• Aberson, S. D., 2002: Two years of operational hurricane synoptic surveillance. Wea. Forecasting, 17, 11011110.

  • Aberson, S. D., 2003: Targeted observations to improve operational tropical cyclone track forecast guidance. Mon. Wea. Rev., 131, 16131628.

    • Search Google Scholar
    • Export Citation
  • Aberson, S. D., 2008: Large forecast degradations due to synoptic surveillance during the 2004 and 2005 hurricane seasons. Mon. Wea. Rev., 136, 31383150.

    • Search Google Scholar
    • Export Citation
  • Aberson, S. D., , and J. L. Franklin, 1999: Impact on hurricane track and intensity forecasts of GPS dropwindsonde observations from the first-season flights of the NOAA Gulfstream-IV jet aircraft. Bull. Amer. Meteor. Soc., 80, 421427.

    • Search Google Scholar
    • Export Citation
  • Ancell, B., , and G. J. Hakim, 2007: Comparing adjoint- and ensemble-sensitivity analysis with applications to observation targeting. Mon. Wea. Rev., 135, 41174134.

    • Search Google Scholar
    • Export Citation
  • Bishop, C. H., , and Z. Toth, 1999: Ensemble transformation and adaptive observations. J. Atmos. Sci., 56, 17481765.

  • 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, 420436.

    • Search Google Scholar
    • Export Citation
  • Buizza, R., , and A. Montani, 1999: Targeted observations using singular vectors. J. Atmos. Sci., 56, 29652985.

  • Chan, J. C. L., , and W. M. Gray, 1982: Tropical cyclone movement and surrounding flow relationships. Mon. Wea. Rev., 110, 13541374.

  • Chen, J.-H., , M. S. Peng, , C. A. Reynolds, , and C.-C. Wu, 2009: Interpretation of tropical cyclone forecast sensitivity from the singular vector perspective. J. Atmos. Sci., 66, 33833400.

    • Search Google Scholar
    • Export Citation
  • Elsberry, R. L., , and P. A. Harr, 2008: Tropical cyclone structure (TCS08) field experiment science basis, observational platforms, and strategy. Asia-Pac. J. Atmos. Sci., 44, 209231.

    • Search Google Scholar
    • Export Citation
  • Errico, R. M., 1997: What is an adjoint model? Bull. Amer. Meteor. Soc., 78, 25772591.

  • Harnisch, F., , and M. Weissmann, 2010: Sensitivity of typhoon forecasts to different subsets of targeted dropsonde observations. Mon. Wea. Rev., 138, 26642680.

    • Search Google Scholar
    • Export Citation
  • Hoover, B. T., 2009: Comments on “Interaction of Typhoon Shanshan (2006) with the midlatitude trough from both adjoint-derived sensitivity steering vector and potential vorticity perspectives.” Mon. Wea. Rev., 137, 44204424.

    • Search Google Scholar
    • Export Citation
  • Hoover, B. T., , and M. C. Morgan, 2010: Validation of a tropical cyclone steering response function with a barotropic adjoint model. J. Atmos. Sci., 67, 18061816.

    • Search Google Scholar
    • Export Citation
  • Kim, H. M., , and B.-J. Jung, 2009a: Singular vector structure and evolution of a recurving tropical cyclone. Mon. Wea. Rev., 137, 505524.

    • Search Google Scholar
    • Export Citation
  • Kim, H. M., , and B.-J. Jung, 2009b: Influence of moist physics and norms on singular vectors for a tropical cyclone. Mon. Wea. Rev., 137, 525543.

    • Search Google Scholar
    • Export Citation
  • Kim, S. H., , H. J. Kwon, , and R. L. Elsberry, 2009: Beta gyres in global analysis fields. Adv. Atmos. Sci., 26, 984994.

  • Langland, R. H., 2005: Issues in targeted observing. Quart. J. Roy. Meteor. Soc., 131, 34093425.

  • 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, 13561369.

    • Search Google Scholar
    • Export Citation
  • 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, 23542372.

    • Search Google Scholar
    • Export Citation
  • Majumdar, S. J., , S.-G. Chen, , and C.-C. Wu, 2011: Characteristics of ensemble transform Kalman filter adaptive sampling guidance for tropical cyclones. Quart. J. Roy. Meteor. Soc., 137, 503520.

    • Search Google Scholar
    • Export Citation
  • McLay, J. G., , C. H. Bishop, , and C. A. Reynolds, 2007: The ensemble-transform scheme adapted for the generation of stochastic perturbations. Quart. J. Roy. Meteor. Soc., 133, 12571266.

    • Search Google Scholar
    • Export Citation
  • Molteni, F., , R. Buizza, , T. N. Palmer, , and T. Petroliagis, 1996: The ECMWF Ensemble Prediction System: Methodology and validation. Quart. J. Roy. Meteor. Soc., 122, 73119.

    • Search Google Scholar
    • Export Citation
  • Peng, M. S., , and C. A. Reynolds, 2006: Sensitivity of tropical cyclone forecasts as revealed by singular vectors. J. Atmos. Sci., 63, 25082528.

    • Search Google Scholar
    • Export Citation
  • Petersen, G. N., , S. J. Majumdar, , and A. J. Thorpe, 2007: The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF). Quart. J. Roy. Meteor. Soc., 133, 697710.

    • Search Google Scholar
    • Export Citation
  • 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, 40064029.

    • Search Google Scholar
    • Export Citation
  • Reynolds, C. A., , J. Teixeira, , and J. G. McLay, 2008: Impact of stochastic convection on the ensemble transform. Mon. Wea. Rev., 136, 45174526.

    • Search Google Scholar
    • Export Citation
  • Weissmann, M., and Coauthors, 2011: The influence of assimilating dropsonde data on typhoon track and midlatitude forecasts. Mon. Wea. Rev., 139, 908920.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., 2006: Targeted observation and data assimilation for tropical cyclone track prediction. Proc. Sixth Int. Workshop on Tropical Cyclones, San Jose, Costa Rica, WMO/CAS/WWW, 409–423.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., , and K. A. Emanuel, 1993: Interaction of a baroclinic vortex with background shear: Application to hurricane movement. J. Atmos. Sci., 50, 6276.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., , T.-S. Huang, , W.-P. Huang, , and K.-H. Chou, 2003: A new look at the binary interaction: Potential vorticity diagnosis of the unusual southward movement of Typhoon Bopha (2000) and its interaction with Typhoon Saomai (2000). Mon. Wea. Rev., 131, 12891300.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., and Coauthors, 2005: Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR): An overview. Bull. Amer. Meteor. Soc., 86, 787790.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., , J.-H. Chen, , P.-H. Lin, , and K.-H. Chou, 2007a: Targeted observations of tropical cyclone movement based on the adjoint-derived sensitivity steering vector. J. Atmos. Sci., 64, 26112626.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., , K.-H. Chou, , P.-H. Lin, , S. D. Aberson, , M. S. Peng, , and T. Nakazawa, 2007b: The impact of dropwindsonde data on typhoon track forecasts in DOTSTAR. Wea. Forecasting, 22, 11571176.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., , S.-G. Chen, , J.-H. Chen, , K.-H. Chou, , and P.-H. Lin, 2009a: Interaction of Typhoon Shanshan (2006) with the midlatitude trough from both adjoint-derived sensitivity steering vector and potential vorticity perspectives. Mon. Wea. Rev., 137, 852862.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., and Coauthors, 2009b: Intercomparison of targeted observation guidance for tropical cyclones in the northwestern Pacific. Mon. Wea. Rev., 137, 24712492.

    • Search Google Scholar
    • Export Citation
  • Wu, C.-C., , S.-G. Chen, , J.-H. Chen, , K.-H. Chou, , and P.-H. Lin, 2009c: Reply. Mon. Wea. Rev., 137, 44254432.

  • Wu, C.-C., , K. K. W. Cheung, , and Y.-Y. Lo, 2009d: Numerical study of the rainfall event due to interaction of Typhoon Babs (1998) and the northeasterly monsoon. Mon. Wea. Rev., 137, 20492064.

    • Search Google Scholar
    • Export Citation
  • Yamaguchi, M., , T. Iriguchi, , T. Nakazawa, , and C.-C. Wu, 2009: An observing system experiment for Typhoon Conson (2004) using a singular vector method and DOTSTAR data. Mon. Wea. Rev., 137, 28012816.

    • Search Google Scholar
    • Export Citation
  • 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-435+STR, 110 pp. [Available from NCAR, P.O. Box 3000, Boulder, CO 80307-3000.]

    • Search Google Scholar
    • Export Citation
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Validation and Interpretation of Adjoint-Derived Sensitivity Steering Vector as Targeted Observation Guidance

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  • 1 Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
  • | 2 NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey
  • | 3 Department of Atmospheric Sciences, Chinese Culture University, Taipei, Taiwan
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Abstract

The adjoint-derived sensitivity steering vector (ADSSV) has been proposed and applied as a guidance for targeted observation in the field programs for improving tropical cyclone predictability, such as The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). The ADSSV identifies sensitive areas at the observing time to the steering flow at the verifying time through adjoint calculation. In addition, the ability of the ADSSV to represent signals of influence from synoptic systems such as the midlatitude trough and the subtropical high prior to the recurvature of Typhoon Shanshan (2006) has also been demonstrated.

In this study, the impact of initial perturbations associated with the high or low ADSSV sensitivity on model simulations is investigated by systematically perturbing initial vorticity fields in the case of Shanshan. Results show that experiments with the perturbed initial conditions located in the high ADSSV area (i.e., the midlatitude trough and the subtropical high) lead to more track deflection relative to the unperturbed control run than experiments with perturbations in the low sensitivity area. The evolutions of the deep-layer-mean steering flow and the direction of the ADSSV are compared to provide conceptual interpretation and validation on the physical meaning of the ADSSV. Concerning the results associated with the perturbed regions in high sensitivity regions, the variation of the steering flow within the verifying area due to the initial perturbations is generally consistent with that of the direction of the ADSSV. In addition, the bifurcation between the ADSSV and the steering change becomes larger with the increased integration time. However, the result for the perturbed region in the low-sensitivity region indicates that the steering change does not have good agreement with the ADSSV. The large initial perturbations to the low-sensitivity region may interact with the trough to the north due to the nonlinearity, which may not be accounted for in the ADSSV. Furthermore, the effect of perturbations specifically within the sensitive vertical layers is investigated to validate the vertical structure of the ADSSV. The structure of kinetic energy shows that the perturbation associated with the trough (subtropical high) specifically in the mid-to-upper (mid-to-lower) troposphere evolves similarly to that in the deep-layer troposphere, leading to comparable track changes. A sensitivity test in which perturbations are locally introduced in a higher-sensitivity area is conducted to examine the different impact as compared to that perturbed with the broader synoptic feature.

Corresponding author address: Chun-Chieh Wu, Dept. of Atmospheric Sciences, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 106, Taiwan. E-mail: cwu@typhoon.as.ntu.edu.tw

This article is included in the Targeted Observations, Data Assimilation, and Tropical Cyclone Predictability special collection.

Abstract

The adjoint-derived sensitivity steering vector (ADSSV) has been proposed and applied as a guidance for targeted observation in the field programs for improving tropical cyclone predictability, such as The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). The ADSSV identifies sensitive areas at the observing time to the steering flow at the verifying time through adjoint calculation. In addition, the ability of the ADSSV to represent signals of influence from synoptic systems such as the midlatitude trough and the subtropical high prior to the recurvature of Typhoon Shanshan (2006) has also been demonstrated.

In this study, the impact of initial perturbations associated with the high or low ADSSV sensitivity on model simulations is investigated by systematically perturbing initial vorticity fields in the case of Shanshan. Results show that experiments with the perturbed initial conditions located in the high ADSSV area (i.e., the midlatitude trough and the subtropical high) lead to more track deflection relative to the unperturbed control run than experiments with perturbations in the low sensitivity area. The evolutions of the deep-layer-mean steering flow and the direction of the ADSSV are compared to provide conceptual interpretation and validation on the physical meaning of the ADSSV. Concerning the results associated with the perturbed regions in high sensitivity regions, the variation of the steering flow within the verifying area due to the initial perturbations is generally consistent with that of the direction of the ADSSV. In addition, the bifurcation between the ADSSV and the steering change becomes larger with the increased integration time. However, the result for the perturbed region in the low-sensitivity region indicates that the steering change does not have good agreement with the ADSSV. The large initial perturbations to the low-sensitivity region may interact with the trough to the north due to the nonlinearity, which may not be accounted for in the ADSSV. Furthermore, the effect of perturbations specifically within the sensitive vertical layers is investigated to validate the vertical structure of the ADSSV. The structure of kinetic energy shows that the perturbation associated with the trough (subtropical high) specifically in the mid-to-upper (mid-to-lower) troposphere evolves similarly to that in the deep-layer troposphere, leading to comparable track changes. A sensitivity test in which perturbations are locally introduced in a higher-sensitivity area is conducted to examine the different impact as compared to that perturbed with the broader synoptic feature.

Corresponding author address: Chun-Chieh Wu, Dept. of Atmospheric Sciences, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 106, Taiwan. E-mail: cwu@typhoon.as.ntu.edu.tw

This article is included in the Targeted Observations, Data Assimilation, and Tropical Cyclone Predictability special collection.

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