Application of Weighted Analog Intensity Prediction (WAIP) guidance on Philippine tropical cyclone events

  • Author(s): Robb P. Gile, John Carlo S. Sugui, Juanito S. Galang, Esperanza O. Cayanan, Hsiao-Chung Tsai, Yung-Lan Lin, Ai-Mei Chia, Ping-Yu Lin, Kuo-Chen Lu, and Ben Jong-Dao Jou
  • DOI: 10.3319/TAO.2021.03.03.01
  • Keywords: Intensity forecast Philippine tropical cyclones Weighted analog technique
  • Citation: Gile, R. P., J. C. S. Sugui, J. S. Galang, E. O. Cayanan, H.-C. Tsai, Y.-L. Lin, A.-M. Chia, P.-Y. Lin, K.-C. Lu, and B. J.-D. Jou, 2021: Application of Weighted Analog Intensity Prediction (WAIP) guidance on Philippine tropical cyclone events. Terr. Atmos. Ocean. Sci., 32, 669-691, doi: 10.3319/TAO.2021.03.03.01
  • Rank-weighted analog technique used to generate intensity forecast guidance
  • WAIP intensity forecast had skill relative to persistence up to 72 h within PAR
  • WAIP struggling to predict lower range of intensity with increasing forecast time
Abstract

The tropical cyclone (TC) intensity forecast from the Weighted Analog Intensity Prediction (WAIP) was evaluated using 63 Philippine TC cases from 2014 to 2017 to determine its applicability as baseline intensity forecast guidance of the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA). The method generates a rank-weighted average of intensity evolutions of 10 historical analogs from the 1945 to 2014 Joint Typhoon Warning Center best tracks that closely resemble the PAGASA official forecast track and initial intensity at the time the forecast is generated. WAIP proved to be more skillful in providing intensity forecast at 12 to 96 h and less skillful at 120 h relative to persistence. Verification revealed that WAIP had significantly smaller mean absolute error and consistently smaller intensity biases up to 96 h. However, the small sample size at 96 h due to the limitations in the extent of the observed track and reference track forecast from PAGASA suggests that the result may not fully represent the model performance within the Philippine Area of Responsibility at 96 h. The probability distribution of intensities at 36, 72, and 96 h predicted by the model showed that the statistical model may not fully capture the full range of the observed intensities or the extreme values, with the model struggling to predict lower range of intensity values with increasing forecast intervals. Three TC cases are presented to emphasize the model dependence on the accuracy of the reference track forecast and the number and representativeness of available historical analogs for a particular forecast scenario.

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