Typhoon Hato Research Articles

Power source–power grid coordinated typhoon defense strategy based on multiagent dynamic game theory

A power source–power grid coordinated typhoon defense strategy is proposed in this study to minimize the cost of power grid anti-typhoon reinforcement measures and improve defense efficiency. It is based on multiagent dynamic game theory. This strategy regards a typhoon as a rational gamer that always causes the greatest damage. Together with the grid planner and black start unit (BSU) planner, it forms a multiagent defense–attack–defense dynamic game model naturally. The model is adopted to determine the optimal reinforcements for the transmission lines, black start power capacity, and location. Typhoon Hato, which struck a partial coastal area in Guangdong province in China in 2017, was adopted to formulate a step-by-step model of a typhoon attacking coastal area power systems. The results were substituted into the multiagent defense–attack–defense dynamic game model to obtain the optimal transmission line reinforcement positions, as well as optimal BSU capacity and geographic positions. An effective typhoon defense strategy and minimum load shedding were achieved, demonstrating the feasibility and correctness of the proposed strategy. The related theories and methods of this study have positive significance for the prevention of uncertain large-scale natural disasters.

Assessment of FY‐2G Atmospheric Motion Vector Data and Assimilating Impacts on Typhoon Forecasts

AbstractAtmospheric motion vectors (AMVs) have produced positive impacts on global weather forecasts, but few studies have evaluated the impacts of AMV data from the Fengyun (FY) geostationary satellite series, especially from FY‐2G and FY‐4, on typhoon forecasts in a regional model. In this study, the qualities of FY‐2G and Himawari‐8 AMV data are comparatively evaluated with several preprocesses (e.g., height assignment, quality control, channel merging, thinning, and observation error assignment) employed, and a super typhoon (Typhoon Hato, which occurred in 2017) is selected to assess the forecasting performances with the AMV data assimilated in the Weather Research and Forecasting data assimilation (WRFDA) system. The results show that the AMV data from Himawari‐8 are better overall than those from FY‐2G, with smaller RMSEs and biases for full wind speeds, and the preprocesses improve the qualities of these two geostationary satellite AMV data sets, as they both depict the same general atmospheric circulations. On the other hand, assimilation of AMV data improves the forecasts of environmental fields, resulting in the simulated track and intensity being closer to the observations. Generally, assimilating FY‐2G AMV data has comparably positive impacts with Himawari‐8 AMVs, and the AMV data retrieved from multiple channels provide even better forecasts. Experiments involving another typhoon case are also performed to further provide evidence that the derived AMV data from the Fengyun geostationary satellite series have value in the operational applications.

Periodic Cycles of Eyewall Convection Limit the Rapid Intensification of Typhoon Hato (2017)

The ability to forecast tropical cyclone (TC) intensity has improved modestly in recent years, partly because of an inadequate understanding of eyewall convection processes. Short-term periodic convection activities (period: 3–5 h) have been identified in a number of TCs, but the effect of these activities on the evolution of TC intensity at the hourly scale is yet to be fully investigated. Using radar observations and a high-resolution numerical simulation based on the Weather Research and Forecasting model, we analyzed the periodic cycles of eyewall convection associated with the intensification of Typhoon Hato (2017). Results indicate the presence of four short-term periodic cycles (period: 3–5 h) in the eyewall convection, which correspond to TC intensification. We further divided each cycle into three stages. The periodic evolution of convection inhibited the rapid intensification of the TC. The highest and lowest intensification rates were associated with the first and third stages according to the virtual potential temperature tendency in the eyewall region, respectively. Heating was dominated by the vertical advection associated with sensible heat and latent heat, which were controlled by the eyewall convection and structure. Of the three stages in each cycle, the vertical transport released the largest amount of latent heat in the first stage; consequently, the highest intensification rate occurred in this stage. In the second stage, heating was reduced because of decreased latent heat and increased cooling of sensible heat associated with vertical advection as the eyewall intensified. Vertical transport was the weakest in the third stage; this resulted in the smallest amount of heating, which limited the rapid intensification of the TC.

A high-fidelity parametric model for tropical cyclone boundary layer wind field by considering effects of land cover and terrain

The proper simulation of the tropical cyclone (TC) boundary layer wind field is essential to predict the maximum wind speed, the imposed wind loading on civil structures, and the related potential disasters. A high-fidelity parametric model is developed to produce the wind field and to study the wind characteristics of TCs in the boundary layer. This model adopts a widely used boundary layer turbulence closure scheme and is built on a terrain-following coordinate system, which can consider various land cover and terrain effects. To improve the computational efficiency, a nested grid system is adopted. The developed model is implemented to reproduce the wind fields of Hurricane Isabel (2003), Hurricane Katrina (2005), Hurricane Irene (2011), Typhoon Hagupit (2008), Typhoon Hato (2017), and Typhoon Mangkhut (2018). Different types of observation datasets are used to validate the developed model, including the Hurricane Research Division's H*Wind snapshots, the National Data Buoy Center's wind records, and several meteorological sounding stations' observations. The spatial wind fields and the wind speed time series are presented. The influence of land cover and terrain on the behavior of TC is investigated. The simulation results demonstrate the high-fidelity and computational efficiency of the developed model, implying its potential applications for TC hazard modeling.

Typhoon Hato's precipitation characteristics based on PERSIANN

Heavy precipitation induced by typhoons is the main driver of catastrophic flooding, and studying precipitation patterns is important for flood forecasting and early warning. Studying the space-time characteristics of heavy precipitation induced by typhoons requires a large range of observation data that cannot be obtained by ground-based rain gauge networks. Satellite-based estimation provides large domains of precipitation with high space-time resolution, facilitating the analysis of heavy precipitation patterns induced by typhoons. In this study, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) satellite data were used to study the temporal and spatial features of precipitation induced by Typhoon Hato, which was the strongest typhoon of 2017 to make landfall in China. The results show that rainfall on the land lasted for six days from the typhoon making landfall to disappearing, reaching the maximum when the typhoon made landfall. Hato produced extremely high accumulated rainfall in South China, almost 300 mm in Guangdong Province and Guangxi Zhuang Autonomous Region and 260 mm in Hainan Province. The rainfall process was separated into three stages and rainfall was the focus in the second stage (5 h before making landfall to 35 h after making landfall).

Comparing and Evaluating Macao Flood Prediction Models

Climate change causes extreme weather in Macao, especially typhoons and flooding. In this paper, some raw flood data is missing from the Macao Meteorological and Geophysical Bureau, due to some flood sensors that were damaged during Typhoon Hato in 2017 and Typhoon Mangkhut in 2018. So we use data interpolation to construct new datasets and curve fitting to simulate real inundation depth. Besides this, we explore Neural Network, Long Short-Term Memory, Random Forest, Adaptive Boosting, and Linear Regression for analyzing, comparing, and evaluating the best combinations of flood prediction models, datasets, and scenarios caused by typhoon presence in Macao. Furthermore, we apply Bayes Network to the aforementioned models to evaluate the accuracy of predicting flood situations because of typhoons. The experiment results show that the different models achieve a different performance in predicting specific scenarios.

Strongly Coupled Assimilation of a Hypothetical Ocean Current Observing Network within a Regional Ocean–Atmosphere Coupled Model: An OSSE Case Study of Typhoon Hato

AbstractThe forecast of tropical cyclone (TC) intensity is a significant challenge. In this study, we showcase the impact of strongly coupled data assimilation with hypothetical ocean currents on analyses and forecasts of Typhoon Hato (2017). Several observation simulation system experiments (OSSE) were undertaken with a regional coupled ocean–atmosphere model. We assimilated combinations of (or individually) a hypothetical coastal current HF radar network, a dense array of drifter floats, and minimum sea level pressure. During the assimilation, instant updates of many important atmospheric variables (winds and pressure) are achieved from the assimilation of ocean current observations using the cross-domain error covariance, significantly improving the track and intensity analysis of Typhoon Hato. Relative to a control experiment (with no assimilation), the error of minimum pressure decreased by up to 13 hPa (4 hPa/57% on average). The maximum wind speed error decreased by up to 18 kt (5 kt/41% on average) (1 kt ≈ 0.5 m s−1). By contrast, weakly coupled implementations cannot match these reductions (10% on average). Although traditional atmospheric observations were not assimilated, such improvements indicate that there is considerable potential in assimilating ocean currents from coastal HF radar and surface drifters within a strongly coupled framework for intense landfalling TCs.

Conditionally simulating nonstationary typhoon winds with time-varying coherences for long-span bridges

Typhoon winds near its external eye wall are not only strong but also nonstationary with time-varying coherences. This study proposes a conditional simulation method for multivariate nonstationary typhoon winds with time-varying coherences for long-span bridges. The Kriging method for conditional simulation and the time-varying wind spectrum and coherence are first introduced. The decomposition of the time-varying spectrum matrix is then discussed in order to obtain the time-varying correlation functions. It is found that the conventional Cholesky decomposition and the proper orthogonal decomposition (POD) are not suitable and only the square root decomposition (SRD) is appropriate for the decomposition of the spectrum matrix with time-varying coherences. Based on the field-measured nonstationary typhoon wind time histories and the time-varying spectrum and coherence models established for the Stonecutters cable-stayed bridge during Typhoon Hato, the proposed conditional simulation method is finally applied to the bridge and validated by comparing the simulated typhoon wind time histories with the measured ones as well as the unconditional simulation results. The comparative results demonstrate that the conditionally simulated wind time histories are similar to the measured ones and that the proposed conditional simulation method can be used to provide a better typhoon wind field than the unconditional simulation method.

Tropical Cyclone Research in Asia: Hong Kong and Macao

Due to climate change, the emergence of extreme weather has affected the global economic activities, human life, and the environmental sustainability. Tropical cyclones are considered as notable destructive weather systems, especially in coastal areas. This study aims to investigate the common features of the most destructive and devastating tropical cyclones in Hong Kong and Macao. A total of three representative tropical cyclones were selected for each city. The considered tropical cyclones were analyzed in terms of different attributes, including the year of occurrence, maximum wind speed, lowest pressure, total deaths, and total monetary losses. The results from the conducted analysis indicate that the costliest tropical cyclones were recorded in Hong Kong and Macao. In particular, the damages caused by typhoons Hato and Mangkhut totalled over $10 billion. Furthermore, this study discusses the need for the development of climate change mitigation strategies as well as increasing the public awareness regarding climate change and its consequences. The findings from this study can be further used by the relevant stakeholders to address the climate change effects on tropical cyclone occurrence as well as to design adaptation and resilience strategies against tropical cyclones in the forthcoming years.

Development of objective forecast guidance on tropical cyclone rapid intensity change

AbstractForecasting tropical cyclone (TC) intensity and rapid intensification (RI) are major challenges for numerical weather prediction models. In the present study, a model post‐processing technique, namely the TC intensity guidance on rapid intensification (TINT‐RI), has been developed for the western North Pacific basin (South China Sea excluded). It combines logistic regression and the naïve Bayes classifier to provide RI forecasts up to the next 48 hr. Predictors describing physical and environmental conditions are taken from the outputs of the European Centre for Medium‐Range Weather Forecasts model and the National Oceanic and Atmospheric Administration tropical cyclone heat potential field. Several observed TC characteristics such as persistence (change of past 12 hr intensity) are also included in the algorithm. To further reduce the false alarm ratio, the TINT‐RI makes reference to the intensity forecasts from a previously developed statistical‐dynamical TC intensity forecast model and the change of model vertical wind shear. Verification for TCs with RI reveals that the TINT‐RI is significantly more skilful than the direct model outputs from major global numerical weather prediction models and climatology. A case study on extreme RI of Super Typhoon Hato (1713) during its substantial intensification over the Luzon Strait before entering the northern part of the South China Sea is presented to discuss the performance of the TINT‐RI. Potential ways to improve the TINT‐RI such as using sea surface temperature and its anomaly as the oceanic predictor are discussed.

Help-seeking intention among Chinese college students exposed to a natural disaster: an application of an extended theory of planned behavior (E-TPB).

Professional mental health help-seeking is generally low among Chinese populations with mental problems, and this may also the case following natural disasters. The help-seeking intention within Chinese populations exposed to natural disaster remain unclear. This study aims to explore the intention to seek professional mental health help utilizing an extended theory of planned behavior (E-TPB) model among Chinese college students exposed to Typhoon Hato. In total, 1876 Chinese participants were recruited using convenience sampling at baseline and 817 participants (mean age = 20.9years, SD = 2.8, 28.4% male) were followed up 6months later. The online questionnaire was applied to measure six constructs including help-seeking intention, attitude, subjective norm, perceived behavioral control, self-stigma, and social stigma. Structural equation modeling showed the subjective norm (β = 0.374, p < 0.001) was the strongest predictor of help-seeking intention, followed by attitude (β = 0.271, p < 0.001) and perceived behavioral control (β = 0.213, p < 0.001), and self-stigma (β = - 0.117, p = 0.006). Unexpectedly, public stigma was not significantly associated with help-seeking intention. Moreover, multi-group analyses revealed paths of the E-TPB model were invariant across gender. These results supported the efficacy ofthe E-TPB model in explaining help-seeking intention and emphasized the importance of subjective norm (e.g., support or disproval from significant others or society) in influencing help-seeking intention among Chinese young adults exposed to a natural disaster.

Evaluation of the efficiency of the imperative ecological remediation regarding tree growth, root development, and edaphic properties after Typhoon Hato (2017) in Zhuhai, China.

Background: urban forest in coastal cities encounters multiple disturbances of frequent typhoon events caused by global change, under which ecological remediation can help to improve urban environment. We measured and analyzed the growth and ecosystem services of four newly-planted tree species in Zhuhai after Typhoon Hato (2017), aiming to evaluate the efficiency of the ecological remediation. Methods: National Meteorological Information Center of China supplied climate variables. From June 2018 to December 2019, we measured soil physical and chemical properties, above- and below-ground development regarding stem, tree height, and root growth of all the selected tree species. Results: Sl (Sterculia lanceolata Cav.), Ir (Ilex rotunda Thunb), Ss (Schima superba Gardn. et Champ.) could be more wind-resistant from the above-ground morphological perspective. For the below-ground process, Sl was the only tree species with continuous development, while Ir, Ss, and Es (Elaeocarpus sylvestris (Lour.) Poir.) decreased. Furthermore, Sl, Ir, and Ss maintained their investment in deep roots when Es had apparent deep root biomass reduction. The edaphic condition showed notable improvement in chemical properties rather than physical properties, especially for AN (available nitrogen), AK (available potassium), and SOM (soil organic matter). Conclusions: The ecological remediation in Zhuhai after Typhoon Hato (2017) was efficient, and in the future, tree species like Sl with advantages in root development and morphological profile were preferentially recommender for plantation in typhoon-affected areas.

Observational and modeling studies of oceanic responses and feedbacks to typhoons Hato and Mangkhut over the northern shelf of the South China Sea

Meteorological and oceanic responses to Typhoons Hato and Mangkhut were captured by storm-monitoring network buoys over the northern shelf of the South China Sea. With similar shelf-traversing trajectories, these two typhoons exhibited distinctly different features in storm-induced oceanic mixing and oceanic heat transfer through the air-sea interface. A well-defined cold wake was detected underneath the storm due to a rapid drop in sea surface temperature during the Hato crossing, but not during the Mangkhut crossing. Impacts of oceanic mixing on forming a storm-produced cold wake were associated with the pre-storm condition of water stratification. In addition to oceanic mixing produced through the diffusion process by shear and buoyancy turbulence productions, the short-time scale of mixing suggested convection/overturning may play a critical role in the rapid cooling at the sea surface. The importance of convection/overturning to mixing depended on the duration of atmospheric cooling above the sea surface-the longer the atmospheric cooling, the more significant effect on mixing. Including the oceanic mixed layer (OML) in the WRF model was capable of reproducing the observed storm-induced variations of wind and air pressure, but not the air and sea surface temperatures. Process-oriented numerical experiments with the OML models supported both observational and modeling findings. To simulate the storm-induced mixing in a coupled atmospheric and oceanic model, we need to improve the physics of vertical mixing with non-hydrostatic convection/overturning. Warming over the shelf is projected to have a more energetic influence on future typhoon intensities and trajectories.

Reduced gust factor for extreme tropical cyclone winds over ocean

Information of gust factor (ratio between a short-duration peak gust wind speed to a long-duration mean) for extreme winds is of paramount importance for structural design and risk assessment. However, in-situ measurements were generally made for weak winds, and observations of gust factors for 10-min mean wind speeds over 50 ​m/s have been rarely reported, especially over the ocean. On August 23, 2017, the center of Super Typhoon Hato passed directly over an offshore island named Huangmaozhou in the South China Sea. An anemometer at the weather station on the island recorded a maximum 3-s gust wind speed of 84.2 ​m/s, 1-min mean wind speed of 74.0 ​m/s, and 10-min mean wind speed of 70.9 ​m/s during the typhoon. Based on the wind records from the anemometer, the variation of the gust factor with wind speed is examined in this paper. It was observed that for 1-min mean wind speeds between 10 and 70 ​m/s, the gust factor initially increased with increasing wind speed and plateaued at wind speed between 30 and 50 ​m/s before exhibiting a decreasing trend until 70 ​m/s. The reduced gust factor at very high wind speeds over ocean was observed and reported for the first time, which may have strong implications in tropical cyclone studies and engineering applications.

Assessment of the damages and direct economic loss in Hong Kong due to Super Typhoon Mangkhut in 2018

Super Typhoon Mangkhut hit Hong Kong on September 16, 2018, necessitating the issuance of the highest tropical cyclone warning signal, No. 10 Hurricane Signal. Packing ferocious winds and record-breaking storm surge, Mangkhut brought the most serious and widespread destruction to the territory in the recent three decades. A series of post event information search, field visits and damage surveys has been conducted by the Hong Kong Observatory (HKO) and the findings on the damages and impacts caused by Mangkhut in different parts of the territory are documented in this paper. Moreover, by analyzing the economic loss data reported by various government departments, public utilities and organizations in Hong Kong and the statistics on insurance claims from the Hong Kong Federation of Insurers (HKFI), the estimated direct economic loss due to Mangkhut in Hong Kong is about HK$ 4.60 billion, which is about 3.8 times to that of Super Typhoon Hato in 2017. On the contrary, in the Guangdong-Hong Kong-Macao Greater Bay Area, the estimated direct economic loss due to Hato is significantly higher than that of Mangkhut. This could be attributed to the early and effective warnings for Mangkhut, increased public awareness and typhoon preparedness for Mangkhut in 2018 since the fierce attack of Hato in 2017, and infrastructure enhancement of the major impact areas.

Observation of Typhoon Hato based on the 356-m high meteorological gradient tower at Shenzhen

Field measurements of tropical cyclone (TC) at coastal areas are of great significance for the prevention and control of TC disasters. Despite the increasing efforts on this topic in the last years, studies based on fast-response records of TC wind at multiple heights over land are still limited. To this end, a 365 ​m high meteorological observation gradient tower at Shenzhen has been constructed and put into use since 2016. It is currently the tallest mast tower in Asia and the second tallest of this kind in the world. There are 13 levels of instruments installed in a range of 10 ​m–350 ​m on the mast, to measure various weather elements at a sampling frequency utmost to 10 ​Hz. This paper presents an observational study on the wind characteristics of Typhoon Hato which made landfall with an intensity of severe typhoon at a distance of ~90 ​km from the tower on Aug. 23, 2017. The vertical profiles of mean wind speed and typical wind turbulence quantities, i.e., gust factor, turbulence intensity, integral length scale, etc., are demonstrated and compared against provisions stipulated in wind load codes. The effects of thermal stratification on these quantities are stressed.

Super typhoons Hato and Mangkhut, part I: analysis of maximum intensity and wind structure

Super typhoons <i>Hato</i> and <i>Mangkhut</i>, part I: analysis of maximum intensity and wind structure

Super typhoons Hato and Mangkhut, part II: challenges in forecasting and early warnings

This is the second paper of a two‐part series about Super Typhoons Hato (1713) and Mangkhut (1822), which hit Hong Kong successively in 2017 and 2018, respectively, and necessitated the issuance of the highest tropical cyclone warning signal. While their maximum intensity and wind structure are analysed in Part I, this paper covers the challenges in forecasting and early warning of the storms. The actual and predicted tropical cyclone track, intensity and storm surge in Hong Kong and their associated storm surge risk are reviewed. Experience in early warning and disaster risk reduction is also shared in this paper.

Help-seeking preferences among Chinese college students exposed to a natural disaster: a person-centered approach

ABSTRACT Background Direct exposure to natural disasters is associated with increased mental disorders. Help-seeking behaviour among Chinese adults is low and the barriers and facilitators of help-seeking among Chinese adults exposed to natural disasters is understudied. Objective Using a person-centred approach, this study describes help-seeking preferences and their correlates in a sample of Chinese college students after experiencing Typhoon Hato, the strongest storm to affect Macao, China in the past 50 years. Method The baseline sample was collected one month following exposure to the Typhoon (September 2017). Six months following the baseline study (April, 2018), a total of 815 students (females = 71.5%) completed follow-up and were included in the data analysis. Latent Class Analysis (LCA) and Multinomial Logistic Regression were used to analyse the data via Mplus 7.4 and Stata 15.0. Results Three latent classes of help-seeking preferences were identified in this study, including: ‘mental health professionals and close people’ (MHPCP, 52%), non-seekers (31%), and ‘multiple sources’ (17%). The results of multinomial logistic regression showed that region of origin (mainland versus Macao, China), self-stigma, perceived helpfulness of professional mental health help, previous professional help-seeking behaviour, and perceived social support, were significantly associated with MHPCP help-seeking preferences. Conclusion A large proportion of students preferred to seek support from loved ones and professionals. However, over 30% of the sample preferred not seeking help for mental health concerns. Further research is needed to enhance mental health treatment seeking preferences among Chinese college students.

Observational study of wind characteristics from 356-meter-high Shenzhen Meteorological Tower during a severe typhoon

The characteristics of winds associated with tropical cyclones are of great significance in many engineering fields. This paper presents an investigation of wind characteristics over a coastal urban terrain based on field measurements collected from multiple cup anemometers and ultrasonic anemometers equipped at 13 height levels on a 356-m-high meteorological tower in Shenzhen during severe Typhoon Hato. Several wind quantities, including wind spectrum, gust factor, turbulence intensity and length scale as well as wind profile, are presented and discussed. Specifically, the probability distributions of fluctuating wind speeds are analyzed in connection with the normal distribution and the generalized extreme value distribution. The von Karman spectral model is found to be suitable to depict the energy distributions of three-dimensionally fluctuating winds. Gust factors, turbulence intensity and length scale are determined and discussed. Moreover, this paper presents the wind profiles measured during the typhoon, and a comparative study of the vertical distribution of wind speeds from the field measurements and existing empirical models is performed. The influences of the topography features and wind speeds on the wind profiles were investigated based on the field-measured wind records. In general, the empirical models can provide reasonable predictions for the measured wind speed profiles over a typical coastal urban area during a severe typhoon.