Meteorological Hazards Research Articles

A three-dimensional numerical simulation approach to assess typhoon hazards in China coastal regions

The paper introduces a three-dimensional numerical technique to assess typhoon hazards in China coastal regions based on a series of full-set numerical meteorology simulations. The boundary and initial conditions of the simulations are provided by adding pseudorandom fluctuations, which represent the localized, short-term meteorological variations, to synoptic fields, which show the large-scale, long-term meteorological patterns. A series of bogus typhoons are inserted into the initial field to provide the “seeds” from which the artificial typhoons could grow. The initial positions and intensities of the bogus typhoons are drawn from the random variables whose statistics agree with those derived from historical typhoon track data. In the present study, 1503 full-set meteorology simulations of artificial typhoons are conducted. The extreme wind speeds versus return periods calculated from the simulation results are compared to not only the specifications in the load code, but also the results from the previous studies. It is found that the extreme wind speeds in the Pearl-River Delta are, contradicting to the common expectation, higher than at the mainland side of the Taiwan Strait, which imply that the typhoons hitting Guangdong are, on average, more intense than those influencing Fujian. Given the possibility to improve the three-dimensional meteorology model in the future, the simulation technique proposed in the present study provides a novel direction to assess the meteorological hazards, including threads posted by typhoons.

Improving the Hurricane Outage Prediction Model by including tree species

Hurricanes can be a major threat to electrical power systems, often resulting in costly repairs and lengthy restoration times. The Hurricane Outage Prediction Model (HOPM) predicts the location and number of outages for a major coastal Gulf of Mexico utility company up to 5 days before a hurricane makes landfall. This model can help electrical utilities to improve their resource allocations and potentially shorten restoration times. The goal of this study is to evaluate whether the accuracy of the HOPM can be improved by including information on tree species. Our results demonstrate that the model accuracy increased by ∼3% when tree species were included. The most important tree species in our study region were Sweetgum and Loblolly Pine. As the relative abundance of these tree species increased, the number of outages tended to increase. In contrast, increases in the relative abundance of Water Oak and Chestnut Oak did not result in more outages. This suggests that certain oaks may be more resistant to uprooting or snapping when there are strong winds. Therefore, the inclusion of tree species variables in the model provides a means for capturing the spatially varying vulnerability of the trees to strong winds. Even though including tree species improved the accuracy of the model, information about the frequency of tree trimming is more important. Accurate prediction of the location and number of power outages requires information on both the meteorological hazard and the vulnerability of the vegetation.

Adaptive strategies and transformation for community recovery – A case study of villages in Hinthada, Ayeyarwady Region, Myanmar

Myanmar is one of the highest meteorological hazard risk countries in the world, owing to geographical factors such as a vast delta along the Ayeyarwady River. As the Ayeyarwady Region has suffered from seasonal floods in the monsoons since historical times, long earthen dykes were constructed in the 19th century during the British colonial period. As a result, one village was divided into two by a dyke about 150 years ago. The region was severely affected by floods in 2015. Most of the unprotected villages were inundated for two to three months, while villages inside of the dyke were protected. This research aims to identify strategies for long-term recovery related to housing, livelihood, and community activities in villages divided by the dyke in Hinthada Township using household surveys. The results show that unprotected villages have adapted their elevated houses against floods and planted water-resistant crops as an income source. Protected villages have relied on mitigation and maintenance of the dyke along with non-elevated houses, and have transformed their livelihoods in different ways.

Operational notifying aircraft crew about dangerous meteorological phenomena in the zones of arctic landing sites

Meteorological support for aviation is an essential element of an integrated system for air traffic management as incorrect meteorological information about hazardous meteorological conditions has a significant impact on the level of flight safety and on all aspects of air traffic management. At present, a number of decisions have been taken at the state level in Russia, according to which a large-scale program is being implemented to develop the infrastructure of the Far North and the Arctic regions, the development of territories, the coast of the Northern Sea Route, and the development of mineral deposits. The climate of the Arctic is one of the severest on Earth. The instability of the meteorological situation is expressed in a sharp change in the wind direction and speed, a decrease in the height of the cloud cover, the rapid inflow of fog from the sea on the coast. Strong winds cause a snowstorm and drifting snow, in summer, under the influence of a powerful cyclone, a sudden increase in air temperature is possible. These natural factors together create adverse, at times extreme climatic conditions, which lead to the emergence of meteorological hazards dangerous to aviation. These phenomena are difficult to predict and significant in terms of impact. Making landing and takeoff in the Arctic, as a rule, is associated with an increased risk. This is due to the fact that temporary aerodromes and landing sites have minimal aerodrome equipment, meteorological provision is almost completely or partially not available, there are no statistical data on weather peculiarities at the place of take-off and landing. The problem of servicing landing sites is the use of outdated equipment, lack or inability of permanent maintenance staff residing in the area. Taking into account the above facts, for effective and safe use of aviation in the Arctic region, it is necessary to automate as much as possible the processes of obtaining, processing and reporting to the crews data on the meteorological situation in the area of the landing site and on the flight route. The article discusses the need to use automated systems for collecting, processing and transmitting meteorological information to inform crews of aircraft carrying out take-offs and landings in the areas of aircraft and helicopter landing areas of the Arctic zone about the state of the surface layer of the atmosphere and the altitudes where icing is possible.

Vulnerability, resilience and adaptation of societies during major extreme storms during the Little Ice Age

Abstract. This paper reviews more than 19 691 French historical documents from 14 French archive centres. To assess data from historical documents, a method has been applied that leads to a record of 101 extreme storms with damage, including 38 coastal floods. Thus, the results show periods of increasing and decreasing storm frequency. These periods are examined. Furthermore, coastal hazards have forced societies to adapt and develop specific skills, lifestyles and coping strategies. This paper analyses some responses of past societies to these hazards. By doing so, useful ideas may be (re)discovered by today's communities in order to enable us to adapt and develop resilience. Similarly, a thorough knowledge of past meteorological hazards may allow our societies to recreate a link with territory, particularly through the (re)construction of an effective memory of these phenomena.

Spatial Analysis of the Vulnerability to Meteorological Hazards in Korea

The purpose of this research is to provide an objective and accurate regional vulnerability index at a finer resolution with the research period from 1983 to 2012 in Korea. To find the spatial patterns and characteristics of regional vulnerability, this research conducted four different types of analyses. First, the most vulnerable regions in terms of demographic, climatological-geographic, socioeconomic, and technological factors were respectively investigated. Second, total vulnerability index combining all the four factors was examined. Next, the most influential factors deciding vulnerability and common spatial patterns of vulnerability were extracted using empirical orthogonal function (EOF) analysis. Lastly, the degree of clustering for each factor was checked using Moran’s I and local indicators of spatial association (LISA). The result found the most vulnerable provinces were Jeolla and Gyeongsang Province, regarding to demographic and climatological- geographic factors, respectively. In the case of socioeconomic factors, the difference between urban and rural areas was larger than the difference between provinces. In addition, the EOF analysis showed that demographic factors would be the most influential factors which explained 32.2 percent of the total variance of data. Lastly, climatological and geographic factors represented the highest degree of clustering (global Moran’s I: 0.51).

Assessing Transportation Assets for Vulnerability to Extreme Weather and Other Natural Hazards

The Kentucky Transportation Cabinet (KYTC) and Kentucky Transportation Center (KTC) at the University of Kentucky developed and performed an assessment of the vulnerability of the state’s national highway system (NHS) to extreme weather events and natural hazards. The assessment was designed as a hybrid process that 1) gathered and analyzed existing and available quantitative data on natural hazards, including meteorological hazards and geological hazards; 2) executed a series of workshops at KYTC districts throughout the state to elicit local expert knowledge on transportation system vulnerabilities; and 3) incorporated all data into a single vulnerability assessment. The workshops involved several facilitated exercises, including map-based discussions and keypad exercises to identify vulnerabilities along highway segments. Data from the mapping and keypad exercises were gathered in a geographic information system (GIS) and combined with the other hazard data to identify vulnerabilities for each highway segment. FHWA’s Vulnerability Assessment Scoring Tool (VAST) was used to process all the data into a single and ultimate assessment. Results from this analysis include a district-level prioritized ranking of NHS segments based on their vulnerability to extreme weather and natural hazard events. Additionally, a district vulnerability assessment report for each district highlighted the most vulnerable assets in the district and discussed their vulnerabilities in detail. This research is intended to aid KYTC in identifying at-risk infrastructure and direct the implementation of preparedness and resilience measures, thus helping to protect the integrity of the transportation system and the sound investment of taxpayer dollars.

TAMSAT-ALERT v1: a new framework for agricultural decision support

Abstract. Early warning of weather-related hazards enables farmers, policy makers and aid agencies to mitigate their exposure to risk. We present a new operational framework, Tropical Applications of Meteorology using SATellite data and ground based measurements-AgricuLtural EaRly warning sysTem (TAMSAT-ALERT), which aims to provide early warning for meteorological risk to agriculture. TAMSAT-ALERT combines information on land-surface properties, seasonal forecasts and historical weather to quantitatively assess the likelihood of adverse weather-related outcomes, such as low yield. This article describes the modular TAMSAT-ALERT framework and demonstrates its application to risk assessment for low maize yield in northern Ghana (Tamale). The modular design of TAMSAT-ALERT enables it to accommodate any impact or land-surface model driven with meteorological data. The implementation described here uses the well-established General Large Area Model (GLAM) for annual crops to provide probabilistic assessments of the meteorological hazard for maize yield in northern Ghana (Tamale) throughout the growing season. The results show that climatic risk to yield is poorly constrained in the beginning of the season, but as the season progresses, the uncertainty is rapidly reduced. Based on the assessment for the period 2002–2011, we show that TAMSAT-ALERT can estimate the meteorological risk on maize yield 6 to 8 weeks in advance of harvest. The TAMSAT-ALERT methodology implicitly weights forecast and observational inputs according to their relevance to the metric being assessed. A secondary application of TAMSAT-ALERT is thus an evaluation of the usefulness of meteorological forecast products for impact assessment. Here, we show that in northern Ghana (Tamale), the tercile seasonal forecasts of seasonal cumulative rainfall and mean temperature, which are routinely issued to farmers, are of limited value because regional and seasonal temperature and rainfall are poorly correlated with yield. This finding speaks to the pressing need for meteorological forecast products that are tailored for individual user applications.

An Extreme Meteorological Events Analysis For Nuclear Power Plant (NPP) Siting Project at Bangka Island, Indonesia

The potential sources of meteorological phenomena in Nuclear Power Plant (NPP) area of interest are identified and the extreme values of the possible resulting hazards associated which such phenomena are evaluated to derive the appropriate design bases for the NPP. The appropriate design bases shall be determined according to the Nuclear Energy Regulatory Agency (Bapeten) applicable regulations, which presently do not indicate quantitative criteria for purposes of determining the design bases for meteorological hazards. These meteorological investigations are also carried out to evaluate the regional and site specific meteorological parameters which affect the transport and dispersion of radioactive effluents on the environment of the region around the NPP site. The meteorological hazards are to be monitored and assessed periodically over the lifetime of the plant to ensure that consistency with the design assumptions is maintained throughout the full lifetime of the facility.

Data integration from intensive observation period in 2016 to detect extreme weather in the vicinity of Jakarta region

Meteorological hazard has been frequently occurred in Indonesia due to torrential rains. It is important to examine the characteristics of the atmosphere during rainy seasons for hazard mitigation. National Laboratory of Weather Modification Technology has conducted a short Intensive Observation Program (IOP) from January 18th to February 16th, 2016 to collect meteorological data in the vicinity of Jakarta Region. During that period several instruments have been used, such as Radar, Microwave Profiling Radiometer, Automatic Weather Station, and Radiosonde. This paper examines the comparison of atmospheric parameters obtained from Radiosonde and Profiling Radiometer during extreme weather days. The results showed that there were significant differences of instability indices of Radiosonde and Profiling Radiometer data: 15 points for KI, 6 points for TT and 100 points for SWEAT. The atmospheric stability indices of the Profiling Radiometer tended to be lower than Radiosonde. A radar image showing a rainstorm as well as rain rate information validates atmospheric index stability data. Radar and atmospheric instability indices data integration can be used as one of the parameters to forecast extreme weather events and as an early warning system of hazard mitigation.

夏玉米对土壤水分持续减少的响应及其转折点阈值分析

PDF HTML阅读 XML下载 导出引用 引用提醒 夏玉米对土壤水分持续减少的响应及其转折点阈值分析 DOI: 10.5846/stxb201706091044 作者: 作者单位: 中国气象科学研究院,中国气象科学研究院,中国气象科学研究院,中国气象科学研究院,中国气象科学研究院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金重点项目（41330531，31661143028）；公益性行业（气象）科研专项（重大专项）（GYHY201506001-3） Responses and tipping point of summer maize to consecutive soil water decrease Author: Affiliation: Chinese Academy of Meteorological Sciences,Chinese Academy of Meteorological Sciences,Chinese Academy of Meteorological Sciences,Chinese Academy of Meteorological Sciences,Chinese Academy of Meteorological Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:玉米是世界三大粮食作物之一，玉米生产在中国粮食安全与畜牧业发展中具有举足轻重的作用。干旱是夏玉米生产最主要气象灾害，及时准确地获取干旱信息对夏玉米安全生产至关重要。以夏玉米郑单958品种为材料，设置充分供水和拔节期开始土壤水分持续减少两种水分处理，研究夏玉米对土壤水分持续减少的响应及其转折点阈值，为夏玉米干旱识别与监测提供依据。结果表明，土壤水分持续减少10d后生理指标开始陆续受到胁迫，20d后生物量积累受到抑制，30d左右形态特征开始受到胁迫。夏玉米生理指标中最先受到胁迫的是顶端第1片完全展开叶的含水量和水势，生物量积累指标中为茎生物量，形态指标中为叶数。夏玉米顶端第1片完全展开叶的含水量或水势、茎生物量和叶数开始受到土壤干旱过程胁迫的时间阈值分别为11、21、27d，水分亏缺阈值分别为34、66、86mm，土壤相对湿度阈值分别为64%、56%和52%。表明夏玉米对土壤干旱过程的响应首先表现为生理特征变化、其次为生物量积累变化、最后为形态特征变化。研究结果可为客观辨识夏玉米干旱的发生发展及监测预警提供参考。 Abstract:Maize plays an important role in food security and the development of livestock husbandry in China. Drought is the most important meteorological hazard for summer maize production. Drought accounts for 64% of the total area affected by the four meteorological disasters (drought, flood, storm, and cold) in major summer maize producing areas in China. Accurate and timely access to drought information is critical to the safety of summer maize production. Drought indicators can indicate the occurrence and degree of drought. The plant eco-physiology indicators can reflect the degree of water shortage and drought tolerance of plants directly. There are tipping points for the response of summer maize to drought. That is, when water is below a certain critical point, it will have a significant impact on plant physiology and other indicators. The different sensitivity of indicators to drought results in different tipping points. In this study, two water treatments (adequate water supply and stop water supply from jointing stage) were designed to simulate the responses and tipping point of summer maize "Zhengdan 958" to consecutive decrease in soil water. The study was conducted at the station of ecological environment and agro-meteorology of the China Meteorological Administration (39°08'N, 115°40'E) in 2015. Six plots (2m×4m) were used for the two water treatments (three replicates for each). The results indicated that:the physiological indicators were adversely affected after 10 days when water deficit accumulated to 34mm and relative soil water content decreased to 64%. Biomass was restricted after 20 days when water deficit accumulated to 66 mm and relative soil water content decreased to 56%. Morphological characteristics began to be depressed when water deficit accumulated to 86mm and relative soil water content decreased to 52%. Among the physiological indicators, the water content and water potential of the first fully expanded leaf at the top were affected first. The sensitivity of physiological indicators' response to consecutive soil water decrease was ranked as:the water content and water potential of first fully expanded leaf at the top > the water content of third fully expanded leaf at the top > the water content of total leaves > the water content of stem=the chlorophyll content of third fully expanded leaf at the top > the chlorophyll content of first fully expanded leaf at the top, and their tipping points in terms of the relative soil water content were 64%, 62%, 61%, 60%, 60%, and 59%, respectively. In terms of the accumulative biomasses, the stem biomass was the first to be impacted, followed by root biomass; and the tipping points in terms of the relative soil water content for both were 56%. For morphological characteristics, the number of leaves decreased first. The sensitivity of morphological indicators to consecutive soil water decrease was ranked as:leaf number > plant height > total leaf area; and the tipping points in terms of the relative soil water content were 52%, 47%, and 46%. The response of summer maize to soil drought process was as follows:physiological characteristics changed firstly, followed by biomass accumulation, and finally morphological characteristics. These results can provide a reference for the development and monitoring of drought in summer maize objectively. 参考文献 相似文献 引证文献

1961-2015年黄淮海地区冬小麦干热风灾害时空分布特征

PDF HTML阅读 XML下载 导出引用 引用提醒 1961-2015年黄淮海地区冬小麦干热风灾害时空分布特征 DOI: 10.5846/stxb201708281553 作者: 作者单位: 国家气象中心,国家气象中心,国家气象中心,中国农业科学院农业资源与农业区划研究所,国家气象中心,国家气象中心 作者简介: 通讯作者: 中图分类号: 基金项目: 公益性行业（气象）科研专项（201506019）；国家重点研发计划（2017YFD0300101） Spatial-temporal characteristics of dry-hot wind for winter wheat in Huang-Huai-Hai region from 1961 to 2015 Author: Affiliation: National Meteorological Center,National Meteorological Center,National Meteorological Center,Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,National Meteorological Center,National Meteorological Center Fund Project: Special Scientific Research Fund of Meteorology in the Public Welfare Profession of China; National Key Research and Development Project of China 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:干热风是影响北方小麦后期生长和产量形成的重大气象灾害之一，在黄淮海地区主要有高温低湿型和雨后青枯型两种类型。利用黄淮海冬麦主产区65个站点1961-2015年的逐日气象数据和冬小麦生育期资料，综合分析了过去55 a该地区干热风日数和干热风过程的总体时空分布与变化特征。结果表明：（1）年平均干热风日数、过程次数高值区位于河北中南部、河南北部、山东北部和西部等地，其中河北中南部为黄淮海地区的干热风重发区。（2）干热风多年平均初日和最早初日的空间分布均呈从南向北、从内陆到沿海逐渐推后的特征；随着小麦灌浆成熟进程，干热风发生日数呈逐渐增多趋势，灌浆中后期干热风日数多、程度重，是干热风危害的集中期和防御关键期。（3）黄淮海地区干热风日数、过程次数总体均呈减少趋势，其中重干热风日数、重过程次数减少趋势更为明显；从地区差异来看，冀东南、鲁西北、豫东北等地减少趋势更为明显。但在气候变暖背景下，极端天气气候事件频发，部分年份仍存在发生较重干热风的可能，如2001年区域平均干热风日数达8.1 d，成为1961-2015年干热风日数最多的年份，因此对干热风的防御仍需引起足够的重视。 Abstract:Dry-hot wind is one of the major meteorological hazards in Huang-Huai-Hai region, which commonly occurs at the filling stage of winter wheat and can severely influence the wheat growth and yield. There are two types of dry-hot wind in Huang-Huai-Hai region:1) high temperature with low humidity and 2) wilting heat after rain. By using daily meteorological data (daily maximum temperature, relative humidity at 14:00, wind speed at 14:00, and daily precipitation) and winter wheat growth data of 65 stations in Huang-Huai-Hai region from 1961 to 2015, the spatial-temporal characteristics of dry-hot wind in the past 55 years was analyzed. The results showed that both the dry-hot wind days and process times were higher in central-south Hebei province, north Henan province, and west and north Shandong province in Huang-Huai-Hai region; among these areas, central-south Hebei province was the most severely affected area. It was found that both the average first occurrence day and the earliest first occurrence day of dry-hot wind was gradually delayed from south to north and from inland to coast. Dry-hot wind days increased gradually with the grain filling process of winter wheat; thus, the mid and late phases of grain filling were identified as the critical resistance stages to dry-hot wind. Both the annual average days and process times of dry-hot wind showed decreasing trend from 1961 to 2015 in Huang-Huai-Hai region, especially the severe dry-hot wind days and severe process times decreased more obviously. Among of which, the decreasing trend was more obviously in southeast Hebei province, northwest Shandong province and northeast Henan province. It should be noted that extreme climate events occur frequently under the background of climate warming, and extreme dry-hot wind events may occur in some regions under certain conditions. For example, the average number of dry-hot wind days in Huang-Huai-Hai region was 8.1d in 2001, which was the maximum record from 1961 to 2015 in this region. It should be taken into account for the prevention of dry-hot wind in wheat planting. 参考文献 相似文献 引证文献

Real-time Application of the Multihazard Hurricane Impact Level Model for the Atlantic Basin

Tropical cyclones are an example of a multi-hazard event with impacts that can highly vary depending on landfall location, wind speed, storm surge, and inland flooding from precipitation. These storms are typically categorized by their wind speed and pressure, while evacuation orders are typically given based on storm surge. The general public relies on these single hazard assessment parameters when attempting to understand the risk of an oncoming event. However, after the fact, these events are ranked by economic damage and death toll. Therefore, it is imperative that when these events are communicated to the public, during the forecast period, the multiple hazards are incorporated in terms the public can easily associate with, such as economic damage. This paper provides an evaluation on the potential for real-time use of artificial neural networks, through the utilization of an already developed Hurricane Impact Level Model, to forecast a range of economic damage from tropical cyclone events, during the 2015 and 2016 United States Hurricane Season. The Hurricane Impact Level Model is built prior to the start of each season and simulated every three hours, in conjunction with National Hurricane Center issued advisories, for oncoming tropical cyclones forecasted to make landfall. Weaker and more common tropical cyclones have a less varied forecast and produce more accurate Impact Level predictions. More complicated and uncertain events, such as 2016 Hurricane Matthew, require the user’s discretion in communicating varying landfall locations for a complex track forecast to the model. As National Hurricane Center (NHC) forecasts change with respect to both track and meteorological hazards affecting land, the estimated Impact Level and the Hurricane Impact Level (HIL) model confidence will also change. In other words, if a track shifts to a more vulnerable location, or to more locations, or the meteorological hazards increase, the Impact Level will subsequently increase. All tropical cyclones from the 2015 and 2016 seasons demonstrate the validity of the Hurricane Impact Level Model with a forecast confidence of at least 60% for up to 30 hours out from an impending landfall as well as reliability for real-time use, if data is available.

Attribution of Weather and Climate Events

Within the past decade, the attribution of extreme weather and climate events has emerged from a theoretical possibility into a subfield of climate science in its own right, providing scientific evidence on the role of anthropogenic climate change in individual extreme weather events, on a regular basis and using a range of approaches. Different approaches and thus different framings of the attribution question lead to very different assessments of the role of human-induced climate change. Although there is no right or wrong approach, the community is currently debating about the appropriate methodologies for addressing various stakeholder needs and scientific limitations. Tackling these limitations with more thorough model evaluation and meaningful bias corrections as well as going beyond the meteorological hazard and attributing the full impacts of extreme weather are the main challenges to face in the coming years.

Computer-based model for the transient dynamics of a tall building during digitally simulated Andrews AFB thunderstorm

Thunderstorm downbursts are near ground-level meteorological hazards, exhibiting transient, non-synoptic, short-duration and high intensity wind velocities. Winds can induce nonstationary loads and large-amplitude dynamic response in a slender vertical structure. The thunderstorm-induced response against non-synoptic wind loads is extremely complex and cannot be investigated by conventional wind analysis approaches. This study examines the thunderstorm-induced dynamic response of tall buildings. The wind load is based on the observation of the Andrews Air Force Base (AFB) thunderstorm. The main objectives are to: (i) reconstruct the Andrews thunderstorm wind speed record and replicate structure, lifecycle and the fundamental wind parameters, (ii) digitally synthesize the non-turbulent and turbulent velocities to derive aerodynamic loads on a reference tall building, (iii) formulate the thunderstorm-induced dynamics of the tall building subjected to the Andrews thunderstorm-induced downburst loads, and (iv) investigate the response of a tall building by considering two different plausible scenarios. Some unanswered scientific questions are investigated: uncertainty in vertical wind velocity profiles, abrupt change of wind direction angles and influence of crosswind velocities. Three amplitude modulation functions are employed to simulate the transient turbulent field observed during the Andrews thunderstorm. Numerical simulations analyze the dynamic response of the 183-m CAARC tall building.

Recent Lightning-Related Fatalities and Injuries in Bangladesh

Abstract A database of lightning-related deaths and injuries in Bangladesh was developed from 1990 to mid-2016 from a variety of sources that contains a total of 5468 casualties, composed of 3086 fatalities and 2382 injuries. Spatial, temporal, and demographic aspects of these lightning casualties are evaluated in order to aid relevant entities in effective management of lightning-related meteorological hazards. The annual averages for Bangladesh are 114 fatalities and 89 injuries over the entire period. Weighting by population reveals a fatality rate of 0.92 per million people per year and an injury rate of 0.71. In contrast, the latest 6 years have a fatality rate of 1.6 and injury rate of 1.4. The rural portion of lightning fatalities is 93%. Most fatalities occurred between early morning (0600 LST) and early evening (2000). Through the year, more fatalities occur during the premonsoon season of March through May than during the monsoon season (June–September). The interannual time series of fatalities indicates an increase since the late 2000s, which is a result of greatly improved communications leading to better media reporting of lightning casualties. Bangladesh has also become much more populous in recent years. As a result, the most recent 6 years have 251 fatalities per year, which may be considered as the current estimate. The majority of lightning-related deaths occurred to males. Farming is the major activity at the time of lightning fatalities followed by being inside a dwelling and returning home or walking around homesteads/courtyards.

Seasonal differences in the response of Arctic cyclones to climate change in CESM1

The dramatic warming of the Arctic over the last three decades has reduced both the thickness and extent of sea ice, opening opportunities for business in diverse sectors and increasing human exposure to meteorological hazards in the Arctic. It has been suggested that these changes in environmental conditions have led to an increase in extreme cyclones in the region, therefore increasing this hazard. In this study, we investigate the response of Arctic synoptic scale cyclones to climate change in a large initial value ensemble of future climate projections with the CESM1-CAM5 climate model (CESM-LE). We find that the response of Arctic cyclones in these simulations varies with season, with significant reductions in cyclone dynamic intensity across the Arctic basin in winter, but with contrasting increases in summer intensity within the region known as the Arctic Ocean cyclone maximum. There is also a significant reduction in winter cyclogenesis events within the Greenland–Iceland–Norwegian sea region. We conclude that these differences in the response of cyclone intensity and cyclogenesis, with season, appear to be closely linked to changes in surface temperature gradients in the high latitudes, with Arctic poleward temperature gradients increasing in summer, but decreasing in winter.

Do Natural Hazards Cause International Migration?*

The estimated amount of people affected by natural hazards stands at a staggering number of about 243 million people per year. While not all of the affected move across borders, international migration potentially provides an adaptation mechanism to natural hazards. The aim of this article is to assess whether natural hazards induce international migration from a macro perspective. We construct a stylized theoretical gravity model of migration that includes hazards as random shocks. To estimate this model, we deploy exogenous data on geological anzd meteorological hazards from 1980 to 2010. We combine these data with the World Bank's Global Bilateral Migration Database. Overall, our results suggest little evidence that natural hazards affect medium- to long-run international migration. However, considering heterogeneity across income groups, we find that particularly middle-income countries experience significant push and pull effects on migration from natural hazards. (JEL codes: F22, O15, Q54).

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Abstract. The assessment of road infrastructure exposure to extreme weather events is of major importance for scientists and practitioners alike. In this study, we compare the different extreme value approaches and fitting methods with respect to their value for assessing the exposure of transport networks to extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series (PDS) over the standardly used annual maxima series (AMS) in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing PDS) being superior to the block maxima approach (employing AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was visible from neither the square-root criterion nor standardly used graphical diagnosis (mean residual life plot) but rather from a direct comparison of AMS and PDS in combined quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best-suited approach. This will make the analyses more robust, not only in cases where threshold selection and dependency introduces biases to the PDS approach but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend the use of conditional performance measures that focus on rare events only in addition to standardly used unconditional indicators. The findings of the study directly address road and traffic management but can be transferred to a range of other environmental variables including meteorological and hydrological quantities.

A risk management system for meteorological disasters of solar greenhouse vegetables

Solar greenhouses are well-established and very popular in the north of China as a way of meeting the demand for fresh local winter vegetables. Nonetheless, they are more susceptible to meteorological disasters, such as fog, haze and cold temperatures. A meteorological risk management system that includes disaster forecasting and control is a useful tool to efficiently capture long-term and up-to-the-minute environmental fluctuations inside greenhouses. Based on the concept of the meteorological disaster warning model, this study has developed a meteorological risk management system built upon a browser/server framework and mobile internet to provide precision agriculture (PA) services with large-scale, long-term, scalable and real-time data collection capabilities for solar greenhouse vegetables. Early warning indicators were established for the main meteorological hazards to winter-spring vegetables in solar greenhouses, including low temperature and sparse sunlight, downy mildew, grey mildew and powdery mildew induced by unfavorable meteorological conditions. The system could provide a valuable framework for farmers and agrometeorological officials in analyzing the relationships between vegetable damage dynamics and meteorological events. Having been applied in Beijing and Tianjin, the system has correctly forecast meteorological disaster and diseases caused by long-term fog and haze from November 2015. Based on the analysis carried out, improved meteorological risk management and a more accurate decision-making strategy can be developed to assist PA in combating meteorological disaster.