Human fatalities from wind-related tree failures in the United States, 1995–2007

There were 407 deaths from wind-related tree failures in the United States, 1995–2007. The most common cause of the deadly fallen tree was a thunderstorm (41%), followed by nonconvective high winds (35%), tropical cyclones (14%), tornadoes (7%), and snow and ice (3%). Most (62%) of the deaths were males while the median age was 44 years. The most common location of the fatality was in a vehicle struck by the tree or a vehicle that crashed into a downed tree on the road (44%), followed by persons outdoors (38%), in mobile homes (9%), and in frame houses (9%). Persons killed by wind-related tree failures during tropical cyclones and tornadoes were more commonly at home (40%) when struck than those killed at home by thunderstorm and nonconvective high winds (13%). Seasonality of the deaths varied by weather type with deaths in thunderstorms clustered during May–August, nonconvective high winds October–April, tropical cyclones August–October, tornadoes in April and November, and snow and ice December–April. Regional patterns result from frequency of the wind events, population density, and tree cover. Suggestions are made for hazard reductions.     

China’s tropical cyclone disaster risk source analysis based on the gray density clustering

In recent years, tropical cyclones on the Pacific Northwest have decreased. We cannot infer that tropical cyclones impact China have reduced, because the Pacific Northwest is not homogeneous, and the variation characteristics of tropical cyclones in different sea areas are not clear. This paper uses gray relational density clustering algorithm to cluster tropical cyclone data sets between 1949 and 2008, according to the generated position of tropical cyclones, generated density and the possibility of landing. The Pacific Northwest is divided into different sea areas. Then, we analyze the risk of tropical cyclones generated in these sea areas. The results show that the probability of tropical cyclones landing generated in some sea areas is very high, reached 74 %, but the probability of tropical cyclones landing generated in other sea areas is only 2 %. Tropical cyclones generated in some sea areas are more likely to develop into typhoons, strong typhoons and so on, but the intensity of tropical cyclones generated in other sea areas is lower, there is little risk for China. Finally, according to the climate change stage trends, we divide the period 1949–2008 into three stages and analyze the tropical cyclone risk of each sea areas.     

Climatology of landfalling tropical cyclones in Bangladesh 1877–2003

Bangladesh is highly susceptible to tropical cyclones. Unfortunately, there is a dearth of climatological studies on the tropical cyclones of Bangladesh. The Global Tropical Cyclone Climatic Atlas (GTCCA) lists historical storm track information for all the seven tropical cyclone ocean basins including the North Indian Ocean. Using GIS, tropical cyclones that made landfall in Bangladesh during 1877–2003 are identified and examined from the climatological perspective. For the convenience of study, the coast of Bangladesh is divided into five segments and comparisons are made among the coastal segments in terms of cyclone landfall and vulnerability. There is a large variability in the year-to-year occurrence of landfalling tropical cyclones in Bangladesh. Most of the tropical cyclones (70%) hit in the months of May–June and October–November generally show the well-known pattern of pre- and post-monsoon cyclone seasons in that region.     

A Study on the Impact of Parameterization of Physical Processes on Prediction of Tropical Cyclones over the Bay of Bengal With NCAR/PSU Mesoscale Model

Prediction of the track and intensity of tropical cyclones is one of the most challenging problems in numerical weather prediction (NWP). The chief objective of this study is to investigate the performance of different cumulus convection and planetary boundary layer (PBL) parameterization schemes in the simulation of tropical cyclones over the Bay of Bengal. For this purpose, two severe cyclonic storms are simulated with two PBL and four convection schemes using non-hydrostatic version of MM5 modeling system. Several important model simulated fields including sea level pressure, horizontal wind and precipitation are compared with the corresponding verification analysis/observation. The track of the cyclones in the simulation and analysis are compared with the best-fit track provided by India Meteorological Department (IMD). The Hong-Pan PBL scheme (as implemented in NCAR Medium Range Forecast (MRF) model) in combination with Grell (or Betts-Miller) cumulus convection scheme is found to perform better than the other combinations of schemes used in this study. Though it is expected that radiative processes may not have pronounced effect in short-range forecasts, an attempt is made to calibrate the model with respect to the two radiation parameterization schemes used in the study. And the results indicate that radiation parameterization has noticeable impact on the simulation of tropical cyclones.     

Modern and historical tropical cyclone and tsunami deposits at the coast of Myanmar: Implications for their identification and preservation in the geological record

The catastrophic storm surge of tropical cyclone Nargis in May 2008 demonstrated Myanmar's exposure to coastal flooding. The investigation of sediments left by tropical cyclone Nargis and its predecessors is an important contribution to prepare for the impact of future tropical cyclones and tsunamis in the region, because they may extend the database for long-term hazard assessment beyond the relatively short instrumental and historical record. This study, for the first time, presents deposits of modern and historical tropical cyclones and tsunamis from the coast of Myanmar. The aim is to establish regional sedimentary characteristics that may help to identify and discriminate cyclones and tsunamis in the geological record, and to document post-depositional changes due to tropical weathering in the first years after deposition. These findings if used to interpret older deposits will extend the existing instrumental record of flooding events in Myanmar. Evaluating deposits that can be related to specific events, such as the 2006 tropical cyclone Mala and the 2004 Indian Ocean tsunami, indicates similar sedimentary characteristics for both types of sediments. Landward thinning and fining trends, littoral sediment sources and sharp lower contacts allow for the differentiation from underlying deposits, while discrimination between tropical cyclone and tsunami origin is challenging based on the applied methods. The modern analogues also demonstrate a rather low preservation potential of the sand sheets due to carbonate dissolution, formation of organic top soils, and coastal erosion. However, in coastal depressions sand sheets of sufficient thickness (>10 cm) may be preserved where the shoreline is prograding or stable. In the most seaward swale of a beach-ridge plain at the Rakhine coast, two sand sheets have been identified in addition to the deposits of 2006 tropical cyclone Mala. Based on a combination of optically stimulated luminescence, radiocarbon and ¹³⁷Cs dating, the younger sand layer is related to 1982 tropical cyclone Gwa, while the older sand layer is most probably the result of an event that took place prior to 1950. Comparison with historical records indicates that the archive is only sensitive to tropical cyclones of category 4 (or higher) with landfall directly in or a few tens of kilometres north of the study area. While the presented tropical cyclone records are restricted to the last 100 years, optically stimulated luminescence ages of the beach ridges indicate that the swales landward of the one investigated in this study might provide tropical cyclone information for at least the past 700 years.     

The economic impact of future increase in tropical cyclones in Japan

This article estimates the non-first-order economic loss in Japan due to a future increase in tropical cyclones. One possible effect of global warming could be the increase in intensity of tropical cyclones. Using historical storm tracks between the years 1978 and 2007 and altering their intensities due to this potential increase in their intensity, this paper calculates the future potential regional GDP loss in a certain area that is affected by tropical cyclones. Most of the literature is concerned with physical damage and the loss of lives due to tropical cyclones. However, there are additional economic costs when sustained wind speeds are higher than 30 knots (55.56 km/h), a level that generally will lead to a precautionary cessation of many human activities. Using a Monte Carlo simulation, the paper calculates the potential economic costs for the year 2085 under a climate change scenario with a linear one-per cent yearly increase in CO₂. Using a spatial distribution of economic activity in Japan, it is possible to forecast which parts of the country are likely to experience the highest loss risk.     

Meteorological Office, Pune-411 005

Natural disasters like floods, tornadoes, tropicalcyclones, heat and cold wavewreak havoc and cause tremendous loss ofproperty all over the world. Most ofthe natural disasters are either dueto weather or are triggered due toweather related processes.Extreme weather events claimed thousands oflives and caused damage on vastscale. Recent super cyclone which affectedOrissa in 1999, Bangladesh cyclone of1970 and Hurricane Andrew in 1992 areexamples of some of the more damagingtropical cyclones which affected developingas well as the developed world. Heatand cold waves are also extreme events,which cause enormous losses in terms oflives lost and human discomfort and ailmentsarising out of them. The heat waveof 1995 and 1998 are still fresh in the mindof the Indian public. The estimated lossof human lives due to heat wave in 1998 was morethan 15,000. Economic losses asa result of these disasters and in particular inassociation with tropical cyclones haveincreased enormously over the last three decades.During 1961–1991, total loss oflives from drought alone was 1,333,728 overthe whole world. In terms of economiclosses, there is 8–10 fold increase from thebase figure of 1960. The socio-economicimpact of natural disaster is complex dependingupon the vulnerability of the placeand mitigation strategies that are put in place.Meteorology plays a crucial role in forewarningpeople about the severe/extremeweather systems and a constant endeavour by themeteorological services worldover has gone a long way towards minimizing thelosses caused by natural disasters.The paper summarises the natural disasterstatistics over south Asia and the possibleprediction strategies for combating theirsocio-economic impacts.     

Swarm intelligence and neural nets in forecasting the maximum sustained wind speed along the track of tropical cyclones over Bay of Bengal

Tropical cyclones are well-known extreme weather and the cause of considerable damages, injuries and loss of life. The assessment of the maximum sustained wind speed along the track of the tropical cyclones is very important for estimating the strength of the cyclones. The swarm intelligence in the form of ant colony optimization (ACO) technique is introduced in this study to compute the pheromone deposition along the track of tropical cyclones followed by neural nets to forecast the maximum sustained wind speed of the cyclones occurring over the Bay of Bengal of North Indian Ocean. The ACO is a nonlinear problem-based meta-heuristic optimization method for finding approximate solutions to discrete optimization problems and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. The method has shown its application potential in various fields including the prediction of monsoon rainfall. In this study, the amount of pheromone deposition during the successive stages of the cyclones has been estimated. A range of minimum central pressure (MCP), central pressure drop (PD), maximum sustained wind speed (MSWS) and intensity (T-No) associated with the cyclones of Bay of Bengal are utilized to form the input matrix of the neural nets. The neural nets are trained to forecast the maximum sustained wind speed along the track of the tropical cyclones over Bay of Bengal. The result reveals that the errors in forecasting the MSWS along the track of tropical cyclones with 6, 12, 18 and 24 h lead time are 2.6, 2.9, 3.1 and 4.8, respectively. The result is compared with the existing dynamical, statistical and adaptive models to evaluate the skill of the present model. The result is well validated with observation.     

Characteristics of tropical cyclones in China and their impacts analysis

This paper discusses the characteristics of tropical cyclones (TCs) based on available data from 1951 to 2008, including the frequency of TC generation in the Western North Pacific (WNP) and those which make landfall in China. The impacts of TCs on both human and economic losses for the period 1983–2008 are also discussed. Examination of the frequency indicates a decreasing trend in the generation of TCs in the WNP since the 1980s, but the number of TCs making landfall has remained constant or shown only a slight decreasing trend. The number of casualties caused by TCs in China appears to show a slight decreasing trend while the value of economic loss is increasing significantly. These results can be attributed to increased natural disaster prevention and mitigation efforts by the Chinese government in recent years, and also reflect the rapid economic development in China particularly in TC-prone areas.     

Assessment of economic losses from tropical cyclone disasters based on PCA-BP

Tropical cyclones are the most common natural disasters in coastal regions and are the most costly in terms of economic losses. Economic loss assessment is the basis for disaster prevention and alleviation and for insurance indemnification. We use data from 1970 to 2008 for Zhejiang Province, China, in this study evaluating economic losses. We convert direct economic losses from tropical cyclone disasters in Zhejiang Province into indices of direct economic losses. To establish our assessment model, we process disaster-inducing assessment factors, disaster-formative environments and disaster-affected bodies using the principal component analysis method, and we abstract the principal component as the input of a BP neural network model. We found in the actual assessments of five tropical cyclones affecting Zhejiang Province in 2007 and 2008 that the post-disaster loss assessment values of tropical cyclones were higher than the actual losses, but that for more severe storms, the gap was smaller. This reflects the beneficial effect of efforts toward disaster prevention and alleviation for severe tropical cyclones. Pre-assessments based on relatively accurate forecast values of wind and precipitation at the start of a tropical cyclone have been in accordance with the post-disaster assessment values, while the pre-assessment results using less accurate forecast values have been unsatisfactory. Therefore, this model can be applied in the actual assessment of direct economic loss from tropical cyclone damage, but increasingly accurate forecasting of wind and precipitation remains crucial to improving the accuracy of pre-assessments.     

中国热带气旋暴雨洪水的分布和水文特性

描述了由热带气旋形成和影响的暴雨及其洪水的地域分布,给出了区划;讨论了热带气旋暴雨洪水的水文特性,并与非热带气旋暴雨洪水作了比较。     

Interannual variability of tropical cyclone activity along the Pacific coast of North America

The interannual variability of near-coastal eastern North Pacific tropical cyclones is described using a data set of cyclone tracks constructed from U.S. and Mexican oceanic and atmospheric reports for the period 1951-2006. Near-coastal cyclone counts are enumerated monthly, allowing us to distinguish interannual variability during different phases of the May-November tropical cyclone season. In these data more tropical cyclones affect the Pacific coast in May-July, the early months of the tropical cyclone season, during La Niña years, when equatorial Pacific sea surface temperatures are anomalously cool, than during El Niño years. The difference in early season cyclone counts between La Niña and El Niño years was particularly pronounced during the mid-twentieth century epoch when cool equatorial temperatures were enhanced as described by an index of the Pacific Decadal Oscillation. Composite maps from years with high and low near-coastal cyclone counts show that the atmospheric circulation anomalies associated with cool sea surface temperatures in the eastern equatorial Pacific are consistent with preferential steering of tropical cyclones northeastward toward the west coast of Mexico.     

The Tropical Cyclone Risk in Cairns

Because of its location close to a region of tropical cyclone formation, the city ofCairns is regularly affected by tropical cyclones. Most cyclones occur in the monthsJanuary–March, although some have affected Cairns in December and April. There is a strong year-to-year variation in tropical cyclone numbers in the Cairns region, with twice as many impacts occurring during La Niña conditions than during El Niño. Several case studies are presented of cyclone impacts on Cairns. Rapidly developing cyclones are a particularly difficult forecast problem, as they can strike the city with less than 24 hours warning. Serious inundation from storm surge often occurs some time after landfall at Cairns.     

Tropical cyclones over north Indian Ocean during El-Niño Modoki years

Tropical cyclones are the most hazardous weather systems, which form over warm ocean waters. The frequencies of tropical cyclones show variabilities over all the oceanic basins, during the El-Niño and El-Niño Modoki years. Recent studies have shown significant impact of air–sea interaction processes like El-Niño and El-Niño Modoki on the cyclone activity over different ocean basins. The results suggest in most cases, El-Niño events suppress the formation of cyclones over various basins. A recent study indicated that concurrent occurrence of El-Niño Modoki and positive Indian Ocean dipole (IOD) events can generate more cyclones over north-west Pacific. We propose to study the impact of El-Niño Modoki events on the formation of tropical cyclones over north Indian Ocean (NIO). Our present study suggests that the cyclogenesis over the NIO is a complex phenomenon, as it is influenced by several coupled ocean atmospheric phenomena such as El-Niño, El-Niño Modki, IOD and Madden–Julian oscillation.     

Mitigation of Flooding and Cyclone Hazard in Orissa, India

Storm surges generated by the strong tangential wind stressesand normal atmospheric pressure gradients at the sea surface due to tropical cyclones (TC'S)have been studied with the goal of detecting any significant and systematic changes due to climatechange. Cyclone and storm surge data for the 19th and 20th centuries for the Bay of Bengalcoast of the state of Orissa in India are available to varying degrees of quality and detail,the data being more scientific since the advent of the India Meteorological Department in 1875.Based on more precise data for the period 1971 to 2000, statistical projections have been madeon the probable intensities of tropical cyclones for various return periods. The super cyclone ofOctober 29, 1999 (SC1999) appears to have a return period of about 50 years. The cyclones of1831, 1885 and possibly the one in 1895 could have been super cyclones. During the 19th century,there were 72 flooding events associated with cyclones, whereas in the 20th century therewere only 56 events. There was no observational evidence to suggest that there was an increaseeither in the frequency or intensity of cyclones or storm surges on the coast of Orissa. However,the impact of cyclones and surges is on the increase due to increase of population and coastalinfrastructure.     

Community Vulnerability to Tropical Cyclones: Cairns, 1996–2000

This paper is a partial discussion of a four-year study that investigated the vulnerability of the people living in the Cairns region to the tropical cyclone hazard. The longitudinal case study, focussing on the Cairns Northern Beaches area, was unique in that it included a social and societal `pre-cyclone impact' evaluation of various resident communities within the region, and then two consecutive `post-cyclone impact' studies. The primary research method supported an inductive qualitative approach to the collection and analysis of survey data. Some quantitative methods were invoked to support qualitative research findings. Survey data was collected in five separate questionnaire-based social surveys that were administered between 1996 and 2000. During the study, residents experiencedthe direct impact of two land-falling tropical cyclones. In addition to this, targeted andfocussed tropical cyclone awareness education was made increasingly available withinthe community. The social and demographic attributes that influence the individual'sperception of risk and contribute to our understanding of community vulnerability were examined and evaluated. Changes in the residents' attitudes, cyclone preparednessbehaviours and willingness to respond to cyclone warnings were monitored and measured. Analysis of early survey data indicated that community residents generally had some knowledge of cyclones but a limited understanding of cyclone processes and very little direct personal experience of the cyclone hazard. Individually and collectively, residents frequently demonstrated a biased perception of the risks associated with cyclones. The resident community was shown to be fragmented, with limited support being available to individual households. Initially, residents were found to be poorly prepared for cyclones and unlikely to respond to warnings appropriately. It appeared that, in the event of a land-falling tropical cyclone impacting the area, the community was highly vulnerable to unnecessary loss of property, livelihood and – in extreme circumstances – life. By 2000, Cairns community residents were somewhat better informed about cyclones and certainly more experienced. This paper provides some insight into how cyclone experience and education may synergisticly have contributed to a change in risk perceptions and a reduction in the vulnerability of Cairns residents to the tropical cyclone and storm surge hazards.     

Tropical Cyclones and Their Transformation into Extratropical: Estimates of the Half-Century Trends

Doklady Earth Sciences - Results from an analysis of the frequency of tropical cyclones, the probability of their transformation into extratropical cyclones, and their trends in different oceanic...     

Impact of sea surface temperature in modulating movement and intensity of tropical cyclones

It is well recognized that sea surface temperature (SST) plays a dominant role in the formation and intensification of tropical cyclones. A number of observational/empirical studies were conducted at different basins to investigate the influence of SST on the intensification of tropical cyclones and in turn, modification in SST by the cyclone itself. Although a few modeling studies confirmed the sensitivity of model simulation/forecast to SST, it is not well quantified, particularly for Bay of Bengal cyclones. The present study is designed to quantify the sensitivity of SST on mesoscale simulation of an explosively deepening storm over the Bay of Bengal, i.e., Orissa super cyclone (1999). Three numerical experiments are conducted with climatological SST, NCEP (National Center for Environmental Prediction) skin temperature as SST, and observed SST (satellite derived) toward 5-day simulation of the storm using mesoscale model MM5. At model initial state, NCEP skin temperature and observed SST over the Bay of Bengal are 1–2°C warmer than climatological SST, but cooler by nearly 1°C along the coastline. Observed SST shows a number of warm patches in the Bay of Bengal compared with NCEP skin temperature. The simulation results indicate that the sea surface temperature has a significant impact on model-simulated track and intensity of the cyclonic storm. The track and intensity of the storm is better simulated with the use of satellite-observed SST.     

Tropical cyclone prediction over Bay of Bengal: a comparison of the performance of NCEP operational HWRF, NCAR ARW, and MM5 models

Much progress has been made in the area of tropical cyclone prediction using high-resolution mesoscale models based on community models developed at National Centers for Environmental Predication (NCEP) and National Center for Atmospheric Research (NCAR). While most of these model research and development activities are focused on predicting hurricanes in the Atlantic and Eastern Pacific domains, there has been much interest in using these models for tropical cyclone prediction in the North Indian Ocean region, particularly for Bay of Bengal storms that are known historically causing severe damage to life and property. In this study, the advanced operational hurricane modeling system developed at NCEP, known as the Hurricane Weather Research and Forecast (HWRF) model, is used to simulate two recent Bay of Bengal tropical cyclones??Nargis of November 2007 and Sidr of April 2008. The advanced NCEP operational vortex initialization procedure is adapted for simulating these Bay of Bengal tropical cyclones. Two additional regional models, the NCAR Advanced Research WRF and NCAR/Penn State University Mesoscale Model version 5 (MM5) are also used in simulating these storms. Results from these experiments highlight the superior performance of HWRF model over other models in predicting the Bay of Bengal cyclones. These results also suggest the need for a sophisticated vortex initialization procedure in conjunction with a model designed exclusively for tropical cyclone prediction for operational considerations.     

Intensity forecast of tropical cyclones over North Indian Ocean using multilayer perceptron model: skill and performance verification

The coastal regions of India are profoundly affected by tropical cyclones during both pre- and post-monsoon seasons with enormous loss of life and property leading to natural disasters. The endeavour of the present study is to forecast the intensity of the tropical cyclones that prevail over Arabian Sea and Bay of Bengal of North Indian Ocean (NIO). A multilayer perceptron (MLP) model is developed for the purpose and compared the forecast through MLP model with other neural network and statistical models to assess the forecast skill and performances of MLP model. The central pressure, maximum sustained surface wind speed, pressure drop, total ozone column and sea surface temperature are taken to form the input matrix of the models. The target output is the intensity of the tropical cyclones as per the T??number. The result of the study reveals that the forecast error with MLP model is minimum (4.70?%) whereas the forecast error with radial basis function network (RBFN) is observed to be 14.62?%. The prediction with statistical multiple linear regression and ordinary linear regression are observed to be 9.15 and 9.8?%, respectively. The models provide the forecast beyond 72?h taking care of the change in intensity at every 3-h interval. The performance of MLP model is tested for severe and very severe cyclonic storms like Mala (2006), Sidr (2007), Nargis (2008), Aila (2009), Laila (2010) and Phet (2010). The forecast errors with MLP model for the said cyclones are also observed to be considerably less. Thus, MLP model in forecasting the intensity of tropical cyclones over NIOs may thus be considered to be an alternative of the conventional operational forecast models.