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  1. Free, publicly-accessible full text available June 12, 2024
  2. The accurate prediction of the weakening of landfalling tropical cyclones (TC) is of great importance to the disaster prevention but is still challenging. In this study, based on the 6-hourly TC best-track data and global reanalysis data, the relationship between the intensity change prior to landfall of TCs and the energy dissipation rate after landfall over mainland China is statistically analyzed, and the difference between East and South China is compared. Results show that TCs making landfall over East China often experienced pre-landfall weakening and usually corresponded to a rapid decay after landfall, while most TCs making landfall over South China intensified prior to landfall and weakened slowly after landfall. The key factors affecting both pre-landfall intensity change and post-landfall energy dissipation rate are quantitatively analyzed. It is found that the decreasing sea surface temperature (SST), increasing SST gradient, and increasing environmental vertical wind shear are the major factors favoring high pre-landfall weakening occurrence, leading to rapid TC weakening after landfall over East China. In South China, changes in the large-scale environmental factors are relatively small and contribute little to the post-landfall weakening rate. 
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  3. Abstract

    Accurate prediction of tropical cyclone (TC) intensity is quite challenging due to multiple competing processes among the TC internal dynamics and the environment. Most previous studies have evaluated the environmental effects on TC intensity change from both internal dynamics and external influence. This study quantifies the environmental effects on TC intensity change using a simple dynamically based dynamical system (DBDS) model recently developed. In this simple model, the environmental effects are uniquely represented by a ventilation parameterB, which can be expressed as multiplicative of individual ventilation parameters of the corresponding environmental effects. Their individual ventilation parameters imply their relative importance to the bulk environmental ventilation effect and thus to the TC intensity change. Six environmental factors known to affect TC intensity change are evaluated in the DBDS model using machine learning approaches with the best track data for TCs over the North Atlantic, central, eastern, and western North Pacific and the Statistical Hurricane Intensity Prediction Scheme (SHIPS) dataset during 1982–2021. Results show that the deep-layer vertical wind shear (VWS) is the dominant ventilation factor to reduce the intrinsic TC intensification rate or to drive the TC weakening, with its ventilation parameter ranging between 0.5 and 0.8 when environmental VWS between 200 and 850 hPa is larger than 8 m s−1. Other environmental factors are generally secondary, with their respective ventilation parameters over 0.8. An interesting result is the strong dependence of the environmental effects on the stage of TC development.

     
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  4. Abstract Previous studies have demonstrated the contribution of dissipative heating (DH) to the maximum potential intensity (MPI) of tropical cyclones (TCs). Since DH is a function of near-surface wind speed and thus TC intensity, a natural question arises as to whether DH contributes to the intensity dependence of TC potential intensification rate (PIR). To address this issue, an attempt has been made to include DH in a recently developed time-dependent theory of TC intensification. With this addition, the theory predicts a shift of the maximum PIR toward the higher intensity side, which is consistent with the intensity dependence of TC intensification rate in observed strong TCs. Since the theory without DH predicts a dependence of TC PIR on the square of the MPI, the inclusion of DH results in an even higher PIR for strong TCs. Considering the projected increase in TC MPI under global warming, the theoretical work implies that as the climate continues to warm, TCs may intensify more rapidly. This may not only make the TC intensity forecasting more difficult, but also may increase the threats of TCs to the coastal populations if TCs intensify more rapidly just before they make landfall. Significance Statement Previous studies have demonstrated that dissipative heating (DH) can significantly contribute to the maximum potential intensity (MPI) that a tropical cyclone (TC) can achieve given favorable environmental thermodynamic conditions of the atmosphere and the underlying ocean. Here we show that because DH is a function of near-surface wind speed and thus TC intensity, DH can also significantly contribute to the intensity dependence of TC potential intensification rate (PIR). This has been demonstrated by introducing DH into a recently developed time-dependent theory of TC intensification. With DH the theory predicts a shift of the maximum PIR toward the higher intensity side as observed in strong TCs. Therefore, as the climate continues to warm, TCs may intensify more rapidly and become stronger. 
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  5. Abstract The phenomenon that rapid contraction (RC) of the radius of maximum wind (RMW) could precede rapid intensification (RI) in tropical cyclones (TCs) has been found in several previous studies, but it is still unclear how frequently and to what extent RC precedes RI in rapidly intensifying and contracting TCs in observations. In this study, the statistical relationship between RMW RC and TC RI is examined based on the extended best track dataset for the North Atlantic and eastern North Pacific during 1999–2019. Results show that for more than ∼65% of available TCs, the time of the peak contraction rate precedes the time of the peak intensification rate, on average, by ∼10–15 h. With the quantitatively defined RC and RI, results show that ∼50% TCs with RC experience RI, and TCs with larger intensity and smaller RMW and embedded in more favorable environmental conditions tend to experience RI more readily following an RC. Among those TCs with RC and RI, more than ∼65% involve the onset of RC preceding the onset of RI, on average, by ∼15–25 h. The preceding time tends to be longer with lower TC intensity and larger RMW and shows weak correlations with environmental conditions. The qualitative results are insensitive to the time interval for the calculation of intensification/contraction rates and the definition of RI. The results from this study can improve our understanding of TC structure and intensity changes. 
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  6. Abstract In a recent study by Wang et al. that introduced a dynamical efficiency to the intensification potential of a tropical cyclone (TC) system, a simplified energetically based dynamical system (EBDS) model was shown to be able to capture the intensity dependence of TC potential intensification rate (PIR) in both idealized numerical simulations and observations. Although the EBDS model can capture the intensity dependence of TC intensification as in observations, a detailed evaluation has not yet been done. This study provides an evaluation of the EBDS model in reproducing the intensity-dependent feature of the observed TC PIR based on the best track data for TCs over the North Atlantic and central, eastern, and western North Pacific during 1982–2019. Results show that the theoretical PIR estimated by the EBDS model can capture basic features of the observed PIR reasonably well. The TC PIR in the best track data increases with increasing relative TC intensity [intensity normalized by its corresponding maximum potential intensity (MPI)] and reaches a maximum at an intermediate relative intensity around 0.6, and then decreases with increasing relative intensity to zero as the TC approaches its MPI, as in idealized numerical simulations. Results also show that the PIR for a given relative intensity increases with the increasing MPI and thus increasing sea surface temperature, which is also consistent with the theoretical PIR implied by the EBDS model. In addition, future directions to include environmental effects and make the EBDS model applicable to predict intensity change of real TCs are also discussed. 
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  7. In this study, the performance of three exponential decay models in estimating intensity change of tropical cyclones (TCs) after landfall over China is evaluated based on the best-track TC data during 1980–2018. Results indicate that the three models evaluated can reproduce the weakening trend of TCs after landfall, but two of them (M1 and M2) tend to overestimate TC intensity and one (M3) tends to overestimate TC intensity in the first 12 h and underestimate TC intensity afterwards. M2 has the best performance with the smallest errors among the three models within 24 h after landfall. M3 has better performance than M1 in the first 20 h after landfall, but its errors increase largely afterwards. M1 and M2 show systematic positive biases in the southeastern China likely due to the fact that they have not explicitly included any topographic effect. M3 has better performance in the southeastern China, where it was originally attempted, but shows negative biases in the eastern China. The relative contributions of different factors, including landfall intensity, translational speed, 850-hPa moist static energy, and topography, to model errors are examined based on classification analyses. Results indicate that the landfall intensity contributes about 18%, translational speed, moist static energy and topography contribute equally about 15% to the model errors. It is strongly suggested that the TC characteristics and the time-dependent decay constant determined by environmental conditions, topography and land cover properties, should be considered in a good exponential decay model of TC weakening after landfall. 
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