Meteorological Risk Research Articles

Automated precipitation monitoring with the Thies disdrometer: biases and ways for improvement

Abstract. The intensity and phase of precipitation at the ground surface can have important implications not only for meteorological and hydrological situations but also in terms of hazards and risks. In the field, Thies disdrometers are sometimes used to monitor the quantity and nature of precipitation with high temporal resolution and very low maintenance and thus provide valuable information for the management of meteorological and hydrological risks. Here, we evaluate the Thies disdrometer with respect to precipitation detection, as well as the estimation of precipitation intensity and phase at a pre-alpine site in Switzerland (1060 m a.s.l.), using a weighing precipitation gauge (OTT pluviometer) and a two-dimensional video disdrometer (2DVD) as a reference. We show that the Thies disdrometer is well suited to detect even light precipitation, reaching a hit rate of around 95 %. However, the instrument tends to systematically underestimate rainfall intensities by 16.5 %, which can be related to a systematic underestimation of the number of raindrops with diameters between 0.5 and 3.5 mm. During snowfall episodes, a similar underestimation is observed in the particle size distribution (PSD), which is, however, not reflected in intensity estimates, probably due to a compensation by snow density assumptions. To improve intensity estimates, we test PSD adjustments (to the 2DVD) and direct adjustments of the resulting intensity estimates (to the OTT pluviometer), the latter of which are able to successfully reduce the systematic deviations during rainfall in the validation period. For snowfall, the combination of the 2DVD and the OTT pluviometer seems promising as it allows for improvement of snow density estimates, which poses a challenge to all optical precipitation measurements. Finally, we show that the Thies disdrometer and the 2DVD agree well insofar as the distinction between rain and snowfall is concerned, such that an important prerequisite for the proposed correction methods is fulfilled. Uncertainties mainly persist during mixed-phase precipitation or low precipitation intensities, where the assignment of precipitation phase is technically challenging, but less relevant for practical applications. We conclude that the Thies disdrometer is suitable not only to estimate precipitation intensity but also to distinguish between rain and snowfall. The Thies disdrometer therefore seems promising for the improvement of precipitation monitoring and the nowcasting of discharge in pre-alpine areas, where considerable uncertainties with respect to these quantities are still posing a challenge to decision-making.

Meteorological drought risk in the Daqing River Basin, North China: current observations and future projections

Drought is a major natural hazard that can have devastating impacts on regional agriculture, water supply, ecological environment and social economy. Extreme events, including droughts, are expected to be severer and more frequent because of climate warming. This paper presents an analysis of observed changes and future projections of meteorological drought in the Daqing River Basin (DRB), North China, based on the modified Standardized Precipitation Index (SPImod). Observed changes of meteorological drought are analyzed based on the precipitation series of 26 meteorological stations from 1971 to 2011, and future projections are made under two representative concentration pathways (RCPs 4.5 and 8.5) from 2021 to 2050. The result shows a change from wet to dry detected in most areas of the DRB in summer, winter and annual series. The drought risk is higher under the condition of “OR” and “AND” return period during the observation period, and the high-risk regions cover a large area. The drought risk from 2021 to 2050 will increase across the basin under RCP 4.5 and RCP 8.5, compared with which in the base period from 1971 to 2000. Most regions will be at a higher drought risk under the condition of “OR” return period, and the area with high-risk under RCP 4.5 is slightly larger than that under RCP 8.5. Under the condition of “AND” return period, the high-risk regions will cover the area from the northwest to the northeast, while the area of high-risk regions under RCP 8.5 will be larger than that under RCP 4.5. The result of this paper will be helpful for performing an efficient water resource management in the DRB under the impacts of global warming and climate change.

The Construction of an Intelligent Risk-Prevention System for Marine Silk Road

The purpose of this study is to explore how to effectively prevent risks in the Marine Silk Road. This paper establishes a hierarchical theoretical framework by using the interpretive structural modeling (ISM) and explores an application system for intelligent prevention. The fuzzy set theory is also used to screen out the unnecessary attributes, and a decision-making and trial evaluation laboratory (DEMATEL) is proposed to manage the complex interrelationships among the aspects and attributes. Finally, we suggest an applicable risk-prevention system for the Marine Silk Road. Our results: (1) the solution to international political and trade risks is the most critical for the risk prevention; (2) the solution to marine meteorological risks relies mainly on the improvement of ocean information sharing mechanism driven by big data which needs international cooperation in terms of information and technology; (3) the solution to marine energy and environmental risks also requires active international cooperation; (4) the application system should be built based on three levels, including the international level, the government level, and the company level. This theoretical hierarchical framework aims to guide the countries alongside the road to effectively prevent the risks on the Marine Silk Road, promote the sustainable development of the Marine Silk Road, and develop the transnational economies and cultures.

Regional atmospheric reanalysis activities at Deutscher Wetterdienst: review of evaluation results and application examples with a focus on renewable energy

Abstract. Based on the numerical weather prediction model COSMO of Germany's national meteorological service (Deutscher Wetterdienst, DWD), regional reanalysis datasets have been developed with grid spacing of up to 2 km. This development started as a fundamental research activity within the Hans-Ertel-Centre for Weather Research (HErZ) at the University of Bonn and the University of Cologne. Today, COSMO reanalyses are an established product of the DWD and have been widely used in applications on European and national German level. Successful applications of COSMO reanalyses include renewable energy assessments as well as meteorological risk estimates. The COSMO reanalysis datasets are now publicly available and provide spatio-temporal consistent data of atmospheric parameters covering both near-surface conditions and vertical profiles. This article reviews the status of the COSMO reanalyses, including evaluation results and applications. In many studies, evaluation of the COSMO reanalyses point to an overall good quality and often an added value compared to different contemporary global reanalysis datasets. We further outline current plans for the further development and application of regional reanalyses in the HErZ research group Cologne/Bonn in collaboration with the DWD.

Meteorological risk identification and assessment of offshore wind farms

During the construction and operation period, an offshore wind farm is exposed to a variety of meteorological threats, which could lead to severe damages and massive financial loss. In this work, we analyse meteorological risks of offshore wind farms in the coastal areas of the south-east Jiangsu Province. Firstly, we identified the risk factors through the Delphi Method and analysis of historical data. The five major risks include typhoon, lightning, extreme temperatures, salt frog, and oceanic disasters caused directly by meteorological disasters. Then, using the Analytic Hierarchy Process (AHP), we established index module of each layer and calculated the risk value of each influence factor. After that, we established the judgement matrix and the weight of each factor. Based on that, we got the comprehensive risk value and considered it as a medium risk. According to the weighting module, we also came to the conclusion that typhoon contributes most to the meteorological disaster of offshore wind farms, with a weight of 0.3937.

Hot Weather and Suicide Deaths among Older Adults in Hong Kong, 1976-2014: A Retrospective Study.

Findings of the association between hot weather and suicide in a subtropical city such as Hong Kong are inconsistent. This study aimed to revisit the association by identifying meteorological risk factors for older-adult suicides in Hong Kong using a time-series approach. A retrospective study was conducted on older-adult (aged ≥65) suicide deaths in Hong Kong from 1976 to 2014. Suicides were classified into those involving violent methods and those involving nonviolent methods. Meteorological data, including ambient temperature, were retrieved. Transfer function time-series models were fitted. In total, 7314 older-adult suicide deaths involving violent methods and 630 involving nonviolent methods were recorded. For violent-method suicides, a monthly average daily minimum ambient temperature was determined to best predict the monthly rate, and a daily maximum ambient temperature of 30.3 °C was considered the threshold. For suicide deaths involving nonviolent methods, the number of days in a month for which the daily maximum ambient temperature exceeded 32.7 °C could best predict the monthly rate. Higher ambient temperature was associated with more older-adult suicide deaths, both from violent and nonviolent methods. Weather-focused preventive measures for older-adult suicides are necessary, such as the provision of more public air-conditioned areas where older adults can shelter from extreme hot weather.

ANALISIS POR ELEMENTOS FINITOS DEL COMPORTAMIENTO ESTRUCTURAL DE FORTIFICACIONES ESPAÑOLAS EN LOS ESTADOS UNIDOS APLICANDO LA NORMA ASCE 7-10 Y SIMULACION DE IMPACTOS Y EXPLOSIONES

The work of Spanish Military Engineers in the United States is a little-known and studied topic. However, throughout the seventeenth, eighteenth and nineteenth centuries, 37 Military Engineers at the service of Spain, designed all kinds of constructions and elaborated maps and plans in U.S.; covering these works from Florida to California. These engineers had a common education in fortifications. However, this will not prevent it from adapting to the characteristics of the different territories. The objective of this study is to analyze, by the calculation of finite elements, the defensive characteristic elements of these masonry walls fortifications and analyze the behavior against meteorological and geological risks through the application of United States regulation; ASCE 7-10 and ASCE 24-05. Specifically, we have conducted the study on the Castillo de San Marcos in Saint Augustine, Florida. The impact of projectiles on the walls was analyzed. The destructive risk against accidental explosions and the behavior of the gunpower rooms before explosions was also analyzed. Keywords: Military Engineers, Finite Element Analysis, Fortifications, Gunpowder rooms, Castillo de San Marcos.

Association between climate and new daily diagnoses of COVID-19

Abstract Background Although evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks, uncertainty remains concerning the real impact of climate factors on viral transmission. Methods. The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto Region, while information on daily weather parameters in the same area was downloaded from IlMeteo website, a renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 to November 11, 2020. The number of new daily COVID-19 cases and meteorological data in Verona were correlated using both univariate and multivariate analysis. Results The number of daily COVID-19 diagnoses in Verona was positively associated with the number of days in lockdown and humidity, and inversely correlated with mean, min and max temperature, mean wind speed and number of days with rainfall. Days of lockdown, mean air temperature, humidity, mean wind speed and number of days with rainfall remained significantly associated in multivariate analysis. The four weather parameters contributed to explaining 61% of variance in new daily COVID-19 diagnoses. Each 1% increase in air temperature, 1% decrease in humidity, 1 km/h increase in wind speed and day with rainfall were independently associated with 1.0%, 0.3%, 1.2% and 5.4% reduction in new COVID-19 daily diagnoses. A significant difference was observed in values of all-weather parameters recorded in Verona between days with Conclusions Climate conditions may play an essential role in conditions of viral transmission, and influence the likelihood or course of local outbreaks. Preventive measures, testing policies and hospital preparedness should be reinforced during periods of higher meteorological risk and in local environments with adverse climate conditions.

Datasets of meteorological drought events and risks for the developing countries in Eurasia

ABSTRACT For the area of Eurasia concentrated with developing countries (referred to here by the abbreviation DPEA), mainly located in Asia and Eastern Europe, this work presents datasets of gridded meteorological drought events and country-based drought risk by combining multiple drought indices and socio-economic data. A basic gridded dataset of the drought events during 1950–2015 is extracted from three drought indices: the self-calibrating Palmer Drought Severity Index, the Standardized Precipitation Index, and the Standardized Precipitation Evapotranspiration Index. The three drought indices generally show consistent characteristics of drought events in DPEA. A second-level dataset (a drought risk dataset) is then produced as the product of drought hazard, exposure and vulnerability during 2000–2015. For drought exposure, the indicators of population and livestock density, agricultural land and water stress are chosen, while drought vulnerability composites multiple social, economic and infrastructural factors. Drought hazard tends to concentrate at the southern rim of Eurasia. Relatively large differences in drought exposure exist between different countries, but for drought vulnerability the differences are small. After considering the socio-economic components in risk assessment, most countries in West, South-Central and South Asia have the highest drought risk in DPEA. The datasets of drought events and risks are available at http://www.dx.doi.org/10.11922/sciencedb.898.

Meteorological Risk Assessment of Rooftop Solar Resource Development in Inner Mongolia

Due to the long and narrow regional characteristics of Inner Mongolia, there are obvious climatic differences between the east and the west, and various meteorological factors have different influences on the development and utilization of solar energy. The abundance and stability index of solar energy resources are relatively high in the central and western region of Inner Mongolia, but there are more sandstorms, high temperature and strong wind. The eastern region is greatly affected by cloud cover, relative humidity and snowfall, which weakens the solar radiation. Through the comprehensive evaluation of the solar energy resources and meteorological elements, it is found that from the Alashan League to the west of Xilin Gol League, and the most of the Chifeng City are low-risk areas, which are relatively suitable for the development and utilization of rooftop solar energy. The central and northern areas of hulunbuir are high-risk areas, which is not suitable for that. Based on the meteorological industry standard “Solar Energy Resource Assessment Method”, we calculate the solar energy resources abundance and stability index, combined with the annual surface meteorological data of 119 meteorological stations in Inner Mongolia from 1988 to 2018. The distribution characteristics of solar energy resources and meteorological elements in Inner Mongolia is analyzed and the suitability and meteorological risks of rooftop solar resources development and utilization are evaluated.

基于GIS的农业气象灾害风险区划应用系统

基于GIS的农业气象灾害风险区划应用系统

Weather derivatives to mitigate meteorological risks in tourism management: An empirical application to celebrations of Comunidad Valenciana (Spain)

This article explores the possibility of implementing weather derivatives in cultural events through an empirical application to celebrations of Comunidad Valenciana (Spain). Temperature- and rainfall-based options geared to the three counties of this Autonomous Community are proposed to mitigate the risk exposure of this event. First, the contracts are priced through the Index Value Simulation and Daily Simulation techniques, which rely on Monte Carlo simulations. Next, they are used to design realistic hedging strategies, which are evaluated under different meteorological scenarios. The degree of geographical basis risk affecting this region, as measured by the root mean square error, is also assessed since it is a common issue refraining the application of weather derivatives. The outcomes attained emphasize the high hedging potential of the suggested tools and indicate the appropriateness of considering, on a case-by-case basis, the possibility of using a combination of derivatives geared to nearby stations as a solution to mitigate basis risk exposure.

Regional detection of multiple change points and workable application for precipitation by maximum likelihood approach

Precipitation is an essential part of the hydrological cycle. Objective change-point detection plays an important role in the research on extreme climate events and risk assessment in the context of global climate change. The study can automatically identify and extract multiple change points over a lengthy time series and calculate trends over several segmentations by uniting the maximum likelihood approach and the nonparametric Mann-Kendall trend test which is also compared with ordinary least squares (OLS). The observed station precipitation data were compiled over Hebei Province in China from 1961 to 2014. Temporal-spatial characteristics were also investigated by using several indices: the number of change points, standard deviation, timing of change points, minimum and maximum trends for segmentations, and the generalization trend. Obvious change points were generally around 1974, 1981, and 1998, and occurred at few stations before 1974 and after 2000, indicating that precipitation was relatively stable in the study area during the periods 1961–1974 and 2000–2014; the minimum trend for segmentations decreased over all stations; the maximum trend for segmentations increased over all stations except Leting; and generalization trend weakened abrupt changes in specific time sections among the multiple segmentations. Change-point detection followed by trend analysis can detect an obvious increasing or decreasing trend over certain parts of the time series and the proposed method can serve as a management tool with proper measures to deal with climate change. The results for both segmentations and generalization can provide a workable reference for managing regional water resources and implementing strategies to mitigate meteorological risks.

Meteorological Risks in Doha 2019 Athletics World Championships: Health Considerations From Organizers.

The Doha 2019 IAAF World Championships represent a challenge for athletes, workforce and spectators who could compete, work or attend under likely extreme meteorological conditions. This short article summarizes the methodology used by the IAAF and the Local Organizing Committee doctors to analyze and reduce risks, while complying as much as possible with existing recommendations or policies. The main steps to be completed are identification and description of weather-related risks, description and whenever possible testing of all their possible mitigation measures during test events, revision of these risks once mitigation implemented, and finally drafting a contingency plan for remaining exceptional and impactful occurrences. Such risk management methodology could apply to other sports, ideally from the host city selection to the delivery of the competitive event.

Low ambient temperature as the only meteorological risk factor of seizure occurrence: A multivariate study

BackgroundThe onset of epileptic seizures is influenced by weather, which is multifactorial. It is unknown which specific weather factors affect the occurrence of seizures. ObjectivesWe studied the correlation between the onset of epileptic seizures and multiple weather parameters based on a population-based registry profile. MethodsWe determined the number of patients who visited emergency services in Taiwan diagnosed as having epilepsy. Then we used a linear regression model to analyze the monthly average number of patients who received emergency treatment for epilepsy in relation to temperature, barometric pressure, accumulated precipitation, relative humidity, and hours of sunshine. The Poisson regression model was used to analyze multiple meteorological factors in relation to the number of daily emergency visits because of epilepsy. A receiver operating characteristic curve was used to determine the cutoff temperature for the occurrence of seizures. ResultsTemperature appeared to be the robust factor for the onset of epilepsy. For every 1 °C decrease in temperature, there was a relative risk increase of 1.016 in the number of emergency visits as a result of epilepsy. Temperature lower than 18 °C had the best predictive value for seizure. Barometric pressure, accumulated precipitation, relative humidity, and the number of hours of sunshine were not related to the occurrence of seizures. SignificanceOur results suggest that temperature is the only influential meteorological factor that affects seizure occurrence.

Weather index-based insurance as a meteorological risk management alternative in viticulture

This article explores the hedging potential of two weather index-based insurance programmes designed for the Rias Baixas Protected Designation of Origin (Spain). The first alternative insures both extreme and non-extreme weather events, while the second instrument covers exclusively extreme meteorological states. Two bioclimatic indicators computed for the period most correlated to grape yields are proposed as underlyings: the Branas, Bernon and Levadoux (BBL) and the Ribéreau-Gayon and Peynaud hydrothermal scale (RGP). Yield-weather dependence is then modelled with two different methodological approaches: copulas and linear regression. To asses the risk reducing potential, a hedging effectiveness analysis based on real and simulated data is carried out. The model uses variance and expected shortfall as risk measures. The results attained point out the high hedging ability of both insurance programmes, especially of the first of them based on RGP. This appraisal also reveals that the copula technique outperforms linear regression. Overall, the study results suggest that the implementation of policies geared to bioclimatic indices able to signal adverse weather events can significantly mitigate weather-related yield variations in viticulture.

Evaluation of the Stationarity Assumption for Meteorological Drought Risk Estimation at the Multidecadal Scale in Contiguous United States

AbstractIn this study, we analyze the nonstationarity in meteorological droughts at the multidecadal scale in different parts of the contiguous United States during 1901–2017. We develop metrics to compare the drought risk calculated under the assumptions of stationarity and nonstationarity and identify their spatial and temporal patterns. By analyzing the variability of drought risk in the past and exploring its ongoing patterns, we evaluate in which regions of the contiguous United States the assumption of stationarity can be safely used for drought risk planning and management. We find statistically significant interdecadal changes in the probability distribution functions of drought severity in parts of the Northwest, upper Midwest, the Northeast, eastern parts of Great Plains and in parts of Arizona, New Mexico, Utah, and Nevada in the Southwest. In these regions, the nonstationary risk has been significantly higher than the stationary estimate of risk in the past, which shows that the assumption of stationarity can lead to the underestimation of drought risk in these regions. The multidecadal drought risk shows low variability in California, parts of northern and western Great Plains, Ohio Valley, and in the Southeast, since the statistical properties of droughts have not changed significantly in these regions during 1901–2017. However, the meteorological drought risk has increased in California and the Southeast in the recent decades due to the influence of global warming and hence the assumption of stationarity for risk estimation may lead to underestimation of drought risk in future in these regions if this effect of global warming persists.

Review of ESACP/WMO Typhoon Committee Development in Past 50 Years

ABSTRACT The ESCAP/WMO Typhoon Committee (TC) is an intergovernmental regional organization, established by Governments of ESCAP Member Countries (or Member Territory) under the joint auspices of ESCAP and WMO in 1968 to minimize the typhoon-related disaster risk reduction and damage mitigation in the region and to facilities closer regional and international cooperation. As of 2017, there are 14 Members. The Typhoon Committee has been repeatedly recognized as an outstanding regional body who has integrated the actions and plans of the meteorological, hydrological, and disaster risk reduction (DRR) components to produce meaningful results. Its work is primarily centered on reduction the damage caused by typhoons and floods, and focus on the following: 1) review the progress made in the various fields of typhoon damage prevention; 2) recommend the participating governments on plans and measures the improvement of community preparedness and disaster prevention; 3) promote the interested Governments and other interested organization for the coordination of research on typhoons; and 4) provide financial and technical support for plans and programs upon request. The paper reviewed the development of the Committee in the past 50 years in the aspects of establishment; membership, secretariat and programme components; strategic plan; and cooperative mechanism. The paper also states the areas of technical activities to be enhanced in the region and the proposals to enhance the Typhoon Committee’s regional and international collaboration mechanism on typhoon-related disaster risk reduction and damage mitigation.

Return period of extreme rainfall substantially decreases under 1.5 °C and 2.0 °C warming: a case study for Uttarakhand, India

In June 2013, Uttarakhand experienced a hydro-meteorological disaster due to a 4 d extreme precipitation event of return period more than 100 years, claiming thousands of lives and causing enormous damage to infrastructure. Using the weather@home climate modelling system and its Half a degree Additional warming, Prognosis and Projected Impacts simulations, this study investigates the change in the return period of similar events in a 1.5 °C and 2 °C warmer world, compared to current and pre-industrial levels. We find that the likelihood of such extreme precipitation events will significantly increase under both future scenarios. We also estimate the change in extreme river flow at the Ganges; finding a considerable increase in the risk of flood events. Our results also suggest that until now, anthropogenic aerosols may have effectively counterbalanced the otherwise increased meteorological flood risk due to greenhouse gas (GHG) induced warming. Disentangling the response due to GHGs and aerosols is required to analyses the changes in future rainfall in the South Asia monsoon region. More research with other climate models is also necessary to make sure these results are robust.

Combination of Probabilistic Linguistic Term Sets and PROMETHEE to Evaluate Meteorological Disaster Risk: Case Study of Southeastern China

The meteorological disasters have brought destructive damages all around the world in the past decades. These disasters have posed great threats to sustainable development. It is necessary to evaluate meteorological disaster risk to make corresponding emergency measures. The process is uncertain and fuzzy regarding the experts’ preferences. To deal with the problem, a novel evaluation approach based on PROMETHEE method and probabilistic linguistic term set (PLTS) is firstly proposed. First of all, PLTS is adopted to express preferences’ of experts. Then, the weights of criteria are obtained by the differential evolution (DE) algorithm, and steps of the method are proposed. Finally, the proposed method is used to evaluate the whole meteorological disaster risk in the southeast coastal areas of China and results have verified the effectiveness of the method. By comparing with some similar methods, results have demonstrated the advantages of the approach.