Cyclone Events Research Articles

UTILIZATION PATTERN OF DIVERSE ICT TOOLS BY COASTAL FARMERS DURING THE WARNING STAGES OF CYCLONES

Despitenumerous advanced scientific technologies, we are still at the mercy of some uncontrollable natural calamities. A tropical cyclone is one of the most devastating hydrological disasters among them. Along with violent wind, torrential rain, high wave, destructive storm surges and coastal flooding, the cyclone is responsible for considerable losses to Indian agriculture. After all, farmers are informed, aware, and cope with these difficulties successfully with past experiences, warn through various ICT tools, social media and organizational sources (Pratik and Vinaya, 2022). The study was carried out with a specific objective to determine the utilization pattern of information sources in the cyclone’s early warning stages. Purposively the state of Odisha was selected because it is vulnerable to cyclonic events. 8 villages from 2 coastal districts of the state were considered for the study, and 20 respondents from each village made the sample size 160. The primary data was collected through a well-structured interview schedule and analyzed using appropriate statistical tools. Results divulged that Television was available to 96.25 percent of the respondents, followed by Mobile phones (71.25%), Smartphone (67.50%), Radio (35.63%), Laptop (22.50%), Personal computer (14.38%) and Tablets (5.53%). TV news was the major social media with mean score (3.55) ranked first, followed by SMS (3.50) and Whatsapp (3.26) which the majority of the farmers regularly retrieve information. In contrast, Blog, with a mean score (2.04) was the least used social media by a small proportion of farmers to gain information before cyclones. With comparision to information access through various social media sources, independent variables such as Education, social participation, annual family income, source of credit were found to be positively significant at 1% level of significance, p<0.01, while mass media exposure and extension contact were at 5% level of significance. In the community, there were 5 primary organizational sources, out of which 51.87% of respondents informed through all of the organization where 19.38% of respondents were from 4 sources, followed by 11.88% from 3 sources, 13.75% from 2 sources and 3.12% from a single source. Early warning and information create a great advantage in dealing with such climatic vagaries.

Mitigating proximate impacts of tropical cyclone landfalls in the Southwest Indian Ocean

The occurrence and impacts of tropical cyclones in the Southwest (SW) Indian Ocean were investigated over five cyclone seasons (November to April) between 2018/19 and 2022/23. Data describing cyclone characteristics, affected populations and economic losses from cyclone landfalls in Madagascar and Mozambique were extracted from the African Risk Capacity (ARC)’s Tropical Cyclone Explorer (TCE) software. Of 56 cyclones that formed in the region, 27 landfalls occurred with an average of 2.8 per season in Madagascar and 2.6 in Mozambique, mainly in January and February of each year. Most cyclone landfalls in Madagascar were categorized as moderate tropical storms (MTS, 43 %) and intense tropical cyclones (ITC, 22 %). In Mozambique, landfalls were mostly ITC (31 %) followed by MTS (23 %). Landfalls of very intense tropical cyclones (VITC) were more common in Mozambique (15 %) than Madagascar (7 %). An average of 1.8 million and 775,000 people per season were exposed to strong cyclone winds in Madagascar and Mozambique, respectively, with economic losses from cyclones per season averaging $544 million in Madagascar and $170 million in Mozambique. The African Risk Capacity (ARC), a specialized agency of the African Union, has implemented a parametric insurance solution to mitigate the proximate effects of cyclones damage on vulnerable populations. Four modules to estimate losses caused by cyclone events are described; the hazard-, vulnerability / damage-, - exposure- and insurance modules. Initial outcomes of the ARC’s parametric cyclone insurance policy in Madagascar and Mozambique are discussed. Since its launch in 2020, the ARC’s parametric cyclone insurance policy including its Replica partner allocated a total payout of $12.2 million to Madagascar following the landfalls of cyclones BATSIRAI in 2022 and FREDDY in 2023.

Global population profile of tropical cyclone exposure from 2002 to 2019.

Tropical cyclones have far-reaching impacts on livelihoods and population health that often persist years after the event1-4. Characterizing the demographic and socioeconomic profile and the vulnerabilities of exposed populations is essential to assess health and other risks associated with future tropical cyclone events5. Estimates of exposure to tropical cyclones are often regional rather than global6 and do not consider population vulnerabilities7. Here we combine spatially resolved annual demographic estimates with tropical cyclone wind fields estimates to construct a global profile of the populations exposed to tropical cyclones between 2002 and 2019. We find that approximately 560 million people are exposed yearly and that the number of people exposed has increased across all cyclone intensities over the study period. The age distribution of those exposed has shifted away from children (less than 5 years old) and towards older people (more than 60 years old) in recent years compared with the early 2000s. Populations exposed to tropical cyclones are more socioeconomically deprived than those unexposed within the same country, and this relationship is more pronounced for people exposed to higher-intensity storms. By characterizing the patterns and vulnerabilities of exposed populations, our results can help identify mitigation strategies and assess the global burden and future risks of tropical cyclones.

Holocene Depositional History of Low-Lying Reef-Rim Carbonate Islets of Fakarava Atoll, Northwest Tuamotu, Central South Pacific

Assumptions about the fate of low-lying coral reef islands (atolls) facing global warming are poorly constrained, due to insufficient information on their depositional history. Based on the U/Th dating of 48 coral clasts, the chronostratigraphic analysis of excavated sections through rim islets (motu) at the windward and leeward sides of Fakarava Atoll (Tuamotu, French Polynesia) reveal that the deposition of coral detritus started approximately 2000 years ago. Most of these deposits lie on conglomerate pavements or reef flat surfaces, and are about 4500 to 3000 years old. The islet expansion at the windward sites seems to have operated coevally across the reef rim, from the ocean-facing shore lagoonwards. Meanwhile, well-developed, continuous, elongated, vegetated islets mostly occur along the windward, northeast to southeast coast, and isolated islets, vegetated or not, associated with the dense networks of conglomerates, are common on the leeward, partly submerged, western rim. Islet accretion on the windward rim sides is believed to have been mainly triggered by winter storms and occasional cyclonic events, whilst the leeward atoll parts were most likely shaped by distant-source swells from mid to high latitudes. The projections of the accelerated sea level rise in the future suggest that the long-term islet stability at Fakarava could be altered because the islets have accreted under the conditions of the falling sea level.

Asymmetric Dipole Trends in Geodynamo Models and the Paleomagnetic Field

AbstractTemporal trends in the paleomagnetic dipole moment exhibit the property of positive skewness. On average, positive trends are larger and occur less frequently than negative trends over timescales of several tens of kyr. We explore the origin of this property using numerical geodynamo models. A suite of models reveals that skewness arises for a restricted set of boundary conditions. Models driven by heat flow at the top and bottom boundaries exhibit very little skewness, whereas models driven solely by heat flow on the lower boundary produce significant positive skewness. Further increases in skewness occur in the presence of thermal stratification at the top of the core. The level of skewness in the geodynamo models is correlated with estimates of upwelling near the core‐mantle boundary. Sustained upwelling is expected to increase magnetic‐flux expulsion, contributing to higher levels of skewness. Similar behavior is recovered from stochastic models in which the dipole is generated by a random series of cyclonic convection events. Skewness in the stochastic models is quantitatively similar to estimates from the geodynamo models when the average recurrence time of the convection events is 100 years. Extending the stochastic models to the paleomagnetic field implies a longer recurrence time of 1,000 years or more. We interpret this recurrence time in terms of the timing of flux‐expulsion events rather than individual convective events. Abrupt increases in the dipole moment from flux expulsion can produce skewed trends on timescales of tens of kyr.

Flood damage and shutdown times for industrial process facilities: a vulnerability assessment process framework

Much of the U.S. petrochemical infrastructure is heavily concentrated along the western coast of the Gulf of Mexico within the impact zone of major tropical cyclone events. Flood impacts of recent tropical disturbances have been exacerbated by an overall lack of recognition of the vulnerabilities to process systems from water intrusion, as well as insufficient disaster mitigation planning. Vulnerability assessment methods currently call for the aggregation of qualitative data to survey the susceptibility of industrial systems to floodwater damage. A means to quantify these consequences is less often employed, resulting in a poor translation of the threat of flood hazards to a crucial element of the economy. This paper reviews flood damage assessment for industrial facilities and presents a component-level conceptual methodology to assess the consequences of flood events. To more effectively communicate loss potential from flood events, the proposed methodology utilizes synthetic estimation to calculate repair requirements, shutdown time, and direct cost.

IMPACT OF TROPICAL CYCLONE SEROJA ON RAINFALL AND WIND SPEED IN EAST NUSA TENGGARA PROVINCE

Tropical cyclone phenomenon can give impacts such as heavy rain, strong winds, and high waves around its growth area. One of the tropical cyclones that has occurred is Seroja Tropical Cyclone which formed in the Sawu Sea on April 3, 2021. Therefore, this study aims to determine the effect of Seroja Tropical Cyclone on rainfall and surface wind speed in East Nusa Tenggara Province and the percentage comparison of rainfall and wind speed during the Seroja tropical cyclone event with the normal value of rainfall and surface wind speed over a 10-year period. The data used are daily rainfall and surface wind speed data during the Seroja tropical cyclone event, namely April 3 to 12, 2021 and daily average rainfall and wind speed data in April for 10 years in several affected districts in East Nusa Tenggara Province. Data processing is done by calculating the percentage comparison of rainfall and wind speed during the Seroja Tropical Cyclone event with normal rainfall and wind speed in several regions in East Nusa Tenggara. Based on the analysis, heavy to extreme rainfall and strong winds were found in several districts at a radius of about 400 km from the center of the cyclone. Although the category of this tropical cyclone is low, it is able to give impacts in the form of heavy to extreme rainfall and strong winds in the surrounding area. So it can be concluded that the tropical cyclone category does not directly affect rainfall and wind speed in an area, but the distance between the area and the center of the tropical cyclone is more influential in increasing rainfall and wind speed in an area. This is also proven by Sumaja's research in the case of tropical cyclones LUA and Narelle.

The Histories of Well-Documented Maritime Cyclones as Portrayed by an Automated Tracking Method

Abstract This study examines extratropical cyclone tracks, central pressure, and maximum intensification rates from a widely used automated cyclone tracking scheme and compares them with the manual tracking of five well-known North Atlantic cyclones whose histories are available in the refereed literature. The automated tracking scheme is applied to sea level pressure data from four different reanalyses of varying levels of sophistication to test the sensitivity of the results to input data resolution and quality. Further, we test the tracking scheme using lower-tropospheric vorticity obtained from the most recent reanalysis (ERA5) for four of these cyclone events. Substantial discrepancies in cyclone position, intensity, and maximum intensification rates exist between the manual tracking and the automated tracking and are not eliminated by using higher-resolution reanalyses or by “turning off” the spatial smoothing feature of the automated tracking scheme (needed to reduce spurious cyclone detections). The results point to a particular problem in detecting weaker and earlier stage cyclones and confirm findings from studies that have examined a broad range of cyclone tracking schemes for a range of reanalyses. Notably, this early cyclone stage often involves a smaller-scale secondary cyclogenesis or cyclone wave, which are detected by the automated scheme only after subsequent growth in the ensuing 6–12 h. It is known that these early stages are critical for a comprehensive understanding of rapid intensification events. A discussion of possible future solutions to this problem is presented. Significance Statement Because of the availability of large modern datasets portraying sea level pressure across the globe, meteorologists have turned to automated detection and tracking of midlatitude cyclones. Detection and tracking are of interest since these storm systems play an important role in weather and climate and potential changes in their location, frequency, and intensity are of considerable societal interest given climate change. This paper compares the results obtained from one commonly used automated tracking method with tracks obtained by human analysts. We find substantial discrepancies in cyclone position, intensity, and intensification rates and that these differences are not eliminated by using improved analyses. A discussion of possible future solutions is presented.

Component Assessment of the Electric Transmission Grid to Hurricanes

AbstractThe increased frequency and intensity of extreme weather events from climate change necessitates understanding impacts on critical infrastructure, particularly electrical transmission grids. One of the foundational concepts of a grid's resilience is its robustness to extreme weather events, such as hurricanes. Resilience of the electric grid to high wind speeds is predicated upon the location and physical characteristics of the system components. Previous modeling assessments of electric grid failure were done at the systems level with assumptions on location and type of specific components. To facilitate more explicit adaptation metrics, accurate component‐level information is needed. In this study, we build and utilize a data set of location, physical characteristics, and age of transmission structures for nine counties in the Florida Panhandle. These component characteristics were then simulated for failure under a variety of scenarios using fragility curves. Eight hurricanes were modeled using Hazus from the Federal Emergency Management Administration and the resulting impact to the network was assessed. The network was generated using the transmission lines and towers, showing increasing impacts to network efficiency with larger storms. Although modern transmission structures are built under the more stringent extreme wind loading construction standards, the prevalence of older, wooden transmission structures throughout the region poses a substantial risk to reliable electricity transmission during tropical cyclone events from the Gulf of Mexico.

Evaluation of overwash vulnerability and shoreline dynamics in cyclone-prone Sagar Island, Sundarbans (India)

Situated in the climatically vulnerable Sundarbans region, Sagar Island has increasingly been subjected to intense cyclonic events, including Yaas, Amphan, Bulbul, and Aila, leading to significant alterations in its coastal morphology. This study aims to elucidate the overwash vulnerability and shoreline dynamics in Sagar Island, spanning the period from 2000 to 2020. Utilizing satellite imagery, the study employs three indices—Overwash Shoreline Ratio (OSR), Maximum Overwash Intrusion Recurrence (MOIR), and Complete Barrier Overwash (CBO)—to assess overwash vulnerability. These indices collectively indicate a heightened susceptibility to overwash intrusion, with a particular focus on the years following severe cyclonic events. Additionally, shoreline change dynamics were quantitatively analyzed using the Digital Shoreline Analysis System (DSAS) tool, revealing a strong positive correlation between shoreline recession and climatic variables. Interlinkages between overwash vulnerability and shoreline dynamics were established, confirming that both phenomena are exacerbated by climate change and extreme weather events. The study's findings have critical implications for a broad range of sectors such as agriculture, fisheries, transportation, and ecosystem conservation. The research underscores the urgency for an integrated coastal management strategy that considers both overwash vulnerability and shoreline change dynamics to enhance sustainability and resilience. This study contributes to the global discourse on coastal dynamics, serving as a benchmark for climate adaptation measures in other cyclone-prone regions.

Influence of monsoon trough length on interannual variability of Northwest Pacific multiple tropical cyclone events

Previous studies have established a link between the intensity of the monsoon trough (MT) and tropical cyclone (TC) activity. This study investigates the impact of the length of the MT on the interannual variability of multiple TC events (MTCEs) over the western North Pacific (WNP) during the typhoon season (June–October) during 1980–2020. Results show a significant positive correlation between the length of the MT and the occurrence frequency of MTCEs. A longer MT is favorable for the occurrence of more MTCEs. During the long MT years, the MT extends eastwards, resulting in strong low-level relative vorticity, mid-level upward motion, and sufficient moisture over the central-eastern WNP, which are conductive to the occurrence of MTCEs. A diagnosis of genesis potential index confirms the crucial role of positive synoptic-scale disturbances. Barotropic energy conversion analysis further shows that the MT-induced mean flow change can modulate barotropic energy conversion from the mean flow to the synoptic eddies, which is a critical energy source for the development of tropical depressions. In this process, changes in meridional shear of the large-scale zonal winds play a dominant role, followed by their meridional convergence. These changes lead to the increasing synoptic-scale disturbances over the central-eastern WNP during the long MT years, resulting in more MTCEs.

Examination of long-term climatic and fish-catch indicators in India at a macro scale

The quantification of trends and attributes helps in better understanding of the long-term changes in the marine ecosystem. Marine fish-catch was analysed using the statistical data provided by the Central Marine fisheries Research Institute, India. These datasets are used internationally to assess changes in marine fisheries along the coasts of India. In addition the data from the Indian Meteorological Department were used to derive temporal trends of cyclonic indicators such as the Frequency and, Intensity of cyclones. Trend analysis of fishery-based data indicated a significant rise in fish-catch across the NIO basin. The sea surface temperature has reported a significant rise in the past 2 decades, reaching peaks during the months from March to October. There is a reduction in the overall frequency of cyclonic events, with a significant increase in extreme cyclonic events. The normal distribution curve also reports a shift towards a positive direction in the case of SST and fish-catch, while the negative shift is obtained for the frequency of cyclones as well as the intensity of depression between the time-period of 1950-99 to 2000-18. The influence of global warming induced climate change can be observed within these trends.

Rapid, Landscape-Scale Assessment of Cyclonic Impacts on Mangrove Forests Using MODIS Imagery

Cyclones are a key disturbance in mangrove ecosystems, but it is challenging to assess post-storm impacts over large areas, along with the recovery of these systems at broad temporal scales. Given the high frequency of these events in the Sundarbans region, prompt and consistent assessment of vegetation conditions is an important research need. Several studies have assessed the impact of an extreme cyclone event in 2007 (Sidr); however, there is little agreement between the extent and severity of the disturbance footprint of the cyclone, and very few studies attempted to assess vegetation recovery. We used a MODIS (Moderate Resolution Imaging Spectroradiometer) time series (2001–2010) to calculate monthly plant productivity anomalies in Google Earth Engine. We summarized dry season anomalies to assess post-storm vegetation change and evaluate the recovery time. Approximately 2100 km2, primarily on the east side, were impacted by Sidr. The number of damaged pixels was reduced by 55% the following dry season (2008) and 93% in the dry season of 2009, indicating a near-full recovery 26 months after the event. Our results provide an additional line of evidence to provide a rapid assessment of the post-storm vegetation damage. The simple framework used can provide a comprehensive view of the extent of the damage, including lag effects on vegetation, in just a matter of months after the event.

An Investigation of a Northeast U.S. Cyclone Event without Well-Defined Snow Banding during IMPACTS

Abstract On 7 February 2020 a relatively deep cyclone (∼980 hPa) with midlevel frontogenesis produced heavy snow (20–30 mm liquid equivalent) over western and central New York State. Despite these characteristics, the precipitation was not organized into a narrow band of intensive snowfall. This event occurred during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Using coordinated flight legs across New York State, a remote sensing aircraft (ER-2) sampled above the cloud, while a P-3 aircraft collected in-cloud data. These data are used to validate several Weather Research and Forecasting (WRF) Model simulations at 2- and 0.67-km grid spacing using different initial and boundary conditions (RAP, GFS, and ERA5 analyses) and microphysics schemes (Thompson and P3). The differences between the WRF runs are used to explore sensitivity to initial conditions and microphysics schemes. All 18–24-h runs realistically produced a broad sloping region of frontogenesis at midlevels typically; however, there were relatively large (20%–30%) uncertainties in the magnitude of this forcing using different analyses and initialization times. The differences in surface precipitation distribution are small (<10%) among the microphysics schemes, likely because there was little riming in the region of heaviest precipitation. Those runs with frontogenesis closest to the RAP analysis and a surface precipitation underprediction of 20%–30% have too little ice aloft and at low levels, suggesting deficiencies in ice generation and snow growth aloft in those runs. The 0.67-km grid produced more realistic convective cells aloft, but only 5%–10% more precipitation than the 2-km grid. Significance Statement Heavy snowfall from U.S. East Coast winter storms can cause major societal problems, yet few studies have investigated these storms using field observations and model data. This study focuses on the 7 February 2020 event, where 20–40 cm of snow fell over west-central New York. Our analysis shows a broad region of ascent, rather than a concentrated region favoring a well-defined snowband was the primary process contributing to snowfall. Last, model microphysics were validated within this storm using the in situ aircraft data. Errors in the snow generation aloft and snow growth at low levels likely contributed to the simulated surface precipitation underprediction, but most of the forecast uncertainty is from initial conditions for this short-term (∼24-h lead time) forecast.

Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions

As tropical forests cycle the most water and carbon, it is crucial to understand the short- and long-term effects of intensifying cyclones on these ecosystems. Soil nutrient status has been shown to moderate forest cyclone responses using field litterfall measurements, but litterfall is one of the multiple cyclone impact metrtics, which may or may not be correlated with one another or with site nutrients. We used remotely sensed vegetation indices to quantify immediate damage and two-year recovery for 42 cases across nine tropical forests in Hawaii, Puerto Rico, Mexico, Australia, and Taiwan affected by 12 cyclones between 2004 and 2017. We tested whether changes in leaf area index (LAI) and enhanced vegetation index (EVI) correlated with changes in litterfall observations and how changes varied with total soil phosphorus (P) concentrations across regions. We compared cyclone-induced changes and recovery of LAI and EVI to litterfall observations compiled in a pantropical meta-analysis. We found large variation in changes in LAI and EVI across forests, with the greatest reductions in LAI (−77%) and EVI (−77%) in Mexico (Jalisco) and Puerto Rico, respectively. LAI (r = −0.52) and EVI (r = −0.60) changes correlated with those in litterfall across cases. Post-cyclone data showed recovery of LAI by four months, EVI by two months, and litterfall by ten months. We detected larger changes in LAI and EVI in forests with higher soil P, but these relationships were not significant when accounting for cyclone and site as random effects. Principal component analyses indicated a regional clustering of cases related to their contrasting cyclone regimes, with the frequency and intensity of cyclone events negatively correlated. Overall, remote sensing observations complement but do not substitute for ground observations that reveal cyclone damage and post-cyclone recovery in tropical forests, and soil phosphorus moderates some but not all metrics of stability in response to cyclones.

Understanding the response of phytoplankton to the cyclonic event Sitrang A case study in the Hooghly estuary of Sundarban Bay of Bengal region

The study aims to investigate the impact of tropical cyclone Sitrang on the phytoplankton community and water quality parameters at estuarine zone of Hooghly River near Namkhana region of Sundarban. Focusing on the response of diatom and dinoflagellates to this post-monsoonal cyclone this study tries to address the questions regarding short-term ecological effects, including changes in water quality, shifts in the phytoplankton composition and abundance, and the potential factors driving these changes. Water samples were collected for consecutive three days before and six days after the occurrence of the Sitrang in October 2022. A substantial drop in pH, DO, and temperature after the immediate passage of the cyclone along with increased salinity, chlorophyll-a content, inorganic macronutrients, and TDS were observed. The cyclone led to a significant reduction in phytoplankton diversity, while concurrently causing a notable increase in their abundance. Prior to the cyclone 45 species of diatoms and 8 species of dinoflagellates were observed which was reduced to 25 and 6 species after the cyclone. Post-cyclonic period exhibited high predominance of dinoflagellates especially Tripos sp., and Noctiluca scintillans (4.3×103 cells/L). Canonical correspondence analysis (CCA) revealed nitrate and salinity are the major factors influencing phytoplankton abundance. The notable phenomenon of massive increase in the number of Tripos furca (2.04 ×104 cells/L) suggests their favourable growth condition triggered by the cyclone. Due to the rising intensity of cyclones in the Indian Sundarbans, close monitoring and continuing research is essential for a thorough understanding of phytoplankton dynamics.

Seasonal variability of eddy kinetic energy in the Banda Sea revealed by an ocean model: An energy budget perspective

Seasonal eddy kinetic energy (EKE) variability in the Banda Sea during 1993–2014 is studied from an energy budget perspective, based on the outputs of Ocean Forecasting Australian Model version 3. High EKE is confined within the upper 300 m of the western Banda Sea with the largest intensity exceeding 3 × 103 J/m2 in the northwest monsoon (NWM) season. In this strong EKE region during NWM, eddies derive almost two thirds of their kinetic energy from the direct wind power input (WP), with additional contributions from the barotropic (BT) and baroclinic instability (BC) of the background flow. Both WP and BT modulate the EKE seasonality and drive the peak energy during NWM, while BC strengthens in the southeast monsoon (SEM) season because of the intensified baroclinicity of the upper circulation. The westerly wind bursts associated with the Madden-Julian Oscillation (MJO), together with steep topography, facilitate more cyclonic eddy generation events in the western Banda Sea during NWM. During SEM, EKE becomes relatively moderate across the Banda Sea but with a regional peak to the southwest of the Buru Island, which can be attributed to island wake effect. Over the Banda Sea, WP, BT and BC contribute 74% (42%), 14% (19%) and 12% (39%) of total energy to EKE during NWM (SEM), respectively. The majority of EKE generated is diverged horizontally by pressure work and dissipated by turbulent viscosity, with dissipation depleting the most. This study highlights the importance of both monsoon and MJO wind forcing in generating EKE variability along the pathway of the Indonesian Throughflow.

Revised system for shallow-water design wave estimation on the coast of the Republic of Korea based on numerical model data

In this study, a new approach to calculate the shallow-water design wave (SWDW, design wave at the coastal structure) applied in the Republic of Korea is introduced and evaluated. Accurate estimation of the SWDW is crucial in designing port and coastal structure. In the Republic of Korea, the deep-water design waves (DWDW, design wave at depths greater than 20 m) are provided by the government, by which the DWDW heights are calculated at 210 grid points in the waters around the Korean peninsula using numerical models with wind fields and through extreme value analysis. For the SWDW estimation, two approaches were suggested. Case 1 was the conventional method by which the SWDW was calculated using the DWDW parameters as boundary conditions for SWAN wave modeling over a small-computational domain around target location. Case 2 was a new approach as it used the wind fields selected from the typhoon and extratropical cyclone events that had significant impacts on the target areas. By running the SWAN model for the large computational domain around the Korean peninsula, wave spectra were generated during selected storm events and these spectra were used as the boundary forcing conditions for the small-computational domain simulations around the target areas. The results of the two model cases were compared with those based on wave observations at four wave stations where the extreme value analysis were applied for the SWDW height estimation, showing that the newly developed approach was in better agreement with the observations for the typhoon events than the extratropical cyclones. In particular, the greatest SWDW height calculated Case 2 was 7.7 m which was much closer to the observation value (8.32 m) than the value by Case 1 (6.8 m), indicating that the error of SWDW estimation could be reduced by the new approach under severe conditions although the overall errors were similar between the two case. The results suggests that the SWDW estimation error could be reduce by combining the results of both approaches. The SWDW estimation and evaluation system in this study could be applied usefully in regions with similar conditions where long-term wave observational data are not sufficient to estimate the SWDWs at the targeted coastal structures.

Joint probability analysis of storm surges and waves caused by tropical cyclones for the estimation of protection standard: a case study on the eastern coast of the Leizhou Peninsula and the island of Hainan in China

Abstract. The impact of natural hazards such as storm surges and waves on coastal areas during extreme tropical cyclone (TC) events can be amplified by the cascading effects of multiple hazards. Quantitative estimation of the marginal distribution and joint probability distribution of storm surges and waves is essential to understanding and managing tropical cyclone disaster risks. In this study, the dependence between storm surges and waves is quantitatively assessed using the extreme value theory (EVT) and the copula function for the Leizhou Peninsula and the island of Hainan of China, based on numerically simulated surge heights (SHs) and significant wave heights (SWHs) for every 30 min from 1949 to 2013. The steps for determining coastal protection standards in scalar values are also demonstrated. It is found that the generalized extreme value (GEV) function and Gumbel copula function are suitable for fitting the marginal and joint distribution characteristics of the SHs and SWHs, respectively, in this study area. Secondly, the SHs show higher values as locations get closer to the coastline, and the SWHs become higher further from the coastline. Lastly, the optimal design values of SHs and SWHs under different joint return periods can be estimated using the nonlinear programming method. This study shows the effectiveness of the bivariate copula function in evaluating the probability for different scenarios, providing a valuable reference for optimizing the design of engineering protection standards.

A Record‐Breaking Cyclone Over the Southern Ocean in 2022

AbstractIn October 2022, an extreme cyclone developed in the South Pacific Ocean with a sea level pressure of 900 hPa, becoming the strongest extratropical cyclone in the satellite era. Using ERA5 reanalysis data, we investigated its development mechanisms and examined long‐term changes in the occurrence of extreme cyclones over the Southern Ocean. Our findings indicate that the cyclone formed within a low‐pressure anomaly over the South Pacific. Its explosive development was initiated by upper‐level dynamic forcing and driven by low‐level latent heat release, which had been preconditioned by surface heat flux. Extreme cyclones have increased significantly in the Amundsen‐Bellingshausen Seas (ABS) and the South Indian Ocean since 1980. The large‐scale environmental variables in the ABS also showed a consistent trend toward more favorable conditions for cyclone intensification. Understanding these extreme cyclone events will help to overcome the uncertainty in projections of climate change impacts and improve weather forecast skills.