TY - JOUR
T1 - High-resolution time-lagged ensemble prediction for landfall intensity of Super Typhoon Haiyan (2013) using a cloud-resolving model
AU - Wang, Chung Chieh
AU - Lee, Chau Yi
AU - Jou, Ben Jong Dao
AU - Celebre, Cynthia P.
AU - David, Shirley
AU - Tsuboki, Kazuhisa
N1 - Funding Information:
The authors would like to thank the anonymous reviewers for their constructive comments and suggestions on the manuscript, and Ms. Y.-W. Wang and S.-Y. Huang for their help during the study. This work was jointly supported by the Ministry of Science and Technology (MOST) of Taiwan (under Grants MOST 105-2923-M-002-012-MY3, MOST 108-2111-M-003-005-MY2, MOST 109-2923-M-002-008, MOST 110-2111-M-003-004, and MOST 110-2625-M-003-001), and by the Department of Science and Technology−Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST−PCIEERD) of the Philippines. The NCEP is appreciated for making the GFS data open and free. The computational resources were provided by the National Center for High-performance Computing (NCHC) of Taiwan and the College of Science of the National Taiwan Normal University (NTNU). Original plots of Fig. 1b and c are from NOAA, USA and PAGASA, DOST of the Philippines, respectively.
Funding Information:
The authors would like to thank the anonymous reviewers for their constructive comments and suggestions on the manuscript, and Ms. Y.-W. Wang and S.-Y. Huang for their help during the study. This work was jointly supported by the Ministry of Science and Technology (MOST) of Taiwan (under Grants MOST 105-2923-M-002-012-MY3 , MOST 108-2111-M-003-005-MY2 , MOST 109-2923-M-002-008 , MOST 110-2111-M-003-004 , and MOST 110-2625-M-003-001 ), and by the Department of Science and Technology−Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST−PCIEERD) of the Philippines. The NCEP is appreciated for making the GFS data open and free. The computational resources were provided by the National Center for High-performance Computing (NCHC) of Taiwan and the College of Science of the National Taiwan Normal University (NTNU). Original plots of Fig. 1 b and c are from NOAA, USA and PAGASA, DOST of the Philippines, respectively.
Publisher Copyright:
© 2022 The Authors
PY - 2022/9
Y1 - 2022/9
N2 - The prediction of tropical cyclone (TC) intensity at landfall is crucial for regions vulnerable to high winds and storm surges, but its accuracy has experienced only limited improvement. At high resolution with a grid size of 2.5 km, the Cloud-Resolving Storm Simulator (CReSS) is applied to Super Typhoon Haiyan (2013), one of the strongest TCs to ever make landfall (at 85 m s−1 in peak wind speed and 900 hPa in central pressure. Predictions are made every 6 h using a time-lagged strategy so that the computational cost is relatively low. Averaging at 64 m s−1 and 925 hPa, our hindcasts during 4–7 November show large improvements in pre-landfall intensity over global models. Furthermore, when the previous CReSS result that best matches the observed intensity is used as the initial field, the predicted intensity consistently reaches 73–76 m s−1 and below 900 hPa. Thus, this approach is shown to produce more accurate TC intensity forecasts for storm-surge simulations for Haiyan.
AB - The prediction of tropical cyclone (TC) intensity at landfall is crucial for regions vulnerable to high winds and storm surges, but its accuracy has experienced only limited improvement. At high resolution with a grid size of 2.5 km, the Cloud-Resolving Storm Simulator (CReSS) is applied to Super Typhoon Haiyan (2013), one of the strongest TCs to ever make landfall (at 85 m s−1 in peak wind speed and 900 hPa in central pressure. Predictions are made every 6 h using a time-lagged strategy so that the computational cost is relatively low. Averaging at 64 m s−1 and 925 hPa, our hindcasts during 4–7 November show large improvements in pre-landfall intensity over global models. Furthermore, when the previous CReSS result that best matches the observed intensity is used as the initial field, the predicted intensity consistently reaches 73–76 m s−1 and below 900 hPa. Thus, this approach is shown to produce more accurate TC intensity forecasts for storm-surge simulations for Haiyan.
KW - Cloud-resolving model
KW - Intensity forecast
KW - Rapid intensification (RI)
KW - Super Typhoon Haiyan (2013)
KW - Time-lagged ensemble
KW - Tropical cyclone
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U2 - 10.1016/j.wace.2022.100473
DO - 10.1016/j.wace.2022.100473
M3 - Article
AN - SCOPUS:85133560590
SN - 2212-0947
VL - 37
JO - Weather and Climate Extremes
JF - Weather and Climate Extremes
M1 - 100473
ER -