Typhoon Mangkhut Research Articles

New parameterization of air-sea exchange coefficients and its impact on intensity prediction under major tropical cyclones

Understanding and quantifying air-sea exchanges of enthalpy and momentum fluxes are crucial for the advanced prediction of tropical cyclone (TC) intensity. Here, we present a new parameterization of air-sea fluxes at extreme wind speeds from 40 m s−1 to 75 m s−1, which covers the range of major TCs. Our approach assumes that the TC can reach its maximum potential intensity (MPI) if there are no influences of external forces such as vertical wind shear or other environmental constraints.This method can estimate the ratio of the enthalpy and momentum exchange coefficient (Ck/Cd) under the most intense TCs without direct flux measurements. The estimation showed that Ck/Cd increases with wind speed at extreme winds above 40 m s−1. Two types of surface layer schemes of the Hurricane Weather and Research Forecast (HWRF) were designed based on the wind speed dependency of the Ck/Cd found at high winds: (i) an increase of Ck/Cd based on decreasing Cd (Cd_DC) and (ii) an increase of Ck/Cd based on increasing Ck (Ck_IC). The modified surface layer schemes were compared to the original HWRF scheme (using nearly fixed Cd and Ck at extreme winds; CTRL) through idealized experiments and real-case predictions. The idealized experiments showed that Cd_DC reduced frictional dissipation in the air-sea interface as well as significantly reduced sea surface cooling, making the TC stronger than other schemes. As a result, Cd_DC reduced the mean absolute error and negative bias by 15.0% (21.0%) and 19.1% (32.0%), respectively, for all lead times of Hurricane Irma in 2017 (Typhoon Mangkhut in 2018) compared to CTRL. This result suggests that new parameterization of Ck/Cd with decreasing Cd at high winds can help improve TC intensity prediction, which currently suffers from underestimating the intensity of the strongest TCs.

Recovery of missing field measured wind pressures on a supertall building based on correlation analysis and machine learning

In long-term field measurements and structural health monitoring (SHM), data loss sometimes occurs due to interruption of power supply, sensor failure, and disruption of data transmission, which inevitably affects subsequent data analysis and structural condition assessment. To address this issue, this paper proposes a novel data recovery method based on correlation analysis and machine learning (ML) for recovery of missing wind pressures on cladding of high-rise buildings in field measurements and SHM. The method first utilizes correlation analysis to select appropriate inputs of the ML model, and subsequently to recover the missing wind pressures using the ML model with the selected appropriate inputs. In this study, four ML models (i.e., data recovery models), including deep neural network (DNN), particle swarm optimization-DNN (PSO-DNN), extreme learning machine (ELM), and support vector regression (SVR), are developed based on the proposed data recovery method. The time series of wind pressures with non-Gaussian features, which were collected by a multi-point synchronous monitoring system on a 600-m-high skyscraper during Super Typhoon Mangkhut, are employed to validate the performance of the developed data recovery models. The results show that all the four ML models perform satisfactorily in the recovery of the missing time series of wind pressures, among which the PSO-DNN model performs best and has good recovery accuracy for data loss that occurs in different areas of building cladding. This demonstrates that the proposed data recovery method based on correlation analysis and machine learning is a reliable and effective tool to recover the missing time series of wind pressures on high-rise buildings under severe wind conditions. Notably, this is the first attempt based on field measurements to recover the missing time series of wind pressures with non-Gaussian characteristics on a skyscraper during an extreme typhoon event, which aims to provide a useful means for the recovery of missing monitoring data in field measurements and SHM.

Observed Impact of Typhoon Mangkhut (2018) on a Continental Slope in the South China Sea

AbstractMooring observations of nearly the full water column on the continental slope in the South China Sea revealed the ocean's response to Typhoon Mangkhut (2018). Mangkhut induced sea surface cooling ∼4°C that was biased to the right side of its track, which recovered with an e‐folding time after approximately 1 week. Mangkhut was a relatively fast‐moving typhoon and caused a fast near‐inertial response throughout the entire depth in its lee. The typhoon‐induced upper ocean (deep‐water) near‐inertial current velocities were >1.5 m/s (∼0.08 m/s), with an e‐folding time of approximately a week (2 weeks) and frequency of 1.04f (1.08f, where f is the local inertial frequency). The near‐inertial currents were near‐circular polarized in the upper ocean and near‐rectilinear polarized with the main axis in the across‐slope direction in deep water. The deep‐water near‐inertial waves amplified the vertical excursions of isotherms from ∼120 to ∼200 m, reduced the stratification, elevated vertical current shears, and enhanced turbulent dissipation rate, especially during 14–17 September when the effects of near‐inertial waves and diurnal spring tides overlapped. A net cooling ∼0.15°C and salinity increase ∼0.05 psu were observed in the deep ocean after Mangkhut. Typhoon‐induced near‐inertial waves may further contribute to the intensification of southwestward along‐slope mean near‐bottom currents. This study indicates the immediate influence of typhoon in deep‐water through near‐inertial waves and their contribution to the bottom mixing on the continental slope.

An All-Sky Scattering Index Derived from Microwave Sounding Data at Dual Oxygen Absorption Bands

Combining the temperature sounding channels near 118 GHz onboard Fengyun-3D (FY-3D) with channels near 50 GHz makes it possible to obtain the spatial and vertical distributions of the clouds through a cloud emission and scattering index (CESI). Previous research has shown its advantages in cloud detection over oceans. In this study, the CESI method is expanded and validated under different surface conditions, and angular corrections are conducted to remove the effect of viewing angles. The landfall process of Typhoon MANGKHUT and a case over special terrain are chosen to investigate its sensitivities to different surface types. It is found that the cloud spatial distribution is well demonstrated in both of the cases. Moreover, the CESI vertical distributions are compared with the Global Precipitation Measurement (GPM) hydrometeor profiles. The results show that CESIs are highly related to the GPM hydrometeor profiles in all of the conditions, and the correlations with the sea surface vary with the weighting functions of the matched channels, while the phenomenon is not obvious for the land surface. In addition, the validation results show that the new threshold combination for different surface types at different heights can be more effective for cloud identification. The probability density distribution for most of the channels of the screened-out clear sky data approximates a Gaussian distribution well, and these radiances can be well assimilated into the numerical weather prediction models.

Multi-scale Incremental Analysis Update Scheme and Its Application to Typhoon Mangkhut (2018) Prediction

Multi-scale Incremental Analysis Update Scheme and Its Application to Typhoon Mangkhut (2018) Prediction

Comparative study between field measurements of wind pressures on a 600-m-high skyscraper during Super Typhoon Mangkhut and wind tunnel test

Wind pressures on cladding of a 600-m-high skyscraper during Super Typhoon Mangkhut were monitored by a synchronous monitoring system including 48 pressure transducers. Then, simultaneous wind pressure measurements on a 1:500 scale model of the skyscraper were conducted in wind tunnel test. The field measurements of wind pressures are further analyzed to investigate the wind pressure characteristics on the skyscraper under extreme windstorm condition and utilized to validate the wind tunnel test results. The full-scale and model-scale wind pressure coefficients (mean, root mean square, maximum and minimum) are compared with each other and analyzed in detail. Moreover, to explore the deviations between the full-scale and model-scale results, the Reynolds number effect (5.5 × 104 to 1.8 × 108) on the wind pressure coefficients, probability distributions, power spectral densities, spatial correlations and coherences of wind pressures are investigated. The comparative study shows that the wind tunnel test can reproduce the wind pressures on the windward face. While for the other faces, the results from the wind tunnel test generally deviate from those from the field measurements. The reasons that caused the discrepancies, especially the Reynolds number effect, are discussed. The objectives of this paper are to examine the accuracy of wind tunnel testing for predicting wind pressures on high-rise buildings under severe wind condition and enhance the understanding of wind pressures on high-rise buildings during strong windstorms, and therefore provide useful information for the wind-resistant design of skyscrapers.

An Improved Sea Spray-Induced Heat Flux Algorithm and Its Application in the Case Study of Typhoon Mangkhut (2018)

The prediction of tropical cyclone (TC) intensity has been a lasting challenge. Numerical models often underestimate the intensity of strong TCs. Accurately describing the air–sea heat flux is essential for improving the simulation of TCs. It is widely accepted that sea spray has a nonnegligible effect on the heat transfer between the atmosphere and the ocean. However, the commonly used sea spray-induced heat flux algorithms have poor applicability under high wind speeds, and it is difficult to apply these algorithms to models to forecast TCs. In this study, we proposed an improved sea spray-induced heat flux algorithm based on the FASTEX dataset. This improved algorithm performs much better under high wind speed conditions than the commonly used algorithms and can be used in a coupled numerical model. The addition of sea spray-induced heat fluxes noticeably enhances the total air–sea heat fluxes and allows more energy to be transferred from the ocean to the lower atmosphere. In the simulation of TCs, the addition of sea spray-induced heat fluxes significantly improves the simulation of TC intensity and makes the low-pressure structure and wind field structure more fully developed in the horizontal direction.

Observed near-inertial waves and shears east of Luzon during Typhoons Mangkhut and Yutu in 2018

Based on acoustic Doppler current profiler observations from three moorings along the 18° N latitude line east of Luzon (at 122.7° E, 123° E, and 123.3° E), the characteristics, vertical propagation, modes, and shear properties of the near-inertial waves (NIWs) induced by Typhoon Mangkhut and Typhoon Yutu in 2018 were investigated. Energetic NIW events were generated that dominated ocean currents after the passage of the typhoons. The wavenumber–frequency spectra and downward/upward current decomposition demonstrated that the near-inertial currents rotated clockwise and mainly propagated downward energy in the Northern Hemisphere. The estimated phase velocities and vertical wavelengths were 4.9–9.4 m/h and 155–376 m, respectively. The NIWs at the three moorings showed red-shifted frequencies in the upper ocean but blue-shifted frequencies in the deep ocean, which were affected by background vorticity. Vertical mode analysis showed that the near-inertial kinetic energy (NIKE) was dominated by the third, fourth, and fifth higher modes above 400 m and by the first, second, and third lower modes below 400 m. The translation speeds of Typhoons Mangkhut (29 km/h) and Yutu (24 km/h) exceeded the critical value (14.4 km/h). Since the intensity of NIWs decreases with an increase in typhoon translation speed, the maximum NIKE caused by Typhoon Yutu was higher than that caused by Typhoon Mangkhut because of the lower translation speed of Typhoon Yutu. However, the NIKE caused by Typhoon Mangkhut propagated vertically into a deeper layer than that caused by Typhoon Yutu. The strong anticyclonic eddy near the moorings during the period of Typhoon Mangkhut played a more important role in the vertical propagation of NIKE than the weaker anticyclonic eddy during the period of Typhoon Yutu. This study shows the significant contribution of NIWs to shear. NIW-induced near-inertial shear was significantly enhanced after the two typhoons passed, with contributions of more than 50%. Although NIW-induced shear appeared to be stronger during the typhoons, no strong shear instabilities or turbulent mixing were observed.

Coastal Protection by Planted Mangrove Forest during Typhoon Mangkhut

Mangroves provide many ecosystem services, including coastal protection against storm surges and waves. As an adaptive method for coastal defense, mangroves were widely restored and planted in tropical and subtropical regions, such as the coastal regions in Southeast Asia. Field surveys were conducted to quantify the nature-based coastal protection provided by a planted mangrove forest along the coasts of Shanwei, Guangdong Province, China, under typhoon influence. The resilience of mangrove trees was assessed under the impact of Typhoon Mangkhut (2018), which induced a maximum storm surge of 1.74 m with a maximum wave height of 1.16 m in the study area. The pre- and post-typhoon surveys and hydrodynamic measurements were conducted at a mudflat with planted mangroves. The wave height reduction reached 77% over 100 m wide mangrove forest. Our results suggest that a six-year-old planted mangrove forest with a ~100 m width might withstand a super typhoon impact and provide substantial protection for the fish ponds and embankments behind the mangrove forest. No uproots or deadly breakage of stems were observed in the mangrove forest, while severe defoliation was spotted for a small portion of trees in the study area, mainly along the wind path, the windward edge of the forest, and among the taller plants. Obvious sedimentation in the mangrove front and the tidal flat was observed during the typhoon Mangkhut (2018) and the entire typhoon season of 2018.

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.

Association between awareness of vulnerability and disaster preparedness in an infrastructure-resilient city: a population-based study

ObjectivesFactors associated with an individual's awareness of vulnerability can be modified by the infrastructure of a city. These factors may impact disaster preparedness among local populations in an infrastructure-resilient city, which further influences the health risks of various population subgroups. Study designThis was a population-based study. MethodsFour population subgroups, which have previously been reported to be related to awareness of vulnerability (i.e. past experiences, sociodemographic deprivation, poor housing conditions and family medical needs), were analysed for their impacts on disaster preparedness. Validated population-based phone interviews (n = 856) were conducted in Hong Kong. Three types of disaster preparedness were studied: (1) physical preparedness; (2) social preparedness; and (3) education preparedness. ResultsPrevious experience of social hazards, accidental hazards and epidemics increased disaster preparedness among the local population. Specifically, experiences of accidental hazards and social hazards were positively associated with physical preparedness (odds ratios 1.626, 95% confidence interval [95% CI] 1.215, 2.172) and 1.501 [95% CI 1.114, 2.024], respectively). However, experiences of natural hazards did not increase preparedness, even in Hong Kong, which is a city with high ‘disaster resilience’ because of its well-developed infrastructure. Moreover, individuals with a low educational level or low income had lower education preparedness, unmarried individuals had lower social preparedness, and poor housing conditions of non-private-housing households had negative associations with education preparedness. These findings partially align with local disaster responses to the 2018 Typhoon Mangkhut, the 2019 social unrest and the 2020 COVID-19 pandemic, all of which were observed after the 2018 survey reported in this study. ConclusionsSocial and environmental interventions should be targeted to marginalised subpopulations through location-based community strategies to encourage increased environmental knowledge and participation in disaster preparedness activities.

Effect of time-variant structural modal parameters on accurate estimation of wind-induced dynamic responses of high-rise buildings during typhoons

Structural modal parameters of high-rise buildings during severe winds generally exhibit time-variant features, which conflicts with the assumption adopted in the wind-resistant design procedure that the modal parameters are time-invariant values. This may lead to inaccurate estimation of wind-induced structural dynamic responses, thus deteriorating the reliability of structural design of high-rise buildings. To address this issue, this paper first evaluates the time-variant modal parameters of a 600-m-high skyscraper based on building accelerations measured during Super Typhoon Mangkhut. Then, the identified time-variant modal parameters are combined with the wind loads estimated from wind tunnel test on a 1:500 scaled model of the skyscraper to reproduce the typhoon-induced building accelerations. The results show that the reproduced accelerations based on the time-variant modal parameters agree well with the field-measured ones. Moreover, a comparative study between adoption of the time-variant modal parameters and time-invariant modal parameters is conducted, which shows that the former case provides more accurate estimation of the building dynamic responses during the extreme typhoon event. This paper aims to explore an effective means for precise evaluation of typhoon-induced dynamic responses of high-rise buildings.

Vulnerability to typhoons: A comparison of consequence and driving factors between Typhoon Hato (2017) and Typhoon Mangkhut (2018)

Typhoon disasters have caused casualties, property loss, and other negative impacts to social and economic development. Vulnerability is an important component of typhoon risk. However, little is known about the contributions of vulnerability factors and their interaction effects on typhoon-induced losses at a fine scale. Focusing on the vulnerability measures of Typhoon Hato in 2017 and Typhoon Mangkhut in 2018, this study aims to quantify the contribution and interactive effects of physical and socioeconomic factors on vulnerability based on the GeoDetector method and determine the factors that account for most of the change in vulnerability. The results show that from Typhoon Hato in 2017 to Typhoon Mangkhut in 2018, the vulnerability of the economy and houses decrease on average. Rain intensity and wind intensity are the dominant factors of disaster loss for Typhoon Hato and Typhoon Mangkhut, respectively. Vegetation cover and landform explain vulnerability better than average slope in most instances. For different loss types, the dominant socioeconomic vulnerability factor is different. For both typhoons, emergency transfer has a higher determining power (q) ranking for the population vulnerability, while the percentage of the GDP made up of primary industry have higher q ranking for economic vulnerability. The dominant interaction effects between two vulnerability factors differ depending on the typhoon and loss type but show a nonlinear enhancement effect in most cases. Moreover, changes in the maximum 4-hour accumulated rainfall account for most of the change in vulnerability between Hato and Mangkhut. Overall, the results can be conducive to understanding the complexity of vulnerability to typhoons and provide a reference for possible indicators for vulnerability assessment models, and determining the reasons for changes in vulnerability can be constructive to the formulation of specific policies for disaster prevention and mitigation.

Variations of Raindrop Size Distribution and Radar Retrieval in Outer Rainbands of Typhoon Mangkhut (2018)

Variations of Raindrop Size Distribution and Radar Retrieval in Outer Rainbands of Typhoon Mangkhut (2018)

Field measurement and wind tunnel experimental investigation of a supertall building with closely spaced modes under typhoon Mangkhut

This paper presents the analysis of full-scale measurement of the Leatop Plaza (303 m) under a super typhoon (i.e., Mangkhut), during which field data such as wind speed, wind direction, and wind-excited structural response were recorded. The modal properties, e.g., natural frequency, damping ratios, of the building at consecutive short time windows are identified using a Bayesian frequency domain approach, which provides information on the most probable value and identification (estimation) uncertainty. Time-varying and amplitude-dependent features of natural frequencies and damping ratios are investigated, taking into account identification uncertainty. The power spectral density of modal wind load identified from field data also provides an opportunity for benchmarking with the prediction from wind tunnel tests developed at the design stage. As Leatop Plaza has similar stiffness and mass properties along the two horizontal directions, the frequencies of corresponding vibration modes are very similar, which inevitably poses a challenge to modal identification. Issues associated with closely spaced modes are highlighted and further studied via a recently developed theory of achievable precision of ambient modal identification.

Accurate Measurement and Assessment of Typhoon-Related Damage to Roadside Trees and Urban Forests Using the Unmanned Aerial Vehicle

With drastic changes to the environment arising from global warming, there has been an increase in both the frequency and intensity of typhoons in recent years. Super typhoons have caused large-scale damage to the natural ecological environment in coastal cities. The accurate assessment and monitoring of urban vegetation damage after typhoons is important, as they contribute to post-disaster recovery and resilience efforts. Hence, this study examined the application of the easy-to-use and cost-effective Unmanned Aerial Vehicle (UAV) oblique photography technology and proposed an improved detection and diagnostic measure for the assessment of street-level damage to urban vegetation caused by the super typhoon Mangkhut in Shenzhen, China. The results showed that: (1) roadside trees and artificially landscaped forests were severely damaged; however, the naturally occurring urban forest was less affected by the typhoon. (2) The vegetation height of roadside trees decreased by 20–30 m in most areas, and that of artificially landscaped forests decreased by 5–15 m; however, vegetation height in natural forest areas did not change significantly. (3) The real damage to vegetation caused by the typhoon is better reflected by measuring the change in vegetation height. Our study validates the use of UAV remote sensing to accurately measure and assess the damage caused by typhoons to roadside trees and urban forests. These findings will help city planners to design more robust urban landscapes that have greater disaster coping capabilities.

The Effect of the Water Tower of Typhoon Mangkhut (2018)

On 16 September 2018, the Yangtze River Delta (YRD) experienced heavy precipitation, with the local daily precipitation exceeding 250 mm. Using ERA5 reanalysis data and satellite observations from the GPM, we review this heavy rain event in terms of its meteorological triggers and water vapor transport. As the high-level water vapor produced by Typhoon Mangkhut continued to be transported northward, the precipitation in the YRD gradually increased, and stratus precipitation played a major role in this event. The high-level water vapor continued to be transported northward to the east of Taiwan Island without falling, so heavy precipitation did not appear to the east of Taiwan Island. In the present study, we suggest that the meteorological trigger of this event was mainly the gradual falling of ice particles moving northward from a high altitude. The high-level ice particles originated from the “water tower” at the center of Typhoon Mangkhut, which pumped low-level water vapor into the high-level water vapor. In general, the appearance of abnormal values of high-level water vapor transport is an important atmospheric disturbance related to heavy precipitation in the downstream areas of high-level wind, and the typhoon water tower can be used as an important forecast signal for long-distance heavy precipitation in China during the active typhoon period.

City-Scale Typhoon Hazard Analysis and Field Monitoring of Wind Effects on Skyscrapers during Super Typhoon Mangkhut

City-Scale Typhoon Hazard Analysis and Field Monitoring of Wind Effects on Skyscrapers during Super Typhoon Mangkhut

How Does Air‐Sea Wave Interaction Affect Tropical Cyclone Intensity? An Atmosphere‐Wave‐Ocean Coupled Model Study Based on Super Typhoon Mangkhut (2018)

AbstractCapturing TC intensity change remains a great challenge for most state‐of‐the‐art operational forecasting systems. Recent studies found TC intensity forecasts are sensitive to three‐dimensional ocean dynamics and air‐sea interface processes beneath extreme winds. By performing a series of numerical simulations based on hierarchical atmosphere‐wave‐ocean (AWO) coupling configurations, we showed how atmosphere‐ocean and atmosphere‐sea wave coupling can affect the intensity of super typhoon Mangkhut (2018). The AWO coupled model can simulate TC‐related strong winds, oceanic cold wake, and wind waves with high fidelity. With atmosphere‐ocean (AO) coupling implemented, the simulated maximum surface wind speed is reduced by 7 m s−1 compared to the atmosphere‐only run, due to TC‐induced oceanic cold wakes in the former experiment. In the fully coupled AWO simulations, the wind speed deficit can be completely compensated by the wave‐air coupling effect. Further analyses showed that, in the AWO experiment, two mechanisms contribute to the improvement of TC intensity. First, in the high wind scenario (>28 m s−1), the surface drag coefficient reaches an asymptotic level, assisting extreme wind speed to be maintained within the eyewall. Second, the wind speed distribution is modulated and becomes broader; higher wind within the TC area helps to offset the negative effect due to leveling off of the heat exchange coefficient as wind speed increases. Overall, the simulated TC in the AWO run can extract 8–9% more total heat energy from the ocean to maintain its strength, compared to that from the AO experiment.