Tropical cyclones (TCs) undergoing extratropical transition (ET) can develop into intense cyclonic systems accompanied by high-impact weather in areas far removed from the original TC. This study presents an analysis of multiseasonal global simulations representative of present-day and projected future climates using the Model for Prediction Across Scales–Atmosphere (MPAS-A), with high resolution (15-km grid) throughout the Northern Hemisphere. TCs are tracked as minima in sea level pressure (SLP) accompanied by a warm core, and TC tracks are extended into the extratropical phase based on local minima in SLP and use of a cyclone phase space method. The present-day simulations adequately represent observed ET characteristics such as frequency, location, and seasonal cycles throughout the Northern Hemisphere. The most significant changes in future ET events occur in the North Atlantic (NATL) basin. Here, a more favorable background environment, a shift toward stronger TC warm cores in the lower troposphere, and a significant poleward shift in TC location lead to a ~40% increase in the number of NATL ET events and a ~6% increase in the fraction of TCs undergoing ET. This equates to approximately 1–2 additional ET events per year in this region. In the future simulations, ET in the NATLmore »
The authors present a global climatology of tropical cyclones (TCs) that undergo extratropical transition (ET). ET is objectively defined based on a TC’s trajectory through the cyclone phase space (CPS), which is calculated using storm tracks from 1979–2017 best track data and geopotential height fields from reanalysis datasets. Two reanalyses are used and compared for this purpose, the Japanese 55-yr Reanalysis and the ECMWF interim reanalysis. The results are used to study the seasonal and geographical distributions of storms undergoing ET and interbasin differences in the statistics of ET occurrence. About 50% of all TCs in the North Atlantic and the western North Pacific undergo ET. In the Southern Hemisphere, ET fractions range from about 20% in the south Indian Ocean and the Australian region to 45% in the South Pacific. In the majority of ETs, TCs become thermally asymmetric before forming a cold core. However, a substantial fraction of TCs take the reverse pathway, developing a cold core before becoming thermally asymmetric. This pathway is most common in the eastern North Pacific and the North Atlantic. Different ET pathways can be linked to different geographical trajectories and environmental settings. In ETs over warmer sea surface temperatures, TCs tend to more »
- Publication Date:
- NSF-PAR ID:
- 10103754
- Journal Name:
- Journal of Climate
- Volume:
- 32
- Issue:
- 12
- Page Range or eLocation-ID:
- p. 3557-3582
- ISSN:
- 0894-8755
- Publisher:
- American Meteorological Society
- Sponsoring Org:
- National Science Foundation
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Abstract -
This study analyzes the differences between an objective, automated identification of tropical cyclones (TCs) that undergo extratropical transition (ET), and the designation of ET determined subjectively by human forecasters in best track data in all basins globally. The objective identification of ET is based on the cyclone phase space (CPS), calculated from the Japanese 55-yr Reanalysis (JRA-55) or the ECMWF interim reanalysis (ERA-Interim). The resulting classification into ET storms and non-ET storms underlies the global climatology of ET presented in Part I of this study. Here, the authors investigate how well the CPS classifications agree with those in the best track records calculated from JRA-55 or from ERA-Interim data. According to F1 scores and Matthews correlation coefficients (MCCs), the classification of ET storms in the CPS agrees best with the best track classification in the western North Pacific (MCC > 0.7) and the North Atlantic (MCC > 0.5). In other basins, the correlation between the CPS classification and the best track classification is only slightly higher than that of a random classification. The JRA-55 classification achieves higher performance scores than does the ERA-Interim classification, and the differences are statistically significant in all basins. The lower performance of ERA-Interim is mainlymore »
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