker, N. L., and R. Daley, 2000: Observation and background adjoint sensitivity in the adaptive observation-targeting problem. Quart. J. Roy. Meteor. Soc., 126, 1431-1454.
3. Bergot, T., 1999: Adaptive observations during FASTEX: A systematic survey of upstream flights. Quart. J. Roy. Meteor. Soc., 125, 3271-3298.
4. Bergot, T., G. Hello, A. Joly, and S. Malardel, 1999: Adaptive observations: A feasibility study. Mon. Wea. Rev., 127, 743-765.
5. Bishop, C. H., and Z. Toth, 1999: Ensemble transformation and adaptive observations. J. Atmos. Sci., 56, 1748-1765.
6. Bishop, C. H., B. J. Etherton, and S. J. Majumdar, 2001: Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects. Mon. Wea. Rev., 129, 420-436.
7. Buizza, R., 1994: Localization of optimal perturbations using a projection operator. Quart. J. Roy. Meteor. Soc., 120, 1647-1681.
8. Buizza, R., and T. N. Palmer, 1995: The singular-vector structure of the atmospheric global circulation. J. Atmos. Sci., 52, 1434-1456.
9. Buizza, R., and A. Montani, 1999: Targeting observations using singular vectors. J. Atmos. Sci., 56, 2965-2985.
10. Ehrendorfer, M., and R. M. Errico, 1995: Mesoscale predictability and the spectrum of optimal perturbations. J. Atmos. Sci., 52, 3475-3500.
11. Errico, R. M., 1997: What is an adjoint model? Bull. Amer. Meteor. Soc., 78, 2577-2591.
12. Errico, R. M., and K. D. Raeder, 1999: An examination of the accuracy of the linearization of a mesoscale model with moist physics. Quart. J. Roy. Meteor. Soc., 125, 169-195.
13. Fehlmann, R., and H. C. Davies, 1997: Misforecasts of synoptic systems: Diagnosis via PV retrodiction. Mon. Wea. Rev., 125, 2247-2264.
14. Gelaro, R., R. H. Langland, G. D. Rohaly, and T. E. Rosmond, 1999: An assessment of the singular-vector approach to targeted observing using the FASTEX dataset. Quart. J. Roy. Meteor. Soc., 125, 3299-3327.
15. Gelaro, R., C. A. Reynolds, R. H. Langland, and G. D. Rohaly, 2000: A predictability study using geostationary satellite wind observations during NORPEX. Mon. Wea. Rev., 128, 3789-3807.
16. Hamill, T. M., and C. Snyder, 2002: Using improved background-error covariances from an ensemble Kalman filter for adaptive observations. Mon. Wea. Rev., 130, 1552-1572.
17. Hansen, J. A., and L. A. Smith, 2000: The role of operational constraints in selecting supplementary observations. J. Atmos. Sci., 57, 2859-2871.
18. Hoskins, B. J., R. Buizza, and J. Badger, 2000: The nature of singular vector growth and structure. Quart. J. Roy. Meteor. Soc., 126, 1565-1580.
19. Kim, H. M., and M. C. Morgan, 2002: Dependence of singular vector structure and evolution on the choice of norm. J. Atmos. Sci., 59, 3099-3116.
20. Kim, H. M., and B.-J. Jung, 2006: Adjoint-based forecast sensitivities of Typhoon Rusa. Geophys. Res. Lett., 33, L21813, doi:10.1029/2006GL027289.
21. Kim, H. M., and B.-J. Jung, 2009: Influence of moist physics and norms on singular vectors for a tropical cyclone. Mon. Wea. Rev., 137, 525-543.
22. Kim, H. M., M. C. Morgan, and R. E. Morss, 2004: Evolution of analysis error and adjoint-based sensitivities: Implications for adaptive observations. J. Atmos. Sci., 61, 795-812.
23. Kleist, D. T., and M. C. Morgan, 2005: Application of adjoint-derived forecast sensitivities to the 24-25 January 2000 U.S. east coast snowstorm. Mon. Wea. Rev., 133, 3148-3175.
24. Lorenz, E. N., and K. A. Emanuel, 1998: Optimal sites for supplementary observations: Simulation with a small model. J. Atmos. Sci., 55, 399-414.
25. Majumdar, S. J., C. H. Bishop, B. J. Etherton, I. Szunyogh, and Z. Toth, 2001: Can an ensemble transformKalman filter predict the reduction in forecast error variance produced by targeted observations? Quart. J. Roy. Meteor. Soc., 127, 2803-2820.
26. Majumdar, S. J., C. H. Bishop, B. J. Etherton, and Z. Toth, 2002: Adaptive sampling with the ensemble transform Kalman filter. Part II: Field program implementation. Mon. Wea. Rev., 130, 1356-1369.
27. Majumdar, S. J., S. D. Aberson, C. H. Bishop, R. Buizza, M. S. Peng, and C. A. Reynolds, 2006: A comparison of adaptive observing guidance for Atlantic tropical cyclones. Mon. Wea. Rev., 134, 2354-2372.
28. Montani, A., A. J. Thorpe, R. Buizza, and P. Unden, 1999: Forecast skill of the ECMWF model using targeted observations during FASTEX. Quart. J. Roy. Meteor. Soc., 125, 3219-3240.
29. Morgan, M. C., 2001: A potential vorticity and wave activity diagnosis of optimal perturbation evolution. J. Atmos. Sci., 58, 2518-2544.
30. Morss, R. E., K. A. Emanuel, and C. Snyder, 2001: Idealized adaptive observation strategies for improving numerical weather prediction. J. Atmos. Sci., 58, 210-232.
31. Palmer, T. N., R. Gelaro, J. Barkmeijer, and R. Buizza, 1998: Singular vectors, metrics, and adaptive observations. J. Atmos. Sci., 55, 633-653.
32. Peng, M. S., and C. A. Reynolds, 2005: Double trouble for typhoon forecasters. Geophys. Res. Lett., 32, L02810, doi:10.1029/ 2004GL021680.
33. Peng, M. S., and C. A. Reynolds, 2006: Sensitivity of tropical cyclone forecasts as revealed by singular vectors. J. Atmos. Sci., 63, 2508-2528.
34. Pu, Z.-X., and E. Kalnay, 1999: Targeting observations with the quasi-inverse linear and adjoint NCEP global models: Performance during FASTEX. Quart. J. Roy. Meteor. Soc., 125, 3329-3337.
35. Reynolds, C. A., R. Gelaro, and J. D. Doyle, 2001: Relationship between singular vectors and transient features in the background flow. Quart. J. Roy. Meteor. Soc., 127, 1731-1760.
36. Reynolds, C. A., M. S. Peng, S. J. Majumdar, S. D. Aberson, C. H. Bishop, and R. Buizza, 2007: Interpretation of adaptive observing guidance for Atlantic tropical cyclones. Mon.Wea. Rev., 135, 4006-4029.
37. Wu, C. C., J.-H. Chen, P.-H. Lin, and K.-H. Chou, 2007: Targeted observations of tropical cyclone movement based on the adjoint-derived sensitivity steering vector. J. Atmos. Sci., 64, 2611-2626.
38. Wu, C. C., S.-G. Chen, J.-H. Chen, K.-H. Chou, and P.-H. Lin, 2009: Interaction of Typhoon Shanshan (2006) with the midlatitude trough from both adjoint-derived sensitivity steering vector and potential vorticity perspectives. Mon. Wea. Rev., in press.
39. Zou, X., F. Vandenberghe, M. Pondeca, and Y.-H. Kuo, 1997: Introduction to adjoint techniques and the MM5 adjoint modeling system. NCAR Tech. Note NCAR/TN- 435STR, 110 pp.