On the intensity decay of tropical cyclones before landfall

Wang, S; Toumi, Ralf

doi:10.1038/s41598-022-07310-4

Cited by 10 publications

(8 citation statements)

References 48 publications

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“…The lifetime maximum intensity (LMI) of a TC is the intensity closest to its theoretical upper limit and has received much more attention than the intensity in any other period of its lifecycle. However, the location of LMI is usually hundreds of kilometres away from land 7 , and an intensity decay from the LMI to LI frequently occur before landfall 8 . The long-term TC socio-economic impact is ultimately driven by the number of intense storms making landfall.…”

Section: Introductionmentioning

confidence: 99%

More tropical cyclones are striking coasts with major intensities at landfall

Wang

Toumi

2022

Sci Rep

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In this study, we show that the number of annual global tropical cyclone (TC) landfalls with major landfall intensity (LI ≥ 50 m s−1) has nearly doubled from 1982 to 2020. The lifetime maximum intensity (LMI) of global major landfalling TCs has been increasing by 0.8 m s−1 per decade (p < 0.05), but this significance of intensity change disappears at landfall (0.3 m s−1 per decade, p = 0.69). The lack of a significant LI trend is caused by the much larger variance of LI than that of LMI in all basins and explains why a significant count change of TCs with major intensity at landfall has only now emerged. Basin-wide TC trends of intensity and spatial distribution have been reported, but this long-term major TC landfall count change may be the most socio-economic significant.

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Section: Introductionmentioning

confidence: 99%

More tropical cyclones are striking coasts with major intensities at landfall

Wang

Toumi

2022

Sci Rep

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“…This can also be seen in the energy balance approaches. For example, the wind speed tendency equation of Wang and Toumi (2022b) also points to a possible universal balance of heating and dissipation with either being dominant reversing the sign. The similar correlation between the central pressure change and reciprocal size for both decaying and intensifying TCs suggests that the geometric core size effect is one of the fundamental properties controlling rates of intensity change.…”

Section: Discussionmentioning

confidence: 99%

“…Montgomery et al. (2001) and Wang and Toumi (2022b) propose turbulent frictional decay as an important driver, but the effect of size is not considered.…”

Section: Introductionmentioning

confidence: 99%

The Dependence of Tropical Cyclone Pressure Tendency on Size

Sparks

Toumi

2022

Geophysical Research Letters

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Current theories of tropical cyclone (TC) intensification give little direct indication of the role of the TC size in intensity changes, although there are observations showing a relationship. We develop a new model of TC central pressure tendency where the pressure change can be expressed as exponential with a time constant determined by the ratio of radius maximum wind (Rmax) and the column inflow or outflow speed. An analysis of observations confirms the relationship which becomes more important for a larger pressure tendency and suggests an upper bound on pressure tendency for a given Rmax. The dependence of the pressure tendency on size poses a challenging constraint on the accurate forecasting of TCs in numerical weather prediction and climate models.

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“…• Distance to land (DTL) DTL is also an important predictor, and the intensity of TC diminishes significantly after landfall, which is well reflected in the SHAP values. The study showed that, the intensity of TCs is affected by their distance from land [45,53]. Generally, the further away a cyclone is from land, the more intense it can become.…”

Section: Explainable Analysismentioning

confidence: 98%

Probabilistic forecasting of tropical cyclones intensity using machine learning model

Meng

Yao

Wang

et al. 2023

Environ. Res. Lett.

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This study proposes a machine learning approach to probabilistic forecasting of tropical cyclone (TC) intensity. The earth system is complex and nonlinear, leading to inherent uncertainty in TC forecasting at all times, and therefore a representation of this uncertainty should be provided. Previous studies construct this uncertainty through ensemble or statistical methods, neither of which can directly characterize this uncertainty and suffer from problems such as excessive computational effort. And for this reason, we propose to assess the forecast without this uncertainty through the forecast distribution. Meanwhile, none of the previous studies on TC intensity forecasting by artificial intelligence(AI) methods characterize the uncertainty, so this study is a new supplement to data-driven TC forecasting. During the 2010-2020 evaluation period, the model’s point forecast can outperform the current state-of-the- art operational statistic-dynamical model resultsand can obtain forecast intervals to provide reliable probabilistic forecasts, which are critical for disaster warnings.

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On the intensity decay of tropical cyclones before landfall

Cited by 10 publications

References 48 publications

More tropical cyclones are striking coasts with major intensities at landfall

More tropical cyclones are striking coasts with major intensities at landfall

The Dependence of Tropical Cyclone Pressure Tendency on Size

Probabilistic forecasting of tropical cyclones intensity using machine learning model

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