Search Results (98)

Ocean forecasting is critical for various applications and is essential for understanding air–sea interactions, which contribute to mitigating the impacts of extreme events. While data-driven forecasting models have demonstrated considerable potential and speed, they often primarily focus on spatial variations while neglecting temporal dynamics. This paper presents the TSformer, a novel non-autoregressive spatio-temporal transformer designed for medium-range ocean eddy-resolving forecasting, enabling forecasts of up to 30 days in advance. We introduce an innovative hierarchical U-Net encoder–decoder architecture based on 3D Swin Transformer blocks, which extends the scope of local attention computation from spatial to spatio-temporal contexts to reduce accumulation errors. The TSformer is trained on 28 years of homogeneous, high-dimensional 3D ocean reanalysis datasets, supplemented by three 2D remote sensing datasets for surface forcing. Based on the near-real-time operational forecast results from 2023, comparative performance assessments against in situ profiles and satellite observation data indicate that the TSformer exhibits forecast performance comparable to leading numerical ocean forecasting models while being orders of magnitude faster. Unlike autoregressive models, the TSformer maintains 3D consistency in physical motion, ensuring long-term coherence and stability. Furthermore, the TSformer model, which incorporates surface auxiliary observational data, effectively simulates the vertical cooling and mixing effects induced by Super Typhoon Saola. Full article

A new quantitative precipitation estimation (QPE) method for Himawari-9 (H9) and Fengyun-4B (FY4B) satellites has been developed based on cloud top brightness temperature (TBB). The 24-hour, 6-hour, and hourly rainfall estimates of H9 and FY4B have been compared with rain gauge datasets and precipitation estimation data from the GPM IMERG V07 (IMERG) and Global Precipitation Satellite (GSMaP) products, especially based on the case study of landfalling super typhoon “Doksuri” in 2023. The results indicate that the bias-corrected QPE algorithm substantially improves precipitation estimation accuracy across multiple temporal scales and intensity categories. For extreme precipitation events (≥100 mm/day), the FY4B-based estimates exhibit markedly better performance. Furthermore, in light-to-moderate rainfall (0.1–24.9 mm/day) and heavy rain to rainstorm ranges (25.0–99.9 mm/day), its retrievals are largely comparable to those from IMERG and GSMaP, demonstrating robust consistency across varying precipitation intensities. Therefore, the new QPE retrieval algorithm in this study could largely improve the accuracy and reliability of satellite precipitation estimation for extreme weather events such as typhoons. Full article

This study aimed to compare and evaluate three satellite-based precipitation estimation products: Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Early Run (IMERG-Early Run), Climate Prediction Center MORPHing technique Real Time (CMORPH-RT), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Dynamic Infrared Rain rate Now (PDIR-Now) to identify the optimal integration strategies to improve the extreme rainfall estimation during Super Typhoon Yagi (September, 2024) in Hanoi, Vietnam, using validation data from 25 ground stations. In-depth analysis of three extreme rainfall series during Typhoon Yagi (6–9 September 2024), examining 93 extreme rainfall events at the 95th percentile precipitation threshold (R95p = 21.78 mm/h), combined with statistics at lower percentile thresholds (R1p, R5p, R10p, and R90p) and upper percentile threshold (R99p), revealed IMERG-Early best captured the peak rainfall, CMORPH-RT achieved highest total rainfall accuracy, while PDIR-Now offered the best spatial analysis. However, limitations included time lags, inability to detect rainfall events above R99p (41.69 mm/hour), and low detection rates (8–12%) in areas first impacted by the typhoon. This study identified that integration strategies combining different satellite products based on their strengths at specific time scales showed potential for improved rainfall estimation: PDIR-Now with IMERG-Early (1–3 h) and IMERG-Early with CMORPH-RT (6–12 h). These integration approaches accounted for each product’s unique capabilities in capturing different aspects of extreme rainfall during super typhoon events. Full article

The accuracy of identifying dynamic characteristics of super-tall buildings under typhoon conditions, as well as their correlation with the vibration amplitude, remains unclear, limiting the effective assessment of the structural performance and optimization of wind-resistant designs. To address this issue, the measured wind-generated vibration responses of Shanghai World Finance Center during the passage of Typhoon “Rumbia” were derived using data obtained from the health monitoring system of a super-tall building in Shanghai. The first and second inherent frequencies, as well as the damping ratio of the structure, were ascertained through the employment of the curve method and the standard deviation method. Based on this, a comparison and analysis were carried out regarding the variation patterns of the first and second inherent frequencies and the damping ratio with reference to the vibration amplitude. Vibration modes were identified using frequency domain analysis. The results of the natural frequency identification were compared to those from the Peak Picking method to see how well the curve method and the standard deviation method worked at finding modal parameters. Ultimately, an assessment of the super-tall building’s performance during the impact of the typhoon was conducted. The results demonstrate that the curve method and the standard deviation method can accurately identify the inherent frequency and damping ratio of the structure, with the curve method revealing a more pronounced regularity of the modal parameters. For the structure, in the horizontal and longitudinal directions, the first and second inherent frequencies exhibit a negative correlation with amplitude, while the damping ratio shows a positive correlation with amplitude. Moreover, as the floor level rises, the vibration modes in both directions of the structure steadily increase. During the impact of Typhoon “Rumbia”, the building’s performance complied with the requirements set by comfort standards. These analytical results not only provide valuable references for the wind-resistant design and vibration control of super-tall buildings but also offer critical support for condition assessment and damage identification within structural health monitoring systems. Full article

Flooding is among the world’s most destructive natural disasters. From 27 July to 1 August 2023, Zhuozhou City and surrounding areas in Hebei Province experienced extreme rainfall, severely impacting local food security. To swiftly map the spatial and temporal distribution of the floodwaters and assess the damage to major crops, this study proposes a water body identification method with a dual polarization band combination for synthetic-aperture radar (SAR) data to solve the differences in water body feature recognition in SAR due to different polarization modes. Based on the SAR water body extent, the flood inundation extent was mapped with GF-6 optical data. In addition, Landsat-8 data were used to generate information on significant crops in the study area, while Sentinel-2 data and the Google Earth Engine (GEE) platform were used to classify the extent of crop damage. The results indicate that the flood inundated 700.51 km², 14.10% of the study area. Approximately 40,700 hectares (ha) or 8.46% of the main crops were affected, including 33,700 ha of maize, 4300 ha of vegetables, and 2800 ha of beans. Moderate crop damage was the most widespread, affecting 37.62% of the crops, while very extreme damage was the least, affecting 5.10%. Zhuozhou City experienced the most significant impact, with 13,700 ha of crop damage, accounting for 33.70% of the total. This study provides a computational framework for rapid flood monitoring using multi-source remote sensing data, which also serves as a reference for post-disaster recovery, agricultural production, and crop risk assessment. Full article

Climate change impacts are unpredictable and can change rapidly or over time; anthropogenic stressors work synergistically to strengthen their impact on vulnerable ecosystems including in the fisheries sector. This study focused on understanding and documenting the historical occurrence of extreme climate change impacts as exemplified by super typhoon Pablo (Bopha), which wreaked havoc in Baganga, Davao Oriental, almost a decade ago. A mixed-methods approach was used, using semi-structured interviews (N = 120) and focus group discussions (FGD) with small-scale fishers in the four fishing villages to assess the impacts of climate change and their adaptation after the events occurred. Our findings indicate that the fishing villages were exposed to the same impacts of climate change or the super typhoon which destroyed their lives and livelihoods. Consequently, this affected their catch per trip and fishing operations. Moreover, due to the impact of the super typhoon, fishers in Baganga developed psychological distress and trauma (emotional 44% and physical 24%) due to the extreme event. To survive, their adaptation strategies relied on government and non-government assistance provisions and projects, e.g., planting mangrove trees, construction of a seawall with wave breakers, cash-for-work activities, and tourism, as an alternative livelihood. Moreover, our study revealed that the communities have limited knowledge about the impacts of climate change, the local government lacks clear management goals for fisheries conservation and there was widespread use of illegal fishing gear. There is a strong need to implement rules, policies, and adaptation measures to build more resilient fishing communities. Full article

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

Sedimentary records of event deposits are crucial for regional natural disaster risk assessments and hazard history reconstructions. After Super Typhoon Haiyan passed through the South China Sea in 2013, five gravity cores were collected along the typhoon path in the southern South China Sea basin (>3800 mbsl). The results showed that Super Typhoon Haiyan deposits with clear graded bedding are preserved at the top of all cores. The thickness of the typhoon layers ranges from 20 to 240 cm and is related to changes in typhoon intensity. The lack of river-connected submarine canyon systems limited the transportation of terrestrial sediments from land to sea. Super Typhoon Haiyan-induced large surface waves played an important role in carrying suspended sediment from the Philippines. The Mn-rich layers at the bottom of the typhoon layers may be related to the soil and rock composition of the Palawan region, which experienced tsunami-like storm surges caused by Super Typhoon Haiyan. These Mn-rich layers may serve as a proxy for sediment export from large-scale extreme terrigenous events. This study provides the first sedimentary record of extreme typhoon events in the deep ocean, which may shed light on reconstructing regional hazard history. 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 Ang Pagtanom og Binhi Project is a University–Community partnership and community-based participatory research project exploring the health benefits of food sovereignty practices in the Philippines. In late 2021, in the midst of data collection, Super Typhoon Odette made landfall in the Philippines causing massive environmental and structural devastation. In the aftermath of the storm, community partners in the Philippines and members of the research team in the United States shared photos, texts, and updates. These messages included descriptions of structural and environmental damage caused by the storm and stories of mutual aid efforts and actions taken by individuals and small organizations, each highlighting connections between food sovereignty efforts in the Philippines and the impacts of climate change. Due to the richness of the stories, the interconnectedness between these conversations and the research topic, and the alignment within the theoretical foundations of the project, the researchers understood that these communications should be included as data. With feedback from the Community Advisory Board, the Research and Design Team amended project protocols, research questions, and consent forms to incorporate this emergent data. This manuscript describes the process that the team undertook and some of the lessons learned by taking this approach. 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

Jeju Island, located in the northern East China Sea, is experiencing a rapid rise in water temperature due to climate change. This has led to the increased activity of subtropical species and extreme fluctuations in coastal ecosystems, such as macroalgal blooms and coral bleaching. Additionally, the region is experiencing more frequent and intense typhoons. This study investigated the green tides caused by Ulva, particularly Ulva ohnoi, a subtropical species, and the effects of typhoons on these blooms through photographic analysis of the Jeju coastline. The study area was consistently covered by Ulva species every August from 2020 to 2022. Super typhoons struck Jeju Island every September during the study period, with wind speeds exceeding 20 m/s. In 2020 and 2022, the green tides largely dissipated following the typhoons. This ironic outcome highlights how climate-driven increases in subtropical Ulva biomass are being mitigated by the increasing frequency of super typhoons. However, despite the impact of super typhoon Chanthu in September 2021, there was no significant reduction in the Ulva bloom area. This anomaly may be attributable to the dominant easterly wind system in 2021, as the study area faces east, preventing the typhoon from influencing the distribution of Ulva blooms. These findings suggest that the wind intensity and direction of annual typhoons play a critical role in determining the resolution of green tide outbreaks. Full article

Using the historical disaster records of 28 typhoons in Cangnan County since 2000, combining typhoon paths and hazard-bearing bodies data and based on the theoretical framework of climate change risk, the social and economic risks of typhoon disasters in Cangnan County with four intensity levels—severe tropical storm, typhoon, severe typhoon, and super typhoon—were quantitatively assessed. The results show that with the increase in typhoon disaster intensity, the spatial pattern of typhoon disaster hazard in Cangnan County changes from high in the west and low in the east to high in the south and low in the north. Super typhoons mainly affected Mazhan town and Dailing town in the south. The vulnerability shows an obvious upward trend. Super typhoons cause more than 40% of the population to be affected, more than 20% of direct economic losses and house collapse, and nearly 30% of crops to be affected in Cangnan County. The spatial pattern of risks that typhoon disasters have on populations, economies, crops, and houses change from low in south and high in north to high in north and south, and these risks increase gradually. The comprehensive risk of typhoon disasters is higher in the north and lower in the south, with the risk level being higher in the central and northern regions. Full article

Potential impacts of projected long-term climate change toward the end of the 21st century on rainfall and peak intensity of six super-typhoons in the western North Pacific (WNP) are assessed using a cloud-resolving model (CRM) and the pseudo-global warming (PGW) method, under two representative concentration pathway (RCP) emission scenarios of RCP4.5 and RCP8.5. Linear long-term trends in June–October are calculated from 38 Coupled Model Intercomparison Project phase 5 (CMIP5) models from 1981–2000 to 2081–2100, with warmings of about 3 °C in sea surface temperature, 4 °C in air temperature in the lower troposphere, and increases of 20% in moisture in RCP8.5. The changes in RCP4.5 are about half the amounts. For each typhoon, three experiments are carried out: a control run (CTL) using analysis data as initial and boundary conditions (IC/BCs), and two future runs with the trend added to the IC/BCs, one for RCP4.5 and the other for RCP8.5, respectively. Their results are compared for potential impacts of climate change. In future scenarios, all six typhoons produce more rain rather consistently, by around 10% in RCP4.5 and 20% in RCP8.5 inside 200–250 km from the center, with increased variability toward larger radii. Such increases are tested to be highly significant and can be largely explained by the increased moisture and water vapor convergence in future scenarios. However, using this method, the results on peak intensity are mixed and inconsistent, with the majority of cases becoming somewhat weaker in future runs. It is believed that in the procedure to determine the best initial time for CTL, which yielded the strongest TC, often within a few hPa in minimum central sea-level pressure to the best track data, an advantage was introduced to the CTL unintentionally. Once the long-term trends were added in future runs, the environment of the storm was altered and became not as favorable for subsequent intensification. Thus, the PGW approach may have some bias in assessing the peak intensity of such super-typhoon cases, and caution should be practiced. Full article