Widespread Damage Research Articles

Empirical hurricane fragility assessment of elevated and slab-on-grade residential houses

The widespread hurricane-induced damage to residential houses in the United States leads to severe social and economic impacts. Recent community-wide efforts by researchers within the natural hazards community to collect and curate post-hazard damage data have advanced the potential to assess structural vulnerability during extreme wind events. These efforts have led to data re-use and further analysis for detailed evaluation, allowing for the comparison of the performance of elevated versus slab-on-grade single-family residential houses during hurricanes. The empirically derived fragility functions from these damage assessment data offer a unique opportunity to evaluate the vulnerability of constructed buildings. This paper presents the development of empirical fragility functions for elevated and slab-on-grade residential houses, along with their building envelope components, when subjected to hurricane winds. It assesses the post-hurricane occupiability and the annual probability of failure for both elevated and slab-on-grade houses. Utilizing post-hurricane building performance data collected from 618 elevated and 1188 slab-on-grade single-family residential houses impacted by Hurricanes Irma and Harvey in 2017, we analyzed the relationship of damage to the estimated peak 3-sec gust wind speed at each house. The analysis yields the assignment of each house to one of five damage state categories, from which we developed the fragility functions of buildings and building components in accordance with FEMA's HAZUS Hurricane model. Results showed that the developed empirical fragility functions for building envelope components of elevated houses have a higher probability of failure compared to those installed on slab-on-grade houses. Additionally, the likelihood of elevated houses being unoccupiable after a hurricane is significantly higher than that of slab-on-grade houses in both Florida and Texas. For residential buildings constructed in the state of Florida, this study finds that elevated houses have a 39 %–74 % higher annual probability of failure due to hurricane wind compared to slab-on-grade houses for the different considered damage states.

Elucidating Factors Contributing to Dicamba Volatilization by Characterizing Chemical Speciation in Dried Dicamba-Amine Residues.

Dicamba is a semivolatile herbicide that has caused widespread unintentional damage to vegetation due to its volatilization from genetically engineered dicamba-tolerant crops. Strategies to reduce dicamba volatilization rely on the use of formulations containing amines, which deprotonate dicamba to generate a nonvolatile anion in aqueous solution. Dicamba volatilization in the field is also expected to occur after aqueous spray droplets dry to produce a residue; however, dicamba speciation in this phase is poorly understood. We applied Fourier transform infrared (FTIR) spectroscopy to evaluate dicamba protonation state in dried dicamba-amine residues. We first demonstrated that commercially relevant amines such as diglycolamine (DGA) and n,n-bis(3-aminopropyl)methylamine (BAPMA) fully deprotonated dicamba when applied at an equimolar molar ratio, while dimethylamine (DMA) allowed neutral dicamba to remain detectable, which corresponded to greater dicamba volatilization. Expanding the amines tested, we determined that dicamba speciation in the residues was unrelated to solution-phase amine pKa, but instead was affected by other amine characteristics (i.e., number of hydrogen bonding sites) that also correlated with greater dicamba volatilization. Finally, we characterized dicamba-amine residues containing an additional component (i.e., the herbicide S-metolachlor registered for use alongside dicamba) to investigate dicamba speciation in a more complex chemical environment encountered in field applications.

Optical coherence tomography angiography features in Waldenström macroglobulinemia patients without Hyperviscosity syndrome: A pilot prospective study

PurposeTo evaluate the retinal vessel density (VD) with optical coherence tomography angiography (OCTA) in asymptomatic patients affected by Waldenström macroglobulinemia (WM) without hyperviscosity syndrome (HVS) and to highlight the presence of microvascular damage in theese clinically asymptomatic WD patients. DesignProspective study. MethodsA total of 43 eyes from 43 WM patients (24 females, 19 males, mean age 55.1 ± 13.6 years) were enrolled from January 2023 to December 2023 in the Eye Clinic of the University of Naples Federico II. Along with WM patients, 40 healthy subjects (HS) (20 females, 20 males, mean age 52.3 ± 15.6 years) with a normal ophthalmic examination and no history of intraocular surgery or retinal pathologic features were included as control group All patients and controls underwent OCTA ResultsThe two groups were not significantly different for age and sex Visual acuity examination showed no statistically significant difference in BCVA between controls and patients Compared to HS, WD patients showed lower VD values in the SCP in the whole image (47.95 ± 5.17% vs. 52.99 ± 2.52 %; p < 0.001), as well as in the parafovea (53.01 ± 6.69% vs. 55.30 ± 2.61 %; p = 0.002), and fovea (21.38 ± 9.01% vs. 30.31 ± 5.84 %; p < 0.0001). On the other hand, in the DCP VD values were significantly higher in patients compared to controls in the whole image (55.82 ± 8.07% vs. 50.83 ± 5.46 %; p = 0.005), as well as in the parafovea (56.76 ± 6.26% vs. 52.59 ± 5.46 %; p = 0.0001), and fovea (38.75 ± 8.59% vs. 33.43 ± 8.68 %; p < 0.0001). ConclusionThe finding that OCTA confirmed the presence of widespread microvascular damage in WD patients clinically silent. Thus, OCTA is a safe rapid imaging technique that could represent a valid biomarker of systemic vascular dysfunction.

Temperature-based damage detection for the commissioning dataset of the MX3D Bridge

Environmental and operational variations (EOV) remain a major obstacle for the successful transfer of structural health monitoring (SHM) techniques from laboratory experiments, such as cracked beam experiments, to full-scale structures, such as long-span bridges. With evidence that timely interventions significantly increase the service-life and reduce the overall life-cycle cost of ageing infrastructure, carrying out SHM in the presence of EOV, such as temperature, is therefore of high priority within the civil engineering community. The temperature-based measurement-interpretation (TB-MI) approach was developed to monitor the thermal response of an instrumented structure and detect changes linked to damage by minimising the impact that temperature variations have on anomaly detection techniques. The iterative regression-based thermal response prediction (IRBTRP) methodology is utilised in the TB-MI approach, and is trained on the healthy condition of the bridge to predict its undamaged response to temperature fluctuations. Thermal response predictions are compared to the measured response and deviations between them are indicative of a variation in the thermal response, due to structural change such as damage. Small deviations can then be identified using anomaly detection techniques, which results in earlier damage detection than if thermal response predictions had not been used. The TB-MI approach and the IRBTRP methodology have been applied to detect damage on the MX3D Bridge, the world’s first structure produced through metal additive manufacturing (i.e. 3D printing). This study demonstrates that the use of the TB-MI approach enables earlier and more widespread damage detection amongst multiple sensor groups, compared to when no temperature effects are considered. The adoption of the TB-MI approach can therefore greatly increase the reliability of and our reliance on SHM techniques for critical infrastructure.

Toward a more resilient Thailand: Developing a machine learning-powered forest fire warning system

Forest fires in Thailand are a recurring and formidable challenge, inflicting widespread damage and ranking among the nation's most devastating natural disasters. Most detection methods are labor-intensive, lack speed for early detection, or result in high infrastructure costs. An essential approach to mitigating this issue involves establishing an efficient forest fire warning system based on amalgamating diverse available data sources and optimized algorithms. This research endeavors to develop a binary machine-learning classifier based on Thailand's forest fire occurrences from January 2019 to October 2022 using data acquired from satellite resources, including the Google Earth engine. We use four gas variables including carbon monoxide, sulfur dioxide, nitrogen dioxide, and ozone. The study explores a range of classification models, encompassing linear classifiers, gradient-boosting classifiers, and artificial neural networks. The XGBoost model is the top-performing option across various classification evaluation metrics. The model provides the accuracy of 99.6 % and ROC-AUC score of 0.939. These findings underscore the necessity for a comprehensive forest fire warning system that integrates gas measurement sensor devices and geospatial data. A feedback mechanism is also imperative to enable model retraining post-deployment, thereby diminishing reliance on geospatial attributes. Moreover, given that decision-tree-based algorithms consistently yield superior results, future research in machine learning for forest fire prediction should prioritize these approaches.

Experimentation, privilege, and difference: The politics of do‐it‐yourself urbanism

AbstractThe Canterbury Earthquake Sequence of 2010–2012 was devastating for Christchurch, New Zealand, a city built on a floodplain. The sequence resulted in widespread damage across the central business district (CBD) and residential areas. Alongside, and in contrast to, orthodox planning responses by the New Zealand Government, playful, creative, and temporary projects emerged in vacant spaces. These were designed to bring back life and energy to the city centre, and such types of activity are referred to by scholars as do‐it‐yourself (DIY) urbanism. A primary critique of DIY urbanism in the literature relates to how it has the potential to contribute to gentrification, despite its amateurish appearance and mildly subversive politics. In Christchurch, a venue built from pallets—known as the Pallet Pavilion—was constructed by an organisation known as “Gap Filler” with the help of volunteers. Gap Filler emerged after the first earthquake, inserting creative projects to bring back life and energy to the damaged CBD. By examining the Pallet Pavilion, we show that, despite its potentially gentrifying effects, DIY urbanism interventions may open up a more inclusive politics of the city. Also, and paradoxically, in the case of the Pallet Pavilion, the exercise of privilege made this inclusive politics possible.

Inhibitory Action of 1,3,5-Trihydroxybenzene on UVB-Induced NADPH Oxidase 4 through AMPK and JNK Signaling Pathways.

Specific sensitivity of the skin to ultraviolet B (UVB) rays is one of the mechanisms responsible for widespread skin damage. This study tested whether 1,3,5-trihydroxybenzene (THB), a compound abundant in marine products, might inhibit UVB radiation-induced NADPH oxidase 4 (NOX4) in both human HaCaT keratinocytes and mouse dorsal skin and explore its cytoprotective mechanism. The mechanism of action was determined using western blotting, immunocytochemistry, NADP+/NADPH assay, reactive oxygen species (ROS) detection, and cell viability assay. THB attenuated UVB-induced NOX4 expression both in vitro and in vivo, and suppressed UVB-induced ROS generation via NADP+ production, resulting in increased cell viability with decreased apoptosis. THB also reduced the expression of UVB-induced phosphorylated AMP-activated protein kinase (AMPK) and phosphorylated c-Jun N-terminal kinase (JNK). THB suppressed UVB-induced NOX4 expression and ROS generation by inhibiting AMPK and JNK signaling pathways, thereby inhibiting cellular damage. These results showed that THB could be developed as a UV protectant.

Evaluating the impact of an invasive pathogen on tree population decline: An evidence based modelling approach

An upsurge of invasive forest pathogens (IFPs) has been causing widespread damage to forest ecosystems worldwide. Modelling future forest loss caused by IFPs is challenging, as it requires a sophisticated understanding of the pathogen-hosts-surrounding interactions. We developed a complexity-appropriate model using an evidence-based approach to predict the decline of the European ash (Fraxinus excelsior L.) population caused by ash dieback (Hymenoscyphus fraxineus) in a British deciduous woodland. Our model predicts that (1) the ash population will decline by ∼26 % in the next 10 year; (2) an ±10 % relative error in mortality survey would cause a ∼8 % bias in 10-year population decline; and (3) a 5 % increase in resistant trees would save ∼3 % population over 10 years. Our research demonstrates the merit of systematic reviews in balancing model complexity against generalisation. By scaling up the methodology to other IFPs, it is possible to forecast forest health with various management scenarios.

Rare case of pulmonary syphilis

Syphilis is a well known bacterium that has a great response to antibiotic treatment. Even though it is well known it can present with a wide array of symptoms. If left untreated, Syphilis will progress through primary, secondary, latent, and tertiary stages. In Secondary Syphilis, the bacterium can become disseminated and could potentially affect any organ. In Tertiary Syphilis, the central nervous system could be affected. These issues could be very detrimental to the patient and could be debilitating. In the past 20 years there has been a slight increase in the numbers of Syphilis seen in the U.S. which could be due to increasing number of men who have sex with men and increasing HIV numbers. The case discussed below entails a young HIV positive female who fulfilled all the guideline recommendations for Pulmonary Syphilis and responded very well to treatment. Pulmonary Syphilis is rare but due to its potential to cause widespread damage, it needs to be taken into consideration whenever an immunocompromised or high-risk patient presents with positive serology, respiratory symptoms, and imaging evidence. Due to its good response to treatment, if detected early patients can be treated appropriately and effectively in a time efficient manner

Highly conductive and durable nanocomposite hard coatings of carbon fiber reinforced thermoplastic composites against lightning strikes

The growing use of thermoplastic composites (TPCs) like low-melting polyaryletherketone (LM-PAEK) matrices reinforced with unidirectional carbon fiber (CF) in aircraft structures presents a significant challenge in terms of lightning strikes and electromagnetic interference shielding during aircraft operations. This is due to the weak electrical conductivity of TPC structures, which results in widespread damage when struck by lightning. The repair and maintenance of these extended damaged sites can increase operational costs and loss of flights. Several lightning strike protection (LSP) systems have been developed and implemented to address these concerns. This study evaluated a highly conductive coating with a low filler rate for its effectiveness as an LSP solution for TPCs on exterior aircraft surfaces. The TPC panel without any coatings was first studied. Subsequently, the level of conductivity was increased by incorporating the nanoscale conductive fillers, silver-coated copper (Ag/Cu) nanoflakes, with a silver content of 20 wt.% (Ag20/Cu) and 30 wt.% (Ag30/Cu), correspondingly, into the coating at two loadings of 55 wt.% and 70 wt.% in an epoxy carrier for the surface coatings. The behavior of electrical and surface conductivity was thoroughly examined to understand the impact of Ag/Cu with a high aspect ratio and the effectiveness of the LSP solution. In addition, the spray-coated TPC panels underwent rigorous Zone 2A lightning strike testing using simulated lightning current, in agreement with the industry standard of Society of Automotive Engineers (SAE) Aerospace Recommended Practice (ARP) 5412B. Despite the higher resistance due to the lower conductive coating weight, the TPC panels with Ag30/Cu at loading of 70 wt.% achieved better results than those with Ag30/Cu at loading of 55 wt.%. This is evidenced by the minor structural delamination and CF breakage on the front surface, which proposes a new economic route for a sustainable post-processed LSP system in the aviation industry.

Synthetic Water-Gel Crystals (Orbeez Balls) as Environmentally Friendly Adsorbent for Removal of Toxic Brilliant Green Dye From Aqueous Solutions

Water pollution caused by dyes is a major threat to marine organisms. Hydrogels (decorative balls), called water-gel crystals, are widely used to treat wastewater pollution caused from toxic dyes. This study aims to remove Brilliant Green (BG), a toxic harmful pigment that can cause widespread biota and environmental damage, from the aqueous solution. Water-Gel Crystals efficiently eliminate BG in a short time frame. Furthermore, several variables, such as counting equilibrium time, pH solution, the concentration of BG dye and adsorbent dosage were investigated. The results of this study exhibited that the adsorption equilibrium increased as BG dye concentration increased at pH = 7 after an equilibrium time of 2h, with 0.1 g of water-gel crystals having the top adsorption efficiency at 95.567 mg/g. This water-gel crystals adsorbent is regarded as an effective candidate that can be utilised for water treatment because the re-usability method of produced beads can successfully complete four cycles, and the adsorbent maintained its ability to remove BG dye. The water-gel crystals are therefore excellent candidates to be used as potent BG dye adsorbents from aqueous solutions. The water-gel crystals regeneration and re-usability investigation for the removal of BG dye was completed in at least four cycles successfully. This indicates that the Water-Gel Crystals produced have a high adsorption value. The (ΔG) was negative for the adsorption processes, indicating that the process was spontaneous. In addition, (ΔH) was determined for the adsorption method utilising water-gel crystals at 5.146 KJ/mol. ΔH Positive indicates that the method is endothermic in the range of 15-35 °C, using water-gel crystals.

Adjoint Synthesis for Trans‐Oceanic Tsunami Waveforms and Simultaneous Inversion of Fault Geometry and Slip Distribution

AbstractTsunamis propagate over long distances and can cause widespread damage even after crossing ocean basins. Prediction of tsunamis in distant areas based on observations near their sources is critical to mitigating damage. In recent years, the accuracy of numerical models of trans‐oceanic tsunami propagation has improved significantly due to the incorporation of effects such as the solid earth response to tsunami loading and wave dispersion. However, these models are computationally expensive and have not been fully utilized for real‐time prediction. Here, we derive the adjoint operator for the linear set of equations describing deep‐ocean tsunami propagation and show how a pre‐computed database of adjoint states can achieve rapid synthesis of tsunami waveforms at target sites from nonpoint arbitrary tsunami sources. The adjoint synthesis method allows for an exhaustive parameter search for tsunami source estimation. A method for simultaneous inversion of fault geometry and slip distribution using adjoint synthesis with Sequential Monte Carlo method was proposed and applied to the 2012 Haida Gwaii earthquake tsunami. The influence of model accuracy and the amount of observed data on the estimation of tsunami sources and waveforms was examined. It was found that with a highly accurate propagation model, using only a limited amount of observed data produced source and waveform estimates very similar to the final models obtained with much larger data sets. The final inferred fault model involved megathrust slip distributed between the Haida Gwaii trench and the Queen Charlotte fault. The proposed method can also quantify the uncertainty of the waveform forecasts.

An overview of diabetes-related foot ulcers.

The escalating prevalence of diabetes mellitus presents concern due to its widespread organ damage, including the heart, kidneys, eyes, and nerves, leading to severe complications such as heart attacks, strokes, blindness, and diabetes-related foot ulcers (DFUs). Management in the community setting should be focused on prevention, assessment and patient-centred care. By understanding the complex aetiology, risk factors, and classification of DFUs, along with utilising evidence-based interventions like the Wound, Infection and Ischemia (WIfI) system, we can streamline care. Neuropathy, peripheral arterial disease and infection are major contributors to DFU development, highlighting the importance of early detection and intervention. Comprehensive care addressing vascular health, infection control, pressure offloading, wound management, metabolic control, and patient education is essential for successful DFU management. Ultimately, proactive prevention strategies and interdisciplinary collaboration are necessary in the management of DFUs and improving patient outcomes.

Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning.

A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess of either pro-inflammatory or anti-inflammatory pathways that can lead to widespread inflammation, tissue damage, and organ failure. A dysregulated immune response can manifest as changes in differentiated immune cell populations and concentrations of circulating biomarkers. To propose an early diagnostic system that enables differentiation and identifies the severity of immune-dysregulated syndromes, we built an artificial intelligence tool that uses input data from single-cell RNA sequencing. In our results, single-cell transcriptomics successfully distinguished between mild and severe sepsis and COVID-19 infections. Moreover, by interpreting the decision patterns of our classification system, we identified that different immune cells upregulating or downregulating the expression of the genes CD3, CD14, CD16, FOSB, S100A12, and TCRɣδ can accurately differentiate between different degrees of infection. Our research has identified genes of significance that effectively distinguish between infections, offering promising prospects as diagnostic markers and providing potential targets for therapeutic intervention.

Navigating the 'moral hazard' argument in synthetic biology's application.

Synthetic biology has immense potential to ameliorate widespread environmental damage. The promise of such technology could, however, be argued to potentially risk the public, industry or governments not curtailing their environmentally damaging behavior or even worse exploit the possibility of this technology to do further damage. In such cases, there is the risk of a worse outcome than if the technology was not deployed. This risk is often couched as an objection to new technologies, that the technology produces a moral hazard. This paper describes how to navigate a moral hazard argument and mitigate the possibility of a moral hazard. Navigating moral hazard arguments and mitigating the possibility of a moral hazard will improve the public and environmental impact of synthetic biology.

Acute Copper Sulfate Poisoning: a case report

Copper Sulfate known as a powerful oxidizing agent and it can lead to widespread cellular damage, depending upon the dose ingested. The systemic effects of poisoning are seen primarily on red blood cells, gastrointestinal system, kidneys and cardiovascular system. The ingestion of poison can be lethal in severe cases. We reported the case of a 16-year-old girl who presented to the emergency department after ingestion of an unknown amount of copper sulfate 3 days earlier. On admission to the hospital, she had upper abdominal pain, vomiting and red colored urine with a normal serum copper level. She underwent symptomatic treatment and was monitored for 3 days. The outcome was favorable, and she had no signs and symptoms of organ failure. Bangladesh J Medicine 2024; 35: 114-117

Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake

The 30 November 2018, magnitude (Mw) 7.1 earthquake in Southcentral Alaska triggered substantial landslides, liquefaction, and ground cracking throughout the region, resulting in widespread geotechnical damage to buildings and infrastructure. Despite a challenging reconnaissance and remote-sensing environment, we constructed a detailed digital inventory of ground failure associated with the event from several sources. Sources included information derived from remotely sensed data, and data compiled from literature, social media postings, and earthquake damage information compiled by local, state, and federal agencies. Each instance of ground failure within the inventory contains information on the location and type of observed ground failure, and the methods and data used to document the occurrence. Where high-quality data, such as LIDAR or satellite imagery, were available and showed the ground-failure instance clearly, the extent is mapped as a polygon or polyline. All other locations are mapped as points. There are a total of 886 ground-failure instances documented within the inventory (400 landslides, 286 liquefaction features, and 200 features unattributed to specific processes). A semi-quantitative confidence scheme is used to describe mapping certainty associated with each ground-failure feature. This inventory represents a relatively moderate ground-failure-triggering event that occurred in a subarctic environment. This data paper describes the content within the inventory, the inventory data collection procedures, and limitations of the data. Events of this type are not often documented in detail; thus, adding the inventory data to the US Geological Survey Open Repository of Earthquake-Triggered Ground-Failure Inventories further diversifies the datasets available to the scientific community to be used to better understand and model earthquake-triggered ground failure.

Seismic performance of buildings during the magnitude 7.3 Kermanshah, Iran earthquake

In this paper, the findings and data of a large-scale reconnaissance mission following the November 12, 2017, M7.3 Kermanshah earthquake near the Iran-Iraq border are presented. The earthquake affected multiple cities in both countries and led to widespread damage and notable casualties and fatalities. The highest peak ground acceleration was recorded in Sarpol-e Zahab at 0.7g. As part of two trips, the data on nearly 1200 buildings in eight cities were collected by devising a sampling scheme to maximize the coverage of the survey, which was then employed to compile regional damage statistics. The spatial distribution of damage is presented for the entire region as well as various cities and neighborhoods in each city. The damage statistics are also disaggregated based on structural building, occupancies, and risk categories. The damage sustained by various categories of building components and contents is also assessed. In addition, the damage at the component level is closely examined for the structural and nonstructural components of severely damaged buildings to reveal the underlying causes that root in poor construction practices, lax enforcement of the building code, and inadequate seismic design provisions. Finally, the damage to hospitals in the region is investigated. This data, which can be augmented through a similar approach in the aftermath of probable future earthquakes, is key in calibrating the regional risk and resilience analysis of communities.

Brain functional network changes in patients with juvenile myoclonic epilepsy: a study based on graph theory and Granger causality analysis.

Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown that the brain networks are disrupted in adolescent patients with juvenile myoclonic epilepsy (JME). However, previous studies have mainly focused on investigating brain connectivity disruptions from the perspective of static functional connections, overlooking the dynamic causal characteristics between brain network connections. In our study involving 37 JME patients and 35 Healthy Controls (HC), we utilized rs-fMRI to construct whole-brain functional connectivity network. By applying graph theory, we delved into the altered topological structures of the brain functional connectivity network in JME patients and identified abnormal regions as key regions of interest (ROIs). A novel aspect of our research was the application of a combined approach using the sliding window technique and Granger causality analysis (GCA). This method allowed us to delve into the dynamic causal relationships between these ROIs and uncover the intricate patterns of dynamic effective connectivity (DEC) that pervade various brain functional networks. Graph theory analysis revealed significant deviations in JME patients, characterized by abnormal increases or decreases in metrics such as nodal betweenness centrality, degree centrality, and efficiency. These findings underscore the presence of widespread disruptions in the topological features of the brain. Further, clustering analysis of the time series data from abnormal brain regions distinguished two distinct states indicative of DEC patterns: a state of strong connectivity at a lower frequency (State 1) and a state of weak connectivity at a higher frequency (State 2). Notably, both states were associated with connectivity abnormalities across different ROIs, suggesting the disruption of local properties within the brain functional connectivity network and the existence of widespread multi-functional brain functional networks damage in JME patients. Our findings elucidate significant disruptions in the local properties of whole-brain functional connectivity network in patients with JME, revealing causal impairments across multiple functional networks. These findings collectively suggest that JME is a generalized epilepsy with localized abnormalities. Such insights highlight the intricate network dysfunctions characteristic of JME, thereby enriching our understanding of its pathophysiological features.

Observational study of Super Typhoon Saola in 2023 when it was close to Hong Kong

AbstractSuper Typhoon Saola came very close to Hong Kong on 1/2 September 2023, necessitating the issuance of the No. 10 hurricane signal, the highest tropical cyclone warning signal in Hong Kong. While there was widespread damage in Hong Kong, no people were killed in the event with effective early warning. It is rare that a super typhoon comes very close to Hong Kong, and this paper is a part in the series of the documentation of Saola to summarize the interesting observations of Saola near Hong Kong for future reference by weather forecasters.