Search Results (38)

As extreme forms of tropical cyclones (TCs), typhoons pose significant threats to both human society and the natural environment. To better understand and predict their behavior, scientists have relied on numerical simulations. Current typhoon modeling primarily falls into two categories: (1) complex simulations based on fluid dynamics and thermodynamics, and (2) empirical parameterized models. Most comparative studies on these models have focused on wind speed below 50 m/s, with fewer studies addressing high wind speed (above 50 m/s). In this study, we design and compare four different simulation approaches to model two super typhoons: Typhoon Surigae (2102) and Typhoon Nepartak (1601). These approaches include: (1) The Weather Research and Forecasting (WRF) model simulation driven by NCEP Final Operational Global Analysis data (FNL), (2) WRF simulation driven by the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA5), (3) the empirical parameterized Holland model, and (4) the empirical parameterized Jelesnianski model. The simulated wind fields were compared with the measured wind data from The Soil Moisture Active Passive (SMAP) platform, and the resulting wind fields were then used as inputs for the Simulating WAves Nearshore (SWAN) model to simulate typhoon-induced waves. Our findings are as follows: (1) for high wind speeds, the performance of the empirical models surpasses that of the WRF simulations; (2) using more accurate driving wind data improves the WRF model’s performance in simulating typhoon wind speeds, and WRF simulations excel in representing wind fields in the outer regions of the typhoon; (3) careful adjustment of the maximum wind speed radius parameter is essential for improving the accuracy of the empirical models. Full article

An atmosphere–ocean–wave coupled regional model, the UWIN-CM, began its operational trial in real time at the Hong Kong Observatory (HKO) in the second half of 2024. Its performance in the analysis of three selected tropical cyclones, Severe Tropical Storm Prapiroon, Super Typhoon Gaemi, and Super Typhoon Yagi, are studied in this paper. The forecast track and intensity of the tropical cyclones were verified against the operational analysis. It is shown that the track error of the UWIN-CM was lower than other regional numerical weather prediction (NWP) models in operation at the HKO, with a reduction in mean direct positional error of up to 50% for the first 48 forecast hours. For cyclone intensity, the performance of the UWIN-CM was the best out of the available global and regional models at HKO for Yagi at forecast hours T + 36 to T + 84 h. The model captured the rapid intensification of Yagi over the SCS with a lead time of 24 h or more. The forecast winds were compared with the in situ measurements of buoy and with the wind field analysis obtained from synthetic-aperture radar (SAR). The correlation of forecast winds with measurements from buoy and SAR ranged between 65–95% and 50–70%, respectively. The model was found to perform generally satisfactorily in the above comparisons. Full article

Super Typhoon Mujigae (2015) was simulated using the WRF-ARW model version 4.1 with the WSM3, WSM5, WSM6, and WSM7 microphysics schemes, which include 3, 5, 6, and 7 hydrometeor classes, respectively. This study investigated the species number of hydrometeors (SNHs) from simple to complex on the rapid intensification (RI) of a tropical cyclone (TC). SNHs significantly affected the distribution of hydrometeors, microphysical conversion processes (MCPs), latent heat budget, and the interaction between thermal and dynamic processes, thereby influencing the RI. Different SNHs resulted in varied MCPs and a latent heat budget. The WSM3 and WSM5 schemes share the same top three dominating MCPs: condensation of cloud water (COND), accretion of cloud water by rain (RACW), and evaporation of rain (REVP). COND, accretion of cloud water by graupel (GACR), and RACW contributed to the WSM6 scheme. The WSM7 scheme included hail, with contributions from the instantaneous melting of snow, graupel, and COND, respectively. The dominating latent cooling processes were identical, while in different orders, which were evaporation of rain (REVP), sublimation of snow (SSUB), and evaporation of cloud water (CEVP) in the WSM3 and WSM5 schemes; while CEVP, REVP, and SSUB were in the WSM6 and WSM7. The interaction between thermal and dynamic processes was ultimately responsible for the RI. The WSM6 scheme presented an excellent latent heating rate, warm-core structure, and secondary circulation, which enhanced convection and absolute angular momentum transportation, and further indicating RI. The results highlighted the importance of an adequate complexity microphysics scheme to better reproduce the RI. Full article

The current study looks at how the characteristics of Arabian Sea tropical cyclones (TCs) change over time. The results show that in the pre-monsoon (April–June) and the post-monsoon (October–December), the activity of TCs > 34 knots, including cyclonic storm (CS), severe cyclonic storm (SCS), very severe cyclonic storm (VSCS), extreme severe cyclonic storm (ESCS), and super cyclonic storm (Sup. CS), has significantly increased, while the tendency of TCs < 34 knots, depressions and deep depressions (Ds) over the Arabian Sea has only slightly increased. Most of the TC activity in the first two decades (1982–2001) over the Arabian Sea activated on the eastern side, while in the last two decades (2002–2021), there was an expansion toward the southwest region of the Arabian Sea, especially in the post-monsoon season. The composite analysis of environmental parameters over the Arabian Sea reveals that the negative anomalies of outgoing longwave radiation (OLR) and the positive anomalies of relative humidity at 500 hPa (RH–500 hPa) in the first decade (1982–1991) and the second decade (1992–2001) are more concentrated on the eastern side of the Arabian Sea, leading to increased activity for TCs. Decades three (2002–2011) and four (2012–2021) demonstrated a wide distribution of weak vertical wind shear (VWS) and strong convection (OLR and RH–500 hPa) over the Arabian Sea basin. This led to TCs occurring more frequently and stronger, especially in the post-monsoon season. SST over the Arabian Sea was sufficient for tropical storm activity (≥26.5 °C) for both typical seasons. 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

Jiangsu is a province in China and has the highest frequency of tornado occurrences. Studying the meteorological background and mechanisms of tornado formation is crucial for predicting tornado events and preventing the resulting disasters. This paper analyzed the meteorological background, instability mechanisms, and lifting conditions of the two Enhanced Fujita Scale level 2 (EF2) and above tornadoes that occurred in southern Jiangsu on 14 May 2021 (“5.14”) and 6 July 2020 (“7.06”) using ERA5 reanalysis data. Detailed analyses of the internal structure of tornado storms were conducted using Changzhou and Qingpu radar data. The results showed that (1) both tornadoes occurred in warm and moist areas ahead of upper-level troughs with significant dry air transport following the cold troughs. The continuous strengthening of low-level warm and moist advection was crucial in maintaining potential instability and triggering tornado vortices. The 14 May tornado formed within a low-level shear line and a warm area of a surface trough, while the 6 July tornado occurred at the end of a low-level jet stream, north of the eastern section of a quasi-stationary front. (2) The convective available potential energy (CAPE) and K indices for both tornado processes were very close (391 for “5.14” and 378 for “7.06”), with the lifting condensation level (LCL) near the ground. The “5.14” showed greater instability and more favorable thermodynamic conditions, with deep southwesterly jets at the mid-level shear line producing rotation under strong convergent action (convergence center value exceeding −1 $\times {10}^{-4}$${\mathrm{s}}^{-1}$). In contrast, the “7.06” was driven by super-low-level jet stream pulsations and wind direction convergence under the influence of the Meiyu Front (convergence center value exceeding −1.5 $\times {10}^{-4}$ ${\mathrm{s}}^{-1}$), resulting in intense lifting and vertical vorticity triggered by a surface convergence line. (3) The “5.14” tornado process involved a supercell storm over a surface dry line experiencing tilting due to strong vertical wind shear, which led to the formation of smaller cyclonic vortices near a hook echo that developed into a tornado. The “7.06” developed on a bow echo structure within a mesoscale convective system formed over the Meiyu Front, where dry air subsidence, entrainment, and convergence of the southeast jet stream triggered a “miniature” supercell. The relevant research results provide a reference for the prediction and early warning of tornadoes. 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

Tropical cyclones affecting Shenzhen city have shown a remarkable tendency to increase in both intensity and quantity, highlighting the urgency of accurate forecasts of storm surges and flooding for effective planning and mitigation. Utilizing satellite and field observations together with the advanced high-resolution baroclinic wave–current model (SCHISM), a comprehensive investigation aimed at storm surge and flooding in Shenzhen was conducted. Statistical work of historical tropical cyclones revealed that Shenzhen was most vulnerable to cyclones propagating from the southeast toward the northwest and passing Shenzhen down the Pearl River Estuary. Thus, a representative, i.e., super typhoon Hato (2017), was selected for further study. Validations of numerical results suggested satisfactory model performance in mapping the wave, tide, and surge processes. Remarkable differences in spatiotemporal distribution and intensity of storm surge and flooding were found along the Shenzhen coast, which was dominated by the propagation of far-field surge and tidal waves, cooperation between wind direction and coastline orientation, estuary morphology, and the land terrain. Intervention of wave–current interaction improved the simulation of the surge and flooding and triggered an earlier occurrence time of the maximum surge in specific areas. The Pearl River discharge significantly elevated the sea level height inside the estuary and contributed to a more severe surge. Given the extremely complicated river networks and huge freshwater flux of Pearl River and the increasing trend of concurrent heavy precipitation of tropical cyclones, future investigations on compound flooding were suggested. Full article

The South China Sea spans the tropics and subtropics. Tropical cyclones in the area are extremely active, due to the features of its marine environment, such as wide water-depth profile, complex topography and hydrology. The maximum wave heights along the coast of China are normally generated by typhoons. Especially in the context of global warming, extreme weather events have significantly increased in the recent years, leading to more frequent strong and super typhoons. With the development of resources and energy in China expanding into the deep sea, extreme waves have caused serious damage to sea projects, endangering people’s lives and properties. Selecting the accurate typhoon gradient model to calculate various extreme waves, including the probable maximum tropical cyclone (PMTC) wave, is of significance for the safety of marine engineering construction and disaster prevention and mitigation. In this paper, we first proposed a wind field fusion model suitable for the South China Sea by superimposing an empirical typhoon model with the background wind field, and further verified it using the measured typhoon data. Secondly, the fused wind field was used as the input wind field of the SWAN (Simulating Waves Nearshore) model, and the wave fields of typhoons “Usagi” and “Mangosteen” were used to verify the model. The relevant parameters of PMTC were calculated using the Pearson Type III frequency fitting method, while the verified SWAN model was used to calculate the probable maximum typhoon wave, and P-III frequency analysis was carried out by direction of the extrapolated result of typhoon waves to obtain the design wave elements of each return period. Finally, a model for calculating the probable maximum typhoon wave suitable for this sea area was proposed to derive the characteristic parameters and time-histories of the probable maximum typhoon wave and the wave heights and their corresponding frequencies of various extreme waves. Full article

The Northern Indian Ocean (NIO) is one of the most vulnerable coasts to tropical cyclones (TCs) and is frequently threatened by global climate change. In the year 2020, two severe cyclones formed in the NIO and devastated the Indian subcontinent. Super cyclone Amphan, which formed in the Bay of Bengal (BOB) on 15 May 2020, made landfall along the West Bengal coast with a wind speed of above 85 knots (155 km/h). The severe cyclone Nisarga formed in the Arabian Sea (ARS) on 1 June 2020 and made landfall along the Maharashtra coast with a wind speed above 60 knots (115 km/h). The present study has characterized both TCs by employing past cyclonic events (1982–2020), satellite-derived sea surface temperature (SST), wind speed and direction, rainfall dataset, and regional elevation. Long-term cyclonic occurrences revealed that the Bay of Bengal encountered a higher number of cyclones each year than the ARS. Both cyclones had different intensities when making landfall; however, the regional elevation played a significant role in controlling the cyclonic wind and associated hazards. The mountain topography on the east coast weakened the wind, while the deltas on the west coast had no control over the wind. Nisarga weakened to 30 knots (56 km/h) within 6 h from making landfall, while Amphan took 24 h to weaken to 30 knots (56 km/h). We analyzed precipitation patterns during the cyclones and concluded that Amphan had much more (1563 mm) precipitation than Nisarga (684 mm). Furthermore, the impact on land use land cover (LULC) was examined in relation to the wind field. The Amphan wind field damaged 363,837 km² of land, whereas the Nisarga wind field affected 167,230 km² of land. This research can aid in the development of effective preparedness strategies for disaster risk reduction during cyclone impacts along the coast of India. Full article

The northward typhoon configuration along the southeast coast of China (TC_N-SEC) is one of the key circulation patterns influencing the coastal cities in southeast China (CCSE). Here, we analyzed the air quality in CCSE during the high-incidence typhoon period from 2019 to 2021. Multi-source measurements were carried out to explore the impact of super typhoon 2114 ‘Chanthu’ on the air quality in CCSE. The results showed that the TC_N-SEC and its surrounding weather situation had a favorable impact on the increase in pollutant concentration in CCSE, especially on the increase in O₃ concentration. From 13 September to 17 September 2021, affected by the cyclonic shear in the south of super typhoon 2114 ‘Chanthu,’ the strong wind near the ground, stable relative humidity, strong precipitation, and the significantly reduced wind speed had a substantial effect on PM₁₀, PM_2.5, SO₂, and NO₂ concentrations. Calm and light air near the ground, weak precipitation, high daily maximum temperatures, and minimum relative humidity may provide favorable meteorological conditions for the accumulation of O₃ precursors and photochemical reactions during the day, resulting in the daily peak values of O₃ exceeding 160 μg/m³. The evolution of wind, relative humidity, and boundary layer height could play an important role in the variations in PM₁₀ and PM_2.5 concentrations by influencing pollutant accumulation or diffusion. It was suggested that the atmospheric structure of horizontal stability and vertical mixing below 1500 m could play a significant role in the accumulation and vertical distribution of ozone. The results highlight the important role of typhoons in the regional environment and provide a scientific basis for further application of multi-source observation data, as well as air pollution control. Full article

Background: This two-study paper developed a climate change risk perception model that considers the role of posttraumatic growth (i.e., a reappraisal of life priorities and deeper appreciation of life), resource loss, posttraumatic stress, coping, and social support. Method: In Study 1, participants were 332 persons in the Philippines who experienced Super Typhoon Haiyan. In Study 2, participants were 709 persons in Fiji who experienced Cyclone Winston. Climate change can increase the size and destructive potential of cyclones and typhoons as a result of warming ocean temperatures, which provides fuel for these storms. Participants completed measures assessing resource loss, posttraumatic stress, coping, social support, posttraumatic growth, and climate change risk perception. Results: Structural equation modeling was used to develop a climate change risk perception model with data collected in the Philippines and to confirm the model with data collected in Fiji. The model showed that climate change risk perception was influenced by resource loss, posttraumatic stress, coping activation, and posttraumatic growth. The model developed in the Philippines was confirmed with data collected in Fiji. Conclusions: Posttraumatic growth played a central role in climate change risk perception. Public health educational efforts should focus on vividly showing how climate change threatens life priorities and that which gives life meaning and can result in loss, stress, and hardship. Disaster response organizations may also use this approach to promote preparedness for disaster threats. Full article

Seawater inundation mapping plays a crucial role in climate change adaptation and flooding risk reduction for coastal low-lying areas. This study presents a new elevation model called the digital impermeable surface model (DISM) based on the topographical data acquired by unmanned aerial vehicle (UAVs) for improving seawater inundation mapping. The proposed DISM model, along with the bathtub model, was used to assess coastal vulnerability to flooding in significant tropical cyclone events in a low-lying region of Victoria Harbor in Hong Kong. The inundation simulations were evaluated based on the typhoon news and reports which indicated the actual storm surge flooding conditions. Our findings revealed that the proposed DISM obtains a higher accuracy than the existing digital elevation model (DEM) and the digital surface model (DSM) with a RMSE of 0.035 m. The DISM demonstrated a higher skill than the DEM and the DSM by better accounting for the water-repellent functionality of each geospatial feature and the water inflow under real-life conditions. The inundation simulations affirmed that at least 88.3% of the inundated areas could be recognized successfully in this newly-designed model. Our findings also revealed that accelerating sea level rise in Victoria Harbor may pose a flooding threat comparable to those induced by super typhoons by the end of the 21st century under two representative emission scenarios (RCP4.5 and RCP8.5). The seawater may overtop the existing protective measures and facilities, making it susceptible to flood-related hazards. Full article

Although previous studies have recorded that tropical cyclones cause a significant increase in chlorophyll a concentration (Chl-a), most of these results were only based on surface Chl-a observed by satellite data. Using satellite, reanalysis and model data, this study investigated the response of the upper ocean and sea surface Chl-a to three different levels of tropical cyclones in the South China Sea. In our results, the severe tropical storm (STS) did not cause an increase in surface Chl-a or depth-integrated Chl-a in the short term (i.e., ~2 days); the typhoon (TY) increased the surface Chl-a from 0.12 mg·m⁻³ to 0.15 mg·m⁻³ in the short term, but the depth-integrated Chl-a did not increase significantly; the super typhoon (STY) caused the surface Chl-a to increase from 0.15 mg·m⁻³ to 0.37 mg·m⁻³ in the short term, and also increased the depth-integrated Chl-a from 40.41 mg·m⁻² to 42.59 mg·m⁻². These results suggest that the increase in the surface Chl-a after TY and STY were primarily caused by physical processes (e.g., vertical mixing). However, the increase in the depth-integrated Chl-a of STY may be due to the entrainment of both nutrients and phytoplankton through upwelling and turbulent mixing under the influence of STY. Full article