Skip to main content
Log in

Observation system experiments for Typhoon Jangmi (200815) observed during T-PARC

  • Published:
Asia-Pacific Journal of Atmospheric Sciences Aims and scope Submit manuscript

Abstract

In this study, the impact of various types of observations on the track forecast of Tropical Cyclone (TC) Jangmi (200815) is examined by using the Weather Research and Forecasting (WRF) model and the corresponding three-dimensional variational (3DVAR) data assimilation system. TC Jangmi is a recurving typhoon that is observed as part of the THORPEX Pacific Asian Regional Campaign (T-PARC). Conventional observations from the Korea Meteorological Administration (KMA) and targeted dropsonde observations from the Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) were used for a series of observation system experiments (OSEs). We found that the assimilation of observations in oceanic areas is important to analyze environmental flows (such as the North Pacific high) and to predict the recurvature of TC Jangmi. The assimilation of targeted dropsonde observations (DROP) results in a significant impact on the track forecast. Observations of ocean surface winds (QSCAT) and satellite temperature soundings (SATEM) also contribute positively to the track forecast, especially two- to three-day forecasts. The impact of sensitivity guidance such as real-time singular vectors (SVs) was evaluated in additional experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Aberson, S. D., 2002: Two years of operational hurricane synoptic surveillance. Wea. Forecasting, 17, 1101–1110.

    Article  Google Scholar 

  • _____, 2003: Targeted observations to improve operational tropical cyclone track forecast guidance. Mon. Wea. Rev., 131, 1613–1628.

    Article  Google Scholar 

  • _____, 2008: Large forecast degradations due to synoptic surveillance during the 2004 and 2005 hurricane seasons. Mon. Wea. Rev., 136, 3138–3150.

    Article  Google Scholar 

  • _____, 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, 421–427.

    Article  Google Scholar 

  • _____, and B. J. Etherton, 2006: Targeting and data assimilation studies during Hurricane Humberto (2001). J. Atmos. Sci., 63, 175–186.

    Article  Google Scholar 

  • Anthes, R. A., and Coauthors, 2008: The COSMIC/FORMOSAT-3 Mission: Early results. Bull. Amer. Meteor. Soc., 89, 313–333.

    Article  Google Scholar 

  • Burpee, R. W., S. D. Aberson, J. L. Franklin, S. J. Lord, and R. E. Tuleya, 1996: The impact of omega dropwindsondes on operational hurricane track forecast models. Bull. Amer. Meteor. Soc., 77, 925–933.

    Article  Google Scholar 

  • Barker, D., W. Huang, T.-R. Guo, and A. Bourgeois, 2003: A threedimensional variational (3DVAR) data assimilation system for use with MM5. NCAR Tech. Note. NCAR/TN-453 + STR, 68 pp.

  • _____, ______, ______, ______, and Q. N. Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897–914.

    Article  Google Scholar 

  • Buizza, R., C. Cardinali, G. Kelly, and J.-N. Thepaut, 2007: The value of observations. II: the value of observations located in singular-vector-based target areas. Quart. J. Roy. Meteor. Soc., 133, 1817–1832.

    Article  Google Scholar 

  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569–585.

    Article  Google Scholar 

  • Chou, K.-H., and C.-C. Wu, 2008: Development of the typhoon initialization in a mesoscale model — Combination of the bogused vortex with the dropwindsonde data in DOTSTAR. Mon. Wea. Rev., 136, 865–879.

    Article  Google Scholar 

  • _____, ______, P.-H. Lin, and S. Majumdar, 2010: Validation of QuikSCAT wind vectors by dropwindsonde data from Dropwindsonde Observations for Typhoon Surveillance Near the Taiwan Region (DOTSTAR). J. Geophys. Res., 115, D02109, doi:10.1029/2009-JD012131.

    Article  Google Scholar 

  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 3077–3107.

    Article  Google Scholar 

  • Elsberry, R. L., and P. A. Harr, 2008: Tropical cyclone structure (TCS08) field experiment science basis, observational platforms, and strategy. Asia-Pacific J. Atmos. Sci., 44, 209–231.

    Google Scholar 

  • Grell, G. A., 1993: Prognostic evaluation of assumptions used by cumulus parameterizations. Mon. Wea. Rev., 121, 764–787.

    Article  Google Scholar 

  • Hong, S.-Y., and J.-O. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129–151.

    Google Scholar 

  • _____, Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318–2341.

    Article  Google Scholar 

  • Huang, C.-Y., Y.-H. Kuo, S.-H. Chen, and F. Vandenberghe, 2005: Improvements in typhoon forecast with assimilated GPS occultation refractivity. Wea. Forecasting., 20, 931–953.

    Article  Google Scholar 

  • Kain, J. S., 2004: The Kain-Fritsch convective parameterization scheme: An update. J. Appl. Meteorol., 43, 170–181.

    Article  Google Scholar 

  • Kim, H. M., and M. Morgan, 2002: Dependence of singular vector structure and evolution on the choice of norm. J. Atmos. Sci., 59, 3099–3116.

    Article  Google Scholar 

  • _____, and B.-J. Jung, 2009a: Singular vector structure and evolution of a recurving tropical cyclone. Mon. Wea. Rev., 137, 505–524.

    Article  Google Scholar 

  • _____, and ______, 2009b: Influence of moist physics and norms on singular vectors for a tropical cyclone. Mon. Wea. Rev., 137, 525–543.

    Article  Google Scholar 

  • _____, ______, Y.-H. Kim, and H.-S. Lee, 2008: Adaptive observation quidance applied to Typhoon Rusa: Implications for THORPEX-PARC 2008. Asia-Pacific J. Atmos. Sci., 44, 297–312.

    Google Scholar 

  • Kurihara, Y., M. A. Bender, R. E. Tuleya, and R. J. Ross, 1995: Improvements in the GFDL hurricane prediction system. Mon. Wea. Rev., 121, 2030–2045.

    Article  Google Scholar 

  • Kwon, H. J., S.-H. Won, M.-H. Ahn, A.-S. Suh, and H.-S. Chung, 2002: GFDL-Type Typhoon Initialization in MM5. Mon. Wea. Rev., 130, 2966–2974.

    Article  Google Scholar 

  • Langland, R. H., C. Velden, P. M. Pauley, and H. Berger, 2009: Impact of Satellite-Derived Rapid-Scan Wind Observations on Numerical Model Forecasts of Hurricane Katrina. Mon. Wea. Rev., 137, 1615–1622.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16663–16682.

    Article  Google Scholar 

  • Palmer, T. N., R. Gelaro, J. Barkmeijer, and R. Buizza, 1998: Singular vectors, metrics, and adaptive observations. J. Atmos. Sci., 55, 633–653.

    Article  Google Scholar 

  • Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s Spectral Statistical Interpolation analysis system. Mon. Wea. Rev., 120, 1747–1763.

    Article  Google Scholar 

  • Pu, Z.-X., and S. A. Braun, 2001: Evaluation of bogus vortex techniques with four-dimensional variational data assimilation. Mon. Wea. Rev., 129, 2023–2039.

    Article  Google Scholar 

  • _____, X. Li, C. S. Velden, S. D. Aberson, and W. T. Lui, 2008: The impact of aircraft dropsonde and satellite wind data on numerical simulations of two landfalling tropical storms during the Tropical Cloud Systems and Processes Experiment. Wea. Forecasting., 23, 62–79.

    Article  Google Scholar 

  • Shapiro, M., and A. Thorpe, 2004: THORPEX International science plan, Version 3, 2 November 2004, WMO/TD No. 1246, WWRP/THORPEX No.2. [Available online at http://www.wmo.int/thorpex.]

  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the Advanced Research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp.

  • Velden, C., and Coauthors, 2005: Recent innovations in deriving tropospheric winds from meteorological satellites. Bull. Amer. Meteor. Soc., 86, 205–223.

    Article  Google Scholar 

  • Weissmann M., F. Harnisch, C.-C. Wu, P.-H. Lin, Y. Ohta, K. Yamashita, Y.-K. Kim, E.-H. Jeon, T. Nakazawa, and S. Aberson, 2010: The influence of dropsondes on typhoon track and mid-latitude forecasts. Mon. Wea. Rev., in press.

  • WMO, 2002: International core steering committee for THORPEX First session (ICSC-1) Final report, 15-16 October 2002. [Available online at http://www.wmo.int/thorpex.]

  • Wu, C.-C., and Coauthors, 2005: Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR): An Overview. Bull. Amer. Meteor. Soc., 86, 787–790.

    Article  Google Scholar 

  • _____, K.-H. Chou, Y. Wang, and Y.-H. Kuo, 2006: Tropical cyclone initialization and prediction based on four-dimensional variational data assimilation. J. Atmos. Sci., 63, 2383–2395.

    Article  Google Scholar 

  • _____, ______, P.-H. Lin, S. D. Aberson, M. S. Peng, and T. Nakazawa, 2007: The impact of dropwindsonde data on typhoon track forecasts in DOTSTAR. Wea. Forecasting., 22, 1157–1176.

    Article  Google Scholar 

  • _____, and Coauthors, 2009: Inter-comparison of Targeted Observation Guidance for Tropical Cyclones in the North western Pacific. Mon. Wea. Rev., 137, 2471–2492.

    Article  Google Scholar 

  • Xiao, Q., Y.-H. Kuo, Y. Zhang, D. M. Barker, and D.-J. Won, 2006: A tropical cyclone bogus data assimilation scheme in the MM5 3D-Var system and numerical experiments with Typhoon Rusa (2002) near landfall. J. Meteor. Soc. Japan., 84, 671–689.

    Article  Google Scholar 

  • _____, L. Chen, and X. Zhang, 2008: Evaluations of BDA Scheme using the Advanced Research WRF (ARW) Model. J. Appl. Meteor. Climatol., 48, 680–689.

    Article  Google Scholar 

  • 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, 2801–2816.

    Article  Google Scholar 

  • Zou, X., and Q. Xiao, 2000: Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme. J. Atmos. Sci., 57, 836–860.

    Article  Google Scholar 

  • _____, 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.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ki-Hoon Kim.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jung, BJ., Kim, H.M., Kim, YH. et al. Observation system experiments for Typhoon Jangmi (200815) observed during T-PARC. Asia-Pacific J Atmos Sci 46, 305–316 (2010). https://doi.org/10.1007/s13143-010-1007-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13143-010-1007-y

Key words

Navigation