Super Typhoon Research Articles

The Hongchi landslide triggered by heavy rainfall from Super Typhoon In-Fa on 25 July 2021 in Hangzhou City, Zhejiang Province, China

The Hongchi landslide triggered by heavy rainfall from Super Typhoon In-Fa on 25 July 2021 in Hangzhou City, Zhejiang Province, China

Resiliency Among Various Businesses in the Philippines in the Context of Post-Disaster Recovery Framework

This research highlights the aspects of resiliency among business establishments in the Visayas regions that were directly affected by super typhoon Yolanda in 2013. This study employs a descriptive method to characterize resiliency factors among various businesses. A survey questionnaire was utilized to gather relevant data from the 106 business proprietors and managers. Multivariate analysis via exploratory factor analysis (EFA) was used to determine the underlying factors. In the context of the post-disaster recovery of businesses in the Visayas regions, the exploratory analysis yielded five dimensions. Based on the finding, five causal factors are significant in developing a post-disaster resiliency and recovery framework among various business types. Any business is considered resilient against any form of disaster if it has complete control of its institutional affairs and plans ahead guided by its philosophy. Futuristic planning is also necessary as it imbibes in its operational philosophy the value of foresight. Besides, every business needs to strengthen its linkages outside its operations. Hence, a resilient business considers the value of information exchange and dissemination. Thus, a business is said to be sustainable if it maintains a sound and working framework to improve an adaptive capacity for any calamity or disaster.

Increasing typhoon impact and economic losses due to anthropogenic warming in Southeast China

Despite a variety of studies on the tropical cyclone (TC) response to climate change, few of them have examined the projected damages of future TCs. Here we quantify the impact of anthropogenic warming on TC-induced damages in the late twenty-first century along the coasts of Southeast China based on convection-permitting TC simulations and machine-learning-based damage models. We found that if the area’s 10 super typhoons between 2013 and 2019 were to occur at the end of the century under the high emissions RCP8.5 scenario, they would have on average a 12% ± 4% increase in landfall intensity, 25% ± 23% increase in precipitation, and 128% ± 70% increase in economic losses, compared to historical simulations. We also found a significant increase in the full risk profile. The estimated typhoon loss with a 50-year return period for Zhejiang, Fujian, Guangdong, and Hainan (four most typhoon-prone provinces among the seven provinces in the region) would increase by 71%, 170%, 20%, and 85%, respectively, towards the end of the century even under the lower emissions RCP4.5 pathway. Our findings imply the need to design effective local hazard mitigation measures to reduce future typhoon risks.

Predicting factors influencing intention to donate for super Typhoon Odette victims: A structural equation model forest classifier approach

Super Typhoon Odette has been reported as one of the world's most devastating natural disasters in 2021. It caused massive damages and casualties in 10 out of 17 regions in the Philippines. Despite the available platforms for donation, a massive amount is still needed to help mitigate the aftermath of the typhoon. This study aimed to predict factors influencing intention to donate to Super Typhoon Odette victims that happened during the holiday season in 2021 by integrating protection motivation theory and extending the theory of planned behavior. An online self-administered survey was administered and 1031 respondents voluntarily participated. Structural Equation Modeling (SEM) and Random Forest Classifier (RFC) showed that understanding Typhoon Odette, perceived severity, and perceived vulnerability led to a very high intention to donate to Typhoon Odette victims. It was seen that when people understand how severe the natural disaster is and how vulnerable the affected area is, they would have a high intention to help through donations. This is the first study that evaluated the intention to donate to typhoon victims that happened during the 2021 holiday season. The results of this study could be utilized to promote different platforms to collect more donations for the victims of the Typhoon Odette in the Philippines. Finally, this study's new use of SEM and RFC can evaluate the intention to donate to massive natural disaster aftermath worldwide.

극한강우 발생에 따른 소규모 댐 위험도 분석

The local heavy rains that didn't happen in the past, super typhoon and local torrential rainfall, generates more rainfall than the design rainfall applied to the design of the hydraulic structure this raises the anxiety about safety from natural disasters. In this study, the risk was analyzed extreme rainfall for a small dam belonging to a relatively large-scale structure among hydraulic structures and The target of analysis is the Cheongsong pumped storage plant in Cheongsong, Gyeongsangbuk-do. In Korea, extreme rainfall occurs mainly in the Jirisan area of the south coast and the east coast area. Therefore, in this study, the extreme rainfall that occurred in the eastern coastal area near the Cheongsong pumped-water power plant was selected and used for analysis. The maximum daily rainfall since 2000 in the east coast area was Typhoon Mitag in 2019, which caused a lot of rainfall in the east coast areas such as Pohang, Yeongdeok, and Uljin. In this study, it was assumed that rainfall such as typhoon Mitak occurred in the basin of the Cheongsong pumped storage plant, and the effect of dam outflow according to power generation on the downstream area was analyzed.

Evaluation of modal properties of high-rise buildings under severe typhoon conditions using correlation function-based modal identification methods

The correlation function-based methods have been widely in the operational modal analysis of engineering structures. However, the understanding of the advantages and disadvantages of these methods for modal estimation remains limited, which may result in inappropriate settings for key parameters adopted in these methods, thereby introducing errors in modal identification. Besides, the non-stationary features of the responses of high-rise buildings under severe wind conditions are a critical factor affecting the accuracy of modal estimates. To address these issues, the performances of several widely used correlation function-based methods are investigated via numerical simulation study of a frame structure. Then, two time-frequency domain methods with obvious advantages are selected and employed to analyze the dynamic responses of a 600 m high supertall building to determine the key parameters adopted in these techniques, and further evaluate the dynamic properties of the skyscraper during two super typhoons. Based on the reliable modal estimates, the time-varying features and amplitude dependency of modal properties as well as the natural frequency-dependent feature in damping ratios are presented and discussed. This paper aims to present effective tools for modal estimation through assessing the performances of the correlation function-based methods and determining the key settings in these methods as well as reveal the dynamic characteristics of high-rise buildings under severe typhoon conditions.

Influence of radiation diurnal variation on the rapid intensification process of super Typhoon Rammasun (1409) in the South China Sea

In this study, a sensitivity experiment based on a numerical model is conducted to study the influence of the diurnal variation of radiation on the rapid intensification process of Super Typhoon Rammasun (1409) in the South China Sea. The result shows that changing the radiation process can change the onset time of the rapid intensification process of the typhoon and its maximum intensity. Vertical wind shear is a key factor in the TC rapid intensification influenced by diurnal radiation cycle, and the diurnal variation of radiation process causes obvious diurnal variation in vertical wind shear by changing the thermal difference between sea and land. The oscillation of vertical wind shear promotes the diurnal variation of the typhoon rainband, with an opposite variation trend in the control and sensitivity experiments, affecting the local convective available potential energy and inward transport of entropy and thus influencing the onset time of deep convective in the typhoon inner core region. By changing the establishment of the typhoon warm core (especially the upper-level warm core), deep convections finally affect the rapid intensification of the typhoon.

Forest Damage by Super Typhoon Rammasun and Post-Disturbance Recovery Using Landsat Imagery and the Machine-Learning Method

Typhoon Rammasun landed on the southern coastal region of Guangdong and Hainan Provinces on 18 July 2014, and is the strongest recorded typhoon since the 1970s in China. It caused enormous losses in human lives, property, and crop yields in two provinces; however, its impact on forests and subsequent recovery has not yet been assessed. Here we detected forest damage area and severity from Typhoon Rammasun using Landsat 8 OLI imagery, the Random Forest (RF) machine-learning algorithm, and univariate image differencing (UID) methods, and the controlling factors on damage severity and canopy greenness recovery were further analyzed. The accuracy evaluations against sample plot data indicated that the RF approach can more accurately detect the affected forest area and damage severity than the UID-based methods, with higher overall accuracy (94%), Kappa coefficient (0.92), and regression coefficient (R2 = 0.81; p < 0.01). The affected forest area in Guangdong and Hainan was 13,556 km2 and 3914 km2, accounting for 13.8% and 18.5% total forest area, respectively. The highest affected forest fractions reached 70% in some cities or counties. The proportions of severe damage category accounted for 20.85% and 21.31% of all affected forests in Guangdong and Hainan, respectively. Our study suggests that increasing tree density and choosing less sensitive tree species would reduce damage from typhoons in vulnerable areas such as fringe, scattered, and high-slope forests. The canopy greenness of damaged forests recovered rapidly within three months for both provinces; however, management strategies should still be applied in the severely damaged areas to sustain forest functions since the persistent forest canopy structure and biomass may require a longer time to recover.

Disturbances in the Ionosphere and Distortion of Radio Wave Characteristics That Accompanied the Super Typhoon Lekima Event of 4–12 August 2019

AbstractWe acquired measurements of four observable parameters of refracted signals received from the ionosphere (Doppler shift, Doppler spectrum, number of rays, and signal amplitude) with the oblique HF Doppler technique in the city of Harbin during the super typhoon Lekima event of 4–12 August 2019. The ionospheric response was observed by the Harbin Engineering University multifrequency multiple path coherent radio system in the People's Republic of China. The maximum distortion of radio‐wave characteristics and ionospheric disturbances were observed to occur during the day when the super typhoon Lekima energy gained a maximum value and when the super typhoon approached close to the ionospheric part of the radio‐wave propagation paths. The magnitude of the ionospheric disturbances decreased with the distance between the super typhoon and propagation path midpoints. Both aperiodic (chaotic) and quasi‐sinusoidal disturbances were observed to accompany the action of the super typhoon in the ionosphere. The action of the typhoon was often accompanied by up to ±1.5 Hz broadening of the Doppler spectra, 10–30 dBV variations in the signal amplitude, and quasi‐sinusoidal variations in the Doppler shift with 0.10‐ to 0.40‐Hz amplitudes and periods of 20–30 to 70–80 min. The quasi‐sinusoidal variations in the signal amplitude with a ∼24‐min period, T, are due to focusing and defocusing of rays by wavelike disturbances in the electron density. The periods of the quasi‐sinusoidal disturbances were observed to be ∼12–24 min. Such periods pertain to atmospheric gravity waves. The atmospheric gravity waves generated by the super typhoon gave rise to quasi‐sinusoidal variations in the electron density with relative amplitudes of ∼3%–∼19%.

Effects of Typhoon on Saltwater Intrusion in a High Discharge Estuary

AbstractSaltwater intrusion in the Changjiang Estuary occurs in winter and dry season, which may affect drinking water supply in Shanghai. An atypical saltwater intrusion event, observed under high river discharge (>20,000 m3/s) in October 2018, coincided with the passage of super typhoon Kong‐rey. The response of the estuarine salt field is reproduced here with a numerical model for analysis with a Eulerian framework. Model results show that saltwater intrusion was mainly due to the landward advection of salt (∼260 t/s), which was driven by the storm surge (∼0.4 m) and landward Ekman transport under typhoon winds. The sheared salt flux (∼145 t/s) significantly contributes to the total landward flux, especially when the surge recedes after the typhoon has passed. Northwesterly winds increased vertical shear and stratification during the event. The maximum saltwater intrusion occurred about a day after the typhoon passage, and the salinity at the freshwater reservoir intake exceeds the local drinking standard of 0.45 psu. A numerical experiment shows that if Kong‐rey had passed during spring tide, the saltwater intrusion would have been weaker due to a stronger northward transport near the coast and a landward transport in the southern channels.

Impacts of wave feedbacks and planetary boundary layer parameterization schemes on air-sea coupled simulations: A case study for Typhoon Maria in 2018

Typhoon Maria was a devastating super typhoon hitting China in 2018. We conducted five numerical experiments based on the Coupled Ocean–Atmosphere–Wave–Sediment Transport model system to explore the sensitivity of typhoon track, intensity, structure, and oceanic response to the feedbacks of ocean surface waves (particular attention was paid to wave-induced sea surface roughness [SSR]), and different planetary boundary layer (PBL) parameterization schemes. The model results were in good agreement with observations. It was found that Typhoon Maria's intensity and structure, especially the distribution of air-sea interface heat flux and the shape of the typhoon centre, were highly sensitive to the feedbacks of waves, the choices of PBL and wave-induced SSR parameterization schemes. Previous model results based only on atmospheric models have shown that typhoon simulation accuracy is very sensitive to the parameterization scheme of PBL. In this study, it was revealed that the effect of wave feedbacks on typhoon simulation results could be comparable to that of using different PBL parameterization schemes. The wave feedbacks include the modification of the SSR and the additional cooling induced by wave-enhanced ocean mixing. From the sensitivity experiments, the former was the most dominant, and its main mechanism lies in the correction of the SSR to affect the exchange coefficients of momentum and heat fluxes at the air-sea interface and ultimately the typhoon simulation results. A systematic analysis of sea temperature response during typhoon was conducted, and the response showed small difference in different experiments. This suggests that the difference in typhoon intensity and structure among the experimental simulations is not significantly related to the difference in simulated sea surface temperature, but is most likely related to the difference in momentum and heat fluxes caused by wave feedbacks and the choices of PBL and wave-induced SSR parameterization schemes. The difference of significant wave height (SWH) in experiments with different wave-induced SSR parameterization schemes reached 10% (1.5 m). The typhoon-induced sea surface height (SSH) reached 2.4 m, and the difference of SSH caused by wave feedbacks, different PBL and wave-induced SSR parameterization schemes reached 12.5%, 12.5% and 8.3%, respectively. This study has significant implication for improving the simulation accuracy of typhoon track, intensity, structure, and disasters caused by typhoons.

Classification and Estimation of Typhoon Intensity from Geostationary Meteorological Satellite Images Based on Deep Learning

In this paper, a novel typhoon intensity classification and estimation network (TICAENet) is constructed to recognize typhoon intensity. The TICAENet model is based on the LeNet-5 model, which uses weight sharing to reduce the number of training parameters, and the VGG16 model, which replaces a large convolution kernel with multiple small kernels to improve feature extraction. Satellite cloud images of typhoons over the Northwest Pacific Ocean and the South China Sea from 1995–2020 are taken as samples. The results show that the classification accuracy of this model is 10.57% higher than that of the LeNet-5 model; the classification accuracy of the TICAENet model is 97.12%, with a classification precision of 97.00% for tropical storms, severe tropical storms and super typhoons. The mean absolute error (MAE) and root mean square error (RMSE) of the samples estimation in 2019 are 4.78 m/s and 6.11 m/s, and the estimation accuracy are 18.98% and 20.65% higher than that of the statistical method, respectively. Additionally, the model takes less memory and runs faster due to the weight sharing and multiple small kernels. The results show that the proposed model performs better than other methods. In general, the proposed model can be used to accurately classify typhoon intensity and estimate the maximum wind speed by extracting features from geostationary meteorological satellite images.

Moist Static Energy and Secondary Circulation Evolution Characteristics during the Rapid Intensification of Super Typhoon Yutu (2007)

A high-resolution Weather Research and Forecasting (WRF) model is used to simulate inner-core thermodynamic (such as moist static energy) and dynamic secondary circulation structure evolutions associated with the rapid intensification (RI) of Super Typhoon Yutu (2007). The results show that the column-integrated moist static energy (MSE) and the secondary circulation strength are significantly correlated to the typhoon intensity change. A rapid increase of the MSE during the RI period is primarily attributed to inner core temperature increase, due to enhanced subsidence within the eye and strengthened convective heating along the eyewall. The column-integrated MSE budget analysis shows that its rapid increase during the RI is mainly caused by surface latent heat flux. A further diagnosis of the Sawyer–Eliassen equation shows that the rapid strengthening of the secondary circulation during RI results from both the radially expanding positive diabatic heating over the eyewall and the occurrence of a second heating center outside the eyewall. While the radially expanding eyewall heating contributes about 70% of the secondary circulation change, the outer heating contributes about 30%.

Observations of boundary layer wind and turbulence of a landfalling tropical cyclone

This study investigates the atmospheric boundary layer structure based on multiple-level tower observations with a height of 350 m during the landfall of Super Typhoon Mangkhut (2018). Results show a layer of log wind profile outside of the radius of maximum wind speed with a height of 100 m or larger. The log layer height increases with the wind speed. The height of the constant flux layer reaches ~ 300 m for 10-m wind speeds less than 13 m s−1 while this height decreases with the wind speed. Momentum fluxes and turbulent kinetic energy increase with the wind speed at all vertical levels. The drag coefficient and surface roughness length estimated at the tower location have values of 7.3 × 10–3 and 0.09 m, respectively, which are independent of wind speed. The estimated vertical eddy diffusivity and mixing length increase with height up to ~ 160 m and then slowly decrease with height. The vertical eddy diffusivity increases with the wind speed while the vertical mixing length has no dependence on the wind speed. Comparing our results with previous work indicates that the vertical eddy diffusivity is larger over land than over ocean at a given wind speed range.

A dynamic disastrous CGE model to optimize resource allocation in post-disaster economic recovery: post-typhoon in an urban agglomeration area, China

Optimizing the allocation schemes of post-disaster recovery resources can promote the sustainable development of a regional economy. However, previous studies determined the inputs and allocation schemes of recovery resources based on direct economic (DE) loss while neglecting indirect economic (IDE) loss, which restricted economic recovery. This study considered DE and IDE loss, and used a dynamic disastrous computable general equilibrium (CGE) model to simulate multiple scenarios with different inputs and allocation schemes to identify a better economic recovery strategy. Taking Super Typhoon Mangkhut’s landing in Guangdong Province in 2018 as an example, the results showed that the IDE loss had a long-term impact and dynamic accumulation without post-disaster recovery, reaching 15.25 times the DE loss by 2022. In the baseline scenario, the recovery resource inputs, including relief funds, reconstruction funds, and natural disaster commercial insurance, were limited, leading to a cumulative loss recovery rate of less than 2% in 2018–2022. According to our findings, recovery resources needed a 15-fold increase to recover to pre-disaster levels. Considering the impacts of sector connections on IDE loss, six allocation schemes were established based on DE loss, IDE loss, and industrial structure. Compared with the typical allocation scheme based on DE loss, allocating recovery resources according to the diffusion coefficient substantially improved the loss recovery rate and recovery resource utilization efficiency. The dynamic disastrous CGE model conducted multi-scenario simulations to identify the optimal recovery resource allocation scheme that supported rapid and efficient post-disaster economic recovery.

Model Simulation of Storm Surge in the Northwestern South China Sea Under the Impact of Sea Level Rise: A Case Study of Super Typhoon Rammasun (2014)

Because of global warming, the sea level is expected to continue to rise, possibly having a significant impact on the intensities and spatial distribution characteristics of coastal storm surges. In this study, we took super typhoon Rammasun (2014) as a case study and applied the SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) to simulate storm surge in the northwestern South China Sea under future sea level rise (SLR) scenarios. To improve the accuracy of storm surge hindcast, we used reconstructed wind field to drive the model in which ERA5 reanalysis data were superposed on the wind field calculated from the Holland parametric cyclone model. The results show that the storm surge hindcast was significantly improved by using this reconstructed wind forcing. 2-D and 3-D model hindcast capabilities were compared; the 3-D model reproduced the storm surge better. The regional sea level projections in 2050, 2100, 2200, and 2300 for RCP 4.5 scenarios (provided by the IPCC AR6 dataset) were superposed on the original water depth as the predicted sea levels, then those depths were used in models of storm surge in the study area under a typhoon identical to Rammasun. Model results demonstrate that storm surge peaks in most sea areas decrease nearly linearly with SLR, especially in regions of high surges.

High-resolution time-lagged ensemble prediction for landfall intensity of Super Typhoon Haiyan (2013) using a cloud-resolving model

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.

Vertical Eddy Diffusivity in the Tropical Cyclone Boundary Layer during Landfall

This study investigated surface layer turbulence characteristics and parameters using 20 Hz eddy covariance data collected from five heights with winds up to 42.27 m s−1 when Super Typhoon Maria (2018) made landfall. The dependence of these parameters including eddy diffusivities for momentum (Km) and heat (Kt), vertical mixing length (Lm), and strain rate (S) on wind speed (un), height, and radii was examined. The results show that momentum fluxes (τ), turbulent kinetic energy (TKE), and Km had a parabolic dependence on un at all five heights outside three times the RMW, the maximum of Km and S increased from the surface to a maximum value at a height of 50 m, and then decreased with greater heights. However, Km and S were nearly constant with wind and height within two to three times the RMW from the TC center before landfall. Our results also found the |τ|, TKE, and Km were larger than over oceanic areas at any given wind, and Km was about one to two orders of magnitude bigger than Kt. The turbulence characteristic and parameters’ change with height and radii from the TC center should be accounted for in sub-grid scale physical processes of momentum fluxes in numerical TC models.

Investigation of Storm Tides Induced by Super Typhoon in Macro-Tidal Hangzhou Bay

Typhoon-induced storm tides can cause serious coastal disasters and considerable economic losses. Understanding the mechanisms controlling storm surges helps the prevention of coastal disasters. Hangzhou Bay (HZB), a typical macro-tidal estuary, is located on the east coast of China, where typhoons frequently occur. The funnel-shaped topography makes this macro-tidal bay even more sensitive to storm tides. Super Typhoon Chan-hom was used as an example to study the characteristics and dynamic mechanisms of storm surges using a well-validated numerical model. The model considers the two-way coupling of waves and tides. The wind strength for the model was reconstructed using multi-source wind data and was refined by considering different rotating and moving wind fields. The Holland–Miyazaki model was used to reconstruct the local wind-field data with a good performance. The model results show that the total water level of HZB during typhoon Chan-hom was mainly dominated by tides, and the storm surge was closely related to the wind field. Surface flow was mostly influenced by winds, followed by tides. The spatial and temporal distributions of the significant wave height were controlled by the wind and local terrain. Wind stress was the largest contributor to storm surges (91%), followed by the pressure effect (15%) and the wave effect (5%). Both wind and wave-induced surges occurred during low slack waters. The tide-surge interaction changes (enhance or suppress) the surge by approximately 0.5 m during the typhoon, comprising approximately 50% of the total surge. Tides interacted with surges through various mechanisms, from the bay mouth (local acceleration and friction) to the bay head (friction and advection). The Coriolis force had a relatively minor effect. The findings of this study provide useful information for studies on sediment dynamics and coastal structures under extreme weather conditions.

Analysis on structural dynamic characteristics of integrated intelligent tower construction machine under effects of strong winds

In view of the fact that integrated intelligent tower construction machine which is designed to improve the construction efficiency and quality and operating conditions of bridge towers always withstand various wind loads (especially super typhoons or gusts) so that hidden dangers may exist in their structural safety and reliability, their structural dynamic characteristics analysis of effects of strong winds shall be an essential part in their design stage. For this purpose, Davenport wind speed spectra were used to simulate the extreme pulsating wind loads and their structural dynamic wind-induced responses were investigated by means of the finite element method (FEM) to gain the displacement and stress responses of key nodes and then determine their structural design safety. The results show that: the maximum stress and displacement occur in the upper parts of their frames; and the forces and displacement of their structural dangerous positions are within their corresponding safe ranges. Our analysis results can provide a theoretical reference for application and structural optimization of tower machine.