Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm.

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  • Additional Information
    • Author-Supplied Keywords:
      ensemble forecasting
      ensemble Kalman filter
      the WRF model
      tropical cyclone vital
      Tropical cyclones
    • Subject Terms:
    • Abstract:
      This study presents an approach to assimilate tropical cyclone (TC) real-time reports and the University of Wisconsin-Cooperative Institute for Meteorological Satellite Studies (CIMSS) Atmospheric Motion Vectors (AMV) data into the Weather Research and Forecasting (WRF) model for TC forecast applications. Unlike current methods in which TC real-time reports are used to either generate a bogus vortex or spin up a model initial vortex, the proposed approach ingests the TC real-time reports through blending a dynamically consistent synthetic vortex structure with the CIMSS-AMV data. The blended dataset is then assimilated into the WRF initial condition, using the local ensemble transform Kalman filter (LETKF) algorithm. Retrospective experiments for a number of TC cases in the northwestern Pacific basin during 2013-2014 demonstrate that this approach could effectively increase both the TC circulation and enhance the large-scale environment that the TCs are embedded in. Further evaluation of track and intensity forecast errors shows that track forecasts benefit more from improvement in the large-scale flow at 4-5-day lead times, whereas the intensity improvement is minimal. While the difference between the track and intensity improvement could be due to a specific model configuration, this result appears to be consistent with the recent reports of insignificant impacts of inner core data assimilation in operational TC models at the long range of 4-5 days. The new approach will be most beneficial for future regional TC models that are directly initialized from very high-resolution global models whose storm initial locations are sufficiently accurate at the initial analysis that there is no need to carry out any artificial vortex removal or filtering steps. [ABSTRACT FROM AUTHOR]
    • Abstract:
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    • Author Affiliations:
      1National Center for Hydro-Meteorological Forecasting , 8 Phao Dai Lang Hanoi Vietnam
      2Department of Space and Aeronautics , University of Science and Technology of Hanoi , Hanoi Vietnam
      3Department of Earth and Atmospheric Sciences , Indiana University , GY428A Geological Building Bloomington 47405 USA
    • ISSN:
      0033-4553
    • Accession Number:
      10.1007/s00024-017-1568-0
    • Accession Number:
      123904928
  • Citations
    • ABNT:
      DU, T.; NGO-DUC, T.; KIEU, C. Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm. Pure & Applied Geophysics, [s. l.], v. 174, n. 7, p. 2803–2825, 2017. DOI 10.1007/s00024-017-1568-0. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=a9h&AN=123904928&custid=s6224580. Acesso em: 11 dez. 2019.
    • AMA:
      Du T, Ngo-Duc T, Kieu C. Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm. Pure & Applied Geophysics. 2017;174(7):2803-2825. doi:10.1007/s00024-017-1568-0.
    • APA:
      Du, T., Ngo-Duc, T., & Kieu, C. (2017). Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm. Pure & Applied Geophysics, 174(7), 2803–2825. https://doi.org/10.1007/s00024-017-1568-0
    • Chicago/Turabian: Author-Date:
      Du, Tien, Thanh Ngo-Duc, and Chanh Kieu. 2017. “Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm.” Pure & Applied Geophysics 174 (7): 2803–25. doi:10.1007/s00024-017-1568-0.
    • Harvard:
      Du, T., Ngo-Duc, T. and Kieu, C. (2017) ‘Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm’, Pure & Applied Geophysics, 174(7), pp. 2803–2825. doi: 10.1007/s00024-017-1568-0.
    • Harvard: Australian:
      Du, T, Ngo-Duc, T & Kieu, C 2017, ‘Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm’, Pure & Applied Geophysics, vol. 174, no. 7, pp. 2803–2825, viewed 11 December 2019, .
    • MLA:
      Du, Tien, et al. “Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm.” Pure & Applied Geophysics, vol. 174, no. 7, July 2017, pp. 2803–2825. EBSCOhost, doi:10.1007/s00024-017-1568-0.
    • Chicago/Turabian: Humanities:
      Du, Tien, Thanh Ngo-Duc, and Chanh Kieu. “Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm.” Pure & Applied Geophysics 174, no. 7 (July 2017): 2803–25. doi:10.1007/s00024-017-1568-0.
    • Vancouver/ICMJE:
      Du T, Ngo-Duc T, Kieu C. Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm. Pure & Applied Geophysics [Internet]. 2017 Jul [cited 2019 Dec 11];174(7):2803–25. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=a9h&AN=123904928&custid=s6224580