Search Results (44)

A two-dimensional ultrasonic anemometer was installed at a height of 20 m on a wind measurement tower in Haiyan Town, Jiangmen, to monitor flow conditions in typhoon Mangkhut (1822) before and after landfall. Mean wind speed, wind direction, turbulence intensity, gust factor, turbulence integral scale, and turbulence power spectral density were derived and analyzed before and after landing. The results show that the central wind speed time history before and after landfall exhibits significant differences, and the mean wind direction undergoes a reverse change of about 180°. The mean downwind and crosswind turbulence intensity before landing were 0.25 and 0.22, respectively, and 0.20 and 0.16 after landing. The associated mean downwind and crosswind gust factors were 1.70 and 0.61 before landing, and 1.55 and 0.46 after. These differences before and after landing are considered significant, and both turbulence intensity and gust factor showed a certain decreasing trend with the increase in wind speed. The relationship between turbulence intensity and gust factor, though somewhat scattered, was basically consistent with the commonly used Ishizaki and Choi empirical formulas. Mean streamwise and crosswind turbulence integral scales before landfall were 218 m and 100 m, respectively, and 198 m and 177 m after. They showed a weak increasing trend with increase in mean wind speed. Power spectra before and after landing were basically consistent. Comparisons with standard forms were inconclusive, though the von Karman spectrum appeared to be slightly superior to the others, particularly as the wind speed and turbulence integral scale increased. Full article

Accurate simulation of boundary layer wind field structures is essential for evaluating tropical cyclone (TC) wind hazards and supporting engineering design in coastal regions. However, existing models often assume radially symmetric and homogeneous surface conditions, leading to limited accuracy near landfall where surface roughness varies significantly. This study conducts a comprehensive evaluation of four representative TC boundary layer models of M95, K01, Y21a, and Y21b, under both idealized and real TC case conditions. The idealized experiments are used to clarify the role of vertical advection and turbulent diffusion in shaping the TC boundary layer, while the landfalling case of Typhoon Mangkhut (2018) is simulated to examine the impacts of surface roughness parameterization. Results show that Y21a, which incorporates nonlinear vertical advection, produces stronger and more realistic super-gradient phenomenon than linear models of M95 and K01. Furthermore, the model of Y21b, which accounts for spatially varying drag coefficients and using a terrain-following coordinate system, successfully reproduces the asymmetric wind patterns observed in the WRF simulations during landfall, achieving the highest correlation (R = 0.93). When the spatially varying drag coefficients incorporated into the linear models, their correlation with WRF improved markedly by about 37%. These findings highlight the necessity of incorporating nonlinear advection, dynamic turbulence, and surface heterogeneity for physically consistent TC boundary layer simulations. The results provide valuable guidance for improving parametric wind field models and enhancing TC wind hazard assessments over complex coastal terrains. Full article

With the growing demand for wind turbines in deep offshore regions, frequent typhoon disasters at sea have impeded the continued development of the wind power industry. To address the problem of typhoons destroying offshore wind power facilities, this paper investigates the aeroelastic characteristics of long flexible blades on ultra-large offshore wind turbines under typhoon loads. The WRF numerical model is employed for high-precision simulations of Typhoon Mangkhut (No. 1822). By optimizing parameterization schemes and incorporating 3DVAR data assimilation techniques, typhoon wind speed profiles in the target sea area are obtained. Based on IEA 15 MW offshore wind turbine data, 3D unsteady CFD models and full-scale finite element models of the blades are established to acquire the aerodynamic loads and structural responses of the blades in typhoon environments. The results indicate that, under extreme typhoon loads and considering wind shear and tower shadow effects, the forces near the blade root are greater; the maximum out-of-plane aerodynamic force occurs at the 14% span position of the blade at 90° azimuth, and the maximum torsional aerodynamic moment is experienced at the 26.5% span position of the blade at 270° azimuth. When the blade pitch angle and rotor yaw angle do not reach ideal states, the deflection of ultra-long flexible blades can increase by up to 3.26 times. These findings overcome the limitations of traditional uniform wind field studies and provide a theoretical basis for subsequent coping strategies for offshore blades under typhoon conditions. Full article

This study employs the storm surge numerical model originally developed for the Bohai Sea. In contrast to the previous work, the current simulation focuses on the South China Sea and severe weather events, with a case study conducted through the numerical simulation of the storm surge induced by Typhoon “Mangkhut” on 15–17 September 2018. The typhoon wind field serves as a critical forcing factor influencing simulation accuracy. Therefore, five different wind fields were employed as driving conditions: the ERA5 reanalysis wind field (EWF), the parameterized Jelesnianski (JWF) and Holland (HWF) wind fields, and two hybrid wind fields (JEWF and HEWF) combining EWF with JWF and HWF, respectively. And the adjoint data assimilation method was applied to invert a physically more consistent wind stress drag coefficient (C_D). The results indicate the model effectively reproduced this dynamic process. After assimilation, the simulated water levels showed significantly improved agreement with measurements, with errors reduced by 50% (EWF), 47% (JWF), 48% (JEWF), 26% (HWF), and 42% (HEWF), respectively. And JWF not only exhibited a smaller MAE than HWF but also yielded a more reasonable C_D, demonstrating its superior performance in this typhoon case. The hybrid strategy further reduced errors to 0.14 m, effectively mitigating the limitations of individual wind fields. This study offers a new perspective on adjoint assimilation-based numerical modeling of storm surges in the South China Sea. Full article

In the context of global climate change and accelerated urbanization, coastal cities face severe threats from storm surges, and accurately predicting coastal water level changes during storm surges has become a core technological demand for disaster prevention and reduction. Storm surges are caused by atmospheric pressure and wind conditions, and their destructive power is closely related to the morphology of the coastline. Traditional tide level prediction models often face difficulties in boundary condition parameterization. Tide level changes result from the combined effect of various complex processes. In past prediction studies, harmonic analysis and numerical simulations have dominated, each with their own limitations. Although machine learning applications in tide prediction have garnered attention, issues such as data inconsistency or missing data still exist. The physical–data fusion approach aims to overcome the limitations of single methods but still faces some challenges. This paper proposes a Deep-Numerical-Reinforcement learning fusion prediction model (DNR), which adopts ensemble learning. First, deep learning models and the numerical model Finite-Volume Coastal Ocean Model (FVCOM) are used to predict tide levels at different tide stations, and then a fusion approach based on the improved reinforcement learning model DDPG_dual is applied for model assimilation. This reinforcement learning fusion model includes a module specifically designed to handle tide extreme points. In the case of the Typhoon Mangkhut storm surge, the DNR model achieved the best results for tide level predictions at six tide stations in the South China Sea. Full article

Sea level is an important variable for studying water cycle and coastal hazards under global warming. Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) has emerged as a relatively new technique for monitoring sea level variations, leveraging signals from GNSS constellations. However, dynamic height errors, primarily caused by non-stationary sea surfaces, compromise the precision of GNSS-IR sea level retrievals and necessitate robust correction. In this study, we propose a new method to correct the dynamic height error by integrating the commonly used tidal analysis method and the cubic spline fitting method. The proposed method is applied to the GNSS-IR sea level retrievals from multiple systems and multiple frequency bands at two coastal GNSS stations, MAYG and HKQT. At MAYG, the results show that our method significantly reduces the Root Mean Square Error (RMSE) of the GNSS-IR sea level retrievals by 42.1% (11.4 cm) to 15.7 cm, performing better than the single tidal analysis method (16.5 cm) and the cubic spline fitting method (21.4 cm). At HKQT, our method improves the accuracy by 21.5% (3.1 cm) to 10.3 cm, which is still better than that of the tidal analysis method (11.3 cm) and the cubic spline fitting method (12.4 cm). Compared to the tidal analysis method and the cubic spline fitting method, our method maintains high retrieval retention while enhancing precision. The effectiveness of our method is further validated in the two storm surge events caused by Typhoon Hato and Typhoon Mangkhut in Hong Kong. Full article

Environmental load data are an essential input for the analysis of offshore wind structures in typhoon-prone marine environments. However, numerical simulations of typhoon waves lack a systematic examination of the specific influence of typhoon trajectories on the spatial evolution of wave fields. In particular, the intricate mechanisms governing wave propagation within wind farm areas remain poorly understood. This present study, drawing upon a real-world case in an offshore wind farm area in the South China Sea, employs the Finite Volume Coastal Ocean Model–Surface Wave Module (FVCOM–SWAVE) wave–current coupling model to assess the joint wind–wave distribution characteristics during 35 typhoon events. The findings reveal that typhoon wave fields exhibit a notable rightward bias. As waves approach the coast, the significant wave height decreases progressively due to wave breaking, friction, refraction, and nonlinear interactions. During the passage of typhoons Prapiroon, Hato, and Mangkhut, the significant wave height distribution in the wind farm area closely correlated with the wind speed distribution. By constructing a joint distribution function of sea wind and wave elements, the joint distribution characteristics of wind speed and significant wave height for different return periods can be obtained, providing important oceanic environmental inputs for the design analysis of offshore wind structures. Full article

The Hong Kong Observatory has been using a parametric storm surge model to forecast the rise of sea level due to the passage of tropical cyclones. This model includes an offset parameter to account for the rise in sea level due to other meteorological factors. By adding the sea level rise forecast to the astronomical tide prediction using the harmonic analysis method, coastal sea level prediction can be produced for the sites with tidal observations, which supports the high water level forecast operation and alert service for risk assessment of sea flooding in Hong Kong. The Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System, which comprises the Weather Research and Forecasting (WRF) Model and Regional Ocean Modelling System (ROMS), which in itself is coupled with wave model WaveWatch III and nearshore wave model SWAN, was tested with tropical cyclone cases where there was significant water level rise in Hong Kong. This case study includes two super typhoons, namely Hato in 2017 and Mangkhut in 2018, three cases of the combined effect of tropical cyclone and northeast monsoon, including Typhoon Kompasu in 2021, Typhoon Nesat and Severe Tropical Storm Nalgae in 2022, as well as two cases of monsoon-induced sea level anomalies in February 2022 and February 2023. This study aims to evaluate the ability of the WRF-ROMS-SWAN model to downscale the meteorological fields and the performance of the coupled models in capturing the maximum sea levels under the influence of significant weather events. The results suggested that both configurations could reproduce the sea level variations with a high coefficient of determination (R²) of around 0.9. However, the WRF-ROMS-SWAN model gave better results with a reduced RMSE in the surface wind and sea level anomaly predictions. Except for some cases where the atmospheric model has introduced errors during the downscaling of the ERA5 dataset, bias in the peak sea levels could be reduced by the WRF-ROMS-SWAN coupled model. The study result serves as one of the bases for the implementation of the three-way coupled atmosphere–ocean–wave modelling system for producing an integrated forecast of storm surge or sea level anomalies due to meteorological factors, as well as meteorological and oceanographic parameters as an upgrade to the two-way coupled Operational Marine Forecasting System in the Hong Kong Observatory. Full article

Numerical experiments using the WRF model were conducted to analyze the sensitivity of Typhoon Mangkhut intensification simulations to seven widely used planetary boundary layer (PBL) parameterization schemes, including YSU, MYJ, QNSE, MYNN2, MYNN3, ACM2, and BouLac. The results showed that all simulations generally reproduced the tropical cyclone (TC) track and intensity, with YSU, QNSE, and BouLac schemes better capturing intensification processes and closely matching observed TC intensity. In terms of surface layer parameterization, the QNSE scheme produced the highest C_k/C_d ratio, resulting in stronger TC intensity based on Emanuel’s potential intensity theory. In terms of PBL parameterization, the YSU and BouLac schemes, with the same revised MM5 surface layer scheme, simulated weaker turbulent diffusivity K_m and shallower mixing height, leading to stronger TC intensity. During the intensification period, the BouLac, YSU, and QNSE PBL schemes exhibited stronger tangential wind, radial inflow within the boundary layer, and updraft around the eye wall, consistent with TC intensity results. Both PBL and surface layer parameterization significantly influenced simulated TC intensity. The QNSE scheme, with the largest C_k/C_d ratio, and the YSU and BouLac schemes, with weaker turbulent diffusivity, generated stronger radial inflow, updraft, and warm core structures, contributing to higher storm intensity. Full article

A third-generation wave model is driven by the synthetic wind field combined with the revised Holland wind and surface wind product from the National Centers for Environmental Prediction (NCEP). The temporal and spatial characteristics of the wind waves and swell during the typhoon are studied, as well as the responses of their wave energy spectra to the source terms. The results show that the typhoon waves have a more complicated asymmetric structure than the wind field, and the maximum significant wave height is always located on the right side of the direction along which the typhoon is moving, where wind waves are dominant, due to the extended fetch. The nonlinear wave–wave interaction helps to redistribute the energy of the wind seas at a high frequency to the remotely generated swells at a low frequency, ensuring that the typhoon wave’s energy spectrum remains unimodal. This process occurs in regions without extended fetch, and a similar continued downshift in frequency as the wave–wave interaction occurs for the wind input as well when the waves outrun the typhoon, due to the nonlinear coupling between the wind and growing swells. Full article

Transportation resilience, as a component of city sustainability, plays a crucial role in the daily management and emergency response of urban road systems. With coastal cities becoming increasingly vulnerable to typhoons, rainstorms, and other disasters, it is essential to assess the resilience of urban road transportation in a refined and differentiated approach. Existing resilience assessment methods often overlook significant biases, neglecting the dynamic response of road traffic and non-stationary characteristics of traffic systems. To address these limitations, we develop a quantitative resilience assessment method for urban road transportation during rainfall that is based on the improved Resilience Triangle. The method is applied to DiDi urban traffic speed and meteorological data of Shenzhen, China, from April to September 2018, with a focus on Typhoon Mangkhut as an extreme weather case. By analyzing transportation resilience variations across road densities, road hierarchies, and rainfall scenarios, we found that road densities and rainfall intensities explain resilience variations better than road hierarchies. Specifically, as accumulative precipitation exceeds 100 mm, a substantial surge in loss of performance is observed. Typhoon rainfalls result in a greater loss in urban road traffic compared to general rainfalls. The results offer valuable insights for urban road planning, traffic emergency management, and transportation resilience construction in the face of increasingly severe weather challenges. Full article

With increasing air and sea temperatures, the thermodynamic environments over the oceans are becoming more favourable for the development of intense tropical cyclones (TCs) with rapid intensification (RI). The South China coastal region consists of highly densely populated cities, especially over the Pearl River Delta (PRD) region. Intense TCs maintaining their strength or the RI of TCs close to the coastal region can present substantial forecasting challenges and have significant potential impacts on the coastal population. This study investigates the effect of sea-surface and sub-surface temperatures and salinity on the intensification of five TCs, namely Super Typhoon Hato in 2017, Super Typhoon Mangkhut in 2018, and Typhoon Talim, Super Typhoon Saola, and Severe Typhoon Koinu in 2023, which have significantly affected the South China coastal region and triggered high TC warning signals in Hong Kong in the past few years. This analysis utilised the Hong Kong Observatory’s TC best-track and intensity data, along with sea temperature and salinity profiles generated using the China Ocean ReAnalysis version 2 (CORA2) product from the National Marine Data and Information Service of China. It was found that high sea-surface temperatures (SST) of 30 °C or above for a depth of about 20 m, low sea-surface salinity (SSS) levels of 33.8 psu or below for a depth of at least 20 m, and strong salinity stratification of at least 0.6 psu per 100 m depth might offer useful hints for predicting the RI of TCs over the western North Pacific and the South China Sea (SCS) in operational forecasting, while noting other contributing environmental factors and synoptic flow patterns conducive to RI. This study represents the first documentation of sub-surface salinity’s impact on some intense TCs traversing the SCS during 2017–2023 based on an observational study. Our aim is to supplement operational techniques for forecasting RI with some quantitative guidance based on upper-level ocean observations of temperatures and salinity, on top of well-known but more rapidly changing dynamical factors like low-level convergence, weak vertical wind shear, and upper-level divergent outflow, as forecasted with numerical weather prediction models. This study will also encourage further research to refine the analysis of quantitative contributions from different RI factors and the identification of essential features for developing AI models as one way to improve the forecasting of TC RI before the TC makes landfall near the PRD, with due consideration given to the effect of freshwater river discharge from the Pearl River. Full article

Satellite products have shown great potential in estimating torrential rainfall due to their wide and consistent global coverage. This study assessed the monitoring capabilities of satellite products for the tropical cyclone remote precipitation (TRP) over the Yangtze River Delta region (YRDR) associated with severe typhoon Khanun (2017) and super-typhoon Mangkhut (2018). The satellite products include the CPC MORPHing technique (CMORPH) data, Tropical Rainfall Measuring Mission 3B42 Version 7 (TRMM 3B42), and Integrated Multi-satellite Retrievals for the Global Precipitation Measurement Mission (GPM IMERG). Eight precision evaluation indexes and statistical methods were used to analyze and evaluate the monitoring capabilities of CMORPH, TRMM 3B42, and GPM IMERG satellite precipitation products. The results indicated that the monitoring capability of TRMM satellite precipitation products was superior in capturing the spatial distribution, and GPM products captured the temporal distributions and different category precipitation observed from gauge stations. In contrast, the CMORPH products performed moderately during two heavy rainfall events, often underestimating or overestimating precipitation amounts and inaccurately detecting precipitation peaks. Overall, the three satellite precipitation products showed low POD, high FAR, low TS, and high FBIAS for heavy rainfall events, and the differences in monitoring torrential TRP may be related to satellite retrieval algorithms. Full article

Coastal cities are increasingly vulnerable to urban storm surge hazards and the secondary hazards they cause (e.g., coastal flooding). Accurate representation of the spatio-temporal process of hazard event development is essential for effective emergency response. However, current knowledge graph representations face the challenge of integrating multi-source information with various spatial and temporal scales. To address this challenge, we propose a new information model for storm surge hazard events, involving a two-step process. First, a hazard event ontology is designed to model the components and hierarchical relationships of hazard event information. Second, we utilize multi-scale time segment integer coding and geographical coordinate subdividing grid coding to create a spatio-temporal framework, for modeling spatio-temporal features and spatio-temporal relationships. Using the 2018 typhoon Mangkhut storm surge event in Shenzhen as a case study and the hazard event information model as a schema layer, a storm surge event knowledge graph is constructed, demonstrating the integration and formal representation of heterogeneous hazard event information and enabling the fast retrieval of disasters in a given spatial or temporal range. Full article

Using the Advanced Research Weather Research and Forecasting (WRF) model, a series of numerical experiments are conducted to examine the sensitivity of the Typhoon Mangkhut intensification simulation to different air–sea flux parameterization schemes (isftcflx option), including option 0 (OPT0), option 1 (OPT1), and option 2 (OPT2). The results show that three schemes basically reproduce tropical cyclone (TC) track and intensity of observation, and the simulated exchange coefficient of three schemes is consistent with theoretical results. Using the same upper limit of $C_d$ as OPT0 and OPT2, OPT1 has much larger $C_k$ than the other two options, which leads to larger latent heat (and sensible heat) flux and produces stronger inflow (within boundary layer) and updrafts (around eyewall), and thus stronger TC intensity. Meanwhile, the results that larger $C_k/C_d$ corresponds with stronger TC in the mature stage are consistent with Emanuel’s potential intensity theory. The fact that $C_k$ in OPT1 is evidently larger than the $C_k$ from previous studies leads to produce a better TC intensity simulation. Generally, we should use more reasonable air–sea flux parameterization based on observation to improve TC intensity simulation. Full article