An ocean coupling potential intensity index for tropical cyclones

Timely and accurate forecasts of tropical cyclones (TCs, i.e., hurricanes and typhoons) are of great importance for risk mitigation. Although in the past two decades there has been steady improvement in track prediction, improvement on intensity prediction is still highly challenging. Cooling of the...

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Veröffentlicht in:Geophysical research letters 2013-05, Vol.40 (9), p.1878-1882
Hauptverfasser: Lin, I.-I., Black, P., Price, J. F., Yang, C.-Y., Chen, S. S., Lien, C.-C., Harr, P., Chi, N.-H., Wu, C.-C., D'Asaro, E. A.
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Sprache:eng
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Zusammenfassung:Timely and accurate forecasts of tropical cyclones (TCs, i.e., hurricanes and typhoons) are of great importance for risk mitigation. Although in the past two decades there has been steady improvement in track prediction, improvement on intensity prediction is still highly challenging. Cooling of the upper ocean by TC‐induced mixing is an important process that impacts TC intensity. Based on detail in situ air‐deployed ocean and atmospheric measurement pairs collected during the Impact of Typhoons on the Ocean in the Pacific (ITOP) field campaign, we modify the widely used Sea Surface Temperature Potential Intensity (SST_PI) index by including information from the subsurface ocean temperature profile to form a new Ocean coupling Potential Intensity (OC_PI) index. Using OC_PI as a TC maximum intensity predictor and applied to a 14 year (1998–2011) western North Pacific TC archive, OC_PI reduces SST_PI‐based overestimation of archived maximum intensity by more than 50% and increases the correlation of maximum intensity estimation from r2 = 0.08 to 0.31. For slow‐moving TCs that cause the greatest cooling, r2 increases to 0.56 and the root‐mean square error in maximum intensity is 11 m s−1. As OC_PI can more realistically characterize the ocean contribution to TC intensity, it thus serves as an effective new index to improve estimation and prediction of TC maximum intensity. Key Points Current potential intensity index considers only ocean's surface contribution Inclusion of ocean's subsurface information to improve estimation Based on a valuable in situ data set from the ITOP field campaign
ISSN:0094-8276
1944-8007
DOI:10.1002/grl.50091