Cyclone Events Research Articles

Hurricanes and Mortality among Patients Receiving Dialysis.

Hurricanes are severe weather events that can disrupt power, water, and transportation systems. These disruptions may be deadly for patients requiring maintenance dialysis. We hypothesized that the mortality risk among patients requiring maintenance dialysis would be increased in the 30 days after a hurricane. Patients registered as requiring maintenance dialysis in the United States Renal Data System who initiated treatment between January 1, 1997 and December 31, 2017 in one of 108 hurricane-afflicted counties were followed from dialysis initiation until transplantation, dialysis discontinuation, a move to a nonafflicted county, or death. Hurricane exposure was determined as a tropical cyclone event with peak local wind speeds ≥64 knots in the county of a patient's residence. The risk of death after the hurricane was estimated using time-varying Cox proportional hazards models. The median age of the 187,388 patients was 65 years (IQR, 53-75) and 43.7% were female. There were 27 hurricanes and 105,398 deaths in 529,339 person-years of follow-up on dialysis. In total, 29,849 patients were exposed to at least one hurricane. Hurricane exposure was associated with a significantly higher mortality after adjusting for demographic and socioeconomic covariates (hazard ratio, 1.13; 95% confidence interval, 1.05-1.22). The association persisted when adjusting for seasonality. Patients requiring maintenance dialysis have a higher mortality risk in the 30 days after a hurricane.

Engineering geomorphological and InSAR investigation of an urban landslide, Gisborne, New Zealand

The East Coast region of New Zealand has some of the highest erosion rates in the world, due to its proximity to an active plate boundary, susceptibility to high-intensity storms and steep terrain underlain by young soft sedimentary rock and soil. In the city of Gisborne, expansion of residential blocks into steeper terrain in peri-urban areas has required improved capacity for the characterisation and monitoring of slope stability. Landslides have affected several properties and have destroyed infrastructure. Slope failure commonly occurs during heavy rainfall events when slow-moving retrogressive slides transition into earthflows and mudflows. In this study, we used in situ sampling and testing methods combined with remote sensing techniques to provide an understanding of the pre-failure and post-failure behaviour of an urban landslide in Gisborne. High-resolution aerial imagery, unmanned aerial vehicle imagery and light detection and ranging data revealed slope morphology and contours of prehistoric failures in the area, and highlighted the more recent impacts of deforestation on slope stability. Furthermore, Sentinel-1 InSAR analysis determined that gradual deformation began in 2017, following two ex-tropical cyclone events. Deformation downslope continued until an initial failure in July 2020. Following that event, some parts of the slope proceeded to accelerate, leading to a further reactivation event in November 2021, following heavy rainfall. During this November 2021 event, average line of sight velocities ranged from −7.9 to −11.2 mm/year, and deformation rates in the vertical direction (related to rotational slumping) averaged −11.2 to −11.9 mm/year, consistent with field observations.

Heightened storm activity drives late Holocene reef island formation in the central Pacific Ocean

The impact of global environmental change on coral reef islands is uncertain, with few studies having resolved the critical controls on island formation and change. Based on detailed, topographic surveys, sediment analysis and radiometric dating, we present a multi-phase model of the formation of two reef islands in Jaluit atoll, Republic of the Marshall Islands. The initial phase of island building occurred 1300 years ago, later than elsewhere in the Marshall Islands and during a period of relative sea level fall from the mid-Holocene sea level highstand . Initial accumulation occurred as a consequence of relative emergence of the reef flat that forced a transition in reef flat ecology and dominant foraminifera sediment producers that contributed to island building. Distinctive sets of progradational ridges and their coarse sediment character provide evidence for the importance of extreme wave events in island expansion from an initial core. Expansion occurred in two principle phases, 650–350 years ago and 200 years ago to the present, each coincident with known phases of increased storminess in the central Pacific. Results highlight the complexity of island formation and show that future change will depend not only on sea level but storm processes that have been a major influence on island development over the past 650 years. Anticipated reduction in cyclogenesis in the southern Marshall Islands region suggests a near-future period of geomorphic stasis of the islands of Jaluit. An increase in cyclogenesis in the central Pacific and higher latitudes may enhance opportunities for storm-driven island accumulation events over the next century where coral growth is able to be maintained. • Island formation in Jaluit atoll occurred over the past 1300 years, during relative sea level fall and subsequent stability. • Cyclonic events were critical in the episodic expansion of islands over the past 700 years. • Relative sea-level fall forced changes in reef ecology and sediment production and transport regimes for island accumulation. • Formation of islands in Jaluit atoll lagged other parts of the archipelago and post-date habitation of the Marshall Islands. • Reduced storm dynamics in the tropical western north Pacific suggests a future period of island geomorphic stasis.

A Study on Astrometeorological Relationship between Planet Azimuth and Temperature

Temperature is one of the key weather parameters, which is a necessity for all life on Earth. Any variation from the normal can impede the physical, chemical, and biological processes of life. Extremes would produce permanent changes that would halt the plant's growth and may cause complete withering. Advance information on temperature events will be helpful in protecting the plant and sustain the productivity under any temperature related disasters. Astrometeorology is one of the oldest organized knowledge systems that interplay between planetary movement and weather. In Tamil Nadu Agricultural University (TNAU), Astrometeorological weather forecast rules for rainfall, wind speed and cyclone events were already well defined. In continuation of this research, identification of Astrometeorological rules for the temperature events had been taken up during 2021-2022 at Agro climate Research Centre, TNAU, Coimbatore. Hourly temperature data from 2011-2016 was collected for 30 districts of Tamil Nadu. In each districts one particular location is selected and is correlated with ephemeris developed for a particular location using Alcyone ephemeris calculator. The findings clearly demonstrated the differential impact of individual planets and their azimuth on the temperature events. The study revealed that low temperature events were influenced when most planets are away (271- 300 degree azimuth) whereas the high temperature events were influenced by the planets that are directly above the location (91 to 120 degrees azimuth) and the in between temperature events were influenced by both 61-90 and 241-270 degrees. The specific azimuth of the Sun, Mercury, Venus, Jupiter, Saturn, Uranus, and Neptune had a makeable influence on a particular temperature event, however all the azimuths of the Moon and Mars had only a mild effect on any temperature event. Based on the results, Astrometeorological rules for the temperature events could be defined and used for the development of hybrid forecasting by overlapping the astromet forecast output on the numerical forecast output. This will produce more accuracy than individual forecast, reduce missing forecast, falls alarms, and improve the usability of forecast.

Assessment of machine learning techniques for prediction of integrated water vapor using meteorological data

Weather and Climatological studies are very important in assessing atmospheric conditions like storms and cyclones. Integrated water vapor (IWV) is an important greenhouse gas in the atmosphere responsible for the Earth's radiative balance. Global Positioning System (GPS) observations have been used for monitoring the IWV variability. The IWV estimations are carried out using ground-based GPS observations at Hyderabad (17.4°N, 78.46°E), India using GAMIT software. GAMIT is GPS analysis software developed by MIT, USA. It takes input as GPS observation data containing pseudo ranges, navigation data containing ephemeris, clock errors, g-files with orbital information, and meteorological data like pressure, temperature, and relative humidity to calculate IWV. However, estimating IWV for forecasting applications is impossible with a GPS system. This paper introduces a methodology to predict IWV during normal days and severe cyclonic events using machine learning (ML) techniques. Rational quadratic Gaussian process regression (RQ-GPR) and neural network (NN) algorithms are considered for identifying suitable ML prediction algorithms over tropical conditions. Meteorological surface data like Pressure, Temperature, and relative humidity are given as input to the machine learning models. The IWV values computed from GPS are compared with the model's predicted values. RQ-GPR model is showing good accuracy with the IWV values computed from GPS against the NN model. The correlation coefficient (ρ) achieved for RQ-GPR is 0.93, and 0.86 is obtained for the NN model.
 The RMSE (Root Mean Square Error) of the predicted IWV value with RQ-GPR is better than the NN model. We have obtained mean square error (MSE) and mean absolute error (MAE) as 18.146 kg/m2 and 3.0762 kg/m2 for RQ-GPR and 27.509 kg/m2 and 3.9102 kg/m2 for the NN model which is showing RQ-GPR is a suitable model for forecasting applications. The HUDHUD cyclonic event that occurred in October 2014 is considered for testing the proposed ML algorithms. RQ-GPR model has better results in the Prediction of IWV than the NN model. The RMSE value obtained is 2.837 kg/m2 for RQ-GPR and 3.327 kg/m2 obtained from the NN model. The results indicate that the RQ-GPR model has more accuracy than the other IWV prediction models. The prediction results are helpful for meteorology, weather, and climatology studies and useful to improve the accuracy of the regional numerical weather prediction models.

Role of Government and Non-Governmental Organisations (NGOs) in Cyclone Recovery in Bangladesh

Immediate relief distribution activities are primarily focused on after a cyclonic event in Bangladesh, where proper long-term recovery and rehabilitation efforts are not strategized with much significance. This study concentrated on understanding and assessing the status and effectiveness of the post-cyclone recovery programmes to improve the lives of cyclone-affected households in southwestern Bangladesh. This study aims to examine the status and efficiency of Government and Non-government organisations (NGO) led cyclone recovery programmes for cyclone SIDR and cyclone AILA and identify the challenges that hindered the successful implementation of effective recovery programmes. The study reviewed existing literature on cyclone recovery in Bangladesh, including government and NGO reports, and conducted focus group discussions on cyclone-affected Dacope Upazila of Khulna. The finding indicates that the cyclone-affected community in southwestern Bangladesh has not recovered satisfactorily across all sectors and timescales from cyclone damages and continues to live in vulnerable conditions even after a decade of cyclonic events. The adopted recovery measures were not efficient and effective in returning to the everyday lifestyle of the affected people. Planned and coordinated recovery efforts should be executed with proper monitoring to ensure the effectiveness of post-cyclone recovery programmes.

Parameter Calibration to Improve the Prediction of Tropical Cyclones over the Bay of Bengal Using Machine Learning–Based Multiobjective Optimization

Abstract The prediction skill of a numerical model can be enhanced by calibrating the sensitive parameters that significantly influence the model forecast. The objective of the present study is to improve the prediction of surface wind speed and precipitation by calibrating the Weather Research and Forecasting (WRF) Model parameters for the simulations of tropical cyclones over the Bay of Bengal region. Ten tropical cyclones across different intensity categories between 2011 and 2017 are selected for the calibration experiments. Eight sensitive model parameters are calibrated by minimizing the prediction error corresponding to 10-m wind speed and precipitation, using a multiobjective adaptive surrogate model-based optimization (MO-ASMO) framework. The 10-m wind speed and precipitation simulated by the default and calibrated parameter values across different aspects are compared. The results show that the calibrated parameters improved the prediction of 10-m wind speed by 17.62% and precipitation by 8.20% compared to the default parameters. The effect of calibrated parameters on other model output variables, such as cyclone track and intensities, and 500-hPa wind fields, is investigated. Eight tropical cyclones across different categories between 2011 and 2018 are selected to corroborate the performance of the calibrated parameter values for other cyclone events. The robustness of the calibrated parameters across different boundary conditions and grid resolutions is also examined. These results will have significant implications for improving the predictability of tropical cyclone characteristics, which allows us to better plan adaptation and mitigation strategies and thus help in reducing the adverse effects of tropical cyclones on society.

Water Level Modulation of Wave Transformation, Setup and Runup Over La Saline Fringing Reef

AbstractCoral reefs represent an efficient natural mechanical coastal defense against ocean waves. The focus of this study is La Saline fringing coral reef, located in the microtidal West of La Réunion Island in the Indian Ocean, frequently exposed to Southern Ocean swell and cyclonic events. The aim is to provide a better understanding of the reef's coastal defense characteristics for several Southern Ocean swell events. Pressure sensors were placed across the reef to measure water level fluctuations and to study wave transformation. A numerical model (XBeach surfbeat), validated using field observations, was used to deepen understanding of wave transformation, wave setup and runup. Field measurements and model outputs show that as gravity waves dissipate over the reef, and frequency‐dependent dissipation of infragravity waves by bottom‐friction occurs, the reef acts as a low‐pass filter. Wave‐induced setup is found to be the dominant hydrodynamic component. Setup and runup are each 98% and 79% driven by the offshore significant wave height, and 2% and 21% driven by the tide. The modulation of the water level by setup is the main contributor to runup in the fringing reef. At semidiurnal timescales, setup and runup are in antiphase with tidal variations as lower water levels result in higher gravity wave energy dissipation, setup and runup. Simple‐to‐use transfer functions relating incident wave characteristics to these hydrodynamic components are proposed. The effects of bottom friction and water level on the defensive capacity of the coral reef highlight future implications of structural damage and sea level rise.

Lateral load capacity of the common steel stud wall framing braced bays in Australia's Northern Territory

Construction within Australia's northern coastal region has undergone many changes over the years to adapt to its tropical climate, which is prone to devastating cyclonic events. Steel stud wall framing (SSWF) is used as a standard construction method for many residential and commercial structures within the Northern Territory. The stability of SSWF structures is primarily achieved by utilising several braced bays for external and internal shear walls to resist wind loading, which is often a critical design factor. However, the lateral load capacity of these SSWF braced bays is estimated as a value based on conservative and fundamental static analysis, which does not account for the complexity of analysing cold-formed channel and welded thin wall steel sections. This paper investigates lateral load capacity, modes of failure, and lateral deflection of a common SSWF braced bay configuration used in NT through full-scale experimental testing. Finite element simulations then have been conducted to compare the experimental results with theoretical capacities and failure modes. After calibration, the simulation model is used to determine the lateral load capacity of other SSWF braced bay configurations. The common failure modes were found to be the tensile failure of the stud flange and failure of the weld between the tensile stud and bottom plate. Results also provide a reliable evaluation of the lateral resistance of the common SSWF configurations in NT housing.

Generating reliable estimates of tropical-cyclone-induced coastal hazards along the Bay of Bengal for current and future climates using synthetic tracks

Abstract. Deriving reliable estimates of design water levels and wave conditions resulting from tropical cyclones is a challenging problem of high relevance for, among other things, coastal and offshore engineering projects and risk assessment studies. Tropical cyclone geometry and wind speeds have been recorded for the past few decades only, thus resulting in poorly reliable estimates of the extremes, especially in regions characterized by a low number of past tropical cyclone events. In this paper, this challenge is overcome by using synthetic tropical cyclone tracks and wind fields generated by the open-source tool TCWiSE (Tropical Cyclone Wind Statistical Estimation Tool) to create thousands of realizations representative of 1000 years of tropical cyclone activity for the Bay of Bengal. Each of these realizations is used to force coupled storm surge and wave simulations by means of the processed-based Delft3D Flexible Mesh Suite. It is shown that the use of synthetic tracks provides reliable estimates of the statistics of the first-order hazard (i.e., wind speed) compared to the statistics derived for historical tropical cyclones. Based on estimated wind fields, second-order hazards (i.e., storm surge and waves) are computed that are generated by the first-order hazard of wind. The estimates of the extreme values derived for wind speed, wave height and storm surge are shown to converge within the 1000 years of simulated cyclone tracks. Comparing second-order hazard estimates based on historical and synthetic tracks shows that, for this case study, the use of historical tracks (a deterministic approach) leads to an underestimation of the mean computed storm surge of up to −30 %. Differences between the use of synthetic versus historical tracks are characterized by a large spatial variability along the Bay of Bengal, where regions with a lower probability of occurrence of tropical cyclones show the largest difference in predicted storm surge and wave heights. In addition, the use of historical tracks leads to much larger uncertainty bands in the estimation of both storm surges and wave heights, with confidence intervals being +80 % larger compared to those estimated by using synthetic tracks (probabilistic approach). Based on the same tropical cyclone realizations, the effect that changes in tropical cyclone frequency and intensity, possibly resulting from climate change, may have on modeled storm surge and wave heights was computed. As a proof of concept, an increase in tropical cyclone frequency of +25.6 % and wind intensity of +1.6 %, based on literature values and without accounting for uncertainties in future climate projection, was estimated to possibly result in an increase in storm surge and wave heights of +11 % and +9 %, respectively. This suggests that climate change could increase tropical-cyclone-induced coastal hazards more than just the actual increase in maximum wind speeds.

Synoptic Climatology of Air Temperatures behind Extreme Cyclone Events over the Bay of Bengal of Southern Bangladesh

Cyclones have occurred more frequently in recent decades in a disaster-prone country like Bangladesh. Twenty-two (22) extreme cyclone events that occurred from 1975-2014 were investigated in this study with respect to air temperature climatology. Air temperature, sea level pressure, rainfall, relative humidity (Rhum), and sunshine hours (SShr) have been analyzed to find out the impact of air temperatures behind cyclogenesis. Historical cyclone data were obtained from Bangladesh Meteorological Department; Bangladesh Bureau of Statistics and Disaster Preparedness Centre (AIT). Historical weather data was collected from the Climate Division of BMD. Principal Component Analysis (PCA) and Clustering were used to find out the whole atmospheric air temperature impact on cyclogenesis. The NCEP–NCAR reanalysis data were used to find out the distribution of air temperature anomaly over Bangladesh and Bay of Bengal (BB). Among the 22 cyclones, cluster 2 belongs to 9 cyclones and cluster 3 comprises of 12 cyclones. Clusters 2 and 3 indicate that temperatures of about 34 to 35°C were mostly responsible for the formation of a total of 21 cyclones from 1975 to 2014. The existence of a relatively cooler zone (strong negative anomaly) near to surface level, in association with a relatively warmer zone (strong positive anomaly) at 850, 700, 500, and 300hPa level were firmly responsible for cyclogenesis over BB. The larger, warmer air mass in the upper atmosphere could have a significant impact on the development of huge instability throughout the entire atmospheric column, potentially leading to the formation of extreme weather phenomena such as severe cyclones in southern Bangladesh.

Hydrodynamic Modelling of Storm Surge with Modified Wind Fields along the East Coast of India

Propagation of tropical cyclones and their landfall along the coast affect the livelihood of the coastal community with loss of life, and Bay of Bengal is particularly vulnerable as past disasters have shown. The present study investigates the effects of tropical cyclones namely Phailin, Hudhud and Vardah during its landfall along the East Coast of India. Numerical modelling of storm surges primarily depends on the wind characteristics, for which, the performance of the simulated storm surge from cyclone wind and pressure fields of ECMWF is examined with Telemac-2D. The quality of the wind field is enhanced by applying available wind modification techniques, such as the parametric cyclone wind model superposed with ECMWF wind field, and the direct modification of ECMWF wind field. The superposed wind speed is found in good agreement with the measured wind data. The hydrodynamic simulation was then performed for the cyclonic events for the computation of the storm surge. The predictions agree well with the observed surges for the simulations performed with modified wind fields. The error reduced from 15 cm to 6 cm and model skill improved by 3% leading to a correlation coefficient of 0.98.

Hybrid three-dimensional modelling for reservoir fluorescent dissolved organic matter risk assessment

ABSTRACT A coupled data-driven and 3-dimensional (3D) process-based fluorescent dissolved organic matter (fDOM) prediction model was developed for a shallow, subtropical Australian reservoir. The extent to which reservoir water volume, inflow, and wind conditions affect the fDOM transport dynamics during cyclonic weather events was assessed through scenario analysis and a data-driven Bayesian network (BN) approach. The analysis shows that (a) inflow plumes are the main sources of fDOM during heavy rainfall; (b) the concentration of fDOM near the dam wall is related to rainfall intensity; (c) higher reservoir volumes reduce the rate of increase and peak of fDOM concentration during rainfall events; and (d) fDOM transport to the dam wall is strongly influenced by the prevailing wind direction. A naïve BN developed for fDOM assessment displayed a strong sensitivity of the peak fDOM value to rainfall-related characteristics while the lag time between rainfall event and fDOM peak at the dam wall was highly sensitive to reservoir water volume and wind speed. The hybrid modelling approach provides both new information on 3D fDOM transport in reservoirs during extreme weather events through the model application and an easy-to-interpret, instantaneous modelling output for treatment operators through the BN modelling component. The BN modelling is an essential addition for water treatment operators to promptly predict the impacts of extreme weather events and proactively adjust treatment operations without the computational time burden of a 3D process-based model.

Future changes in extreme precipitation over the San Francisco Bay Area: Dependence on atmospheric river and extratropical cyclone events

Extreme precipitation poses a major challenge for local governments, including the City and County of San Francisco, California, as flooding can damage and destroy infrastructure and property. As the climate continues to warm, reliable future precipitation projections are needed to provide the best possible information to decision makers. However, future changes in the magnitude of extreme precipitation are uncertain, as current state-of-the-art global climate models are typically run at relatively coarse horizontal resolutions that require the use of convective parameterization and have difficulty simulating observed extreme rainfall rates. Here, we performed ensembles of convection-permitting regional climate model simulations to investigate how five historically impactful extreme precipitation events over the San Francisco Bay Area could change if similar events occurred in future climates. We found that changes in storm-total precipitation depend strongly on storm type. Precipitation associated with an atmospheric river (AR) accompanied by an extratropical cyclone (ETC) is projected to increase at a rate exceeding (by up to 1.5 times) the theoretical Clausius Clapeyron scaling of 6–7% per °C warming. On the other hand, future precipitation changes are weak or negative for events characterized by an AR only, despite increases in precipitable water and integrated vapor transport that are similar to those of the co-occurring AR and ETC events. The differences in the sign of future precipitation change between AR-only events and co-occurring AR and ETC events is instead linked with changes in mid-tropospheric vertical velocity. Given that the majority of observed ARs are associated with an ETC, this research has important implications for future precipitation impacts over the Bay Area, as it indicates that storm-total precipitation associated with the most common type of storm event may increase by up to 26–37% in 2100 relative to historical.

Unified Wind-Wave Growth and Spectrum Functions for All Water Depths: Field Observations and Model Results

Abstract Wind-wave development is governed by the fetch- or duration-limited growth principle that is expressed as a pair of similarity functions relating the dimensionless elevation variance (wave energy) and spectral peak frequency to fetch or duration. Combining the pair of similarity functions, the fetch or duration variable can be removed to form a dimensionless function of elevation variance and spectral peak frequency, which is interpreted as the wave energy evolution with wave age. The relationship is initially developed for quasi-neural stability and quasi-steady wind forcing conditions. Further analyses show that the same fetch, duration, and wave-age similarity functions are applicable to unsteady wind forcing conditions, including rapidly accelerating and decelerating mountain gap wind episodes and tropical cyclone (TC) wind fields. Here it is shown that with the dimensionless frequency converted to dimensionless wavenumber using the surface wave dispersion relationship, the same similarity function is applicable in all water depths. Field data collected in shallow to deep waters and mild to TC wind conditions and synthetic data generated by spectrum model computations are assembled to illustrate the applicability. For the simulation work, the finite-depth wind-wave spectrum model and its shoaling function are formulated for variable spectral slopes. Given wind speed, wave age, and water depth, the measured and spectrum-computed significant wave heights and the associated growth parameters are in good agreement in forcing conditions from mild to TC winds and in all depths from deep ocean to shallow lake. Significance Statement This paper presents a growth function and spectrum model to describe wind-wave development in all water depths. Their applicability covers a wide range of wind forcing conditions including steady, accelerating, decelerating, and tropical cyclone events. Support for the unified spectrum model and growth function is presented with field observations and numerical computations.

A Systematic Revision of the NFIP Claims Hazard Data in Florida for Flood Risk Assessment

The hazard components of National Flood Insurance Program (NFIP) claims data in Florida were systematically analyzed and revised in the current study. The provided fields in NFIP claims data are not always complete or accurate and are often missing. The authors associated each claim to a proper flood hazard event by updating the provided catastrophe number using the National Hurricane Center HURDAT2 (best track data). The claims with presumably incorrect cause of loss fields were identified and revised by adding a variety of other available information to claims data. These datasets included tropical cyclone events, rainfall maxima, and distances to the nearest coast. The enhanced information assisted in identifying the cause or likelihood of a hazard event or attributing a particular hazard event to a loss claim. The revised NFIP claims data will be intensively used to validate the outcomes from flood hazard (i.e., surge, wave and inland flooding) models and to develop a flood vulnerability model in the forthcoming Florida Public Flood Loss Model (FPFLM).

Previous Shoreline Dynamics Determine Future Susceptibility to Cyclone Impact in the Sundarban Mangrove Forest

Extreme weather events are a cause of mangrove forest loss and degradation globally. Almost half of the world’s mangroves are found in the tropical cyclone belt, and forests often experience disturbance in structure, functioning and ecosystem service provision. Understanding the factors that increase the vulnerability of mangroves to such disturbances is a challenge. Using a novel remote sensing analysis combining water class change with vegetation classification, we showed that mangrove loss across multiple cyclone events is influenced by previous erosion history, suggesting that the prior state of the coastline affects susceptibility to future disturbance events. During Cyclone Amphan in May 2020, more than 1,200 km2 of mangroves were damaged and 40.6 km2 of shoreline was lost. Cyclone Amphan caused the most damage out of three recent cyclones, with the most mangrove loss (18.8%) experienced along shorelines that were eroding over the past 35 years. This can be explained by the long-term effect of erosion on the overall intertidal morphology of the shoreline. Landscape-scale mangrove management, particularly of sediment budgets is essential to switch previously eroding mangroves to a state where they can withstand cumulative storm impacts.

Characterization of tropical cyclones to identify the response based design metocean conditions for an FPSO mooring system

Design metocean conditions (DMC) for a single-point moored weathervaning vessel exposed to the cyclonic environment are obtained by characterising the tropical cyclones on the basis of extreme responses induced in its mooring system. Determination of design metocean conditions, as combinations of wave, wind and current associated with the extreme response, is a multivariate problem that does not have a unique solution. Its probabilistic nature dictates that the design metocean condition should be a short-term sea state which is most probable to occur while at the same time inducing the extreme N-year response of the system. This study aims at the development of a methodology for obtaining the DMC for a mooring system of a weathervaning vessel by characterizing the tropical cyclonic environment based on the mooring responses. First, a method for identifying the DMCs within the metocean history is described, along with its limitations. Then, the storm characterisation approach is introduced, based upon the maximum responses of the system rather than the extreme sea states in a particular event. The metocean conditions at a specific location during the passage of a cyclone are described by a set of dimensionless shape functions, with their main parameters linked to the most probable mooring tension experienced during each cyclonic event. It is further determined that for a weathervaning floating system, cyclones should be separated into two distinct types according to the relative wave-wind direction highly affecting the mooring response. The cyclone shape functions are generalized to describe the characteristic cyclones at the N-year return period response, which are determined by considering a limited group of storms inducing the mooring responses close to the N-year response. By averaging the dimensionless shape functions for each of the two cyclone types, the characteristic cyclones can be synthesized to describe two types of events, where the N-year mooring response is most likely to occur. The robustness of the method is checked through a case study, in which the characteristic 5-year, 10-year and 100-year DMCs are produced for a mooring system of a floating production, storage and offloading vessel (FPSO) permanently moored offshore Australia. By using a 44-year hindcast time history of cyclonic metocean conditions, the DMCs were developed from the response-based synthesized N-year cyclones and compared with the specific short-term conditions retrieved from the same time history. An alternative averaging method for the cyclone shape functions is also considered and results are discussed.

Spherical Poisson point process intensity function modeling and estimation with measure transport

Recent years have seen an increased interest in the application of methods and techniques commonly associated with machine learning and artificial intelligence to spatial statistics. Here, in a celebration of the ten-year anniversary of the journal Spatial Statistics, we bring together normalizing flows, commonly used for density function estimation in machine learning, and spherical point processes, a topic of particular interest to the journal’s readership, to present a new approach for modeling non-homogeneous Poisson process intensity functions on the sphere. The central idea of this framework is to build, and estimate, a flexible bijective map that transforms the underlying intensity function of interest on the sphere into a simpler, reference, intensity function, also on the sphere. Map estimation can be done efficiently using automatic differentiation and stochastic gradient descent, and uncertainty quantification can be done straightforwardly via nonparametric bootstrap. We investigate the viability of the proposed method in a simulation study, and illustrate its use in a proof-of-concept study where we model the intensity of cyclone events in the North Pacific Ocean. Our experiments reveal that normalizing flows present a flexible and straightforward way to model intensity functions on spheres, but that their potential to yield a good fit depends on the architecture of the bijective map, which can be difficult to establish in practice.

ДОЛГОВРЕМЕННАЯ ИЗМЕНЧИВОСТЬ ОПРОКИДЫВАНИЯ ВОЛН РОССБИ В РАЙОНЕ СУБТРОПИЧЕСКОГО СТРУЙНОГО ТЕЧЕНИЯ

Climatology and variability of anticyclonic (AC-type) and cyclonic (C-type) wave breaking in the region of the subtropical jet stream are investigated using the previously developed method for identifying and clustering Rossby wave breaking events. Potential vorticity at an isentropic surface of 350 K from the ERA-Interim and ERA5 reanalyses are used. The results of applying the methods for the two reanalyses are similar. However, there is a high inconsistency for cyclonic wave breaking events, especially in summer. The maximum for both types of wave breaking is registered in summer. There are two main maximum areas for the AC type: Atlantic and Pacific. A specific feature of the C type is the climatic maximum in East Asia, probably due to the summer development of the East Asian monsoon. The intensity of the AC-type wave breaking for the entire Northern Hemisphere during the year demonstrates a positive trend. Seasonal changes of the AC type were also consistent for the two reanalyses, global changes are less consistent for cyclonic wave breakings, and significant trends are basically absent. The regional analysis revealed that the frequency of AC-type wave breaking in summer decreases over the Eastern Atlantic and increases over Europe. The agreed and possibly related changes in the AC and C types are recorded in the Asia-Pacific. In summer, there is a decrease in the C-type occurrence over East Asia and an increase in the AC-type occurrence over the Eastern Pacific. However, these changes were found only for the ERA-Interim and require further analysis and interpretation.