Quantifying the Contribution of Track Changes to Interannual Variations of North Atlantic Intense Hurricanes

Previous studies have linked interannual variability of tropical cyclone(TC)intensity in the North Atlantic basin(NA)to Sahelian rainfall,vertical shear of the environmental flow,and relative sea surface temperature(SST).In this study,the contribution of TC track changes to the interannual variations of intense hurricane activity in the North Atlantic basin is evaluated through numerical experiments.It is found that that observed interannual variations of the frequency of intense hurricanes during the period 1958–2017 are dynamically consistent with changes in the large-scale ocean/atmosphere environment.Track changes can account for~50%of the interannual variability of intense hurricanes,while no significant difference is found for individual environmental parameters between active and inactive years.The only significant difference between active and inactive years is in the duration of TC intensification in the region east of 60°W.The duration increase is not due to the slow-down of TC translation.In active years,a southeastward shift of the formation location in the region east of 60°W causes TCs to take a westward prevailing track,which allows TCs to have a longer opportunity for intensification.On the other hand,most TCs in inactive years take a recurving track,leading to a shorter duration of intensification.This study suggests that the influence of track changes should be considered to understand the basin-wide intensity changes in the North Atlantic basin on the interannual time scale.

ANALYSES OF THE ANNUAL FREQUENCY ANOMALIES OF TYPHOONS AND HURRICANES IN 1998

In 1998, the annual frequency of typhoon (including tropical storms) genesis created a minimum value — 14, far lower than the minimum of 20 in 1950 over North-West Pacific, while in the Atlantic Ocean, the annual frequency of hurricanes (including the tropical storm) created a maximum value — 14, far higher than the average number — 9.2. In this paper, an analysis on the relationship between the generation of Typhoon, Hurricane and the Cross-Equatorial Flow was done by using the NCEP/NCAR reanalysis data for 1979 – 1995. It is pointed out that the anomalies of the CEF over the Pacific and Atlantic Ocean is the main cause for the 1998 annual frequency anomalies of Typhoon and Hurricane, respectively.

Cross - equatorial flow and its effects on the hurricanes occurrence over the Southern Hemisphere

Channels of cross - equatorial flow and their characteristics Winds at every 5 deg. grid point from 30°E to 180° over the equator at 850 hPa and 200hPa from December 1984 to February 1985 have been separated into U(zonal wind) andV(meridional wind).The V component has been used to represent cross- equatorial flow. FromFig. 1 we obtained that as during the Northern summer,there are also severa1 regions in which

Formation and Prevention of Hurricanes,Typhoons and Cyclones

Hurricanes,typhoons and cyclones are the most destructive weather systems.In order to mitigate the disasters caused by these storms,it is necessary to clarify the cause and activity rule of these storms.However,the formation of hurricanes,typhoons and cyclones as well as the cause of their path and strength changes still remains the major unsolved problems in today’s world.Fortunately,the author has recently studied the formation and activity of polar vortices,therefore can reveal the formation and current driving warm core structure of hurricanes,typhoons and cyclones,which plays an important guiding role in preventing major disasters caused by them.The author finds that all hurricanes,typhoons and cyclones are formed by polar vortices pulled by the moon.In order to prevent hurricanes from raging along the east coast of the United States or cyclones from setting wildfires in western United States,the potentially dangerous vortex genesises near Baffin Island and those over northeastern Siberia should be monitored and weakened in the month before they prevail;in order to prevent typhoons from ravaging the Northwest Pacific or South China Sea,the potentially dangerous vortex genesises over northeastern Siberia should be monitored and weakened in the month before they prevail;in order to prevent cyclones from raging over the South Indian Ocean or the Bay of Bengal,the potentially dangerous vortex genesises in Antarctic should be monitored and weakened in the month before they prevail;in order to avoid abnormal cold in late winter or early spring in the Northern Hemisphere,the potentially dangerous Arctic cold vortex genesises near Baffin Island and those over northeastern Siberia should be monitored and weakened in the month before they prevail.

A Brief Parametric Analysis of Catastrophic or Disastrous Hurricanes That Have Hit the Florida Keys between 1900 and 2000

The most intense and catastrophic hurricanes on record to hit the Florida Keys during 1900 to 1950 were in 1919, and 1935. From 1950 to 2000, the most intense hurricanes to hit or affect the Florida Keys were in 1960, 1965, and 1992. In this paper, we will present a brief parametric analysis of the hurricanes that have hit the Florida Keys in the last 100 years. This analysis will include the descriptive statistics, best fit probability distribution of the latitude of the catastrophic hurricanes and a confidence interval that detects the average latitude of hurricanes (category 3 or higher) which have hit the Florida Keys in the last 100 years.

Resilience in a Mexican Pacific Mangrove after Hurricanes: Implications for Conservation Restoration

High resilience is a mangrove trait that is compatible with life in a dynamic environment, however, catastrophic disturbance can lead to the entire forest structure being re-defined. In the Pochutla district of Oaxaca, two hurricanes made landfall in 1997 and one more in 2012. Following the 1997 hurricanes, extensive mangrove restoration was carried out in the study area. A cohort of Rhizophora mangle saplings planted in 2007 showed 10% mortality during the first year after transplantation, an average growth of 39 cm, and a positive association between growth rate and the level of water in the lagoon. Following Hurricane Carlotta of 2012, measurements of structural impact and tree mortality were taken in restored R. mangle stands and in naturally regenerated patches of Laguncularia racemosa. The role of tree girth in R. mangle susceptibility to wind damage was also investigated. The stands of R. mangle suffered 80% reduction in stem density and 86% loss of basal area, whereas the corresponding values for L. racemosa were 26% and 15%, respectively. Within stands of R. mangle, mortality conserved a positive relationship with structural impact categories and the frequency of snapped stems was segregated across girth classes. The results suggest that L. racemosa has greater resilience to hurricane damage, which has some consistency with previous research and implications for conservation restoration protocols. In order to promote a system with higher resilience, we recommend an on-going restoration effort with mixed mangrove species.

Analytical Models for Hurricanes

A two-layer theoretical model of hurricanes traveling (quasi-) steadily over open seas has been developed. The use of coherency concept allowed avoiding the common turbulent approximations, except a thin sub-layer near the air/sea interface. The model analytically describes 3D distributions of dynamic and thermodynamic variables in hurricanes and analyzes processes of evaporation and condensation. Using this modeling, the following fundamental problems were naturally resolved-change in the cyclonic/anti-cyclonic directions of hurricane rotation and the directions of radial wind in lower and upper parts of hurricane;increase in wind angular momentum in hurricane boundary layer;dramatic effect of ocean spray and its radial distribution;and a high increase in temperature at the upper region of boundary layer. Additionally, integral balances allowed expressing the governing parameters of field variables via two external parameters, the sailing wind and temperature of a warm air band, in which direction the hurricane travels. A rude model for the hurricane genesis and maturing has also been developed.

Possibility of Predicting Category-5 North Atlantic Hurricanes

Category-5 hurricanes are the most devastating from the standpoint of human and economic losses. The occurrence of this kind of hurricane is believed to be of quasi-random nature, so it is very difficult to predict them well in advance. Warnings at this regard are generally given in the course of their development. We propose here, that there are some inherently periodicities of the phenomena that allow to predict category-5 hurricanes, even with some years of anticipation. For our study, we consider the North Atlantic category-5 hurricanes since 1920. We consider in this study data of the SST （sea surface temperature） of the North Atlantic Ocean as a representative parameter of hurricane activity. Then, by means of the wavelet analysis, we determine the dominant oscillation periods and establish correspondence rules using fuzzy logic. The wavelet power spectrum yields the following dominant periodicities： 0.5, 1, 3, 11, 22 and 32 years. The fuzzy logic searches for associations between the hurricanes occurrence and the behavior of the harmonics. Such correspondence rules lead us to restrict dates of possible hurricane occurrence. Interpolation of the periodic behavior allows for a good reconstruction of past hurricanes dates since 1920, as well as extrapolation to predict dates of occurrence in the future. We conclude that the conditions for the formation of the next category-5 hurricane in the North Atlantic may occur during the seasons of 2015-2017 with the highest probability in 2017.

Thermodynamics of Hurricanes Revisited

Hurricanes and tropical storms are heat engines operating between warm tropical oceans and the cold upper troposphere. The purpose of this article is to examine the existing theories for hurricanes and tropical storms, and to discuss their validity. It is argued that contrary to previous claims that hurricanes are Carnot engines, these systems operate at efficiencies considerably below their maximum thermodynamic efficiency. As such, the validity of the current theories of thermodynamics of hurricanes remains questionable, and the phenomenon continues to be a geophysical enigma.

Weathering the Storm: Mitigating Hurricanes with Ground-Based CCN and Lightning

This research introduces a groundbreaking methodology aimed at mitigating storm and hurricane intensity through the application of a ground-based, manually operated Cloud Condensation Nuclei (CCN) Generator. To meet the demand for more comprehensive context and rationale, this study explores the escalating challenges presented by the growing intensity of hurricanes, exemplified by Hurricane IAN (2022). The controlled release of environmentally friendly aerosols into the atmosphere, achieved by combusting selected wood pieces and organic edible materials, is a pivotal response to the escalating threat of extreme weather events. By generating CCN, the novel approach seeks to augment positive lightning in the eyewall, providing a potential solution to the intensification of hurricanes. Results illustrate the successful implementation of the methodology, with released aerosols effectively reaching the clouds for seeding, thus contributing to the modification of convection in the outer wall of Hurricane IAN and consequent intensity reduction. Rigorous experiments, incorporating considerations of various parameters such as wind patterns and the experimental location in Sarasota City, emphasize the scientific rigor applied to weakening Hurricane IAN. This comprehensive approach not only holds promise in mitigating hurricane intensity but also sheds light on the potential impact of cloud seeding in reducing the severity of future hurricanes, addressing a critical need for sustainable solutions to climate-related challenges.

A Wavelet-Based Deep Learning Framework for Predicting Peak Intensity of Hurricanes in the Atlantic Ocean

Every year, hurricanes pose a serious threat to coastal communities, and forecasting their maximum intensities has been a crucial task for scientists. Computational methods have been used to forecast the intensities of hurricanes across varying time horizons. However, as climate change has increased the volatility of the intensities of recent hurricanes, newer and adaptable methods must be devised. In this study, a framework is proposed to estimate the maximum intensity of tropical cyclones (TCs) in the Atlantic Ocean using a multi-input convolutional neural network (CNN). From the Atlantic hurricane seasons of 2000 through 2021, over 100 TCs that reached hurricane-level wind speeds are used. Novel algorithms are used to collect and preprocess both satellite image data and non-image data for these TCs. Namely, Discrete Wavelet Transforms (DWTs) are used to decompose individual bands of satellite image data, eliminating noise and extracting hidden frequency details before training. Validation tests indicate that this framework can estimate the maximum wind speed of TCs with a root mean square error of 15 knots. This framework provides preliminary predictions that can supplement current computational methods that would otherwise not be able to account for climate change. Future work can be done by forecasting with time constraints, and to provide estimations for more metrics such as pressure and precipitation.

A digital twin framework for efficient electric power restoration and resilient recovery in the aftermath of hurricanes considering the interdependencies with road network and essential facilities

The community’s resilience in the face of natural hazards relies heavily on the rapid and efficient restoration of electric power networks,which plays a critical role in emergency response,economic recovery,and the func-tionality of essential lifeline and social infrastructure systems.Leveraging the recent data revolution,the digital twin(DT)concept emerges as a promising tool to enhance the effectiveness of post-disaster recovery efforts.This paper introduces a novel framework for post-hurricane electric power restoration using a hybrid DT approach that combines physics-based and data-driven models by utilizing a dynamic Bayesian network.By capturing the complexities of power system dynamics and incorporating the road network’s influence,the framework offers a comprehensive methodology to guide real-time power restoration efforts in post-disaster scenarios.A discrete event simulation is conducted to demonstrate the proposed framework’s efficacy.The study showcases how the electric power restoration DT can be monitored and updated in real-time,reflecting changing conditions and facilitating adaptive decision-making.Furthermore,it demonstrates the framework’s flexibility to allow decision-makers to prioritize essential,residential,and business facilities and compare different restoration plans and their potential effect on the community.

Deep learning for real-time social media text classification for situation awareness-using Hurricanes Sandy,Harvey,and Irma as case studies

Social media platforms have been contributing to disaster management during the past several years.Text mining solutions using traditional machine learning techniques have been developed to categorize the messages into different themes,such as caution and advice,to better understand the meaning and leverage useful information from the social media text content.However,these methods are mostly event specific and difficult to generalize for cross-event classifications.In other words,traditional classification models trained by historic datasets are not capable of categorizing social media messages from a future event.This research examines the capability of a convolutional neural network(CNN)model in cross-event Twitter topic classification based on three geo-tagged twitter datasets collected during Hurricanes Sandy,Harvey,and Irma.The performance of the CNN model is compared to two traditional machine learning methods:support vector machine(SVM)and logistic regression(LR).Experiment results showed that CNN models achieved a consistently better accuracy for both single event and crossevent evaluation scenarios whereas SVM and LR models had lower accuracy compared to their own single event accuracy results.This indicated that the CNN model has the capability of pre-training Twitter data from past events to classify for an upcoming event for situational awareness.

AN INTRODUCTION TO THE NASA EAST PACIFIC ORIGINS AND CHARACTERISTICS OF HURRICANES(EPOCH) FIELD CAMPAIGN

Over the past fi ve years, tropical activity in the East Pacifi c has increased, while declining in the Atlantic Basin. In addition, during El Ni?o years, warmer than average sea surface temperatures further increase the likelihood of tropical cyclone formation in the East Pacifi c. Hurricane fi eld campaigns used the Ku-/Ka-band HighAltitude Wind and Rain Airborne Profi ler(HIWRAP) radar on the Global Hawk(GH) unmanned aircraft, in GRIP(Genesis and Rapid Intensifi cation Processes 2010), HS3(Hurricane and Severe Storm Sentinel 2012-14), and the NOAA Sensing Hazards with Operational Unmanned Technology(SHOUT 2015-16) fi eld campaigns. Although originally designed for the GH, the X-band high-altitude RADar(EXRAD) has yet to be integrated and fl own on an unmanned aerial vehicle. EXRAD will provide data with less attenuation of signal over deep convection as well as better estimates of three-dimensional winds with its nadir-pointing beam. As part of the NASA Hand On Project Experience(HOPE) Training Opportunity, our team proposed to fl y the AV-6 GH aircraft with the EXRAD radar, the High Altitude MMIC Sounding Radiometer(HAMSR), and NOAA Advanced Vertical Atmospheric Profi ling System(AVAPS) dropsondes to investigate genesis and/or rapid intensifi cation(RI) of an East Pacifi c hurricane by measuring both the environment and interior structures. Information on planned activities primarily focused on the EXRAD high-altitude radar integration for the July-August 2017 science fl ight will be presented.

Nonlinear interaction of axisymmetric circulation and nonaxisymmetric disturbances in hurricanes

The nonlinear interaction of axisymmetric circulation and nonaxisymmetric disturbances in hurricanes is numerically studied with a quasigeostrophic barotropic model of a higher resolution. It is pointed out that the interaction may be divided into two categories. In the first category, nonaxisymmetric disturbances decay, the coordinate locus of maximum relative vorticity ζmax is seemingly unordered, and the central pressure of hurricane rises; while in the second one, nonaxisymmetric disturbances develop, the locus of ζmax shows an ordered limit cycle pattern, and the central pressure falls remarkably. A succinct criterion is given to judge which category the interaction belongs to, i.e. the vortex beta Rossby number at the initial time Rβ< 1 belongs to the decaying category and Rβ> 1 to the developing one. Finally, practical applications of theoretical results of the rotational adaptation process presented by Zeng and numerical results in this paper to the hurricane intensity prediction in China are also discussed.

Assessing impacts of energy storage on resilience of distribution systems against hurricanes

This paper develops a comprehensive framework to analyze the impact of energy storage on improving the resilience of distribution systems against hurricanes.This paper first develops a spatio-temporal model of progressing hurricane when making landfall that can be used to anticipate outage scenarios caused by the gust-wind speed.An optimization model is then developed for optimizing the operation of distribution systems during hurricane that captures both pre-outage and post-outage network operation constraints.Numerical simulations are performed on the modified IEEE 33-bus distribution system with real hurricane data in Houston to demonstrate the effectiveness of the proposed model.

三维变分同化机载雷达资料对飓风预报的影响研究——2012年Isaac试验

随着气旋内部资料(Inner core data)在热带气旋预报中的使用,其重要性逐渐受到人们越来越多的关注。为了研究该资料中尾部机载雷达(Tail Doppler Radar,TDR)资料在业务系统中的应用效果,本文利用2012年飓风等级热带气旋Isaac期间的TDR资料,采用业务HWRF(Weather Research and Forecasting model for Hurricane)数值模式与业务GSI(Grid-point Statistical Interpolation system)三维变分同化(Three-Dimensional Variational Data Assimilation,3DVar)系统对TDR资料进行了同化,展开了一系列预报试验,并对其效果进行了分析和研究。结果表明与HWRF的业务预报相比,GSI系统同化TDR资料后对热带气旋的路径和强度预报有明显改进;但其同化效果同时也表明业务三维变分中的静态背景误差协方差在TDR资料的应用中仍需要进一步的改进。

Linkage between the Atlantic Tropical Hurricane Frequency and the Antarctic Oscillation in the Western Hemisphere

To examine the zonal asymmetry of the Antarctic oscillation (AAO), different portions of the AAO from June to October (JJASO) in the interannual variability of the Atlantic tropical hurricanes number (ATHN) are documented in this research. It follows that the AAO in the Western Hemisphere (AAOWH) is positively correlated with the ATHN, at 0.36 during the period of 1871-1998 and 0.42 during the period of 1949-98. After removing the linear regressions on the Southern Oscillation Index (SOI) in all time series, the above correlation coefficients are 0.25 and 0.30, respectively. The underlying mechanisms are studied through analyses of the atmospheric general circulation variability associated with the AAOWH. It turns out that the positive (negative) phase of JJASO AAOWH corresponds with several factors: decreased (increased) vertical zonal wind shear magnitude, low-level anomalous convergence (divergence), high-level anomalous divergence (convergence), and warmed (cooled) sea surface temperature in the tropical Atlantic. Therefore, the positive (negative) phase of JJASO AAOWH is favorable (unfavorable) to the tropical hurricane genesis.

Measuring Capacity for Resilience among Coastal Counties of the U. S. Northern Gulf of Mexico Region

Many have voiced concern about the long-term survival of coastal communities in the face of increasingly intense storms and sea level rise. In this study we select indicators of key theoretical concepts from the social-ecological resilience literature, aggregate those indicators into a resilience-capacity index, and calculate an index score for each of the 52 coastal counties of Louisiana, Texas, Mississippi, Alabama and Florida. Building upon Cutter’s Social Vulnerability Index work [1], we use Factor Analysis to combine 43 variables measuring demographics, social capital, economic re- sources, local government actions, and environmental conditions within the counties. Then, we map the counties’ scores to show the spatial distribution of resilience capacities. The counties identified as having the highest resilience capaci- ties include the suburban areas near New Orleans, Louisiana and Tampa, Florida, and the growing beach-tourist com- munities of Alabama and central Florida. Also, we examine whether those counties more active in oil and gas develop- ment and production, part of the region’s “energy coast”, have greater capacity for resilience than other counties in the region. Correlation analyses between the resilience-capacity index scores and two measures of oil and gas industry ac- tivity (total employment and number of business establishments within five industry categories) yielded no statistically significant associations. By aggregating a range of important contextual variables into a single index, the study demonstrates a useful approach for the more systematic examination and comparison of exposure, vulnerability and capacity for resilience among coastal communities.

Synergistic effects of tropical cyclones on forest ecosystems:a global synthesis

Tropical cyclones are large-scale strong wind disturbance events that occur frequently in tropical and subtropical coastal regions and often bring catastrophic physical destruction to ecosystems and economic disruption to societies along their paths. Major tropical cyclones can infrequently move into the midaltitudes and inland areas. Ecologically, tropical cyclones have profound impacts on diversity, structure, succession and function of forest ecosystems. The ecological effects are both dramatic and subtle. The dramatic effects can be visible, noticeable and to some extent predictable over the short-term and relatively well documented in the literature. However, the subtle effects are often invisible, complex and at smaller scale relatively unpredictable in the long-term. Many factors, meteorologic, topographic and biologic, simultaneously interact to influence the complexity of patterns of damage and dynamics of recovery. I present a global synthesis on the effects of tropical cyclones on forest ecosystems and the complexity of forest responses, with particular attention on the response to large hurricanes in the neotropics and the temperate North America, and strong typhoons on the subtropical and temperate forests in the East and Southeast Asia. Four major aspects provide on organizational framework for this synthesis：（1） consistent damage patterns,（2） factors that influence response patterns and predict damage risks,（3） complexity of forest responses and recovery, and（4） the long-term effects. This review reveals highly variable and complex effects of tropical cyclones on forest ecosystems. A deep understanding of the synergistic effects of tropical cyclones is essential for effective forest management and biodiversity conservation.