Non-catastrophic and catastrophic fractures in racing Thoroughbreds at the Hong Kong Jockey Club.

Science.gov (United States)

Sun, T C; Riggs, C M; Cogger, N; Wright, J; Al-Alawneh, J I

2018-04-19

Reports of fractures in racehorses have predominantly focused on catastrophic injuries, and there is limited data identifying the location and incidence of fractures that did not result in a fatal outcome. To describe the nature and the incidence of non-catastrophic and catastrophic fractures in Thoroughbreds racing at the Hong Kong Jockey Club (HKJC) over seven racing seasons. Retrospective cohort study. Data of fractures sustained in horses while racing and of race characteristics were extracted from the HKJC Veterinary Management Information System (VMIS) and Racing Information System (RIS) respectively. The fracture event was determined from the first clinical entry for each specific injury. The incidence rates of non-catastrophic and catastrophic fractures were calculated per 1000 racing starts for racetrack, age, racing season, sex and trainer. 179 first fracture events occurred in 64,807 racing starts. The incidence rate of non-catastrophic fractures was 2.2 per 1000 racing starts and of catastrophic fractures was 0.6 per 1000 racing starts. Fractures of the proximal sesamoid bones represented 55% of all catastrophic fractures while the most common non-catastrophic fractures involved the carpus and the first phalanx. Significant associations were detected between the incidence of non-catastrophic fractures and sex, trainer and racing season. The first fracture event was used to calculate the incidence rate in this study and may have resulted in underestimation of the true incidence rate of fractures in this population. However, given the low number of recorded fracture events compared to the size of the study population, this underestimation is likely to be small. There were 3.6 times as many non-catastrophic fractures as catastrophic fractures in Thoroughbreds racing in Hong Kong between 2004 and 2011. Non-catastrophic fractures interfere with race training schedules and may predispose to catastrophic fracture. Future analytical studies on non-catastrophic

Forecasting potential crises

International Nuclear Information System (INIS)

Neufeld, W.P.

1984-01-01

Recently, the Trend Analysis Program (TAP) of the American Council of Life Insurance commissioned the Futures Group of Glastonbury, Connecticut, to examine the potential for large-scale catastrophic events in the near future. TAP was specifically concerned with five potential crises: the warming of the earth's atmosphere, the water shortage, the collapse of the physical infrastructure, the global financial crisis, and the threat of nuclear war. We are often unprepared to take action; in these cases, we lose an advantage we might have otherwise had. This is the whole idea behind forecasting: to foresee possibilities and to project how we can respond. If we are able to create forecasts against which we can test policy options and choices, we may have the luxury of adopting policies ahead of events. Rather than simply fighting fires, we have the option of creating a future more to our choosing. Short descriptions of these five potential crises and, in some cases, possible solutions are presented

Extreme events and predictability of catastrophic failure in composite materials and in the Earth

Science.gov (United States)

Main, I.; Naylor, M.

2012-05-01

Despite all attempts to isolate and predict extreme earthquakes, these nearly always occur without obvious warning in real time: fully deterministic earthquake prediction is very much a `black swan'. On the other hand engineering-scale samples of rocks and other composite materials often show clear precursors to dynamic failure under controlled conditions in the laboratory, and successful evacuations have occurred before several volcanic eruptions. This may be because extreme earthquakes are not statistically special, being an emergent property of the process of dynamic rupture. Nevertheless, probabilistic forecasting of event rate above a given size, based on the tendency of earthquakes to cluster in space and time, can have significant skill compared to say random failure, even in real-time mode. We address several questions in this debate, using examples from the Earth (earthquakes, volcanoes) and the laboratory, including the following. How can we identify `characteristic' events, i.e. beyond the power law, in model selection (do dragon-kings exist)? How do we discriminate quantitatively between stationary and non-stationary hazard models (is a dragon likely to come soon)? Does the system size (the size of the dragon's domain) matter? Are there localising signals of imminent catastrophic failure we may not be able to access (is the dragon effectively invisible on approach)? We focus on the effect of sampling effects and statistical uncertainty in the identification of extreme events and their predictability, and highlight the strong influence of scaling in space and time as an outstanding issue to be addressed by quantitative studies, experimentation and models.

Catastrophic Incident Recovery: Long-Term Recovery from an Anthrax Event Symposium

Energy Technology Data Exchange (ETDEWEB)

Lesperance, Ann M.

2008-06-30

On March 19, 2008, policy makers, emergency managers, and medical and Public Health officials convened in Seattle, Washington, for a workshop on Catastrophic Incident Recovery: Long-Term Recovery from an Anthrax Event. The day-long symposium was aimed at generating a dialogue about restoration and recovery through a discussion of the associated challenges that impact entire communities, including people, infrastructure, and critical systems.

Forecasting with quantitative methods the impact of special events in time series

OpenAIRE

Nikolopoulos, Konstantinos

2010-01-01

Abstract Quantitative methods are very successful for producing baseline forecasts of time series; however these models fail to forecast neither the timing nor the impact of special events such as promotions or strikes. In most of the cases the timing of such events is not known so they are usually referred as shocks (economics) or special events (forecasting). Sometimes the timing of such events is known a priori (i.e. a future promotion); but even then the impact of the forthcom...

A Novel Forecasting System for Solar Particle Events and Flares (FORSPEF)

International Nuclear Information System (INIS)

Papaioannou, A; Anastasiadis, A; Sandberg, I; Tsiropoula, G; Tziotziou, K; Georgoulis, M K; Jiggens, P; Hilgers, A

2015-01-01

Solar Energetic Particles (SEPs) result from intense solar eruptive events such as solar flares and coronal mass ejections (CMEs) and pose a significant threat for both personnel and infrastructure in space conditions. In this work, we present FORSPEF (Forecasting Solar Particle Events and Flares), a novel dual system, designed to perform forecasting of SEPs based on forecasting of solar flares, as well as independent SEP nowcasting. An overview of flare and SEP forecasting methods of choice is presented. Concerning SEP events, we make use for the first time of the newly re-calibrated GOES proton data within the energy range 6.0-243 MeV and we build our statistics on an extensive time interval that includes roughly 3 solar cycles (1984-2013). A new comprehensive catalogue of SEP events based on these data has been compiled including solar associations in terms of flare (magnitude, location) and CME (width, velocity) characteristics. (paper)

The Ongoing Catastrophe

DEFF Research Database (Denmark)

Kublitz, Anja

2015-01-01

as camps. Based on fieldwork among Palestinians in the Danish camps, this article explores why my interlocutors describe their current lives as a catastrophe. Al-Nakba literally means the catastrophe and, in Palestinian national discourse, it is used to designate the event of 1948, when the Palestinians...

New Developments Regarding the KT Event and Other Catastrophes in Earth History

Science.gov (United States)

1994-01-01

Papers presented at the conference on New Developments Regarding the KT Event and Other Catastrophes in Earth History are included. Topics covered include: trajectories of ballistic impact ejecta on a rotating earth; axial focusing of impact energy in the earth's interior: proof-of-principle tests of a new hypothesis; in search of Nemesis; impact, extinctions, volcanism, glaciations, and tectonics: matches and mismatches.

Catastrophic events leading to de facto limits on liability

International Nuclear Information System (INIS)

Solomon, K.A.; Okrent, D.

1977-05-01

This study conducts an overview of large technological systems in society to ascertain prevalence, if any, of situations that can lead to catastrophic effects where the resultant liabilities far exceed the insurances or assets subject to suit in court, thereby imposing de facto limits on liability. Several potential situations are examined: dam rupture, aircraft crash into a sports stadium, chemical plant accident, shipping disaster, and a toxic drug disaster. All of these events are estimated to have probabilities per year similar to or larger than a major nuclear accident and they are found to involve potential liability far exceeding the available resources, such as insurance, corporation assets, or government revenues

GPS-based PWV for precipitation forecasting and its application to a typhoon event

Science.gov (United States)

Zhao, Qingzhi; Yao, Yibin; Yao, Wanqiang

2018-01-01

The temporal variability of precipitable water vapour (PWV) derived from Global Navigation Satellite System (GNSS) observations can be used to forecast precipitation events. A number of case studies of precipitation events have been analysed in Zhejiang Province, and a forecasting method for precipitation events was proposed. The PWV time series retrieved from the Global Positioning System (GPS) observations was processed by using a least-squares fitting method, so as to obtain the line tendency of ascents and descents over PWV. The increment of PWV for a short time (two to six hours) and PWV slope for a longer time (a few hours to more than ten hours) during the PWV ascending period are considered as predictive factors with which to forecast the precipitation event. The numerical results show that about 80%-90% of precipitation events and more than 90% of heavy rain events can be forecasted two to six hours in advance of the precipitation event based on the proposed method. 5-minute PWV data derived from GPS observations based on real-time precise point positioning (RT-PPP) were used for the typhoon event that passed over Zhejiang Province between 10 and 12 July, 2015. A good result was acquired using the proposed method and about 74% of precipitation events were predicted at some ten to thirty minutes earlier than their onset with a false alarm rate of 18%. This study shows that the GPS-based PWV was promising for short-term and now-casting precipitation forecasting.

Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.

Science.gov (United States)

Kelly, David; Majda, Andrew J; Tong, Xin T

2015-08-25

The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.

Pathways linking drug use and labour market trajectories: the role of catastrophic events.

Science.gov (United States)

Richardson, Lindsey; Small, Will; Kerr, Thomas

2016-01-01

People affected by substance use disorders often experience sub-optimal employment outcomes. The role of drug use in processes that produce and entrench labour market precarity among people who inject drugs (PWID) have not, however, been fully described. We recruited 22 PWID from ongoing prospective cohort studies in Vancouver, Canada, with whom we conducted semi-structured retrospective interviews and then employed a thematic analysis that drew on concepts from life course theory to explore the mechanisms and pathways linking drug use and labour market trajectories. The participants' narratives identified processes corresponding to causation, whereby suboptimal employment outcomes led to harmful drug use; direct selection, where impairment, health complications or drug-seeking activities selected individuals out of employment; and indirect selection, where external factors, such as catastrophic events, marked the initiation or intensification of substance use concurrent with sudden changes in capacities for employment. Catastrophic events linking negative transitions in both drug use and labour market trajectories were of primary importance, demarcating critical initiation and transitional events in individual risk trajectories. These results challenge conventional assumptions about the primacy of drug use in determining employment outcomes among PWID and suggest the importance of multidimensional support to mitigate the initiation, accumulation and entrenchment of labour market and drug-related disadvantage. © 2015 Foundation for the Sociology of Health & Illness.

Forecasting E > 50-MeV Proton Events with the Proton Prediction System (PPS)

Science.gov (United States)

Kahler, S. W.; White, S. M.; Ling, A. G.

2017-12-01

Forecasting solar energetic (E > 10 MeV) particle (SEP) events is an important element of space weather. While several models have been developed for use in forecasting such events, satellite operations are particularly vulnerable to higher-energy (> 50 MeV) SEP events. Here we validate one model, the proton prediction system (PPS), which extends to that energy range. We first develop a data base of E > 50-MeV proton events > 1.0 proton flux units (pfu) events observed on the GOES satellite over the period 1986 to 2016. We modify the PPS to forecast proton events at the reduced level of 1 pfu and run PPS for four different solar input parameters: (1) all > M5 solar X-ray flares; (2) all > 200 sfu 8800-MHz bursts with associated > M5 flares; (3) all > 500 sfu 8800-MHz bursts; and (4) all > 5000 sfu 8800-MHz bursts. For X-ray flare inputs the forecasted event peak intensities and fluences are compared with observed values. The validation contingency tables and skill scores are calculated for all groups and used as a guide to use of the PPS. We plot the false alarms and missed events as functions of solar source longitude.

Changes in Climate Extremes and Catastrophic Events in the Mongolian Plateau from 1951 to 2012

DEFF Research Database (Denmark)

Wang, Lei; Yao, Zhi-Jun; Jiang, Liguang

2016-01-01

The spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and s...

Advanced mesoscale forecasts of icing events for Gaspe wind farms

International Nuclear Information System (INIS)

Gayraud, A.; Benoit, R.; Camion, A.

2009-01-01

Atmospheric icing includes every event which causes ice accumulations of various shapes on different structures. In terms of its effects on wind farms, atmospheric icing can decrease the aerodynamic performance, cause structure overloading, and add vibrations leading to failure and breaking. This presentation discussed advanced mesoscale forecasts of icing events for Gaspe wind farms. The context of the study was discussed with particular reference to atmospheric icing; effects on wind farms; and forecast objectives. The presentation also described the models and results of the study. These included MC2, a compressible community model, as well as a Milbrandt and Yau condensation scheme. It was shown that the study has provided good estimates of the duration of events as well as reliable precipitation categories. tabs., figs.

Assimilation of lightning data by nudging tropospheric water vapor and applications to numerical forecasts of convective events

Science.gov (United States)

Dixon, Kenneth

A lightning data assimilation technique is developed for use with observations from the World Wide Lightning Location Network (WWLLN). The technique nudges the water vapor mixing ratio toward saturation within 10 km of a lightning observation. This technique is applied to deterministic forecasts of convective events on 29 June 2012, 17 November 2013, and 19 April 2011 as well as an ensemble forecast of the 29 June 2012 event using the Weather Research and Forecasting (WRF) model. Lightning data are assimilated over the first 3 hours of the forecasts, and the subsequent impact on forecast quality is evaluated. The nudged deterministic simulations for all events produce composite reflectivity fields that are closer to observations. For the ensemble forecasts of the 29 June 2012 event, the improvement in forecast quality from lightning assimilation is more subtle than for the deterministic forecasts, suggesting that the lightning assimilation may improve ensemble convective forecasts where conventional observations (e.g., aircraft, surface, radiosonde, satellite) are less dense or unavailable.

The impact of climate change on catastrophe risk models : implications for catastrophe risk markets in developing countries

OpenAIRE

Seo, John; Mahul, Olivier

2009-01-01

Catastrophe risk models allow insurers, reinsurers and governments to assess the risk of loss from catastrophic events, such as hurricanes. These models rely on computer technology and the latest earth and meteorological science information to generate thousands if not millions of simulated events. Recently observed hurricane activity, particularly in the 2004 and 2005 hurricane seasons, i...

Direct catastrophic injury in sports.

Science.gov (United States)

Boden, Barry P

2005-11-01

Catastrophic sports injuries are rare but tragic events. Direct (traumatic) catastrophic injury results from participating in the skills of a sport, such as a collision in football. Football is associated with the greatest number of direct catastrophic injuries for all major team sports in the United States. Pole vaulting, gymnastics, ice hockey, and football have the highest incidence of direct catastrophic injuries for sports in which males participate. In most sports, the rate of catastrophic injury is higher at the collegiate than at the high school level. Cheerleading is associated with the highest number of direct catastrophic injuries for all sports in which females participate. Indirect (nontraumatic) injury is caused by systemic failure as a result of exertion while participating in a sport. Cardiovascular conditions, heat illness, exertional hyponatremia, and dehydration can cause indirect catastrophic injury. Understanding the common mechanisms of injury and prevention strategies for direct catastrophic injuries is critical in caring for athletes.

Simulation of the catastrophic floods caused by extreme rainfall events - Uh River basin case study

OpenAIRE

Pekárová, Pavla; Halmová, Dana; Mitková, Veronika

2005-01-01

The extreme rainfall events in Central and East Europe on August 2002 rise the question, how other basins would respond on such rainfall situations. Such theorisation helps us to arrange in advance the necessary activity in the basin to reduce the consequence of the assumed disaster. The aim of the study is to recognise a reaction of the Uh River basin (Slovakia, Ukraine) to the simulated catastrophic rainfall events from August 2002. Two precipitation scenarios, sc1 and sc2, were created. Th...

Catastrophic event modeling. [lithium thionyl chloride batteries

Science.gov (United States)

Frank, H. A.

1981-01-01

A mathematical model for the catastrophic failures (venting or explosion of the cell) in lithium thionyl chloride batteries is presented. The phenomenology of the various processes leading to cell failure is reviewed.

Forecast of icing events at a wind farm in Sweden

DEFF Research Database (Denmark)

Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

2014-01-01

This paper introduces a method for identifying icing events using a physical icing model, driven by atmospheric data from the Weather Research and Forecasting (WRF) model, and applies it to a wind park in Sweden. Observed wind park icing events were identified by deviation from an idealized power...

Quantum catastrophe of slow light

OpenAIRE

Leonhardt, Ulf

2001-01-01

Catastrophes are at the heart of many fascinating optical phenomena. The rainbow, for example, is a ray catastrophe where light rays become infinitely intense. The wave nature of light resolves the infinities of ray catastrophes while drawing delicate interference patterns such as the supernumerary arcs of the rainbow. Black holes cause wave singularities. Waves oscillate with infinitely small wave lengths at the event horizon where time stands still. The quantum nature of light avoids this h...

Near-term probabilistic forecast of significant wildfire events for the Western United States

Science.gov (United States)

Haiganoush K. Preisler; Karin L. Riley; Crystal S. Stonesifer; Dave E. Calkin; Matt Jolly

2016-01-01

Fire danger and potential for large fires in the United States (US) is currently indicated via several forecasted qualitative indices. However, landscape-level quantitative forecasts of the probability of a large fire are currently lacking. In this study, we present a framework for forecasting large fire occurrence - an extreme value event - and evaluating...

Review of Wind Energy Forecasting Methods for Modeling Ramping Events

Energy Technology Data Exchange (ETDEWEB)

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Problems in the forecasting of solar particle events for manned missions

International Nuclear Information System (INIS)

Feynman, J.; Ruzmaikin, A.

1999-01-01

Manned spacecraft will require a much improved ability to forecast solar particle events. The lead time required will depend on the use to which the forecast is put. Here we discuss problems of forecasting with the lead times of hours to weeks. Such forecasts are needed for scheduling and carrying out activities. Our present capabilities with these lead times is extremely limited. To improve our capability we must develop an ability to predict fast coronal mass ejections (CMEs). It is not sufficient to observe that a CME has already taken place since by that time it is already too late to make predictions with these lead times. Both to learn how to predict CMEs and to carry out forecasts on time scales of several days to weeks, observations of the other side of the Sun are required. We describe a low-cost space mission of this type that would further the development of an hours-to-weeks forecast capability

High-Resolution Discharge Forecasting for Snowmelt and Rainfall Mixed Events

Directory of Open Access Journals (Sweden)

Tomasz Berezowski

2018-01-01

Full Text Available Discharge events induced by mixture of snowmelt and rainfall are strongly nonlinear due to consequences of rain-on-snow phenomena and snowmelt dependence on energy balance. However, they received relatively little attention, especially in high-resolution discharge forecasting. In this study, we use Random Forests models for 24 h discharge forecasting in 1 h resolution in a 105.9 km 2 urbanized catchment in NE Poland: Biala River. The forcing data are delivered by Weather Research and Forecasting (WRF model in 1 h temporal and 4 × 4 km spatial resolutions. The discharge forecasting models are set in two scenarios with snowmelt and rainfall and rainfall only predictors in order to highlight the effect of snowmelt on the results (both scenarios use also pre-forecast discharge based predictors. We show that inclusion of snowmelt decrease the forecast errors for longer forecasts’ lead times. Moreover, importance of discharge based predictors is higher in the rainfall only models then in the snowmelt and rainfall models. We conclude that the role of snowmelt for discharge forecasting in mixed snowmelt and rainfall environments is in accounting for nonlinear physical processes, such as initial wetting and rain on snow, which cannot be properly modelled by rainfall only.

Empirical Bayes Credibility Models for Economic Catastrophic Losses by Regions

Directory of Open Access Journals (Sweden)

Jindrová Pavla

2017-01-01

Full Text Available Catastrophic events affect various regions of the world with increasing frequency and intensity. The number of catastrophic events and the amount of economic losses is varying in different world regions. Part of these losses is covered by insurance. Catastrophe events in last years are associated with increases in premiums for some lines of business. The article focus on estimating the amount of net premiums that would be needed to cover the total or insured catastrophic losses in different world regions using Bühlmann and Bühlmann-Straub empirical credibility models based on data from Sigma Swiss Re 2010-2016. The empirical credibility models have been developed to estimate insurance premiums for short term insurance contracts using two ingredients: past data from the risk itself and collateral data from other sources considered to be relevant. In this article we deal with application of these models based on the real data about number of catastrophic events and about the total economic and insured catastrophe losses in seven regions of the world in time period 2009-2015. Estimated credible premiums by world regions provide information how much money in the monitored regions will be need to cover total and insured catastrophic losses in next year.

Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System.

Science.gov (United States)

Doyle, Andy; Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

2014-12-01

Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years.

Failure Forecasting in Triaxially Stressed Sandstones

Science.gov (United States)

Crippen, A.; Bell, A. F.; Curtis, A.; Main, I. G.

2017-12-01

Precursory signals to fracturing events have been observed to follow power-law accelerations in spatial, temporal, and size distributions leading up to catastrophic failure. In previous studies this behavior was modeled using Voight's relation of a geophysical precursor in order to perform `hindcasts' by solving for failure onset time. However, performing this analysis in retrospect creates a bias, as we know an event happened, when it happened, and we can search data for precursors accordingly. We aim to remove this retrospective bias, thereby allowing us to make failure forecasts in real-time in a rock deformation laboratory. We triaxially compressed water-saturated 100 mm sandstone cores (Pc= 25MPa, Pp = 5MPa, σ = 1.0E-5 s-1) to the point of failure while monitoring strain rate, differential stress, AEs, and continuous waveform data. Here we compare the current `hindcast` methods on synthetic and our real laboratory data. We then apply these techniques to increasing fractions of the data sets to observe the evolution of the failure forecast time with precursory data. We discuss these results as well as our plan to mitigate false positives and minimize errors for real-time application. Real-time failure forecasting could revolutionize the field of hazard mitigation of brittle failure processes by allowing non-invasive monitoring of civil structures, volcanoes, and possibly fault zones.

Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

Directory of Open Access Journals (Sweden)

J. Hosek

2011-02-01

Full Text Available The northeast coast of North America is frequently hit by severe ice storms. These freezing rain events can produce large ice accretions that damage structures, frequently power transmission and distribution infrastructure. For this reason, it is highly desirable to model and forecast such icing events, so that the consequent damages can be prevented or mitigated. The case study presented in this paper focuses on the March 2010 ice storm event that took place in eastern Newfoundland. We apply a combination of a numerical weather prediction model and an ice accretion algorithm to simulate a forecast of this event.

The main goals of this study are to compare the simulated meteorological variables to observations, and to assess the ability of the model to accurately predict the ice accretion load for different forecast horizons. The duration and timing of the freezing rain event that occurred between the night of 4 March and the morning of 6 March was simulated well in all model runs. The total precipitation amounts in the model, however, differed by up to a factor of two from the observations. The accuracy of the model air temperature strongly depended on the forecast horizon, but it was acceptable for all simulation runs. The simulated accretion loads were also compared to the design values for power delivery structures in the region. The results indicated that the simulated values exceeded design criteria in the areas of reported damage and power outages.

"Near-term" Natural Catastrophe Risk Management and Risk Hedging in a Changing Climate

Science.gov (United States)

Michel, Gero; Tiampo, Kristy

2014-05-01

Competing with analytics - Can the insurance market take advantage of seasonal or "near-term" forecasting and temporal changes in risk? Natural perils (re)insurance has been based on models following climatology i.e. the long-term "historical" average. This is opposed to considering the "near-term" and forecasting hazard and risk for the seasons or years to come. Variability and short-term changes in risk are deemed abundant for almost all perils. In addition to hydrometeorological perils whose changes are vastly discussed, earthquake activity might also change over various time-scales affected by earlier local (or even global) events, regional changes in the distribution of stresses and strains and more. Only recently has insurance risk modeling of (stochastic) hurricane-years or extratropical-storm-years started considering our ability to forecast climate variability herewith taking advantage of apparent correlations between climate indicators and the activity of storm events. Once some of these "near-term measures" were in the market, rating agencies and regulators swiftly adopted these concepts demanding companies to deploy a selection of more conservative "time-dependent" models. This was despite the fact that the ultimate effect of some of these measures on insurance risk was not well understood. Apparent short-term success over the last years in near-term seasonal hurricane forecasting was brought to a halt in 2013 when these models failed to forecast the exceptional shortage of hurricanes herewith contradicting an active-year forecast. The focus of earthquake forecasting has in addition been mostly on high rather than low temporal and regional activity despite the fact that avoiding losses does not by itself create a product. This presentation sheds light on new risk management concepts for over-regional and global (re)insurance portfolios that take advantage of forecasting changes in risk. The presentation focuses on the "upside" and on new opportunities

Predicting catastrophes of non-autonomous networks with visibility graphs and horizontal visibility

Science.gov (United States)

Zhang, Haicheng; Xu, Daolin; Wu, Yousheng

2018-05-01

Prediction of potential catastrophes in engineering systems is a challenging problem. We first attempt to construct a complex network to predict catastrophes of a multi-modular floating system in advance of their occurrences. Response time series of the system can be mapped into an virtual network by using visibility graph or horizontal visibility algorithm. The topology characteristics of the networks can be used to forecast catastrophes of the system. Numerical results show that there is an obvious corresponding relationship between the variation of topology characteristics and the onset of catastrophes. A Catastrophe Index (CI) is proposed as a numerical indicator to measure a qualitative change from a stable state to a catastrophic state. The two approaches, the visibility graph and horizontal visibility algorithms, are compared by using the index in the reliability analysis with different data lengths and sampling frequencies. The technique of virtual network method is potentially extendable to catastrophe predictions of other engineering systems.

Forecasting E > 50-MeV proton events with the proton prediction system (PPS)

Science.gov (United States)

Kahler, Stephen W.; White, Stephen M.; Ling, Alan G.

2017-11-01

Forecasting solar energetic (E > 10-MeV) particle (SEP) events is an important element of space weather. While several models have been developed for use in forecasting such events, satellite operations are particularly vulnerable to higher-energy (≥50-MeV) SEP events. Here we validate one model, the proton prediction system (PPS), which extends to that energy range. We first develop a data base of E ≥ 50-MeV proton events >1.0 proton flux units (pfu) events observed on the GOES satellite over the period 1986-2016. We modify the PPS to forecast proton events at the reduced level of 1 pfu and run PPS for four different solar input parameters: (1) all ≥M5 solar X-ray flares; (2) all ≥200 sfu 8800-MHz bursts with associated ≥M5 flares; (3) all ≥500 sfu 8800-MHz bursts; and (4) all ≥5000 sfu 8800-MHz bursts. The validation contingency tables and skill scores are calculated for all groups and used as a guide to use of the PPS. We plot the false alarms and missed events as functions of solar source longitude, and argue that the longitude-dependence employed by PPS does not match modern observations. Use of the radio fluxes as the PPS driver tends to result in too many false alarms at the 500 sfu threshold, and misses more events than the soft X-ray predictor at the 5000 sfu threshold.

Global and regional aspects for genesis of catastrophic floods - the problems of forecasting and estimates for mass and water balance (surface and groundwater contribution)

Science.gov (United States)

Trifonova, Tatiana; Arakelian, Sergei; Trifonov, Dmitriy; Abrakhin, Sergei

2017-04-01

1. The principal goal of present talk is, to discuss the existing uncertainty and discrepancy between water balance estimation for the area under heavy rain flood, on the one hand from the theoretical approach and reasonable data base due to rainfall going from atmosphere and, on the other hand the real practicle surface water flow parameters measured by some methods and/or fixed by some eye-witness (cf. [1]). The vital item for our discussion is that the last characteristics sometimes may be noticeably grater than the first ones. Our estimations show the grater water mass discharge observation during the events than it could be expected from the rainfall process estimation only [2]. The fact gives us the founding to take into account the groundwater possible contribution to the event. 2. We carried out such analysis, at least, for two catastrophic water events in 2015, i.e. (1) torrential rain and catastrophic floods in Lousiana (USA), June 16-20; (2) Assam flood (India), Aug. 22 - Sept. 8. 3. Groundwater flood of a river terrace discussed e.g. in [3] but in respect when rise of the water table above the land surface occurs coincided with intense rainfall and being as a relatively rare phenomenon. In our hypothesis the principal part of possible groundwater exit to surface is connected with a crack-net system state in earth-crust (including deep layers) as a water transportation system, first, being in variated pressure field for groundwater basin and, second, modified by different reasons ( both suddenly (the Krimsk-city flash flood event, July 2012, Russia) and/or smoothly (the Amur river flood event, Aug.-Sept. 2013, Russia) ). Such reconstruction of 3D crack-net under external reasons (resulting even in local variation of pressures in any crack-section) is a principal item for presented approach. 4. We believe that in some cases the interconnection of floods and preceding earthquakes may occur. The problem discuss by us for certain events ( e.g. in addition to

Does an inter-flaw length control the accuracy of rupture forecasting in geological materials?

Science.gov (United States)

Vasseur, Jérémie; Wadsworth, Fabian B.; Heap, Michael J.; Main, Ian G.; Lavallée, Yan; Dingwell, Donald B.

2017-10-01

Multi-scale failure of porous materials is an important phenomenon in nature and in material physics - from controlled laboratory tests to rockbursts, landslides, volcanic eruptions and earthquakes. A key unsolved research question is how to accurately forecast the time of system-sized catastrophic failure, based on observations of precursory events such as acoustic emissions (AE) in laboratory samples, or, on a larger scale, small earthquakes. Until now, the length scale associated with precursory events has not been well quantified, resulting in forecasting tools that are often unreliable. Here we test the hypothesis that the accuracy of the forecast failure time depends on the inter-flaw distance in the starting material. We use new experimental datasets for the deformation of porous materials to infer the critical crack length at failure from a static damage mechanics model. The style of acceleration of AE rate prior to failure, and the accuracy of forecast failure time, both depend on whether the cracks can span the inter-flaw length or not. A smooth inverse power-law acceleration of AE rate to failure, and an accurate forecast, occurs when the cracks are sufficiently long to bridge pore spaces. When this is not the case, the predicted failure time is much less accurate and failure is preceded by an exponential AE rate trend. Finally, we provide a quantitative and pragmatic correction for the systematic error in the forecast failure time, valid for structurally isotropic porous materials, which could be tested against larger-scale natural failure events, with suitable scaling for the relevant inter-flaw distances.

Evaluating sub-seasonal skill in probabilistic forecasts of Atmospheric Rivers and associated extreme events

Science.gov (United States)

Subramanian, A. C.; Lavers, D.; Matsueda, M.; Shukla, S.; Cayan, D. R.; Ralph, M.

2017-12-01

Atmospheric rivers (ARs) - elongated plumes of intense moisture transport - are a primary source of hydrological extremes, water resources and impactful weather along the West Coast of North America and Europe. There is strong demand in the water management, societal infrastructure and humanitarian sectors for reliable sub-seasonal forecasts, particularly of extreme events, such as floods and droughts so that actions to mitigate disastrous impacts can be taken with sufficient lead-time. Many recent studies have shown that ARs in the Pacific and the Atlantic are modulated by large-scale modes of climate variability. Leveraging the improved understanding of how these large-scale climate modes modulate the ARs in these two basins, we use the state-of-the-art multi-model forecast systems such as the North American Multi-Model Ensemble (NMME) and the Subseasonal-to-Seasonal (S2S) database to help inform and assess the probabilistic prediction of ARs and related extreme weather events over the North American and European West Coasts. We will present results from evaluating probabilistic forecasts of extreme precipitation and AR activity at the sub-seasonal scale. In particular, results from the comparison of two winters (2015-16 and 2016-17) will be shown, winters which defied canonical El Niño teleconnection patterns over North America and Europe. We further extend this study to analyze probabilistic forecast skill of AR events in these two basins and the variability in forecast skill during certain regimes of large-scale climate modes.

The incidence of rugby-related catastrophic injuries (including cardiac events) in South Africa from 2008 to 2011: a cohort study

NARCIS (Netherlands)

Brown, J.C.; Lambert, M.I.; Verhagen, E.A.L.M.; Readhead, C.; van Mechelen, W.; Viljoen, W.

2013-01-01

Objectives: To establish an accurate and comprehensive injury incidence registry of all rugby union-related catastrophic events in South Africa between 2008 and 2011. An additional aim was to investigate correlates associated with these injuries. Design: Prospective. Setting: The South African

From Tornadoes to Earthquakes: Forecast Verification for Binary Events Applied to the 1999 Chi-Chi, Taiwan,Earthquake

Directory of Open Access Journals (Sweden)

Chien-Chih Chen

2006-01-01

Full Text Available Forecast verification procedures for statistical events with binary outcomes typically rely on the use of contingency tables and Relative Operating Characteristic (ROC diagrams. Originally developed for the statistical evaluation of tornado forecasts on a county-by-county basis, these methods can be adapted to the evaluation of competing earthquake forecasts. Here we apply these methods retrospectively to two forecasts for the M 7.3 1999 Chi-Chi, Taiwan, earthquake. We show that a previously proposed forecast method that is based on evaluating changes in seismic intensity on a regional basis is superior to a forecast based only on the magnitude of seismic intensity in the same region. Our results confirm earlier suggestions that the earthquake preparation process for events such as the Chi-Chi earthquake involves anomalous activation or quiescence, and that signatures of these processes can be detected in seismicity data using appropriate methods.

PARAMETRIC INSURANCE COVER FOR NATURAL CATASTROPHE RISKS

Directory of Open Access Journals (Sweden)

Serghei Margulescu

2013-11-01

Full Text Available With economic losses of over USD 370 bn caused by 325 catastrophic events, 2011 ranks as the worst ever year in terms of costs to society due to natural catastrophes and man-made disasters. Inthe same time, 2011 is the second most expensive year in the history for the insurance industry, with insured losses from catastrophic events amounting to USD 116 bn. Both the high level of damages and insured losses, as well as the unprecedented gap between the two values, made insurers and reinsurers worldwide to understand that some risks had so far been underestimated and they have to be better integrated in the catastrophes modelling.On the other hand, governments have to protect themselves against the financial impact of natural catastrophes and new forms of cooperation between the public and private sectors can help countries finance disaster risks. Viewed in a country’s wider risk management context, the purchase of parametric insurance cover, which transfers natural catastrophe risk to the private sector using an index- based trigger, is a necessary shift towards a pre-emptive risk management strategy. This kind of approach can be pursued by central governments or at the level of provincial or municipal governments, and a number of case studies included in the publication “Closing the financial gap” by Swiss Re (2011 illustrates how new forms of parametric insurance can help countries finance disaster risks.

Rate of recovery from perturbations as a means to forecast future stability of living systems.

Science.gov (United States)

Ghadami, Amin; Gourgou, Eleni; Epureanu, Bogdan I

2018-06-18

Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can indicate that the system is approaching an impending transition. An exciting question is, however, whether we can predict more characteristics of the future system stability using measurements taken away from the transition. We address this question by introducing a model-less forecasting method to forecast catastrophic transition of an experimental ecological system. The experiment is based on the dynamics of a yeast population, which is known to exhibit a catastrophic transition as the environment deteriorates. By measuring the system's response to perturbations prior to transition, we forecast the distance to the upcoming transition, the type of the transition (i.e., catastrophic/non-catastrophic) and the future equilibrium points within a range near the transition. Experimental results suggest a strong potential for practical applicability of this approach for ecological systems which are at risk of catastrophic transitions, where there is a pressing need for information about upcoming thresholds.

Next-generation probabilistic seismicity forecasting

Energy Technology Data Exchange (ETDEWEB)

Hiemer, S.

2014-07-01

The development of probabilistic seismicity forecasts is one of the most important tasks of seismologists at present time. Such forecasts form the basis of probabilistic seismic hazard assessment, a widely used approach to generate ground motion exceedance maps. These hazard maps guide the development of building codes, and in the absence of the ability to deterministically predict earthquakes, good building and infrastructure planning is key to prevent catastrophes. Probabilistic seismicity forecasts are models that specify the occurrence rate of earthquakes as a function of space, time and magnitude. The models presented in this thesis are time-invariant mainshock occurrence models. Accordingly, the reliable estimation of the spatial and size distribution of seismicity are of crucial importance when constructing such probabilistic forecasts. Thereby we focus on data-driven approaches to infer these distributions, circumventing the need for arbitrarily chosen external parameters and subjective expert decisions. Kernel estimation has been shown to appropriately transform discrete earthquake locations into spatially continuous probability distributions. However, we show that neglecting the information from fault networks constitutes a considerable shortcoming and thus limits the skill of these current seismicity models. We present a novel earthquake rate forecast that applies the kernel-smoothing method to both past earthquake locations and slip rates on mapped crustal faults applied to Californian and European data. Our model is independent from biases caused by commonly used non-objective seismic zonations, which impose artificial borders of activity that are not expected in nature. Studying the spatial variability of the seismicity size distribution is of great importance. The b-value of the well-established empirical Gutenberg-Richter model forecasts the rates of hazard-relevant large earthquakes based on the observed rates of abundant small events. We propose a

Next-generation probabilistic seismicity forecasting

International Nuclear Information System (INIS)

Hiemer, S.

2014-01-01

The development of probabilistic seismicity forecasts is one of the most important tasks of seismologists at present time. Such forecasts form the basis of probabilistic seismic hazard assessment, a widely used approach to generate ground motion exceedance maps. These hazard maps guide the development of building codes, and in the absence of the ability to deterministically predict earthquakes, good building and infrastructure planning is key to prevent catastrophes. Probabilistic seismicity forecasts are models that specify the occurrence rate of earthquakes as a function of space, time and magnitude. The models presented in this thesis are time-invariant mainshock occurrence models. Accordingly, the reliable estimation of the spatial and size distribution of seismicity are of crucial importance when constructing such probabilistic forecasts. Thereby we focus on data-driven approaches to infer these distributions, circumventing the need for arbitrarily chosen external parameters and subjective expert decisions. Kernel estimation has been shown to appropriately transform discrete earthquake locations into spatially continuous probability distributions. However, we show that neglecting the information from fault networks constitutes a considerable shortcoming and thus limits the skill of these current seismicity models. We present a novel earthquake rate forecast that applies the kernel-smoothing method to both past earthquake locations and slip rates on mapped crustal faults applied to Californian and European data. Our model is independent from biases caused by commonly used non-objective seismic zonations, which impose artificial borders of activity that are not expected in nature. Studying the spatial variability of the seismicity size distribution is of great importance. The b-value of the well-established empirical Gutenberg-Richter model forecasts the rates of hazard-relevant large earthquakes based on the observed rates of abundant small events. We propose a

'Performative narrativity': Palestinian identity and the performance of catastrophe

NARCIS (Netherlands)

Saloul, I.

2008-01-01

The day Israel annually celebrates as its "Day of Independence" Palestinians commemorate as their day of catastrophe (al-nakba). To most Palestinians, the catastrophic loss of Palestine in 1948 represents the climactic formative event of their lives. In the aftermath of this loss, the Palestinian

Human reaction and risk perception to catastrophic events: a psycho-social and cultural perspective

International Nuclear Information System (INIS)

Barthakur, M.

1998-01-01

Catastrophes of various kinds occur worldwide inflicting major human suffering, more so in the less privileged regions of the world. Human beings react differently to different traumatic situations and to the threat of an event in spite of man common underlying factors. Psychological reactions to catastrophic natural events like flooding on the perception of risk of flooding across various communities thus becomes an interesting study. Economic situation, lack of knowledge and resources are assumed to give a totally different perspective to reactions and perception of risk and its interpretation specially in an underprivileged country like India, compared to other developed countries. For the proposed session, the results of a study carried out in India will be presented. This includes reactions and responses of individuals and general public affected by flooding and their perceptions of risk of flooding. The study also focuses on a comparison between the people affected and at risk of flooding. Socio-cultural values, religion and superstitions, common beliefs and expectations from authorities will be studied as underlying variables, to what extent they might have an impact on the behavioral pattern of an individual in a situation and the perception of oncoming risk. A sizeable number of the Indian population resides in areas, which are generally affected by flooding or highly prone to flooding. Could perceptions vary among individuals within the society or is it simply poverty and unaffordability that drive these people info such hazardous areas? Lack of consciousness may seem to be an important variable, but what really matters and needs to be looked into is how threatened they actually feel. (author)

Pricing the property claim service (PCS) catastrophe insurance options using gamma distribution

Science.gov (United States)

Noviyanti, Lienda; Soleh, Achmad Zanbar; Setyanto, Gatot R.

2017-03-01

The catastrophic events like earthquakes, hurricanes or flooding are characteristics for some areas, a properly calculated annual premium would be closely as high as the loss insured. From an actuarial perspective, such events constitute the risk that are not insurable. On the other hand people living in such areas need protection. In order to securitize the catastrophe risk, futures or options based on a loss index could be considered. Chicago Board of Trade launched a new class of catastrophe insurance options based on new indices provided by Property Claim Services (PCS). The PCS-option is based on the Property Claim Service Index (PCS-Index). The index are used to determine and payout in writing index-based insurance derivatives. The objective of this paper is to price PCS Catastrophe Insurance Option based on PCS Catastrophe index. Gamma Distribution is used to estimate PCS Catastrophe index distribution.

Forecasting rain events - Meteorological models or collective intelligence?

Science.gov (United States)

Arazy, Ofer; Halfon, Noam; Malkinson, Dan

2015-04-01

Collective intelligence is shared (or group) intelligence that emerges from the collective efforts of many individuals. Collective intelligence is the aggregate of individual contributions: from simple collective decision making to more sophisticated aggregations such as in crowdsourcing and peer-production systems. In particular, collective intelligence could be used in making predictions about future events, for example by using prediction markets to forecast election results, stock prices, or the outcomes of sport events. To date, there is little research regarding the use of collective intelligence for prediction of weather forecasting. The objective of this study is to investigate the extent to which collective intelligence could be utilized to accurately predict weather events, and in particular rainfall. Our analyses employ metrics of group intelligence, as well as compare the accuracy of groups' predictions against the predictions of the standard model used by the National Meteorological Services. We report on preliminary results from a study conducted over the 2013-2014 and 2014-2015 winters. We have built a web site that allows people to make predictions on precipitation levels on certain locations. During each competition participants were allowed to enter their precipitation forecasts (i.e. 'bets') at three locations and these locations changed between competitions. A precipitation competition was defined as a 48-96 hour period (depending on the expected weather conditions), bets were open 24-48 hours prior to the competition, and during betting period participants were allowed to change their bets with no limitation. In order to explore the effect of transparency, betting mechanisms varied across study's sites: full transparency (participants able to see each other's bets); partial transparency (participants see the group's average bet); and no transparency (no information of others' bets is made available). Several interesting findings emerged from

Abstracts of papers of international scientific conference 'Ten Years After the Chernobyl Catastrophe (Scientific Aspects of Problem)'

International Nuclear Information System (INIS)

Konoplya, E.F.; Amvros'ev, A.P.; Bogdevich, I.M.; Bondar', Yu.I.; Karaseva, E.I.; Lobanok, L.M.; Matsko, V.P.; Pikulik, M.M.; Rolevich, I.V.; Stozharov, A.N.; Yakushev, B.I.

1996-02-01

The collection is dedicated to the 10 anniversary of Chernobyl catastrophe and contains the results of researches carried out in Belarus, as well as in Ukraine and Russian Federation, on different aspects of the Chernobyl problems: radiation medicine and risks, biological radiation effects and their forecasting, agricultural radiology and radioecology, decontamination and radioactive waste management, socio-economic and psychologic problems caused by the Chernobyl Catastrophe. (authors)

Changing Weather Extremes Call for Early Warning of Potential for Catastrophic Fire

Science.gov (United States)

Boer, Matthias M.; Nolan, Rachael H.; Resco De Dios, Víctor; Clarke, Hamish; Price, Owen F.; Bradstock, Ross A.

2017-12-01

Changing frequencies of extreme weather events and shifting fire seasons call for enhanced capability to forecast where and when forested landscapes switch from a nonflammable (i.e., wet fuel) state to the highly flammable (i.e., dry fuel) state required for catastrophic forest fires. Current forest fire danger indices used in Europe, North America, and Australia rate potential fire behavior by combining numerical indices of fuel moisture content, potential rate of fire spread, and fire intensity. These numerical rating systems lack the physical basis required to reliably quantify forest flammability outside the environments of their development or under novel climate conditions. Here, we argue that exceedance of critical forest flammability thresholds is a prerequisite for major forest fires and therefore early warning systems should be based on a reliable prediction of fuel moisture content plus a regionally calibrated model of how forest fire activity responds to variation in fuel moisture content. We demonstrate the potential of this approach through a case study in Portugal. We use a physically based fuel moisture model with historical weather and fire records to identify critical fuel moisture thresholds for forest fire activity and then show that the catastrophic June 2017 forest fires in central Portugal erupted shortly after fuels in the region dried out to historically unprecedented levels.

Rare event simulation using Monte Carlo methods

CERN Document Server

Rubino, Gerardo

2009-01-01

In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...

Simulation of Flash-Flood-Producing Storm Events in Saudi Arabia Using the Weather Research and Forecasting Model

KAUST Repository

Deng, Liping; McCabe, Matthew; Stenchikov, Georgiy L.; Evans, Jason P.; Kucera, Paul A.

2015-01-01

The challenges of monitoring and forecasting flash-flood-producing storm events in data-sparse and arid regions are explored using the Weather Research and Forecasting (WRF) Model (version 3.5) in conjunction with a range of available satellite

Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

OpenAIRE

J. Hosek; P. Musilek; E. Lozowski; P. Pytlak

2011-01-01

The northeast coast of North America is frequently hit by severe ice storms. These freezing rain events can produce large ice accretions that damage structures, frequently power transmission and distribution infrastructure. For this reason, it is highly desirable to model and forecast such icing events, so that the consequent damages can be prevented or mitigated. The case study presented in this paper focuses on the March 2010 ice storm event that took place in eastern Newfoundland. We apply...

Forecast of solar proton flux profiles for well-connected events

Science.gov (United States)

Ji, Eun-Young; Moon, Yong-Jae; Park, Jinhye

2014-12-01

We have developed a forecast model of solar proton flux profiles (> 10 MeV channel) for well-connected events. Among 136 solar proton events (SPEs) from 1986 to 2006, we select 49 well-connected ones that are all associated with single X-ray flares stronger than M1 class and start to increase within 4 h after their X-ray peak times. These events show rapid increments in proton flux. By comparing several empirical functions, we select a modified Weibull curve function to approximate a SPE flux profile. The parameters (peak flux, rise time, and decay time) of this function are determined by the relationship between X-ray flare parameters (peak flux, impulsive time, and emission measure) and SPE parameters. For 49 well-connected SPEs, the linear correlation coefficient between the predicted and the observed proton peak fluxes is 0.65 with the RMS error of 0.55 log10(pfu). In addition, we determine another forecast model based on flare and coronal mass ejection (CME) parameters using 22 SPEs. The used CME parameters are linear speed and angular width. As a result, we find that the linear correlation coefficient between the predicted and the observed proton peak fluxes is 0.83 with the RMS error of 0.35 log10(pfu). From the relationship between error of model and CME acceleration, we find that CME acceleration is an important factor for predicting proton flux profiles.

Factors that Influence the Use of Climate Forecasts: Evidence from the 1997/98 El Niño Event in Peru.

Science.gov (United States)

Orlove, Benjamin S.; Broad, Kenneth; Petty, Aaron M.

2004-11-01

This article analyzes the use of climate forecasts among members of the Peruvian fishing sector during the 1997/98 El Niño event. It focuses on the effect of the time of hearing a forecast on the socioeconomic responses to the forecast. Findings are based on data collected from a survey of 596 persons in five ports spanning the length of the Peruvian coast. Respondents include commercial and artisanal fishers, plant workers, managers, and firm owners.These data fill an important gap in the literature on the use of forecasts. Though modelers have discussed the effects of the timing of the dissemination and reception of forecasts, along with other factors, on acting on a forecast once it has been heard, few researchers have gathered empirical evidence on these topics.The 1997/98 El Niño event was covered extensively by the media throughout Peru, affording the opportunity to study the effect of hearing forecasts on actions taken by members of a population directly impacted by ENSO events. Findings of this study examine the relationships among 1) socioeconomic variables, including geographic factors, age, education, income level, organizational ties, and media access; 2) time of hearing the forecast; and 3) actions taken in response to the forecast. Socioeconomic variables have a strong effect on the time of hearing the forecast and the actions taken in response to the forecast; however, time of hearing does not have an independent effect on taking action. The article discusses the implications of these findings for the application of forecasts.A supplement to this article is available online (dx.doi.org/10.1175/BAMS-85-11-Orlove)

AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

Science.gov (United States)

Reale, O.; Lau, W. K.; Susskind, J.; Rosenberg, R.

2011-01-01

A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

Optimal natural resources management under uncertainty with catastrophic risk

Energy Technology Data Exchange (ETDEWEB)

Motoh, Tsujimura [Graduate School of Economics, Kyoto University, Yoshida-honmochi, Sakyo-ku, Kyoto 606-8501 (Japan)

2004-05-01

We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource.

Optimal natural resources management under uncertainty with catastrophic risk

International Nuclear Information System (INIS)

Motoh, Tsujimura

2004-01-01

We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource

Role of the Internet in Anticipating and Mitigating Earthquake Catastrophes, and the Emergence of Personal Risk Management (Invited)

Science.gov (United States)

Rundle, J. B.; Holliday, J. R.; Donnellan, A.; Graves, W.; Tiampo, K. F.; Klein, W.

2009-12-01

Risks from natural and financial catastrophes are currently managed by a combination of large public and private institutions. Public institutions usually are comprised of government agencies that conduct studies, formulate policies and guidelines, enforce regulations, and make “official” forecasts. Private institutions include insurance and reinsurance companies, and financial service companies that underwrite catastrophe (“cat”) bonds, and make private forecasts. Although decisions about allocating resources and developing solutions are made by large institutions, the costs of dealing with catastrophes generally fall for the most part on businesses and the general public. Information on potential risks is generally available to the public for some hazards but not others. For example, in the case of weather, private forecast services are provided by www.weather.com and www.wunderground.com. For earthquakes in California (only), the official forecast is the WGCEP-USGS forecast, but provided in a format that is difficult for the public to use. Other privately made forecasts are currently available, for example by the JPL QuakeSim and Russian groups, but these efforts are limited. As more of the world’s population moves increasingly into major seismic zones, new strategies are needed to allow individuals to manage their personal risk from large and damaging earthquakes. Examples include individual mitigation measures such as retrofitting, as well as microinsurance in both developing and developed countries, as well as other financial strategies. We argue that the “long tail” of the internet offers an ideal, and greatly underutilized mechanism to reach out to consumers and to provide them with the information and tools they need to confront and manage seismic hazard and risk on an individual, personalized basis. Information of this type includes not only global hazard forecasts, which are now possible, but also global risk estimation. Additionally

Technical note: New particle formation event forecasts during PEGASOS-Zeppelin Northern mission 2013 in Hyytiälä, Finland

Science.gov (United States)

Nieminen, T.; Yli-Juuti, T.; Manninen, H. E.; Petäjä, T.; Kerminen, V.-M.; Kulmala, M.

2015-11-01

New particle formation (NPF) occurs frequently in the global atmosphere. During recent years, detailed laboratory experiments combined with intensive field observations in different locations have provided insights into the vapours responsible for the initial formation of particles and their subsequent growth. In this regard, the importance of sulfuric acid, stabilizing bases such as ammonia and amines as well as extremely low volatile organics, have been proposed. The instrumentation to observe freshly formed aerosol particles has developed to a stage where the instruments can be implemented as part of airborne platforms, such as aircrafts or a Zeppelin-type airship. Flight measurements are technically more demanding and require a greater detail of planning than field studies at the ground level. The high cost of flight hours, limited time available during a single research flight for the measurements, and different instrument payloads in Zeppelin airship for various flight missions demanded an analysis tool that would forecast whether or not there is a good chance for an NPF event. Here we present a methodology to forecast NPF event probability at the SMEAR II site in Hyytiälä, Finland. This methodology was used to optimize flight hours during the PEGASOS (Pan-European Gas Aerosol Climate Interaction Study)-Zeppelin Northern mission in May-June 2013. Based on the existing knowledge, we derived a method for estimating the nucleation probability that utilizes forecast air mass trajectories, weather forecasts, and air quality model predictions. With the forecast tool we were able to predict the occurrence of NPF events for the next day with more than 90 % success rate (10 out of 11 NPF event days correctly predicted). To our knowledge, no similar forecasts of NPF occurrence have been developed for other sites. This method of forecasting NPF occurrence could be applied also at other locations, provided that long-term observations of conditions favouring particle

A New Integrated Threshold Selection Methodology for Spatial Forecast Verification of Extreme Events

Science.gov (United States)

Kholodovsky, V.

2017-12-01

Extreme weather and climate events such as heavy precipitation, heat waves and strong winds can cause extensive damage to the society in terms of human lives and financial losses. As climate changes, it is important to understand how extreme weather events may change as a result. Climate and statistical models are often independently used to model those phenomena. To better assess performance of the climate models, a variety of spatial forecast verification methods have been developed. However, spatial verification metrics that are widely used in comparing mean states, in most cases, do not have an adequate theoretical justification to benchmark extreme weather events. We proposed a new integrated threshold selection methodology for spatial forecast verification of extreme events that couples existing pattern recognition indices with high threshold choices. This integrated approach has three main steps: 1) dimension reduction; 2) geometric domain mapping; and 3) thresholds clustering. We apply this approach to an observed precipitation dataset over CONUS. The results are evaluated by displaying threshold distribution seasonally, monthly and annually. The method offers user the flexibility of selecting a high threshold that is linked to desired geometrical properties. The proposed high threshold methodology could either complement existing spatial verification methods, where threshold selection is arbitrary, or be directly applicable in extreme value theory.

Dust storm events over Delhi: verification of dust AOD forecasts with satellite and surface observations

Science.gov (United States)

Singh, Aditi; Iyengar, Gopal R.; George, John P.

2016-05-01

Thar desert located in northwest part of India is considered as one of the major dust source. Dust storms originate in Thar desert during pre-monsoon season, affects large part of Indo-Gangetic plains. High dust loading causes the deterioration of the ambient air quality and degradation in visibility. Present study focuses on the identification of dust events and verification of the forecast of dust events over Delhi and western part of IG Plains, during the pre-monsoon season of 2015. Three dust events have been identified over Delhi during the study period. For all the selected days, Terra-MODIS AOD at 550 nm are found close to 1.0, while AURA-OMI AI shows high values. Dust AOD forecasts from NCMRWF Unified Model (NCUM) for the three selected dust events are verified against satellite (MODIS) and ground based observations (AERONET). Comparison of observed AODs at 550 nm from MODIS with NCUM predicted AODs reveals that NCUM is able to predict the spatial and temporal distribution of dust AOD, in these cases. Good correlation (~0.67) is obtained between the NCUM predicted dust AODs and location specific observations available from AERONET. Model under-predicted the AODs as compared to the AERONET observations. This may be mainly because the model account for only dust and no anthropogenic activities are considered. The results of the present study emphasize the requirement of more realistic representation of local dust emission in the model both of natural and anthropogenic origin, to improve the forecast of dust from NCUM during the dust events.

Assessment of effectiveness of geologic isolation systems. Geologic factors in the isolation of nuclear waste: evaluation of long-term geomorphic processes and catastrophic events

International Nuclear Information System (INIS)

Mara, S.J.

1980-03-01

SRI International has projected the rate, duration, and magnitude of geomorphic processes and events in the Southwest and Gulf Coast over the next million years. This information will be used by the Department of Energy's Pacific Northwest Laboratory (PNL) as input to a computer model, which will be used to simulate possible release scenarios and the consequences of the release of nuclear waste from geologic containment. The estimates in this report, although based on best scientific judgment, are subject to considerable uncertainty. An evaluation of the Quaternary history of the two study areas revealed that each had undergone geomorphic change in the last one million years. Catastrophic events were evaluated in order to determine their significance to the simulation model. Given available data, catastrophic floods are not expected to occur in the two study areas. Catastrophic landslides may occur in the Southwest, but because the duration of the event is brief and the amount of material moved is small in comparison to regional denudation, such events need not be included in the simulation model. Ashfalls, however, could result in removal of vegetation from the landscape, thereby causing significant increases in erosion rates. Because the estimates developed during this study may not be applicable to specific sites, general equations were presented as a first step in refining the analysis. These equations identify the general relationships among the important variables and suggest those areas of concern for which further data are required. If the current model indicates that geomorphic processes (taken together with other geologic changes) may ultimately affect the geologic containment of nuclear waste, further research may be necessary to refine this analysis for application to specific sites

Sub-seasonal Predictability of Heavy Precipitation Events: Implication for Real-time Flood Management in Iran

Science.gov (United States)

Najafi, H.; Shahbazi, A.; Zohrabi, N.; Robertson, A. W.; Mofidi, A.; Massah Bavani, A. R.

2016-12-01

Each year, a number of high impact weather events occur worldwide. Since any level of predictability at sub-seasonal to seasonal timescale is highly beneficial to society, international efforts is now on progress to promote reliable Ensemble Prediction Systems for monthly forecasts within the WWRP/WCRP initiative (S2S) project and North American Multi Model Ensemble (NMME). For water resources managers in the face of extreme events, not only can reliable forecasts of high impact weather events prevent catastrophic losses caused by floods but also contribute to benefits gained from hydropower generation and water markets. The aim of this paper is to analyze the predictability of recent severe weather events over Iran. Two recent heavy precipitations are considered as an illustration to examine whether S2S forecasts can be used for developing flood alert systems especially where large cascade of dams are in operation. Both events have caused major damages to cities and infrastructures. The first severe precipitation was is in the early November 2015 when heavy precipitation (more than 50 mm) occurred in 2 days. More recently, up to 300 mm of precipitation is observed within less than a week in April 2016 causing a consequent flash flood. Over some stations, the observed precipitation was even more than the total annual mean precipitation. To analyze the predictive capability, ensemble forecasts from several operational centers including (European Centre for Medium-Range Weather Forecasts (ECMWF) system, Climate Forecast System Version 2 (CFSv2) and Chinese Meteorological Center (CMA) are evaluated. It has been observed that significant changes in precipitation anomalies were likely to be predicted days in advance. The next step will be to conduct thorough analysis based on comparing multi-model outputs over the full hindcast dataset developing real-time high impact weather prediction systems.

The incidence of rugby-related catastrophic injuries (including cardiac events) in South Africa from 2008 to 2011: a cohort study

Science.gov (United States)

Brown, James Craig; Lambert, Mike I; Verhagen, Evert; Readhead, Clint; van Mechelen, Willem; Viljoen, Wayne

2013-01-01

Objectives To establish an accurate and comprehensive injury incidence registry of all rugby union-related catastrophic events in South Africa between 2008 and 2011. An additional aim was to investigate correlates associated with these injuries. Design Prospective. Setting The South African amateur and professional rugby-playing population. Participants An estimated 529 483 Junior and 121 663 Senior rugby union (‘rugby’) players (population at risk). Outcome measures Annual average incidences of rugby-related catastrophic injuries by type (cardiac events, traumatic brain and acute spinal cord injuries (ASCIs)) and outcome (full recoveries—fatalities). Playing level (junior and senior levels), position and event (phase of play) were also assessed. Results The average annual incidence of ASCIs and Traumatic Brain Injuries combined was 2.00 per 100 000 players (95% CI 0.91 to 3.08) from 2008 to 2011. The incidence of ASCIs with permanent outcomes was significantly higher at the Senior level (4.52 per 100 000 players, 95% CI 0.74 to 8.30) than the Junior level (0.24 per 100 000 players, 95% CI 0 to 0.65) during this period. The hooker position was associated with 46% (n=12 of 26) of all permanent ASCI outcomes, the majority of which (83%) occurred during the scrum phase of play. Conclusions The incidence of rugby-related catastrophic injuries in South Africa between 2008 and 2011 is comparable to that of other countries and to most other collision sports. The higher incidence rate of permanent ASCIs at the Senior level could be related to the different law variations or characteristics (eg, less regular training) compared with the Junior level. The hooker and scrum were associated with high proportions of permanent ASCIs. The BokSmart injury prevention programme should focus efforts on these areas (Senior level, hooker and scrum) and use this study as a reference point for the evaluation of the effectiveness of the programme. PMID:23447464

An operational integrated short-term warning solution for solar radiation storms: introducing the Forecasting Solar Particle Events and Flares (FORSPEF) system

Science.gov (United States)

Anastasiadis, Anastasios; Sandberg, Ingmar; Papaioannou, Athanasios; Georgoulis, Manolis; Tziotziou, Kostas; Jiggens, Piers; Hilgers, Alain

2015-04-01

We present a novel integrated prediction system, of both solar flares and solar energetic particle (SEP) events, which is in place to provide short-term warnings for hazardous solar radiation storms. FORSPEF system provides forecasting of solar eruptive events, such as solar flares with a projection to coronal mass ejections (CMEs) (occurrence and velocity) and the likelihood of occurrence of a SEP event. It also provides nowcasting of SEP events based on actual solar flare and CME near real-time alerts, as well as SEP characteristics (peak flux, fluence, rise time, duration) per parent solar event. The prediction of solar flares relies on a morphological method which is based on the sophisticated derivation of the effective connected magnetic field strength (Beff) of potentially flaring active-region (AR) magnetic configurations and it utilizes analysis of a large number of AR magnetograms. For the prediction of SEP events a new reductive statistical method has been implemented based on a newly constructed database of solar flares, CMEs and SEP events that covers a large time span from 1984-2013. The method is based on flare location (longitude), flare size (maximum soft X-ray intensity), and the occurrence (or not) of a CME. Warnings are issued for all > C1.0 soft X-ray flares. The warning time in the forecasting scheme extends to 24 hours with a refresh rate of 3 hours while the respective warning time for the nowcasting scheme depends on the availability of the near real-time data and falls between 15-20 minutes. We discuss the modules of the FORSPEF system, their interconnection and the operational set up. The dual approach in the development of FORPSEF (i.e. forecasting and nowcasting scheme) permits the refinement of predictions upon the availability of new data that characterize changes on the Sun and the interplanetary space, while the combined usage of solar flare and SEP forecasting methods upgrades FORSPEF to an integrated forecasting solution. This

Impact of a natural catastrophe on life events.

Science.gov (United States)

Janney, J G; Masuda, M; Holmes, T H

1977-06-01

A major earthquake struck Peru in May 1970. This post-quake study compares the impact of this natural catastrophe on the residents of two different cities; one was 90 percent levelled by the quake and one was untouched. A relatively homogeneous population of Peruvians obtained from the two cities completed two paper-and-pencil tests, the Social Readjustment Rating Questionnaire (SRRQ) and the Schedule of Recent Experience (SRE). Both questionnaires were adapted from the SRRQ which had been translated for studies in Spain and EL Salvador. The data from the SRRQ generated two Peruvian Social Readjustment Rating Scales (SRRS), one for each of the cities studied. The differences in the two scales were striking. The lowest intra-cultural correlation yet observed on four studies was obtained. Comparison with a United States population yielded no significant relationships (rs = 0.15), the first time this has occurred in nine intercultural studies. A comparison of the profile of items generated by their subjective magnitude estimations indicated striking qualitative and quantitative differences between the two populations. The SRE generated frequency of occurrence of items and life change magnitudes in five proscribed time intervals. Significant differences in these two quantitative indices (including the health change items) were observed in the two populations in some of the time intervals and not in others. The data formulated suggest that the occurrence of a natural catastrophe--an earthquake which devastated one city--accounted for much of the difference observed between the populations of the two cities.

A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin

Science.gov (United States)

Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie

2016-07-01

This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.

Addressing the Federal-State-Local Interface Issues During a Catastrophic Event Such as an Anthrax Attack

Energy Technology Data Exchange (ETDEWEB)

Stein, Steven L.; Lesperance, Ann M.; Upton, Jaki F.

2010-02-01

On October 9, 2008, federal, state and local policy makers, emergency managers, and medical and public health officials convened in Seattle, Washington, for a workshop on Addressing the Federal-State-Local Interface Issues During a Catastrophic Event Such as an Anthrax Attack. The day-long symposium was aimed at generating a dialogue about recovery and restoration through a discussion of the associated challenges that impact entire communities, including people, infrastructure, and critical systems. The Principal Federal Official (PFO) provided an overview of the role of the PFO in a catastrophic event. A high-level summary of an anthrax scenario was presented. The remainder of the day was focused on interactive discussions among federal, state and local emergency management experts in the areas of: • Decision-making, prioritization, and command and control • Public health/medical services • Community resiliency and continuity of government. Key topics and issues that resulted from discussions included: • Local representation in the Joint Field Office (JFO) • JFO transition to the Long-Term Recovery Office • Process for prioritization of needs • Process for regional coordination • Prioritization - process and federal/military intervention • Allocation of limited resources • Re-entry decision and consistency • Importance of maintaining a healthy hospital system • Need for a process to establish a consensus on when it is safe to re-enter. This needs to be across all jurisdictions including the military. • Insurance coverage for both private businesses and individuals • Interaction between the government and industry. The symposium was sponsored by the Interagency Biological Restoration Demonstration, a collaborative regional program jointly funded by the U.S. Department of Homeland Security and the U.S. Department of Defense. To aid the program’s efforts and inform the development of blueprint for recovery from a biological incident

Portals for Real-Time Earthquake Data and Forecasting: Challenge and Promise (Invited)

Science.gov (United States)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Feltstykket, R.; Donnellan, A.; Glasscoe, M. T.

2013-12-01

Earthquake forecasts have been computed by a variety of countries world-wide for over two decades. For the most part, forecasts have been computed for insurance, reinsurance and underwriters of catastrophe bonds. However, recent events clearly demonstrate that mitigating personal risk is becoming the responsibility of individual members of the public. Open access to a variety of web-based forecasts, tools, utilities and information is therefore required. Portals for data and forecasts present particular challenges, and require the development of both apps and the client/server architecture to deliver the basic information in real time. The basic forecast model we consider is the Natural Time Weibull (NTW) method (JBR et al., Phys. Rev. E, 86, 021106, 2012). This model uses small earthquakes (';seismicity-based models') to forecast the occurrence of large earthquakes, via data-mining algorithms combined with the ANSS earthquake catalog. This method computes large earthquake probabilities using the number of small earthquakes that have occurred in a region since the last large earthquake. Localizing these forecasts in space so that global forecasts can be computed in real time presents special algorithmic challenges, which we describe in this talk. Using 25 years of data from the ANSS California-Nevada catalog of earthquakes, we compute real-time global forecasts at a grid scale of 0.1o. We analyze and monitor the performance of these models using the standard tests, which include the Reliability/Attributes and Receiver Operating Characteristic (ROC) tests. It is clear from much of the analysis that data quality is a major limitation on the accurate computation of earthquake probabilities. We discuss the challenges of serving up these datasets over the web on web-based platforms such as those at www.quakesim.org , www.e-decider.org , and www.openhazards.com.

Catastrophic risk : Social influences on insurance decisions

NARCIS (Netherlands)

Krawczyk, Michal; Trautmann, Stefan; van de Kuilen, Gijs

We study behavioral patterns of insurance demand for low-probability large-loss events (catastrophic losses). Individual patterns of belief formation and risk attitude that were suggested in the behavioral decisions literature emerge robustly in the current set of insurance choices. However, social

The 1985 Nevado del Ruiz volcano catastrophe: anatomy and retrospection

Science.gov (United States)

Voight, Barry

1990-12-01

This paper seeks to analyze in an objective way the circumstances and events that contributed to the 1985 Nevado del Ruiz catastrophe, in order to provide useful guidelines for future emergencies. The paper is organized into two principal parts. In the first part, an Anatomy of the catastrophe is developed as a step-by-step chronicle of events and actions taken by individuals and organizations during the period November 1984 through November 1985. This chronicle provides the essential background for the crucial events of November 13. This year-long period is broken down further to emphasize important chapters: the gradual awareness of the awakening of the volcano; a long period of institutional skepticism reflecting an absence of credibility; the closure of the credibility gap with the September 11 phreatic eruption, followed by an intensive effort to gird for the worst; and a detailed account of the day of reckoning. The second part of the paper, Retrospection, examines the numerous complicated factors that influenced the catastrophic outcome, and attempts to cull a few "lessons from Armero" in order to avoid similar occurrences in the future. In a nutshell, the government on the whole acted responsibly but was not willing to bear the economic or political costs of early evacuation or a false alarm. Science accurately foresaw the hazards but was insufficiently precise to render reliable warning of the crucial event at the last possible minute. Catastrophe was therefore a calculated risk, and this combination - the limitations of prediction/detection, the refusal to bear a false alarm and the lack of will to act on the uncertain information available - provided its immediate and most obvious causes. But because the crucial event occurred just two days before the Armero emergency management plan was to be critically examined and improved, the numerous circumstances which delayed progress of emergency management over the previous year also may be said to have

Catastrophes control problem

International Nuclear Information System (INIS)

Velichenko, V.V.

1994-01-01

The problem of catastrophe control is discussed. Catastrophe control aims to withdraw responsible engineering constructions out of the catastrophe. The mathematical framework of catastrophes control systems is constructed. It determines the principles of systems filling by the concrete physical contents and, simultaneously, permits to employ modern control methods for the synthesis of optimal withdrawal strategy for protected objects

Morphological response of a barrier island system on a catastrophic event

DEFF Research Database (Denmark)

Fruergaard, Mikkel; Kroon, Aart

2016-01-01

storms are capable of moving large amounts of sediments over relatively short time-periods and can create barrier shoals, whereas moderate storms mostly rework the shoal or barrier and create more local erosion and/or landward migration. Catastrophic storms substantially influence long-term and large...

Forecasting Skill

Science.gov (United States)

1981-01-01

for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

Science.gov (United States)

Adams, E. C.; Nyaga, J. W.; Ellenburg, W. L.; Limaye, A. S.; Mugo, R. M.; Flores Cordova, A. I.; Irwin, D.; Case, J.; Malaso, S.; Sedah, A.

2017-12-01

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of 1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about 200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately $80 annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through

INEX 5 - General information. INEX 5 Exercise on Notification, Communication and Interfaces Related to Catastrophic Events Involving Radiation or Radiological Materials

International Nuclear Information System (INIS)

Okyar, Halil Burcin; Lazo, Ted

2014-01-01

The INEX series of international nuclear emergency exercises, organised under the OECD Nuclear Energy Agency (NEA), has proven successful in testing, investigating and improving the arrangements for responding to nuclear accidents and radiological emergencies at the national and international level. Previous INEX exercises focussed largely on national and international aspects of early phase management of emergencies at nuclear power plants and more recently, in INEX 4, on issues in consequence management and transition to recovery in response to malicious acts involving the release of radioactive materials in an urban setting. Since the events at the Fukushima Nuclear Power Plant, it has been recognised that notification, communication, and identifying and obtaining resources during catastrophic events can be difficult and the need for established protocols, policies, and procedures among and between country entities is critical for minimizing negative impacts. Therefore, the benefit and goal of INEX 5 is to provide a basis for enhancing national and international emergency management arrangements related to notification, communication and obtaining resources through the exchange of exercise outcomes and experiences from participating countries, in order to identify good practice and common issues to be addressed. INEX 5 will address emergency management aspects of notification, communication and interfaces between and among country and international organizations. INEX 5 is set up as a table top exercise with three levels of discussion for participants (prior to a release, recognizing/validating a release, and impacts to the radiological event from a catastrophic natural event). Countries can develop additional materials to expand this table top to a full field exercise if preferred. Prior to initiation of the table top, participants will be provided clear guidance about how the exercise will be conducted. Because this exercise may involve government agencies and

Pediatric catastrophic antiphospholipid syndrome: descriptive analysis of 45 patients from the "CAPS Registry".

Science.gov (United States)

Berman, Horacio; Rodríguez-Pintó, Ignasi; Cervera, Ricard; Gregory, Simone; de Meis, Ernesto; Rodrigues, Carlos Ewerton Maia; Aikawa, Nádia Emi; de Carvalho, Jozélio Freire; Springer, Janusz; Niedzwiecki, Maciej; Espinosa, Gerard

2014-02-01

Given the lack of information about catastrophic antiphospholipid syndrome (APS) in pediatric patients, the objective of the current study was to describe the clinical characteristics, laboratory features, treatment, and outcome of pediatric patients with catastrophic APS and compare them with the adult patients with catastrophic APS. We identified patients who were under 18years of age at time of catastrophic APS diagnosis included in the international registry of patients with catastrophic APS (CAPS Registry). Their main demographic and clinical characteristics, laboratory features, treatment, and outcome were described and compared with those of adult patients with catastrophic APS. From the 446 patients included in the CAPS Registry as of May 2013, 45 (10.3%) patients developed 46 catastrophic events before 18years of age (one patient presented two episodes). Overall, 32 (71.1%) patients were female and the mean age was 11.5±4.6years (range, 3months-18years). A total of 31 (68.9%) patients suffered from primary APS and 13 (28.9%) from systemic lupus erythematosus (SLE). The main differences between the two groups of patients were the higher prevalence of infections as precipitating factor for catastrophic event in the pediatric population (60.9% versus 26.8% in the adult population, p<0.001) and of peripheral vessel thrombosis (52.2% versus 34.3%, p=0.017). In addition, catastrophic APS was the first manifestation of APS more frequently in pediatric patients (86.6% versus 45.2%, p<0.001). Interestingly, pediatric patients showed a trend of lower mortality, although the difference was not statistically significant (26.1% versus 40.2%; odds ratio, 1.9; 95% confidence interval, 0.96-3.79; p=0.063). No differences were found neither in the laboratory features nor in the isolated or combination treatments between groups. Catastrophic APS in pediatric patients is a rare disease. There are minimal differences in the clinical and laboratory features, treatment, and

Forecasting the Earth’s radiation belts and modelling solar energetic particle events: Recent results from SPACECAST

Directory of Open Access Journals (Sweden)

Poedts Stefaan

2013-05-01

Full Text Available High-energy charged particles in the van Allen radiation belts and in solar energetic particle events can damage satellites on orbit leading to malfunctions and loss of satellite service. Here we describe some recent results from the SPACECAST project on modelling and forecasting the radiation belts, and modelling solar energetic particle events. We describe the SPACECAST forecasting system that uses physical models that include wave-particle interactions to forecast the electron radiation belts up to 3 h ahead. We show that the forecasts were able to reproduce the >2 MeV electron flux at GOES 13 during the moderate storm of 7–8 October 2012, and the period following a fast solar wind stream on 25–26 October 2012 to within a factor of 5 or so. At lower energies of 10 – a few 100 keV we show that the electron flux at geostationary orbit depends sensitively on the high-energy tail of the source distribution near 10 RE on the nightside of the Earth, and that the source is best represented by a kappa distribution. We present a new model of whistler mode chorus determined from multiple satellite measurements which shows that the effects of wave-particle interactions beyond geostationary orbit are likely to be very significant. We also present radial diffusion coefficients calculated from satellite data at geostationary orbit which vary with Kp by over four orders of magnitude. We describe a new automated method to determine the position at the shock that is magnetically connected to the Earth for modelling solar energetic particle events and which takes into account entropy, and predict the form of the mean free path in the foreshock, and particle injection efficiency at the shock from analytical theory which can be tested in simulations.

Improving short-term forecasting during ramp events by means of Regime-Switching Artificial Neural Networks

Science.gov (United States)

Gallego, C.; Costa, A.; Cuerva, A.

2010-09-01

Since nowadays wind energy can't be neither scheduled nor large-scale storaged, wind power forecasting has been useful to minimize the impact of wind fluctuations. In particular, short-term forecasting (characterised by prediction horizons from minutes to a few days) is currently required by energy producers (in a daily electricity market context) and the TSO's (in order to keep the stability/balance of an electrical system). Within the short-term background, time-series based models (i.e., statistical models) have shown a better performance than NWP models for horizons up to few hours. These models try to learn and replicate the dynamic shown by the time series of a certain variable. When considering the power output of wind farms, ramp events are usually observed, being characterized by a large positive gradient in the time series (ramp-up) or negative (ramp-down) during relatively short time periods (few hours). Ramp events may be motivated by many different causes, involving generally several spatial scales, since the large scale (fronts, low pressure systems) up to the local scale (wind turbine shut-down due to high wind speed, yaw misalignment due to fast changes of wind direction). Hence, the output power may show unexpected dynamics during ramp events depending on the underlying processes; consequently, traditional statistical models considering only one dynamic for the hole power time series may be inappropriate. This work proposes a Regime Switching (RS) model based on Artificial Neural Nets (ANN). The RS-ANN model gathers as many ANN's as different dynamics considered (called regimes); a certain ANN is selected so as to predict the output power, depending on the current regime. The current regime is on-line updated based on a gradient criteria, regarding the past two values of the output power. 3 Regimes are established, concerning ramp events: ramp-up, ramp-down and no-ramp regime. In order to assess the skillness of the proposed RS-ANN model, a single

Signatures of natural catastrophic events and anthropogenic impact in an estuarine environment, New Zealand

International Nuclear Information System (INIS)

Chague-Goff, C.; Nichol, S.L.; Jenkinson, A.V.; Heijnis, H.

2000-01-01

The sedimentary record of known natural catastrophic events and human activity in the Ahuriri Estuary, Hawke's Bay, is assessed using sedimentological, chemical and geochronological techniques. Evidence for the 1931 Hawke's Bay earthquake, which resulted in an uplift of one to two metres in the Napier area, is given by a change from silt- to sand-dominated sediment in the lower estuary, which is consistent with a shift toward higher energy depositional conditions following uplift. Post-European settlement impact is mainly restricted to the lower estuary, where increased concentrations of Zn, Cr, Pb and Cu are attributed to industrial discharges. Chemical data (Cl and S) suggest a change in the depositional environment in the upper estuary due to increased freshwater influx and/or decrease in seawater influence. Dating by 210 Pb suggests that this occurred around the middle of the 19th century, and might be attributed to river flooding at that time. 50 refs., 9 figs

Using additional external inputs to forecast water quality with an artificial neural network for contamination event detection in source water

Science.gov (United States)

Schmidt, F.; Liu, S.

2016-12-01

Source water quality plays an important role for the safety of drinking water and early detection of its contamination is vital to taking appropriate countermeasures. However, compared to drinking water, it is more difficult to detect contamination events because its environment is less controlled and numerous natural causes contribute to a high variability of the background values. In this project, Artificial Neural Networks (ANNs) and a Contamination Event Detection Process (CED Process) were used to identify events in river water. The ANN models the response of basic water quality sensors obtained in laboratory experiments in an off-line learning stage and continuously forecasts future values of the time line in an on-line forecasting step. During this second stage, the CED Process compares the forecast to the measured value and classifies it as regular background or event value, which modifies the ANN's continuous learning and influences its forecasts. In addition to this basic setup, external information is fed to the CED Process: A so-called Operator Input (OI) is provided to inform about unusual water quality levels that are unrelated to the presence of contamination, for example due to cooling water discharge from a nearby power plant. This study's primary goal is to evaluate how well the OI fits into the design of the combined forecasting ANN and CED Process and to understand its effects on the online forecasting stage. To test this, data from laboratory experiments conducted previously at the School of Environment, Tsinghua University, have been used to perform simulations highlighting features and drawbacks of this method. Applying the OI has been shown to have a positive influence on the ANN's ability to handle a sudden change in background values, which is unrelated to contamination. However, it might also mask the presence of an event, an issue that underlines the necessity to have several instances of the algorithm run in parallel. Other difficulties

Flood Risk Assessment and Forecasting for the Ganges-Brahmaputra-Meghna River Basins

Science.gov (United States)

Hopson, T. M.; Priya, S.; Young, W.; Avasthi, A.; Clayton, T. D.; Brakenridge, G. R.; Birkett, C. M.; Riddle, E. E.; Broman, D.; Boehnert, J.; Sampson, K. M.; Kettner, A.; Singh, D.

2017-12-01

During the 2017 South Asia monsoon, torrential rains and catastrophic floods affected more than 45 million people, including 16 million children, across the Ganges-Brahmaputra-Meghna (GBM) basins. The basin is recognized as one of the world's most disaster-prone regions, with severe floods occurring almost annually causing extreme loss of life and property. In light of this vulnerability, the World Bank and collaborators have contributed toward reducing future flood impacts through recent developments to improve operational preparedness for such events, as well as efforts in more general preparedness and resilience building through planning based on detailed risk assessments. With respect to improved event-specific flood preparedness through operational warnings, we discuss a new forecasting system that provides probability-based flood forecasts developed for more than 85 GBM locations. Forecasts are available online, along with near-real-time data maps of rainfall (predicted and actual) and river levels. The new system uses multiple data sets and multiple models to enhance forecasting skill, and provides improved forecasts up to 16 days in advance of the arrival of high waters. These longer lead times provide the opportunity to save both lives and livelihoods. With sufficient advance notice, for example, farmers can harvest a threatened rice crop or move vulnerable livestock to higher ground. Importantly, the forecasts not only predict future water levels but indicate the level of confidence in each forecast. Knowing whether the probability of a danger-level flood is 10 percent or 90 percent helps people to decide what, if any, action to take. With respect to efforts in general preparedness and resilience building, we also present a recent flood risk assessment, and how it provides, for the first time, a numbers-based view of the impacts of different size floods across the Ganges basin. The findings help identify priority areas for tackling flood risks (for

Operational flash flood forecasting platform based on grid technology

Science.gov (United States)

Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

2009-04-01

Flash flood events of south of France such as the 8th and 9th September 2002 in the Grand Delta territory caused important economic and human damages. Further to this catastrophic hydrological situation, a reform of flood warning services have been initiated (set in 2006). Thus, this political reform has transformed the 52 existing flood warning services (SAC) in 22 flood forecasting services (SPC), in assigning them territories more hydrological consistent and new effective hydrological forecasting mission. Furthermore, national central service (SCHAPI) has been created to ease this transformation and support local services in their new objectives. New functioning requirements have been identified: - SPC and SCHAPI carry the responsibility to clearly disseminate to public organisms, civil protection actors and population, crucial hydrologic information to better anticipate potential dramatic flood event, - a new effective hydrological forecasting mission to these flood forecasting services seems essential particularly for the flash floods phenomenon. Thus, models improvement and optimization was one of the most critical requirements. Initially dedicated to support forecaster in their monitoring mission, thanks to measuring stations and rainfall radar images analysis, hydrological models have to become more efficient in their capacity to anticipate hydrological situation. Understanding natural phenomenon occuring during flash floods mainly leads present hydrological research. Rather than trying to explain such complex processes, the presented research try to manage the well-known need of computational power and data storage capacities of these services. Since few years, Grid technology appears as a technological revolution in high performance computing (HPC) allowing large-scale resource sharing, computational power using and supporting collaboration across networks. Nowadays, EGEE (Enabling Grids for E-science in Europe) project represents the most important

Insurance and catastrophic events: can we expect de facto limits on liability recoveries

International Nuclear Information System (INIS)

Solomon, K.A.; Whipple, C.; Okrent, D.

1978-01-01

The purpose of this study is to take an overview of large technological systems in society to ascertain the prevalence, if any, of situations that can lead to catastrophic effects where the resultant liabilities far exceed the insurances or assets subject to suit in court, thereby imposing de facto limits on liability recoveries. In part, interest in this topic is spurred by the continuing discussion and controversy over the Price-Anderson Act which requires operators of nuclear plants to waive certain defenses and which limits the combined liability of the operator and the government to an amount less than the maximum potential public cost of a major nuclear reactor accident. A variety of technological events could result in assignable liabilities up to $25 billion, or more, depending on the value of life. These postulated events include: (1) the crash of a large aircraft into a crowded sports facility (an estimated $20.3 billion liability); (2) an explosion and subsequent dispersion of a chemical (such as chlorine or LNG) into a population center from a large manufacturing, storage, or transport facility (estimated $25.5 billion liability); (3) a massive nuclear power plant accident and the subsequent dispersal of large quantities of radioactive material to a large downwind population center ($25 billion liability); (4) the collision of two ships, such as a large LNG tanker and a large passenger liner, resulting in the deaths of all passengers on board ($5.5 billion liability); and (5) collapse of a large building in an earthquake, known by the owners to be seismically deficient and no steps having been taken to warn occupants or to remedy the situation (major deficiencies). All these events are found to involve potential liability far exceeding the available resources, whether they be insurance, corporation assets, or government revenues

Tackling The Global Challenge: Humanitarian Catastrophes

Directory of Open Access Journals (Sweden)

Kenneth V. Iserson

2014-03-01

Full Text Available “Humanitarian catastrophes,” conflicts and calamities generating both widespread human suffering and destructive events, require a wide range of emergency resources. This paper answers a number of questions that humanitarian catastrophes generate: Why and how do the most-developed countries—those with the resources, capabilities, and willingness to help—intervene in specific types of disasters? What ethical and legal guidelines shape our interventions? How well do we achieve our goals? It then suggests a number of changes to improve humanitarian responses, including better NGO-government cooperation, increased research on the best disaster response methods, clarification of the criteria and roles for humanitarian (military interventions, and development of post-2015 Millennium Development Goals with more accurate progress measures. [West J Emerg Med. 2014;15(2:231–240.

The Impact of Ocean Data Assimilation on Seasonal-to-Interannual Forecasts: A Case Study of the 2006 El Nino Event

Science.gov (United States)

Yang, Shu-Chih; Rienecker, Michele; Keppenne, Christian

2010-01-01

This study investigates the impact of four different ocean analyses on coupled forecasts of the 2006 El Nino event. Forecasts initialized in June 2006 using ocean analyses from an assimilation that uses flow-dependent background error covariances are compared with those using static error covariances that are not flow dependent. The flow-dependent error covariances reflect the error structures related to the background ENSO instability and are generated by the coupled breeding method. The ocean analyses used in this study result from the assimilation of temperature and salinity, with the salinity data available from Argo floats. Of the analyses, the one using information from the coupled bred vectors (BV) replicates the observed equatorial long wave propagation best and exhibits more warming features leading to the 2006 El Nino event. The forecasts initialized from the BV-based analysis agree best with the observations in terms of the growth of the warm anomaly through two warming phases. This better performance is related to the impact of the salinity analysis on the state evolution in the equatorial thermocline. The early warming is traced back to salinity differences in the upper ocean of the equatorial central Pacific, while the second warming, corresponding to the mature phase, is associated with the effect of the salinity assimilation on the depth of the thermocline in the western equatorial Pacific. The series of forecast experiments conducted here show that the structure of the salinity in the initial conditions is important to the forecasts of the extension of the warm pool and the evolution of the 2006 El Ni o event.

On sociological catastrophe analysis

International Nuclear Information System (INIS)

Clausen, L.

1974-01-01

The present paper deals with standard terms of sociological catastrophe theory hitherto existing, collective behaviour during the catastrophe, and consequences for the empiric catastrophe sociology. (RW) [de

Death, Catastrophe, and the Significance of Tragedy

Directory of Open Access Journals (Sweden)

Jennifer Ballengee

2014-05-01

Full Text Available This NANO note will examine the tension between representation, memorial, and the catastrophe of death that emerges in the space of tragedy, as the problem arises in two quite different works: Oedipus at Colonus, a fairly typical fifth-century Greek tragedy, and Falling Man, Don DeLillo’s novel that, in its attempt to address the events of 9/11, reflects in form and subject matter many of Aristotle’s terms of tragic representation. It is not the intent of this note to engage with the recent proliferation of work in “performance theory.” Rather than being concerned with an imagined exchange between audience and actor, this study examines how the supplementary relationship of gesture and speech in tragedy disrupts the public/private distinction, and how this articulation effects and enables the public memorialization of death. Thus, this paper will consider the representation of death as an event whose catastrophic, and somewhat mysterious, collision of the public and the private lends it its tragic significance.

Simulation of Flash-Flood-Producing Storm Events in Saudi Arabia Using the Weather Research and Forecasting Model

KAUST Repository

Deng, Liping

2015-05-01

The challenges of monitoring and forecasting flash-flood-producing storm events in data-sparse and arid regions are explored using the Weather Research and Forecasting (WRF) Model (version 3.5) in conjunction with a range of available satellite, in situ, and reanalysis data. Here, we focus on characterizing the initial synoptic features and examining the impact of model parameterization and resolution on the reproduction of a number of flood-producing rainfall events that occurred over the western Saudi Arabian city of Jeddah. Analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data suggests that mesoscale convective systems associated with strong moisture convergence ahead of a trough were the major initial features for the occurrence of these intense rain events. The WRF Model was able to simulate the heavy rainfall, with driving convective processes well characterized by a high-resolution cloud-resolving model. The use of higher (1 km vs 5 km) resolution along the Jeddah coastline favors the simulation of local convective systems and adds value to the simulation of heavy rainfall, especially for deep-convection-related extreme values. At the 5-km resolution, corresponding to an intermediate study domain, simulation without a cumulus scheme led to the formation of deeper convective systems and enhanced rainfall around Jeddah, illustrating the need for careful model scheme selection in this transition resolution. In analysis of multiple nested WRF simulations (25, 5, and 1 km), localized volume and intensity of heavy rainfall together with the duration of rainstorms within the Jeddah catchment area were captured reasonably well, although there was evidence of some displacements of rainstorm events.

Developing a forecast model of solar proton flux profiles for well-connected events

Science.gov (United States)

Ji, E. Y.; Moon, Y. J.; Park, J.

2014-12-01

We have developed a forecast model of solar proton flux profile (> 10 MeV channel) for well-connected events. Among 136 solar proton events (SPEs) from 1986 to 2006, we select 49 well-connected ones that are all associated with single X-ray flares stronger than M1 class and start to increase within four hours after their X-ray peak times. These events show rapid increments in proton flux. By comparing several empirical functions, we select a modified Weibull curve function to approximate a SPE flux profile, which is similar to the particle injection rate. The parameters (peak value, rise time and decay time) of this function are determined by the relationship between X-ray flare parameters (peak flux, impulsive time, and emission measure) and SPE parameters. For 49 well-connected SPEs, the linear correlation between the predicted proton peak flux and the observed proton peak fluxes is 0.65 with the RMS error of 0.55 pfu in the log10. In addition, we have developed another forecast model based on flare and CME parameters using 22 SPEs. The used CME parameters are linear speed and angular width. As a result, we find that the linear correlation between the predicted proton peak flux and the observed proton peak fluxes is 0.83 with the RMS error of 0.35 pfu in the log10. From the relationship between the model error and CME acceleration, we find that CME acceleration is also an important factor for predicting proton flux profiles.

Catastrophic Outcomes in Free Tissue Transfer: A Six-Year Review of the NSQIP Database

Directory of Open Access Journals (Sweden)

David W. Grant

2014-01-01

Full Text Available Background. No studies report robust data on the national incidence and risk factors associated with catastrophic medical outcomes following free tissue transfer. Methods. The American College of Surgeons (ACS multicenter, prospective National Surgical Quality Improvement Program (NSQIP database was used to identify patients who underwent free tissue transfer between 2006 and 2011. Multivariable logistic regression was used for statistical analysis. Results. Over the 6-year study period 2,349 patients in the NSQIP database underwent a free tissue transfer procedure. One hundred and twenty-two patients had at least one catastrophic medical outcome (5.2%. These 122 patients had 151 catastrophic medical outcomes, including 93 postoperative respiratory failure events (4.0%, 14 pulmonary emboli (0.6%, 13 septic shock events (0.5%, 12 myocardial infarctions (0.5%, 6 cardiac arrests (0.3%, 4 strokes (0.2%, 1 coma (0.0%, and 8 deaths (0.3%. Total length of hospital stay was on average 14.7 days longer for patients who suffered a catastrophic medical complication (P<0.001. Independent risk factors were identified. Conclusions. Free tissue transfer is a proven and safe technique. Catastrophic medical complications were infrequent but added significantly to length of hospital stay and patient morbidity.

Operational foreshock forecasting: Fifteen years after

Science.gov (United States)

Ogata, Y.

2010-12-01

We are concerned with operational forecasting of the probability that events are foreshocks of a forthcoming earthquake that is significantly larger (mainshock). Specifically, we define foreshocks as the preshocks substantially smaller than the mainshock by a magnitude gap of 0.5 or larger. The probability gain of foreshock forecast is extremely high compare to long-term forecast by renewal processes or various alarm-based intermediate-term forecasts because of a large event’s low occurrence rate in a short period and a narrow target region. Thus, it is desired to establish operational foreshock probability forecasting as seismologists have done for aftershocks. When a series of earthquakes occurs in a region, we attempt to discriminate foreshocks from a swarm or mainshock-aftershock sequence. Namely, after real time identification of an earthquake cluster using methods such as the single-link algorithm, the probability is calculated by applying statistical features that discriminate foreshocks from other types of clusters, by considering the events' stronger proximity in time and space and tendency towards chronologically increasing magnitudes. These features were modeled for probability forecasting and the coefficients of the model were estimated in Ogata et al. (1996) for the JMA hypocenter data (M≧4, 1926-1993). Currently, fifteen years has passed since the publication of the above-stated work so that we are able to present the performance and validation of the forecasts (1994-2009) by using the same model. Taking isolated events into consideration, the probability of the first events in a potential cluster being a foreshock vary in a range between 0+% and 10+% depending on their locations. This conditional forecasting performs significantly better than the unconditional (average) foreshock probability of 3.7% throughout Japan region. Furthermore, when we have the additional events in a cluster, the forecast probabilities range more widely from nearly 0% to

A model of pathways to artificial superintelligence catastrophe for risk and decision analysis

Science.gov (United States)

Barrett, Anthony M.; Baum, Seth D.

2017-03-01

An artificial superintelligence (ASI) is an artificial intelligence that is significantly more intelligent than humans in all respects. Whilst ASI does not currently exist, some scholars propose that it could be created sometime in the future, and furthermore that its creation could cause a severe global catastrophe, possibly even resulting in human extinction. Given the high stakes, it is important to analyze ASI risk and factor the risk into decisions related to ASI research and development. This paper presents a graphical model of major pathways to ASI catastrophe, focusing on ASI created via recursive self-improvement. The model uses the established risk and decision analysis modelling paradigms of fault trees and influence diagrams in order to depict combinations of events and conditions that could lead to AI catastrophe, as well as intervention options that could decrease risks. The events and conditions include select aspects of the ASI itself as well as the human process of ASI research, development and management. Model structure is derived from published literature on ASI risk. The model offers a foundation for rigorous quantitative evaluation and decision-making on the long-term risk of ASI catastrophe.

Seizing Catastrophes

DEFF Research Database (Denmark)

Kublitz, Anja

2013-01-01

to a distant past but takes place in the present. They use the term Nakba not only to refer to the catastrophe of 1948 but also to designate current catastrophes, such as the Danish Muhammad cartoons affair in 2005 and the Israeli invasion of Gaza in 2008. Through an analysis of the 60th commemoration...

Real-time Social Internet Data to Guide Forecasting Models

Energy Technology Data Exchange (ETDEWEB)

Del Valle, Sara Y. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-20

Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematical approaches and heterogeneous data streams.

Climate catastrophes

Science.gov (United States)

Budyko, Mikhail

1999-05-01

Climate catastrophes, which many times occurred in the geological past, caused the extinction of large or small populations of animals and plants. Changes in the terrestrial and marine biota caused by the catastrophic climate changes undoubtedly resulted in considerable fluctuations in global carbon cycle and atmospheric gas composition. Primarily, carbon dioxide and other greenhouse gas contents were affected. The study of these catastrophes allows a conclusion that climate system is very sensitive to relatively small changes in climate-forcing factors (transparency of the atmosphere, changes in large glaciations, etc.). It is important to take this conclusion into account while estimating the possible consequences of now occurring anthropogenic warming caused by the increase in greenhouse gas concentration in the atmosphere.

Seasonal forecasting of discharge for the Raccoon River, Iowa

Science.gov (United States)

Slater, Louise; Villarini, Gabriele; Bradley, Allen; Vecchi, Gabriel

2016-04-01

The state of Iowa (central United States) is regularly afflicted by severe natural hazards such as the 2008/2013 floods and the 2012 drought. To improve preparedness for these catastrophic events and allow Iowans to make more informed decisions about the most suitable water management strategies, we have developed a framework for medium to long range probabilistic seasonal streamflow forecasting for the Raccoon River at Van Meter, a 8900-km2 catchment located in central-western Iowa. Our flow forecasts use statistical models to predict seasonal discharge for low to high flows, with lead forecasting times ranging from one to ten months. Historical measurements of daily discharge are obtained from the U.S. Geological Survey (USGS) at the Van Meter stream gage, and used to compute quantile time series from minimum to maximum seasonal flow. The model is forced with basin-averaged total seasonal precipitation records from the PRISM Climate Group and annual row crop production acreage from the U.S. Department of Agriculture's National Agricultural Statistics Services database. For the forecasts, we use corn and soybean production from the previous year (persistence forecast) as a proxy for the impacts of agricultural practices on streamflow. The monthly precipitation forecasts are provided by eight Global Climate Models (GCMs) from the North American Multi-Model Ensemble (NMME), with lead times ranging from 0.5 to 11.5 months, and a resolution of 1 decimal degree. Additionally, precipitation from the month preceding each season is used to characterize antecedent soil moisture conditions. The accuracy of our modelled (1927-2015) and forecasted (2001-2015) discharge values is assessed by comparison with the observed USGS data. We explore the sensitivity of forecast skill over the full range of lead times, flow quantiles, forecast seasons, and with each GCM. Forecast skill is also examined using different formulations of the statistical models, as well as NMME forecast

GC13I-0857: Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

Science.gov (United States)

Adams, Emily C.; Wanjohi, James Nyaga; Ellenburg, Walter Lee; Limaye, Ashutosh S.; Mugo, Robinson M.; Flores Cordova, Africa Ixmucane; Irwin, Daniel; Case, Jonathan; Malaso, Susan; Sedah, Absae

2017-01-01

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of $1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about $200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately 80 USD annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared

A comparison of regional and global catastrophic hazards associated with energy technologies

International Nuclear Information System (INIS)

Heising, C.D.; Inhaber, H.

1983-01-01

This paper reviews some of what is known about the relative catastrophic hazards, on both a regional and global level, of energy technologies, and proposes a logical framework for their comparison. A review of the Inhaber study results is made indicating the relative position of overall nuclear power related risks. Then, concentration is placed on describing the catastrophic and global hazards of energy technologies. Regionally catastrophic hazards include sabotage and other malicious human activities, in addition to severe accidents caused inadvertantly by man, such as fires, reactor core damage events, chemical and poisonous gas releases, fuel storage fires and explosions, in addition to others. Global risks include such hazards as nuclear proliferation, CO 2 , build-up, oil shortages and possible national conflicts over dwindling energy fuels. The conclusion is drawn that consideration of both regional and global catastrophic risks must be made in making energy decisions, and that further study is necessary to better quantify and compare these risks. A simple decision analytic framework for making energy decisions inclusive of catastrophic risk is proposed

Forecast, observation and modelling of a deep stratospheric intrusion event over Europe

Directory of Open Access Journals (Sweden)

P. Zanis

2003-01-01

Full Text Available A wide range of measurements was carried out in central and southeastern Europe within the framework of the EU project STACCATO (Influence of Stratosphere-Troposphere Exchange in a Changing Climate on Atmospheric Transport and Oxidation Capacity with the principle goal to create a comprehensive data set on stratospheric air intrusions into the troposphere along a rather frequently observed pathway over central Europe from the North Sea to the Mediterranean Sea. The measurements were based on predictions by suitable quasi-operational trajectory calculations using ECMWF forecast data. A predicted deep Stratosphere to Troposphere Transport (STT event, encountered during the STACCATO period on 20-21 June 2001, was followed by the measurements network almost from its inception. Observations provide evidence that the intrusion affected large parts of central and southeastern Europe. Especially, the ozone lidar observations on 20-21 June 2001 at Garmisch-Partenkirchen, Germany captured the evolution of two marked tongues of high ozone with the first one descending to nearly 2 km, thus providing an excellent data set for model intercomparisons and validation. In addition, for the first time to our knowledge concurrent surface measurements of the cosmogenic radionuclides 10Be and 7Be and their ratio 10Be/7Be are presented together as stratospheric tracers in a case study of a stratospheric intrusion. The ozone tracer columns calculated with the FLEXPART model were found to be in good agreement with water vapour satellite images, capturing the evolution of the observed dry streamers of stratospheric origin. Furthermore, the time-height cross section of ozone tracer simulated with FLEXPART over Garmisch-Partenkirchen captures many details of the evolution of the two observed high-ozone filaments measured with the IFU lidar, thus demonstrating the considerable progress in model simulations. Finally, the modelled ozone (operationally available since October

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

Science.gov (United States)

Barghouty, Nasser; Falconer, David

2015-01-01

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

Storm Prediction Center Forecast Products

Science.gov (United States)

select the go button to submit request Local forecast by "City, St" or "ZIP" City, St Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC services. Forecast Products Current Weather Watches This is the current graphic showing any severe

Wind power forecast

Energy Technology Data Exchange (ETDEWEB)

Pestana, Rui [Rede Electrica Nacional (REN), S.A., Lisboa (Portugal). Dept. Systems and Development System Operator; Trancoso, Ana Rosa; Delgado Domingos, Jose [Univ. Tecnica de Lisboa (Portugal). Seccao de Ambiente e Energia

2012-07-01

Accurate wind power forecast are needed to reduce integration costs in the electric grid caused by wind inherent variability. Currently, Portugal has a significant wind power penetration level and consequently the need to have reliable wind power forecasts at different temporal scales, including localized events such as ramps. This paper provides an overview of the methodologies used by REN to forecast wind power at national level, based on statistical and probabilistic combinations of NWP and measured data with the aim of improving accuracy of pure NWP. Results show that significant improvement can be achieved with statistical combination with persistence in the short-term and with probabilistic combination in the medium-term. NWP are also able to detect ramp events with 3 day notice to the operational planning. (orig.)

The critical catastrophe revisited

International Nuclear Information System (INIS)

De Mulatier, Clélia; Rosso, Alberto; Dumonteil, Eric; Zoia, Andrea

2015-01-01

The neutron population in a prototype model of nuclear reactor can be described in terms of a collection of particles confined in a box and undergoing three key random mechanisms: diffusion, reproduction due to fissions, and death due to absorption events. When the reactor is operated at the critical point, and fissions are exactly compensated by absorptions, the whole neutron population might in principle go to extinction because of the wild fluctuations induced by births and deaths. This phenomenon, which has been named critical catastrophe, is nonetheless never observed in practice: feedback mechanisms acting on the total population, such as human intervention, have a stabilizing effect. In this work, we revisit the critical catastrophe by investigating the spatial behaviour of the fluctuations in a confined geometry. When the system is free to evolve, the neutrons may display a wild patchiness (clustering). On the contrary, imposing a population control on the total population acts also against the local fluctuations, and may thus inhibit the spatial clustering. The effectiveness of population control in quenching spatial fluctuations will be shown to depend on the competition between the mixing time of the neutrons (i.e. the average time taken for a particle to explore the finite viable space) and the extinction time

Communicating natural hazards. The case of marine extreme events and the importance of the forecast's errors.

Science.gov (United States)

Marone, Eduardo; Camargo, Ricardo

2013-04-01

Scientific knowledge has to fulfill some necessary conditions. Among them, it has to be properly communicated. Usually, scientists (mis)understand that the communication requirement is satisfied by publishing their results on peer reviewed journals. Society claims for information in other formats or languages and other tools and approaches have to be used, otherwise the scientific discoveries will not fulfill its social mean. However, scientists are not so well trained to do so. These facts are particularly relevant when the scientific work has to deal with natural hazards, which do not affect just a lab or a computer experiment, but the life and fate of human beings. We are actually working with marine extreme events related with sea level changes, waves and other coastal hazards. Primary, the work is developed on the classic scientific format, but focusing not only in the stochastic way of predicting such extreme events, but estimating the potential errors the forecasting methodologies intrinsically have. The scientific results are translated to a friendly format required by stakeholders (which are financing part of the work). Finally, we hope to produce a document prepared for the general public. Each of the targets has their own characteristics and we have to use the proper communication tools and languages. Also, when communicating such knowledge, we have to consider that stakeholders and general public have no obligation of understanding the scientific language, but scientists have the responsibility of translating their discoveries and predictions in a proper way. The information on coastal hazards is analyzed in statistical and numerical ways, departing from long term observation of, for instance, sea level. From the analysis it is possible to recognize different natural regimes and to present the return times of extreme events, while from the numerical models, properly tuned to reproduce the same past ocean behavior using hindcast approaches, it is

Using inferred probabilities to measure the accuracy of imprecise forecasts

Directory of Open Access Journals (Sweden)

Paul Lehner

2012-11-01

Full Text Available Research on forecasting is effectively limited to forecasts that are expressed with clarity; which is to say that the forecasted event must be sufficiently well-defined so that it can be clearly resolved whether or not the event occurred and forecasts certainties are expressed as quantitative probabilities. When forecasts are expressed with clarity, then quantitative measures (scoring rules, calibration, discrimination, etc. can be used to measure forecast accuracy, which in turn can be used to measure the comparative accuracy of different forecasting methods. Unfortunately most real world forecasts are not expressed clearly. This lack of clarity extends to both the description of the forecast event and to the use of vague language to express forecast certainty. It is thus difficult to assess the accuracy of most real world forecasts, and consequently the accuracy the methods used to generate real world forecasts. This paper addresses this deficiency by presenting an approach to measuring the accuracy of imprecise real world forecasts using the same quantitative metrics routinely used to measure the accuracy of well-defined forecasts. To demonstrate applicability, the Inferred Probability Method is applied to measure the accuracy of forecasts in fourteen documents examining complex political domains. Key words: inferred probability, imputed probability, judgment-based forecasting, forecast accuracy, imprecise forecasts, political forecasting, verbal probability, probability calibration.

Electron-density critical points analysis and catastrophe theory to forecast structure instability in periodic solids.

Science.gov (United States)

Merli, Marcello; Pavese, Alessandro

2018-03-01

The critical points analysis of electron density, i.e. ρ(x), from ab initio calculations is used in combination with the catastrophe theory to show a correlation between ρ(x) topology and the appearance of instability that may lead to transformations of crystal structures, as a function of pressure/temperature. In particular, this study focuses on the evolution of coalescing non-degenerate critical points, i.e. such that ∇ρ(x c ) = 0 and λ 1 , λ 2 , λ 3 ≠ 0 [λ being the eigenvalues of the Hessian of ρ(x) at x c ], towards degenerate critical points, i.e. ∇ρ(x c ) = 0 and at least one λ equal to zero. The catastrophe theory formalism provides a mathematical tool to model ρ(x) in the neighbourhood of x c and allows one to rationalize the occurrence of instability in terms of electron-density topology and Gibbs energy. The phase/state transitions that TiO 2 (rutile structure), MgO (periclase structure) and Al 2 O 3 (corundum structure) undergo because of pressure and/or temperature are here discussed. An agreement of 3-5% is observed between the theoretical model and experimental pressure/temperature of transformation.

Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

Directory of Open Access Journals (Sweden)

Jinyin Ye

2016-01-01

Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

Forecast communication through the newspaper Part 1: Framing the forecaster

Science.gov (United States)

Harris, Andrew J. L.

2015-04-01

This review is split into two parts both of which address issues of forecast communication of an environmental disaster through the newspaper during a period of crisis. The first part explores the process by which information passes from the scientist or forecaster, through the media filter, to the public. As part of this filter preference, omission, selection of data, source, quote and story, as well as placement of the same information within an individual piece or within the newspaper itself, can serve to distort the message. The result is the introduction of bias and slant—that is, the message becomes distorted so as to favor one side of the argument against another as it passes through the filter. Bias can be used to support spin or agenda setting, so that a particular emphasis becomes placed on the story which exerts an influence on the reader's judgment. The net result of the filter components is either a negative (contrary) or positive (supportive) frame. Tabloidization of the news has also resulted in the use of strong, evocative, exaggerated words, headlines and images to support a frame. I illustrate these various elements of the media filter using coverage of the air space closure due to the April 2010 eruption of Eyjafjallajökull (Iceland). Using the British press coverage of this event it is not difficult to find examples of all media filter elements, application of which resulted in bias against the forecast and forecaster. These actors then became named and blamed. Within this logic, it becomes only too easy for forecasters and scientists to be framed in a negative way through blame culture. The result is that forecast is framed in such a way so as to cause the forecaster to be blamed for all losses associated with the loss-causing event. Within the social amplification of risk framework (SARF), this can amplify a negative impression of the risk, the event and the response. However, actions can be taken to avoid such an outcome. These actions

Flood forecasting and uncertainty of precipitation forecasts

International Nuclear Information System (INIS)

Kobold, Mira; Suselj, Kay

2004-01-01

The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

Uncertainty in dispersion forecasts using meteorological ensembles

International Nuclear Information System (INIS)

Chin, H N; Leach, M J

1999-01-01

The usefulness of dispersion forecasts depends on proper interpretation of results. Understanding the uncertainty in model predictions and the range of possible outcomes is critical for determining the optimal course of action in response to terrorist attacks. One of the objectives for the Modeling and Prediction initiative is creating tools for emergency planning for special events such as the upcoming the Olympics. Meteorological forecasts hours to days in advance are used to estimate the dispersion at the time of the event. However, there is uncertainty in any meteorological forecast, arising from both errors in the data (both initial conditions and boundary conditions) and from errors in the model. We use ensemble forecasts to estimate the uncertainty in the forecasts and the range of possible outcomes

Uncertainty Forecasts Improve Weather-Related Decisions and Attenuate the Effects of Forecast Error

Science.gov (United States)

Joslyn, Susan L.; LeClerc, Jared E.

2012-01-01

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather…

Impact of soil moisture initialization on boreal summer subseasonal forecasts: mid-latitude surface air temperature and heat wave events

Science.gov (United States)

Seo, Eunkyo; Lee, Myong-In; Jeong, Jee-Hoon; Koster, Randal D.; Schubert, Siegfried D.; Kim, Hye-Mi; Kim, Daehyun; Kang, Hyun-Suk; Kim, Hyun-Kyung; MacLachlan, Craig; Scaife, Adam A.

2018-05-01

This study uses a global land-atmosphere coupled model, the land-atmosphere component of the Global Seasonal Forecast System version 5, to quantify the degree to which soil moisture initialization could potentially enhance boreal summer surface air temperature forecast skill. Two sets of hindcast experiments are performed by prescribing the observed sea surface temperature as the boundary condition for a 15-year period (1996-2010). In one set of the hindcast experiments (noINIT), the initial soil moisture conditions are randomly taken from a long-term simulation. In the other set (INIT), the initial soil moisture conditions are taken from an observation-driven offline Land Surface Model (LSM) simulation. The soil moisture conditions from the offline LSM simulation are calibrated using the forecast model statistics to minimize the inconsistency between the LSM and the land-atmosphere coupled model in their mean and variability. Results show a higher boreal summer surface air temperature prediction skill in INIT than in noINIT, demonstrating the potential benefit from an accurate soil moisture initialization. The forecast skill enhancement appears especially in the areas in which the evaporative fraction—the ratio of surface latent heat flux to net surface incoming radiation—is sensitive to soil moisture amount. These areas lie in the transitional regime between humid and arid climates. Examination of the extreme 2003 European and 2010 Russian heat wave events reveal that the regionally anomalous soil moisture conditions during the events played an important role in maintaining the stationary circulation anomalies, especially those near the surface.

Neutron flux distribution forecasting device of reactor

International Nuclear Information System (INIS)

Uematsu, Hitoshi

1991-01-01

A neutron flux distribution is forecast by using current data obtained from a reactor. That is, the device of the present invention comprises (1) a neutron flux monitor disposed in various positions in the reactor, (2) a forecasting means for calculating and forecasting a one-dimensional neutron flux distribution relative to imaginable events by using data obtained from the neutron flux monitor and physical models, and (3) a display means for displaying the results forecast in the forecasting means to a reactor operation console. Since the forecast values for the one-dimensional neutron flux distribution relative to the imaginable events are calculated in the device of the present invention by using data obtained from the neutron flux monitor and the physical models, the data as a base of the calculation are new and the period for calculating the forecast values can be shortened. Accordingly, although there is a worry of providing some errors in the forecast values, they can be utilized sufficiently as reference data. As a result, the reactor can be operated more appropriately. (I.N.)

Catastrophe theory—one of the basic components in the analysis of the seismic response of rock mass to explosions

Science.gov (United States)

Khachay, OA; Khachay, OYu

2018-03-01

It is shown that the dynamic process of mining can be controlled using the catastrophe theory. The control parameters can be values of blasting energy and locations of explosions relative to an area under study or operation. The kinematic and dynamic parameters of the deformation waves, as well as the structural features of rock mass through which these waves pass act as internal parameters. The use of the analysis methods for short-term and medium-term forecast of rock mass condition with the control parameters only is insufficient in the presence of sharp heterogeneity. However, the joint use of qualitative recommendations of the catastrophe theory and spatial–temporal data of changes in the internal parameters of rock mass will allow accident prevention in the course of mining.

Effects of microtubule mechanics on hydrolysis and catastrophes

International Nuclear Information System (INIS)

Müller, N; Kierfeld, J

2014-01-01

We introduce a model for microtubule (MT) mechanics containing lateral bonds between dimers in neighboring protofilaments, bending rigidity of dimers, and repulsive interactions between protofilaments modeling steric constraints to investigate the influence of mechanical forces on hydrolysis and catastrophes. We use the allosteric dimer model, where tubulin dimers are characterized by an equilibrium bending angle, which changes from 0 ∘ to 22 ∘ by hydrolysis of a dimer. This also affects the lateral interaction and bending energies and, thus, the mechanical equilibrium state of the MT. As hydrolysis gives rise to conformational changes in dimers, mechanical forces also influence the hydrolysis rates by mechanical energy changes modulating the hydrolysis rate. The interaction via the MT mechanics then gives rise to correlation effects in the hydrolysis dynamics, which have not been taken into account before. Assuming a dominant influence of mechanical energies on hydrolysis rates, we investigate the most probable hydrolysis pathways both for vectorial and random hydrolysis. Investigating the stability with respect to lateral bond rupture, we identify initiation configurations for catastrophes along the hydrolysis pathways and values for a lateral bond rupture force. If we allow for rupturing of lateral bonds between dimers in neighboring protofilaments above this threshold force, our model exhibits avalanche-like catastrophe events. (papers)

Catastrophic Failure and Fault-Tolerant Design of IGBT Power Electronic Converters - An Overview

DEFF Research Database (Denmark)

Wu, Rui; Blaabjerg, Frede; Wang, Huai

2013-01-01

Reliability is one of the key issues for the application of Insulated Gate Bipolar Transistors (IGBTs) in power electronic converters. Many efforts have been devoted to the reduction of IGBT wear out failure induced by accumulated degradation and catastrophic failure triggered by single-event ove......Reliability is one of the key issues for the application of Insulated Gate Bipolar Transistors (IGBTs) in power electronic converters. Many efforts have been devoted to the reduction of IGBT wear out failure induced by accumulated degradation and catastrophic failure triggered by single...

Affective forecasting and self-rated symptoms of depression, anxiety, and hypomania: evidence for a dysphoric forecasting bias.

Science.gov (United States)

Hoerger, Michael; Quirk, Stuart W; Chapman, Benjamin P; Duberstein, Paul R

2012-01-01

Emerging research has examined individual differences in affective forecasting; however, we are aware of no published study to date linking psychopathology symptoms to affective forecasting problems. Pitting cognitive theory against depressive realism theory, we examined whether dysphoria was associated with negatively biased affective forecasts or greater accuracy. Participants (n=325) supplied predicted and actual emotional reactions for three days surrounding an emotionally evocative relational event, Valentine's Day. Predictions were made a month prior to the holiday. Consistent with cognitive theory, we found evidence for a dysphoric forecasting bias-the tendency of individuals in dysphoric states to overpredict negative emotional reactions to future events. The dysphoric forecasting bias was robust across ratings of positive and negative affect, forecasts for pleasant and unpleasant scenarios, continuous and categorical operationalisations of dysphoria, and three time points of observation. Similar biases were not observed in analyses examining the independent effects of anxiety and hypomania. Findings provide empirical evidence for the long-assumed influence of depressive symptoms on future expectations. The present investigation has implications for affective forecasting studies examining information-processing constructs, decision making, and broader domains of psychopathology.

Affective Forecasting and Self-Rated Symptoms of Depression, Anxiety, and Hypomania: Evidence for a Dysphoric Forecasting Bias

Science.gov (United States)

Hoerger, Michael; Quirk, Stuart W.; Chapman, Benjamin P.; Duberstein, Paul R.

2011-01-01

Emerging research has examined individual differences in affective forecasting; however, we are aware of no published study to date linking psychopathology symptoms to affective forecasting problems. Pitting cognitive theory against depressive realism theory, we examined whether dysphoria was associated with negatively biased affective forecasts or greater accuracy. Participants (n = 325) supplied predicted and actual emotional reactions for three days surrounding an emotionally-evocative relational event, Valentine’s Day. Predictions were made a month prior to the holiday. Consistent with cognitive theory, we found evidence for a dysphoric forecasting bias – the tendency of individuals in dysphoric states to overpredict negative emotional reactions to future events. The dysphoric forecasting bias was robust across ratings of positive and negative affect, forecasts for pleasant and unpleasant scenarios, continuous and categorical operationalizations of dysphoria, and three time points of observation. Similar biases were not observed in analyses examining the independent effects of anxiety and hypomania. Findings provide empirical evidence for the long assumed influence of depressive symptoms on future expectations. The present investigation has implications for affective forecasting studies examining information processing constructs, decision making, and broader domains of psychopathology. PMID:22397734

Climatological attribution of wind power ramp events in East Japan and their probabilistic forecast based on multi-model ensembles downscaled by analog ensemble using self-organizing maps

Science.gov (United States)

Ohba, Masamichi; Nohara, Daisuke; Kadokura, Shinji

2016-04-01

Severe storms or other extreme weather events can interrupt the spin of wind turbines in large scale that cause unexpected "wind ramp events". In this study, we present an application of self-organizing maps (SOMs) for climatological attribution of the wind ramp events and their probabilistic prediction. The SOM is an automatic data-mining clustering technique, which allows us to summarize a high-dimensional data space in terms of a set of reference vectors. The SOM is applied to analyze and connect the relationship between atmospheric patterns over Japan and wind power generation. SOM is employed on sea level pressure derived from the JRA55 reanalysis over the target area (Tohoku region in Japan), whereby a two-dimensional lattice of weather patterns (WPs) classified during the 1977-2013 period is obtained. To compare with the atmospheric data, the long-term wind power generation is reconstructed by using a high-resolution surface observation network AMeDAS (Automated Meteorological Data Acquisition System) in Japan. Our analysis extracts seven typical WPs, which are linked to frequent occurrences of wind ramp events. Probabilistic forecasts to wind power generation and ramps are conducted by using the obtained SOM. The probability are derived from the multiple SOM lattices based on the matching of output from TIGGE multi-model global forecast to the WPs on the lattices. Since this method effectively takes care of the empirical uncertainties from the historical data, wind power generation and ramp is probabilistically forecasted from the forecasts of global models. The predictability skill of the forecasts for the wind power generation and ramp events show the relatively good skill score under the downscaling technique. It is expected that the results of this study provides better guidance to the user community and contribute to future development of system operation model for the transmission grid operator.

A Tool for Empirical Forecasting of Major Flares, Coronal Mass Ejections, and Solar Particle Events from a Proxy of Active-Region Free Magnetic Energy

Science.gov (United States)

Barghouty, A. F.; Falconer, D. A.; Adams, J. H., Jr.

2010-01-01

This presentation describes a new forecasting tool developed for and is currently being tested by NASA s Space Radiation Analysis Group (SRAG) at JSC, which is responsible for the monitoring and forecasting of radiation exposure levels of astronauts. The new software tool is designed for the empirical forecasting of M and X-class flares, coronal mass ejections, as well as solar energetic particle events. Its algorithm is based on an empirical relationship between the various types of events rates and a proxy of the active region s free magnetic energy, determined from a data set of approx.40,000 active-region magnetograms from approx.1,300 active regions observed by SOHO/MDI that have known histories of flare, coronal mass ejection, and solar energetic particle event production. The new tool automatically extracts each strong-field magnetic areas from an MDI full-disk magnetogram, identifies each as an NOAA active region, and measures a proxy of the active region s free magnetic energy from the extracted magnetogram. For each active region, the empirical relationship is then used to convert the free magnetic energy proxy into an expected event rate. The expected event rate in turn can be readily converted into the probability that the active region will produce such an event in a given forward time window. Descriptions of the datasets, algorithm, and software in addition to sample applications and a validation test are presented. Further development and transition of the new tool in anticipation of SDO/HMI is briefly discussed.

Application of probabilistic precipitation forecasts from a ...

African Journals Online (AJOL)

Application of probabilistic precipitation forecasts from a deterministic model towards increasing the lead-time of flash flood forecasts in South Africa. ... The procedure is applied to a real flash flood event and the ensemble-based rainfall forecasts are verified against rainfall estimated by the SAFFG system. The approach ...

Impact bias or underestimation? Outcome specifications predict the direction of affective forecasting errors.

Science.gov (United States)

Buechel, Eva C; Zhang, Jiao; Morewedge, Carey K

2017-05-01

Affective forecasts are used to anticipate the hedonic impact of future events and decide which events to pursue or avoid. We propose that because affective forecasters are more sensitive to outcome specifications of events than experiencers, the outcome specification values of an event, such as its duration, magnitude, probability, and psychological distance, can be used to predict the direction of affective forecasting errors: whether affective forecasters will overestimate or underestimate its hedonic impact. When specifications are positively correlated with the hedonic impact of an event, forecasters will overestimate the extent to which high specification values will intensify and low specification values will discount its impact. When outcome specifications are negatively correlated with its hedonic impact, forecasters will overestimate the extent to which low specification values will intensify and high specification values will discount its impact. These affective forecasting errors compound additively when multiple specifications are aligned in their impact: In Experiment 1, affective forecasters underestimated the hedonic impact of winning a smaller prize that they expected to win, and they overestimated the hedonic impact of winning a larger prize that they did not expect to win. In Experiment 2, affective forecasters underestimated the hedonic impact of a short unpleasant video about a temporally distant event, and they overestimated the hedonic impact of a long unpleasant video about a temporally near event. Experiments 3A and 3B showed that differences in the affect-richness of forecasted and experienced events underlie these differences in sensitivity to outcome specifications, therefore accounting for both the impact bias and its reversal. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The PRESSCA operational early warning system for landslide forecasting: the 11-12 November 2013 rainfall event in Central Italy.

Science.gov (United States)

Ciabatta, Luca; Brocca, Luca; Ponziani, Francesco; Berni, Nicola; Stelluti, Marco; Moramarco, Tommaso

2014-05-01

The Umbria Region, located in Central Italy, is one of the most landslide risk prone area in Italy, almost yearly affected by landslides events at different spatial scales. For early warning procedures aimed at the assessment of the hydrogeological risk, the rainfall thresholds represent the main tool for the Italian Civil Protection System. As shown in previous studies, soil moisture plays a key-role in landslides triggering. In fact, acting on the pore water pressure, soil moisture influences the rainfall amount needed for activating a landslide. In this work, an operational physically-based early warning system, named PRESSCA, that takes into account soil moisture for the definition of rainfall thresholds is presented. Specifically, the soil moisture conditions are evaluated in PRESSCA by using a distributed soil water balance model that is recently coupled with near real-time satellite soil moisture product obtained from ASCAT (Advanced SCATterometer) and from in-situ monitoring data. The integration of three different sources of soil moisture information allows to estimate the most accurate possible soil moisture condition. Then, both observed and forecasted rainfall data are compared with the soil moisture-based thresholds in order to obtain risk indicators over a grid of ~ 5 km. These indicators are then used for the daily hydrogeological risk evaluation and management by the Civil Protection regional service, through the sharing/delivering of near real-time landslide risk scenarios (also through an open source web platform: www.cfumbria.it). On the 11th-12th November, 2013, Umbria Region was hit by an exceptional rainfall event with up to 430mm/72hours that resulted in significant economic damages, but fortunately no casualties among the population. In this study, the results during the rainfall event of PRESSCA system are described, by underlining the model capability to reproduce, two days in advance, landslide risk scenarios in good spatial and temporal

An independent system operator's perspective on operational ramp forecasting

Energy Technology Data Exchange (ETDEWEB)

Porter, G. [New Brunswick System Operator, Fredericton, NB (Canada)

2010-07-01

One of the principal roles of the power system operator is to select the most economical resources to reliably supply electric system power needs. Operational wind power production forecasts are required by system operators in order to understand the impact of ramp event forecasting on dispatch functions. A centralized dispatch approach can contribute to a more efficient use of resources that traditional economic dispatch methods. Wind ramping events can have a significant impact on system reliability. Power systems can have constrained or robust transmission systems, and may also be islanded or have large connections to neighbouring systems. Power resources can include both flexible and inflexible generation resources. Wind integration tools must be used by system operators to improve communications and connections with wind power plants. Improved wind forecasting techniques are also needed. Sensitivity to forecast errors is dependent on current system conditions. System operators require basic production forecasts, probabilistic forecasts, and event forecasts. Forecasting errors were presented as well as charts outlining the implications of various forecasts. tabs., figs.

Grey Forecast Rainfall with Flow Updating Algorithm for Real-Time Flood Forecasting

Directory of Open Access Journals (Sweden)

Jui-Yi Ho

2015-04-01

Full Text Available The dynamic relationship between watershed characteristics and rainfall-runoff has been widely studied in recent decades. Since watershed rainfall-runoff is a non-stationary process, most deterministic flood forecasting approaches are ineffective without the assistance of adaptive algorithms. The purpose of this paper is to propose an effective flow forecasting system that integrates a rainfall forecasting model, watershed runoff model, and real-time updating algorithm. This study adopted a grey rainfall forecasting technique, based on existing hourly rainfall data. A geomorphology-based runoff model can be used for simulating impacts of the changing geo-climatic conditions on the hydrologic response of unsteady and non-linear watershed system, and flow updating algorithm were combined to estimate watershed runoff according to measured flow data. The proposed flood forecasting system was applied to three watersheds; one in the United States and two in Northern Taiwan. Four sets of rainfall-runoff simulations were performed to test the accuracy of the proposed flow forecasting technique. The results indicated that the forecast and observed hydrographs are in good agreement for all three watersheds. The proposed flow forecasting system could assist authorities in minimizing loss of life and property during flood events.

Probabilistic flood forecasting tool for Andalusia (Spain). Application to September 2012 disaster event in Vera Playa.

Science.gov (United States)

García, Darío; Baquerizo, Asunción; Ortega, Miguel; Herrero, Javier; Ángel Losada, Miguel

2013-04-01

Torrential and heavy rains are frequent in Andalusia (Southern Spain) due to the characteristic Mediterranean climate (semi-arid areas). This, in combination with a massive occupation of floodable (river sides) and coastal areas, produces severe problems of management and damage to the population and social and economical activities when extreme events occur. Some of the most important problems are being produced during last years in Almería (Southeastern Andalusia). Between 27 and 28 September 2012 rainstorms characterized by 240mm in 24h (exceeding precipitation for a return period of 500 years) occurred. Antas River and Jático creek, that are normally dry, became raging torrents. The massive flooding of occupied areas resulted in eleven deaths and two missing in Andalucía, with a total estimated cost of all claims for compensation on the order of 197 million euros. This study presents a probabilistic flood forecasting tool including the effect of river and marine forcings. It is based on a distributed, physically-based hydrological model (WiMMed). For Almería the model has been calibrated with the largest event recorded in Cantoria gauging station (data since 1965) on 19 October 1973. It was then validated with the second strongest event (26 October 1977). Among the different results of the model, it can provide probability floods scenarios in Andalusia with up 10 days weather forecasts. The tool has been applied to Vera, a 15.000 inhabitants town located in the east of Almería along the Antas River at an altitude of 95 meters. Its main economic resource is the "beach and sun" based-tourism, which has experienced an enormous growth during last decades. Its coastal stretch has been completely built in these years, occupying floodable areas and constricting the channel and rivers mouths. Simulations of the model in this area for the 1973 event and published in March 2011 on the internet event already announced that the floods of September 2012 may occur.

Coping with ecological catastrophe: crossing major thresholds

Directory of Open Access Journals (Sweden)

John Cairns, Jr.

2004-08-01

Full Text Available The combination of human population growth and resource depletion makes catastrophes highly probable. No long-term solutions to the problems of humankind will be discovered unless sustainable use of the planet is achieved. The essential first step toward this goal is avoiding or coping with global catastrophes that result from crossing major ecological thresholds. Decreasing the number of global catastrophes will reduce the risks associated with destabilizing ecological systems, which could, in turn, destabilize societal systems. Many catastrophes will be local, regional, or national, but even these upheavals will have global consequences. Catastrophes will be the result of unsustainable practices and the misuse of technology. However, avoiding ecological catastrophes will depend on the development of eco-ethics, which is subject to progressive maturation, comments, and criticism. Some illustrative catastrophes have been selected to display some preliminary issues of eco-ethics.

Against all odds -- Probabilistic forecasts and decision making

Science.gov (United States)

Liechti, Katharina; Zappa, Massimiliano

2015-04-01

In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

A composite stability index for dichotomous forecast of thunderstorms

Science.gov (United States)

Chaudhuri, Sutapa; Middey, Anirban

2012-12-01

Thunderstorms are the perennial feature of Kolkata (22° 32' N, 88° 20' E), India during the premonsoon season (April-May). Precise forecast of these thunderstorms is essential to mitigate the associated catastrophe due to lightning flashes, strong wind gusts, torrential rain, and occasional hail and tornadoes. The present research provides a composite stability index for forecasting thunderstorms. The forecast quality detection parameters are computed with the available indices during the period from 1997 to 2006 to select the most relevant indices with threshold ranges for the prevalence of such thunderstorms. The analyses reveal that the lifted index (LI) within the range of -5 to -12 °C, convective inhibition energy (CIN) within the range of 0-150 J/kg and convective available potential energy (CAPE) within the ranges of 2,000 to 7,000 J/kg are the most pertinent indices for the prevalence thunderstorms over Kolkata during the premonsoon season. A composite stability index, thunderstorm prediction index (TPI) is formulated with LI, CIN, and CAPE. The statistical skill score analyses show that the accuracy in forecasting such thunderstorms with TPI is 99.67 % with lead time less than 12 h during training the index whereas the accuracies are 89.64 % with LI, 60 % with CIN and 49.8 % with CAPE. The performance diagram supports that TPI has better forecast skill than its individual components. The forecast with TPI is validated with the observation of the India Meteorological Department during the period from 2007 to 2009. The real-time forecast of thunderstorms with TPI is provided for the year 2010.

A Short-term ESPERTA-based Forecast Tool for Moderate-to-extreme Solar Proton Events

Science.gov (United States)

Laurenza, M.; Alberti, T.; Cliver, E. W.

2018-04-01

The ESPERTA (Empirical model for Solar Proton Event Real Time Alert) forecast tool has a Probability of Detection (POD) of 63% for all >10 MeV events with proton peak intensity ≥10 pfu (i.e., ≥S1 events, S1 referring to minor storms on the NOAA Solar Radiation Storms scale), from 1995 to 2014 with a false alarm rate (FAR) of 38% and a median (minimum) warning time (WT) of ∼4.8 (0.4) hr. The NOAA space weather scale includes four additional categories: moderate (S2), strong (S3), severe (S4), and extreme (S5). As S1 events have only minor impacts on HF radio propagation in the polar regions, the effective threshold for significant space radiation effects appears to be the S2 level (100 pfu), above which both biological and space operation impacts are observed along with increased effects on HF propagation in the polar regions. We modified the ESPERTA model to predict ≥S2 events and obtained a POD of 75% (41/55) and an FAR of 24% (13/54) for the 1995–2014 interval with a median (minimum) WT of ∼1.7 (0.2) hr based on predictions made at the time of the S1 threshold crossing. The improved performance of ESPERTA for ≥S2 events is a reflection of the big flare syndrome, which postulates that the measures of the various manifestations of eruptive solar flares increase as one considers increasingly larger events.

Madame Bovary and Catastrophism: Revolving narratives

Directory of Open Access Journals (Sweden)

Ruth Morris

2011-07-01

Bovary within the scientific milieu of 1850s French society by reading Flaubert’s narrative as a Cuverian text. The French scientist Georges Cuvier, along with many of his contemporaries, formulated the catastrophist theory as a means of explaining the origins of the world. In catastrophism, the world is divided into very discrete time periods which are punctuated by vast catastrophes, or in Cuverian terminology ‘revolutions’ that have eradicated life and enabled the world to be repopulated afresh. This has implications for the concept of ‘time’. Cuvier theorises the earth as being relatively recent in origin, with the present epoch being only five thousand years old. This compression of time can be inferred in Madame Bovary through references to rapidity and the tempo which increases towards the denouement. In catastrophism and Madame Bovary, time is not constructed in a linear or chronological manner. The ‘revolutions’ disrupt a realisation of continuous time and Emma is frequently unable to distinguish between past, present and future experiences. The ‘revolutions’ also serve to puncture and disrupt the status quo of life by creating massive events within the earth’s history. Emma’s life too parallels this. She regards her existence as being informed by magnitudinous events, such as the ball, which creates dislocated and fragmented time as in Cuviers’ theory. I will also argue for a connection between the suddenness and violence of the ‘revolutions’ and Emma Bovary’s emotional outbursts which occur without for-warning and border on the hysterical. A Cuverian concept of time has implications for other considerations which are arguably the main differences between catastrophism and evolution theory. These include the notions of adaptation, inheritance and death within Flaubert’s narrative.

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

Science.gov (United States)

Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

2013-12-01

Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

Public policy and risk financing strategies for global catastrophe risk management - the role of global risk initiatives

Science.gov (United States)

McSharry, Patrick; Mitchell, Andrew; Anderson, Rebecca

2010-05-01

Decision-makers in both public and private organisations depend on accurate data and scientific understanding to adequately address climate change and the impact of extreme events. The financial impacts of catastrophes on populations and infrastructure can be offset through effective risk transfer mechanisms, structured to reflect the specific perils and levels of exposure to be covered. Optimal strategies depend on the likely socio-econonomic impact, the institutional framework, the overall objectives of the covers placed and the level of both the frequency and severity of loss potential expected. The diversity of approaches across different countries has been documented by the Spanish "Consorcio de Compensación de Seguros". We discuss why international public/private partnerships are necessary for addressing the risk of natural catastrophes. International initiatives such as the Global Earthquake Model (GEM) and the World Forum of Catastrophe Programmes (WFCP) can provide effective guidelines for constructing natural catastrophe schemes. The World Bank has been instrumental in the creation of many of the existing schemes such as the Turkish Catastrophe Insurance Pool, the Caribbean Catastrophe Risk Insurance Facility and the Mongolian Index-Based Livestock Insurance Program. We review existing schemes and report on best practice in relation to providing protection against natural catastrophe perils. The suitability of catastrophe modelling approaches to support schemes across the world are discussed and we identify opportunities to improve risk assessment for such schemes through transparent frameworks for quantifying, pricing, sharing and financing catastrophe risk on a local and global basis.

Classification of rainfall events for weather forecasting purposes in andean region of Colombia

Science.gov (United States)

Suárez Hincapié, Joan Nathalie; Romo Melo, Liliana; Vélez Upegui, Jorge Julian; Chang, Philippe

2016-04-01

This work presents a comparative analysis of the results of applying different methodologies for the identification and classification of rainfall events of different duration in meteorological records of the Colombian Andean region. In this study the work area is the urban and rural area of Manizales that counts with a monitoring hydro-meteorological network. This network is composed of forty-five (45) strategically located stations, this network is composed of forty-five (45) strategically located stations where automatic weather stations record seven climate variables: air temperature, relative humidity, wind speed and direction, rainfall, solar radiation and barometric pressure. All this information is sent wirelessly every five (5) minutes to a data warehouse located at the Institute of Environmental Studies-IDEA. With obtaining the series of rainfall recorded by the hydrometeorological station Palogrande operated by the National University of Colombia in Manizales (http://froac.manizales.unal.edu.co/bodegaIdea/); it is with this information that we proceed to perform behavior analysis of other meteorological variables, monitored at surface level and that influence the occurrence of such rainfall events. To classify rainfall events different methodologies were used: The first according to Monjo (2009) where the index n of the heavy rainfall was calculated through which various types of precipitation are defined according to the intensity variability. A second methodology that permitted to produce a classification in terms of a parameter β introduced by Rice and Holmberg (1973) and adapted by Llasat and Puigcerver, (1985, 1997) and the last one where a rainfall classification is performed according to the value of its intensity following the issues raised by Linsley (1977) where the rains can be considered light, moderate and strong fall rates to 2.5 mm / h; from 2.5 to 7.6 mm / h and above this value respectively for the previous classifications. The main

Catastrophizing in Patients with Burning Mouth Syndrome

Directory of Open Access Journals (Sweden)

Ana ANDABAK ROGULJ

2014-01-01

Full Text Available Background: Burning mouth syndrome (BMS is an idiopathic painful condition which manifests with burning sensations in the oral cavity in patients with clinically normal oral mucosa and without any local and/or systemic causative factor. Catastrophizing is defined as an exaggerated negative orientation toward pain stimuli and pain experience. The aim of this study was to examine the association between catastrophizing and clinical parameters of BMS, and to examine the association between catastrophizing and the quality of life in patients with BMS. Materials and methods: Anonymous questionnaire consisting of 3 parts (demographic and clinical data with 100 mm visual analogue scale (VAS, Croatian version of the Oral Health Impact Profile (OHIP-14 scale and Croatian version of the Pain Catastrophizing scale (PC, was distributed to 30 patients diagnosed with BMS. Results: A higher level of catastrophizing was clinically significant in 30% of the patients. Total catastrophizing score and all three subcomponents of catastrophizing significantly correlated with the intensity of symptoms, but did not correlate with the duration of symptoms. Gender and previous treatment did not affect the catastrophizing. Conclusion: Obtaining the information about catastrophizing could help a clinician to identify patients with negative behavioural patterns. Additional psychological intervention in these individuals could reduce/eliminate negative cognitive factors and improve coping with chronic painful condition such as BMS.

Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS

Directory of Open Access Journals (Sweden)

Sheng-Chi Yang

2014-01-01

Full Text Available During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.

Adaptation to and Recovery from Global Catastrophe

Directory of Open Access Journals (Sweden)

Seth D. Baum

2013-03-01

Full Text Available Global catastrophes, such as nuclear war, pandemics and ecological collapse threaten the sustainability of human civilization. To date, most work on global catastrophes has focused on preventing the catastrophes, neglecting what happens to any catastrophe survivors. To address this gap in the literature, this paper discusses adaptation to and recovery from global catastrophe. The paper begins by discussing the importance of global catastrophe adaptation and recovery, noting that successful adaptation/recovery could have value on even astronomical scales. The paper then discusses how the adaptation/recovery could proceed and makes connections to several lines of research. Research on resilience theory is considered in detail and used to develop a new method for analyzing the environmental and social stressors that global catastrophe survivors would face. This method can help identify options for increasing survivor resilience and promoting successful adaptation and recovery. A key point is that survivors may exist in small isolated communities disconnected from global trade and, thus, must be able to survive and rebuild on their own. Understanding the conditions facing isolated survivors can help promote successful adaptation and recovery. That said, the processes of global catastrophe adaptation and recovery are highly complex and uncertain; further research would be of great value.

Action-based flood forecasting for triggering humanitarian action

Science.gov (United States)

Coughlan de Perez, Erin; van den Hurk, Bart; van Aalst, Maarten K.; Amuron, Irene; Bamanya, Deus; Hauser, Tristan; Jongma, Brenden; Lopez, Ana; Mason, Simon; Mendler de Suarez, Janot; Pappenberger, Florian; Rueth, Alexandra; Stephens, Elisabeth; Suarez, Pablo; Wagemaker, Jurjen; Zsoter, Ervin

2016-09-01

Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new forecast-based financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society forecast-based financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

Replication Catastrophe

DEFF Research Database (Denmark)

Toledo, Luis; Neelsen, Kai John; Lukas, Jiri

2017-01-01

Proliferating cells rely on the so-called DNA replication checkpoint to ensure orderly completion of genome duplication, and its malfunction may lead to catastrophic genome disruption, including unscheduled firing of replication origins, stalling and collapse of replication forks, massive DNA...... breakage, and, ultimately, cell death. Despite many years of intensive research into the molecular underpinnings of the eukaryotic replication checkpoint, the mechanisms underlying the dismal consequences of its failure remain enigmatic. A recent development offers a unifying model in which the replication...... checkpoint guards against global exhaustion of rate-limiting replication regulators. Here we discuss how such a mechanism can prevent catastrophic genome disruption and suggest how to harness this knowledge to advance therapeutic strategies to eliminate cancer cells that inherently proliferate under...

Accuracy and artifact: reexamining the intensity bias in affective forecasting.

Science.gov (United States)

Levine, Linda J; Lench, Heather C; Kaplan, Robin L; Safer, Martin A

2012-10-01

Research on affective forecasting shows that people have a robust tendency to overestimate the intensity of future emotion. We hypothesized that (a) people can accurately predict the intensity of their feelings about events and (b) a procedural artifact contributes to people's tendency to overestimate the intensity of their feelings in general. People may misinterpret the forecasting question as asking how they will feel about a focal event, but they are later asked to report their feelings in general without reference to that event. In the current investigation, participants predicted and reported both their feelings in general and their feelings about an election outcome (Study 1) and an exam grade (Study 3). We also assessed how participants interpreted forecasting questions (Studies 2 and 4) and conducted a meta-analysis of affective forecasting research (Study 5). The results showed that participants accurately predicted the intensity of their feelings about events. They overestimated only when asked to predict how they would feel in general and later report their feelings without reference to the focal event. Most participants, however, misinterpreted requests to predict their feelings in general as asking how they would feel when they were thinking about the focal event. Clarifying the meaning of the forecasting question significantly reduced overestimation. These findings reveal that people have more sophisticated self-knowledge than is commonly portrayed in the affective forecasting literature. Overestimation of future emotion is partly due to a procedure in which people predict one thing but are later asked to report another.

How crucial is it to account for the antecedent moisture conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments

Directory of Open Access Journals (Sweden)

L. Berthet

2009-06-01

Full Text Available This paper compares event-based and continuous hydrological modelling approaches for real-time forecasting of river flows. Both approaches are compared using a lumped hydrologic model (whose structure includes a soil moisture accounting (SMA store and a routing store on a data set of 178 French catchments. The main focus of this study was to investigate the actual impact of soil moisture initial conditions on the performance of flood forecasting models and the possible compensations with updating techniques. The rainfall-runoff model assimilation technique we used does not impact the SMA component of the model but only its routing part. Tests were made by running the SMA store continuously or on event basis, everything else being equal. The results show that the continuous approach remains the reference to ensure good forecasting performances. We show, however, that the possibility to assimilate the last observed flow considerably reduces the differences in performance. Last, we present a robust alternative to initialize the SMA store where continuous approaches are impossible because of data availability problems.

Measuring the effectiveness of earthquake forecasting in insurance strategies

Science.gov (United States)

Mignan, A.; Muir-Wood, R.

2009-04-01

Given the difficulty of judging whether the skill of a particular methodology of earthquake forecasts is offset by the inevitable false alarms and missed predictions, it is important to find a means to weigh the successes and failures according to a common currency. Rather than judge subjectively the relative costs and benefits of predictions, we develop a simple method to determine if the use of earthquake forecasts can increase the profitability of active financial risk management strategies employed in standard insurance procedures. Three types of risk management transactions are employed: (1) insurance underwriting, (2) reinsurance purchasing and (3) investment in CAT bonds. For each case premiums are collected based on modelled technical risk costs and losses are modelled for the portfolio in force at the time of the earthquake. A set of predetermined actions follow from the announcement of any change in earthquake hazard, so that, for each earthquake forecaster, the financial performance of an active risk management strategy can be compared with the equivalent passive strategy in which no notice is taken of earthquake forecasts. Overall performance can be tracked through time to determine which strategy gives the best long term financial performance. This will be determined by whether the skill in forecasting the location and timing of a significant earthquake (where loss is avoided) is outweighed by false predictions (when no premium is collected). This methodology is to be tested in California, where catastrophe modeling is reasonably mature and where a number of researchers issue earthquake forecasts.

Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

Science.gov (United States)

Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

2015-12-01

Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be

Theory of a slow-light catastrophe

International Nuclear Information System (INIS)

Leonhardt, Ulf

2002-01-01

In diffraction catastrophes such as the rainbow, the wave nature of light resolves ray singularities and draws delicate interference patterns. In quantum catastrophes such as the black hole, the quantum nature of light resolves wave singularities and creates characteristic quantum effects related to Hawking radiation. This paper describes the theory behind a recent proposal [U. Leonhardt, Nature (London) 415, 406 (2002)] to generate a quantum catastrophe of slow light

Theory of a slow-light catastrophe

Science.gov (United States)

Leonhardt, Ulf

2002-04-01

In diffraction catastrophes such as the rainbow, the wave nature of light resolves ray singularities and draws delicate interference patterns. In quantum catastrophes such as the black hole, the quantum nature of light resolves wave singularities and creates characteristic quantum effects related to Hawking radiation. This paper describes the theory behind a recent proposal [U. Leonhardt, Nature (London) 415, 406 (2002)] to generate a quantum catastrophe of slow light.

Theory of a Slow-Light Catastrophe

OpenAIRE

Leonhardt, Ulf

2001-01-01

In diffraction catastrophes such as the rainbow the wave nature of light resolves ray singularities and draws delicate interference patterns. In quantum catastrophes such as the black hole the quantum nature of light resolves wave singularities and creates characteristic quantum effects related to Hawking radiation. The paper describes the theory behind a recent proposal [U. Leonhardt, arXiv:physics/0111058, Nature (in press)] to generate a quantum catastrophe of slow light.

Catastrophe theory with application in nuclear technology

International Nuclear Information System (INIS)

Valeca, Serban Constantin

2002-01-01

The monograph is structured on the following seven chapters: 1. Correlation of risk, catastrophe and chaos at the level of polyfunctional systems with nuclear injection; 1.1 Approaching the risk at the level of power systems; 1.2 Modelling the chaos-catastrophe-risk correlation in the structure of integrated classical and nuclear processes; 2. Catastrophe theory applied in ecosystems models and applications; 2.1 Posing the problems in catastrophe theory; 2.2 Application of catastrophe theory in the engineering of the power ecosystems with nuclear injection; 4.. Decision of abatement of the catastrophic risk based on minimal costs; 4.1 The nuclear power systems sensitive to risk-catastrophe-chaos in the structure of minimal costs; 4.2 Evaluating the market structure on the basis of power minimal costs; 4.3 Decisions in power systems built on minimal costs; 5. Models of computing the minimal costs in classical and nuclear power systems; 5.1 Calculation methodologies of power minimal cost; 5.2 Calculation methods of minimal costs in nuclear power sector; 6. Expert and neuro expert systems for supervising the risk-catastrophe-chaos correlation; 6.1 The structure of expert systems; 6.2 Application of the neuro expert program; 7. Conclusions and operational proposals; 7.1 A synthesis of the problems presented in this work; 7.2 Highlighting the novel aspects applicable in the power systems with nuclear injection

Forecasting winds over nuclear power plants statistics

International Nuclear Information System (INIS)

Marais, Ch.

1997-01-01

In the event of an accident at nuclear power plant, it is essential to forecast the wind velocity at the level where the efflux occurs (about 100 m). At present meteorologists refine the wind forecast from the coarse grid of numerical weather prediction (NWP) models. The purpose of this study is to improve the forecasts by developing a statistical adaptation method which corrects the NWP forecasts by using statistical comparisons between wind forecasts and observations. The Multiple Linear Regression method is used here to forecast the 100 m wind at 12 and 24 hours range for three Electricite de France (EDF) sites. It turns out that this approach gives better forecasts than the NWP model alone and is worthy of operational use. (author)

Verification of space weather forecasts at the UK Met Office

Science.gov (United States)

Bingham, S.; Sharpe, M.; Jackson, D.; Murray, S.

2017-12-01

The UK Met Office Space Weather Operations Centre (MOSWOC) has produced space weather guidance twice a day since its official opening in 2014. Guidance includes 4-day probabilistic forecasts of X-ray flares, geomagnetic storms, high-energy electron events and high-energy proton events. Evaluation of such forecasts is important to forecasters, stakeholders, model developers and users to understand the performance of these forecasts and also strengths and weaknesses to enable further development. Met Office terrestrial near real-time verification systems have been adapted to provide verification of X-ray flare and geomagnetic storm forecasts. Verification is updated daily to produce Relative Operating Characteristic (ROC) curves and Reliability diagrams, and rolling Ranked Probability Skill Scores (RPSSs) thus providing understanding of forecast performance and skill. Results suggest that the MOSWOC issued X-ray flare forecasts are usually not statistically significantly better than a benchmark climatological forecast (where the climatology is based on observations from the previous few months). By contrast, the issued geomagnetic storm activity forecast typically performs better against this climatological benchmark.

Ensemble Forecasts with Useful Skill-Spread Relationships for African meningitis and Asia Streamflow Forecasting

Science.gov (United States)

Hopson, T. M.

2014-12-01

One potential benefit of an ensemble prediction system (EPS) is its capacity to forecast its own forecast error through the ensemble spread-error relationship. In practice, an EPS is often quite limited in its ability to represent the variable expectation of forecast error through the variable dispersion of the ensemble, and perhaps more fundamentally, in its ability to provide enough variability in the ensembles dispersion to make the skill-spread relationship even potentially useful (irrespective of whether the EPS is well-calibrated or not). In this paper we examine the ensemble skill-spread relationship of an ensemble constructed from the TIGGE (THORPEX Interactive Grand Global Ensemble) dataset of global forecasts and a combination of multi-model and post-processing approaches. Both of the multi-model and post-processing techniques are based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. The methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. A context for these concepts is provided by assessing the constructed ensemble in forecasting district-level humidity impacting the incidence of meningitis in the meningitis belt of Africa, and in forecasting flooding events in the Brahmaputra and Ganges basins of South Asia.

Interevent times in a new alarm-based earthquake forecasting model

Science.gov (United States)

Talbi, Abdelhak; Nanjo, Kazuyoshi; Zhuang, Jiancang; Satake, Kenji; Hamdache, Mohamed

2013-09-01

This study introduces a new earthquake forecasting model that uses the moment ratio (MR) of the first to second order moments of earthquake interevent times as a precursory alarm index to forecast large earthquake events. This MR model is based on the idea that the MR is associated with anomalous long-term changes in background seismicity prior to large earthquake events. In a given region, the MR statistic is defined as the inverse of the index of dispersion or Fano factor, with MR values (or scores) providing a biased estimate of the relative regional frequency of background events, here termed the background fraction. To test the forecasting performance of this proposed MR model, a composite Japan-wide earthquake catalogue for the years between 679 and 2012 was compiled using the Japan Meteorological Agency catalogue for the period between 1923 and 2012, and the Utsu historical seismicity records between 679 and 1922. MR values were estimated by sampling interevent times from events with magnitude M ≥ 6 using an earthquake random sampling (ERS) algorithm developed during previous research. Three retrospective tests of M ≥ 7 target earthquakes were undertaken to evaluate the long-, intermediate- and short-term performance of MR forecasting, using mainly Molchan diagrams and optimal spatial maps obtained by minimizing forecasting error defined by miss and alarm rate addition. This testing indicates that the MR forecasting technique performs well at long-, intermediate- and short-term. The MR maps produced during long-term testing indicate significant alarm levels before 15 of the 18 shallow earthquakes within the testing region during the past two decades, with an alarm region covering about 20 per cent (alarm rate) of the testing region. The number of shallow events missed by forecasting was reduced by about 60 per cent after using the MR method instead of the relative intensity (RI) forecasting method. At short term, our model succeeded in forecasting the

Grasshopper Population Ecology: Catastrophe, Criticality, and Critique

Directory of Open Access Journals (Sweden)

Dale R. Lockwood

2008-06-01

Full Text Available Grasshopper population dynamics are an important part of the North American rangeland ecosystem and an important factor in the economies that derive from the rangeland. Outbreak dynamics have plagued management strategies in the rangeland, and attempts to find simple, linear and mechanistic solutions to both understanding and predicting the dynamics have proved fruitless. These efforts to ground theory in a correspondence with the "real" world, including whether the population dynamics are ultimately density dependent or density independent, have generated abundant heat but little light. We suggest that a pragmatic approach, in which theories are taken to be "tools" rather than competing claims of truth, has greater promise to move ecological research in a constructive direction. Two recent non-linear approaches exploiting the tools of complexity science provide insights relevant to explaining and forecasting population dynamics. Observation and data collection were used to structure models derived from catastrophe theory and self-organized criticality. These models indicate that nonlinear processes are important in the dynamics of the outbreaks. And the conceptual structures of these approaches provide clear, albeit constrained or contingent, implications for pest managers. We show that, although these two frameworks, catastrophe theory and self-organized criticality, are very different, the frequency distributions of time series from both systems result in power law relationships. Further, we show that a simple lattice-based model, similar to SOC but structured on the biology of the grasshoppers gives a spatial time series similar to data over a 50-year span and the frequency distribution is also a power law relationship. This demonstration exemplifies how a "both-and" rather than an "either-or" approach to ecological modeling, in which the useful elements of particular theories or conceptual structures are extracted, may provide a way forward

How are the catastrophical risks quantifiable

International Nuclear Information System (INIS)

Chakraborty, S.

1985-01-01

For the assessment and evaluation of industrial risks the question must be asked how are the catastrophical risks quantifiable. Typical real catastrophical risks and risk assessment based on modelling assumptions have been placed against each other in order to put the risks into proper perspective. However, the society is risk averse when there is a catastrophic potential of severe accidents in a large scale industrial facility even though there is extremely low probability of occurence. (orig.) [de

Monitoring and forecasting of radiation hazard from great solar energetic particle events by using on-line one-min neutron monitor and satellite data

International Nuclear Information System (INIS)

Dorman, L. I.

2007-01-01

The method of automatically determining the start of great solar energetic particle (SEP) events are described on the basis of cosmic ray (CR) one-min observations by neutron monitors in real-time scale. It is shown that the probabilities of false alarms and missed triggers are negligible. After the start of SEP event, it is automatically determined by the method of coupling functions the SEP energy spectrum and flux for each minute of observations. By solving the inverse problem during few first minutes of SEP event, diffusion coefficient in the interplanetary space, source function on the Sun, and time of ejection of SEP into solar wind are determined. For extending obtained results into small energy range we use also available from Internet the satellite one-min CR data. This make possible to give forecast of space-time variation of SEP for more than 2 days and estimate expected radiation dose for satellite and aircraft. With each new minute of observations, the quality of forecast increased, and after ∼30 min became near 100%. (authors)

Environmental catastrophes under time-inconsistent preference

Energy Technology Data Exchange (ETDEWEB)

Michielsen, T.

2013-02-15

I analyze optimal natural resource use in an intergenerational model with the risk of a catastrophe. Each generation maximizes a weighted sum of discounted utility (positive) and the probability that a catastrophe will occur at any point in the future (negative). The model generates time inconsistency as generations disagree on the relative weights on utility and catastrophe prevention. As a consequence, future generations emit too much from the current generation's perspective and a dynamic game ensues. I consider a sequence of models. When the environmental problem is related to a scarce exhaustible resource, early generations have an incentive to reduce emissions in Markov equilibrium in order to enhance the ecosystem's resilience to future emissions. When the pollutant is expected to become obsolete in the near future, early generations may however increase their emissions if this reduces future emissions. When polluting inputs are abundant and expected to remain essential, the catastrophe becomes a self-fulfilling prophecy and the degree of concern for catastrophe prevention has limited or even no effect on equilibrium behaviour.

Combining empirical approaches and error modelling to enhance predictive uncertainty estimation in extrapolation for operational flood forecasting. Tests on flood events on the Loire basin, France.

Science.gov (United States)

Berthet, Lionel; Marty, Renaud; Bourgin, François; Viatgé, Julie; Piotte, Olivier; Perrin, Charles

2017-04-01

An increasing number of operational flood forecasting centres assess the predictive uncertainty associated with their forecasts and communicate it to the end users. This information can match the end-users needs (i.e. prove to be useful for an efficient crisis management) only if it is reliable: reliability is therefore a key quality for operational flood forecasts. In 2015, the French flood forecasting national and regional services (Vigicrues network; www.vigicrues.gouv.fr) implemented a framework to compute quantitative discharge and water level forecasts and to assess the predictive uncertainty. Among the possible technical options to achieve this goal, a statistical analysis of past forecasting errors of deterministic models has been selected (QUOIQUE method, Bourgin, 2014). It is a data-based and non-parametric approach based on as few assumptions as possible about the forecasting error mathematical structure. In particular, a very simple assumption is made regarding the predictive uncertainty distributions for large events outside the range of the calibration data: the multiplicative error distribution is assumed to be constant, whatever the magnitude of the flood. Indeed, the predictive distributions may not be reliable in extrapolation. However, estimating the predictive uncertainty for these rare events is crucial when major floods are of concern. In order to improve the forecasts reliability for major floods, an attempt at combining the operational strength of the empirical statistical analysis and a simple error modelling is done. Since the heteroscedasticity of forecast errors can considerably weaken the predictive reliability for large floods, this error modelling is based on the log-sinh transformation which proved to reduce significantly the heteroscedasticity of the transformed error in a simulation context, even for flood peaks (Wang et al., 2012). Exploratory tests on some operational forecasts issued during the recent floods experienced in

Catastrophe medicine; Medecine de catastrophe

Energy Technology Data Exchange (ETDEWEB)

Lebreton, A. [Service Technique de l`Energie Electrique et des Grands Barrages (STEEGB), (France)

1996-12-31

The `Catastrophe Medicine` congress which took place in Amiens (France) in December 5 to 7 1996 was devoted to the assessment and management of risks and hazards in natural and artificial systems. The methods of risk evaluation and prevision were discussed in the context of dams accidents with the analysis of experience feedbacks and lessons gained from the organisation of emergency plans. Three round table conferences were devoted to the importance of psychological aspects during such major crises. (J.S.)

Axial and focal-plane diffraction catastrophe integrals

International Nuclear Information System (INIS)

Berry, M V; Howls, C J

2010-01-01

Exact expressions in terms of Bessel functions are found for some of the diffraction catastrophe integrals that decorate caustics in optics and mechanics. These are the axial and focal-plane sections of the elliptic and hyperbolic umbilic diffraction catastrophes, and symmetric elliptic and hyperbolic unfoldings of the X 9 diffraction catastrophes. These representations reveal unexpected relations between the integrals.

An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature

Directory of Open Access Journals (Sweden)

J. Zhang

2016-05-01

Full Text Available A major continental-scale biomass burning smoke event from 28–30 June 2015, spanning central Canada through the eastern seaboard of the United States, resulted in unforecasted drops in daytime high surface temperatures on the order of 2–5  °C in the upper Midwest. This event, with strong smoke gradients and largely cloud-free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near-surface air temperatures between Bismarck (clear and Grand Forks (overcast smoke, to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm smoke aerosol optical thickness (AOT, τ reached values above 5. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, τ550 was found. A further analysis of European Centre for Medium-Range Weather Forecasts (ECMWF, National Centers for Environmental Prediction (NCEP, United Kingdom Meteorological Office (UKMO near-surface air temperature forecasts for up to 54 h as a function of Moderate Resolution Imaging Spectroradiometer (MODIS Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 to −1.0 °C per unit τ550. In addition, using observations from the surface stations, uncertainties in near-surface air temperatures from ECMWF, NCEP, and UKMO model runs are estimated. This study further suggests that significant daily changes in τ550 above 1, at which the smoke-aerosol-induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events

Coronal Flux Rope Catastrophe Associated With Internal Energy Release

Science.gov (United States)

Zhuang, Bin; Hu, Youqiu; Wang, Yuming; Zhang, Quanhao; Liu, Rui; Gou, Tingyu; Shen, Chenglong

2018-04-01

Magnetic energy during the catastrophe was predominantly studied by the previous catastrophe works since it is believed to be the main energy supplier for the solar eruptions. However, the contribution of other types of energies during the catastrophe cannot be neglected. This paper studies the catastrophe of the coronal flux rope system in the solar wind background, with emphasis on the transformation of different types of energies during the catastrophe. The coronal flux rope is characterized by its axial and poloidal magnetic fluxes and total mass. It is shown that a catastrophe can be triggered by not only an increase but also a decrease of the axial magnetic flux. Moreover, the internal energy of the rope is found to be released during the catastrophe so as to provide energy for the upward eruption of the flux rope. As far as the magnetic energy is concerned, it provides only part of the energy release, or even increases during the catastrophe, so the internal energy may act as the dominant or even the unique energy supplier during the catastrophe.

Energy catastrophes and energy consumption

International Nuclear Information System (INIS)

Davis, G.

1991-01-01

The possibility of energy catastrophes in the production of energy serves to make estimation of the true social costs of energy production difficult. As a result, there is a distinct possibility that the private marginal cost curve of energy producers lies to the left or right of the true cost curve. If so, social welfare will not be maximized, and underconsumption or overconsumption of fuels will exist. The occurrence of energy catastrophes and observance of the market reaction to these occurrences indicates that overconsumption of energy has been the case in the past. Postulations as to market reactions to further energy catastrophes lead to the presumption that energy consumption levels remain above those that are socially optimal

Communicating likelihoods and probabilities in forecasts of volcanic eruptions

Science.gov (United States)

Doyle, Emma E. H.; McClure, John; Johnston, David M.; Paton, Douglas

2014-02-01

The issuing of forecasts and warnings of natural hazard events, such as volcanic eruptions, earthquake aftershock sequences and extreme weather often involves the use of probabilistic terms, particularly when communicated by scientific advisory groups to key decision-makers, who can differ greatly in relative expertise and function in the decision making process. Recipients may also differ in their perception of relative importance of political and economic influences on interpretation. Consequently, the interpretation of these probabilistic terms can vary greatly due to the framing of the statements, and whether verbal or numerical terms are used. We present a review from the psychology literature on how the framing of information influences communication of these probability terms. It is also unclear as to how people rate their perception of an event's likelihood throughout a time frame when a forecast time window is stated. Previous research has identified that, when presented with a 10-year time window forecast, participants viewed the likelihood of an event occurring ‘today’ as being of less than that in year 10. Here we show that this skew in perception also occurs for short-term time windows (under one week) that are of most relevance for emergency warnings. In addition, unlike the long-time window statements, the use of the phrasing “within the next…” instead of “in the next…” does not mitigate this skew, nor do we observe significant differences between the perceived likelihoods of scientists and non-scientists. This finding suggests that effects occurring due to the shorter time window may be ‘masking’ any differences in perception due to wording or career background observed for long-time window forecasts. These results have implications for scientific advice, warning forecasts, emergency management decision-making, and public information as any skew in perceived event likelihood towards the end of a forecast time window may result in

A Novel Flood Forecasting Method Based on Initial State Variable Correction

Directory of Open Access Journals (Sweden)

Kuang Li

2017-12-01

Full Text Available The influence of initial state variables on flood forecasting accuracy by using conceptual hydrological models is analyzed in this paper and a novel flood forecasting method based on correction of initial state variables is proposed. The new method is abbreviated as ISVC (Initial State Variable Correction. The ISVC takes the residual between the measured and forecasted flows during the initial period of the flood event as the objective function, and it uses a particle swarm optimization algorithm to correct the initial state variables, which are then used to drive the flood forecasting model. The historical flood events of 11 watersheds in south China are forecasted and verified, and important issues concerning the ISVC application are then discussed. The study results show that the ISVC is effective and applicable in flood forecasting tasks. It can significantly improve the flood forecasting accuracy in most cases.

Forecasting in Complex Systems

Science.gov (United States)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

2014-12-01

Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

An observational and modeling study of the August 2017 Florida climate extreme event.

Science.gov (United States)

Konduru, R.; Singh, V.; Routray, A.

2017-12-01

A special report on the climate extremes by the Intergovernmental Panel on Climate Change (IPCC) elucidates that the sole cause of disasters is due to the exposure and vulnerability of the human and natural system to the climate extremes. The cause of such a climate extreme could be anthropogenic or non-anthropogenic. Therefore, it is challenging to discern the critical factor of influence for a particular climate extreme. Such kind of perceptive study with reasonable confidence on climate extreme events is possible only if there exist any past case studies. A similar rarest climate extreme problem encountered in the case of Houston floods and extreme rainfall over Florida in August 2017. A continuum of hurricanes like Harvey and Irma targeted the Florida region and caused catastrophe. Due to the rarity of August 2017 Florida climate extreme event, it requires the in-depth study on this case. To understand the multi-faceted nature of the event, a study on the development of the Harvey hurricane and its progression and dynamics is significant. Current article focus on the observational and modeling study on the Harvey hurricane. A global model named as NCUM (The global UK Met office Unified Model (UM) operational at National Center for Medium Range Weather Forecasting, India, was utilized to simulate the Harvey hurricane. The simulated rainfall and wind fields were compared with the observational datasets like Tropical Rainfall Measuring Mission rainfall datasets and Era-Interim wind fields. The National Centre for Environmental Prediction (NCEP) automated tracking system was utilized to track the Harvey hurricane, and the tracks were analyzed statistically for different forecasts concerning the Harvey hurricane track of Joint Typhon Warning Centre. Further, the current study will be continued to investigate the atmospheric processes involved in the August 2017 Florida climate extreme event.

Model-free aftershock forecasts constructed from similar sequences in the past

Science.gov (United States)

van der Elst, N.; Page, M. T.

2017-12-01

The basic premise behind aftershock forecasting is that sequences in the future will be similar to those in the past. Forecast models typically use empirically tuned parametric distributions to approximate past sequences, and project those distributions into the future to make a forecast. While parametric models do a good job of describing average outcomes, they are not explicitly designed to capture the full range of variability between sequences, and can suffer from over-tuning of the parameters. In particular, parametric forecasts may produce a high rate of "surprises" - sequences that land outside the forecast range. Here we present a non-parametric forecast method that cuts out the parametric "middleman" between training data and forecast. The method is based on finding past sequences that are similar to the target sequence, and evaluating their outcomes. We quantify similarity as the Poisson probability that the observed event count in a past sequence reflects the same underlying intensity as the observed event count in the target sequence. Event counts are defined in terms of differential magnitude relative to the mainshock. The forecast is then constructed from the distribution of past sequences outcomes, weighted by their similarity. We compare the similarity forecast with the Reasenberg and Jones (RJ95) method, for a set of 2807 global aftershock sequences of M≥6 mainshocks. We implement a sequence-specific RJ95 forecast using a global average prior and Bayesian updating, but do not propagate epistemic uncertainty. The RJ95 forecast is somewhat more precise than the similarity forecast: 90% of observed sequences fall within a factor of two of the median RJ95 forecast value, whereas the fraction is 85% for the similarity forecast. However, the surprise rate is much higher for the RJ95 forecast; 10% of observed sequences fall in the upper 2.5% of the (Poissonian) forecast range. The surprise rate is less than 3% for the similarity forecast. The similarity

Application of Discrete EventSimulation in Mine Production Forecast*

African Journals Online (AJOL)

Michael

2016-06-01

Jun 1, 2016 ... Mine production forecast is pertinent to mining as it serves production ... Besides the inability of this method to mimic the .... management and truck operators understood the ..... Mining Engineering Handbook, Hartman, H. L..

Human-model hybrid Korean air quality forecasting system.

Science.gov (United States)

Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun

2016-09-01

The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the

An interdisciplinary approach for earthquake modelling and forecasting

Science.gov (United States)

Han, P.; Zhuang, J.; Hattori, K.; Ogata, Y.

2016-12-01

Earthquake is one of the most serious disasters, which may cause heavy casualties and economic losses. Especially in the past two decades, huge/mega earthquakes have hit many countries. Effective earthquake forecasting (including time, location, and magnitude) becomes extremely important and urgent. To date, various heuristically derived algorithms have been developed for forecasting earthquakes. Generally, they can be classified into two types: catalog-based approaches and non-catalog-based approaches. Thanks to the rapid development of statistical seismology in the past 30 years, now we are able to evaluate the performances of these earthquake forecast approaches quantitatively. Although a certain amount of precursory information is available in both earthquake catalogs and non-catalog observations, the earthquake forecast is still far from satisfactory. In most case, the precursory phenomena were studied individually. An earthquake model that combines self-exciting and mutually exciting elements was developed by Ogata and Utsu from the Hawkes process. The core idea of this combined model is that the status of the event at present is controlled by the event itself (self-exciting) and all the external factors (mutually exciting) in the past. In essence, the conditional intensity function is a time-varying Poisson process with rate λ(t), which is composed of the background rate, the self-exciting term (the information from past seismic events), and the external excitation term (the information from past non-seismic observations). This model shows us a way to integrate the catalog-based forecast and non-catalog-based forecast. Against this background, we are trying to develop a new earthquake forecast model which combines catalog-based and non-catalog-based approaches.

Estimating the benefits of single value and probability forecasting for flood warning

NARCIS (Netherlands)

Verkade, J.S.; Werner, M.G.F.

2011-01-01

Flood risk can be reduced by means of flood forecasting, warning and response systems (FFWRS). These systems include a forecasting sub-system which is imperfect, meaning that inherent uncertainties in hydrological forecasts may result in false alarms and missed events. This forecasting uncertainty

POSEIDON: An integrated system for analysis and forecast of hydrological, meteorological and surface marine fields in the Mediterranean area

Science.gov (United States)

Speranza, A.; Accadia, C.; Casaioli, M.; Mariani, S.; Monacelli, G.; Inghilesi, R.; Tartaglione, N.; Ruti, P. M.; Carillo, A.; Bargagli, A.; Pisacane, G.; Valentinotti, F.; Lavagnini, A.

2004-07-01

The Mediterranean area is characterized by relevant hydrological, meteorological and marine processes developing at horizontal space-scales of the order of 1-100 km. In the recent past, several international programs have been addressed (ALPEX, POEM, MAP, etc.) to "resolving" the dynamics of such motions. Other projects (INTERREG-Flooding, MEDEX, etc.) are at present being developed with special emphasis on catastrophic events with major impact on human society that are, quite often, characterized in their manifestation by processes with the above-mentioned scales of motion. In the dynamical evolution of such events, however, equally important is the dynamics of interaction of the local (and sometimes very damaging) processes with others developing at larger scales of motion. In fact, some of the most catastrophic events in the history of Mediterranean countries are associated with dynamical processes covering all the range of space-time scales from planetary to local. The Prevision Operational System for the mEditerranean basIn and the Defence of the lagOon of veNice (POSEIDON) is an integrated system for the analysis and forecast of hydrological, meteorological, oceanic fields specifically designed and set up in order to bridge the gap between global and local scales of motion, by modeling explicitly the above referred to dynamical processes in the range of scales from Mediterranean to local. The core of POSEIDON consists of a "cascade" of numerical models that, starting from global scale numerical analysis-forecast, goes all the way to very local phenomena, like tidal propagation in Venice Lagoon. The large computational load imposed by such operational design requires necessarily parallel computing technology: the first model in the cascade is a parallelised version of BOlogna Limited Area Model (BOLAM) running on a Quadrics 128 processors computer (also known as QBOLAM). POSEIDON, developed in the context of a co-operation between the Italian Agency for New

Application of probabilistic precipitation forecasts from a ...

African Journals Online (AJOL)

2014-02-14

Feb 14, 2014 ... Application of probabilistic precipitation forecasts from a deterministic model ... aim of this paper is to investigate the increase in the lead-time of flash flood warnings of the SAFFG using probabilistic precipitation forecasts ... The procedure is applied to a real flash flood event and the ensemble-based.

Severe abdominal pain as a presenting symptom of probable catastrophic antiphospholipid syndrome.

Science.gov (United States)

Haskin, Orly; Amir, Jacob; Schwarz, Michael; Schonfeld, Tommy; Nahum, Elhanan; Ling, Galina; Prais, Dario; Harel, Liora

2012-07-01

Catastrophic antiphospholipid syndrome (APS) in pediatric medicine is rare. We report 3 adolescents who presented with acute onset of severe abdominal pain as the first manifestation of probable catastrophic APS. The 3 patients, 2 male patients and 1 female patient were 14 to 18 years old. One had been diagnosed with systemic lupus erythematosus in the past, but the other 2 had no previous relevant medical history. All presented with excruciating abdominal pain without additional symptoms. Physical examination was noncontributory. Laboratory results were remarkable for high inflammatory markers. Abdominal ultrasonography was normal, and abdominal computed tomography scan showed nonspecific findings of liver infiltration. Only computed tomography angiography revealed evidence of extensive multiorgan thrombosis. All patients had elevated titers of antiphospholipid antibodies. The patients were treated with full heparinization, high-dose steroids, and intravenous immunoglobulin with a resolution of symptoms. One patient was resistant to the treatment and was treated with rituximab. In conclusion, severe acute abdominal pain can be the first manifestation of a thromboembolic event owing to catastrophic APS even in previously healthy adolescents. Diagnosis requires a high index of suspicion with prompt evaluation and treatment to prevent severe morbidity and mortality.

Business continuity in blood services: two case studies from events with potentially catastrophic effect on the national provision of blood components.

Science.gov (United States)

Morgan, S J; Rackham, R A; Penny, S; Lawson, J R; Walsh, R J; Ismay, S L

2015-02-01

NHS Blood and Transplant (NHSBT) and the Australian Red Cross Blood Service (ARCBS) are national blood establishments providing blood components to England and North Wales, and Australia, respectively. In 2012, both services experienced potentially catastrophic challenges to key assets. NHSBT suffered a flood that closed the largest blood-manufacturing centre in Europe, whilst ARCBS experienced the failure of a data centre network switch that rendered the national blood management system inaccessible for 42 h. This paper describes both crisis events, including the immediate actions, recovery procedures and lessons learned. Both incidents triggered emergency response plans. These included hospital reprovisioning and recovery from the incident. Once normal services had been restored, both events were subjected to root cause analysis (RCA) and production of 'lessons learned' reports. In both scenarios, the key enablers of rapid recovery were established emergency plans, clear leadership and the support of a flexible workforce. Product issues to hospitals were unaffected, and there were no abnormal trends in hospital complaints. RCA identified the importance of risk mitigations that require co-operation with external organizations. Reviews of both events identified opportunities to enhance business resilience through prior identification of external risks and improvements to contingency plans, for example by implementing mass messaging to staff and other stakeholders. Blood establishment emergency plans tend to focus on responding to mass casualty events. However, consolidation of manufacturing to fewer sites combined with a reliance on national IT systems increases the impact of loss of function. Blood services should develop business continuity plans which include prevention of such losses, and the maintenance of services and disaster recovery. © 2014 International Society of Blood Transfusion.

Socio-economic consequences of Chernobyl catastrophe. Social protection of the citizens, affected owing to Chernobyl catastrophe

International Nuclear Information System (INIS)

Kholosha, V.; Kovalchuk, V.

2003-01-01

The accident on Chernobyl NPP has affected the destiny of 35 million people in Ukraine. The social protection of the population affected during Chernobyl catastrophe is founded on the Law of Ukraine 'About the status and social protection of citizens affected owing to Chernobyl catastrophe' (see further - 'Law'), and is the principal direction of activity and the subject of the special state attention to total complex of problems bound to Chernobyl catastrophe consequences elimination. The current legislation stipulates partial compensation of material losses connected with resettlement of the affected population. According to the current legislation in Ukraine about 50 kinds of aid, privileges and compensations are submitted to the affected citizens

Catastrophe Finance: An Emerging Discipline

Science.gov (United States)

Elsner, James B.; Burch, R. King; Jagger, Thomas H.

2009-08-01

While the recent disasters in the world's financial markets demonstrate that finance theory remains far from perfected, science also faces steep challenges in the quest to predict and manage the effects of natural disasters. Worldwide, as many as half a million people have died in disasters such as earthquakes, tsunamis, and tropical cyclones since the turn of the 21st century [Wirtz, 2008]. Further, natural disasters can lead to extreme financial losses, and independent financial collapses can be exacerbated by natural disasters. In financial cost, 2008 was the second most expensive year on record for such catastrophes and for financial market declines. These extreme events in the natural and financial realms push the issue of risk management to the fore, expose the deficiencies of existing knowledge and practice, and suggest that progress requires further research and training at the graduate level.

Multiple Sclerosis and Catastrophic Health Expenditure in Iran.

Science.gov (United States)

Juyani, Yaser; Hamedi, Dorsa; Hosseini Jebeli, Seyede Sedighe; Qasham, Maryam

2016-09-01

There are many disabling medical conditions which can result in catastrophic health expenditure. Multiple Sclerosis is one of the most costly medical conditions through the world which encounter families to the catastrophic health expenditures. This study aims to investigate on what extent Multiple sclerosis patients face catastrophic costs. This study was carried out in Ahvaz, Iran (2014). The study population included households that at least one of their members suffers from MS. To analyze data, Logit regression model was employed by using the default software STATA12. 3.37% of families were encountered with catastrophic costs. Important variables including brand of drug, housing, income and health insurance were significantly correlated with catastrophic expenditure. This study suggests that although a small proportion of MS patients met the catastrophic health expenditure, mechanisms that pool risk and cost (e.g. health insurance) are required to protect them and improve financial and access equity in health care.

Forecasting Social Unrest Using Activity Cascades.

Science.gov (United States)

Cadena, Jose; Korkmaz, Gizem; Kuhlman, Chris J; Marathe, Achla; Ramakrishnan, Naren; Vullikanti, Anil

2015-01-01

Social unrest is endemic in many societies, and recent news has drawn attention to happenings in Latin America, the Middle East, and Eastern Europe. Civilian populations mobilize, sometimes spontaneously and sometimes in an organized manner, to raise awareness of key issues or to demand changes in governing or other organizational structures. It is of key interest to social scientists and policy makers to forecast civil unrest using indicators observed on media such as Twitter, news, and blogs. We present an event forecasting model using a notion of activity cascades in Twitter (proposed by Gonzalez-Bailon et al., 2011) to predict the occurrence of protests in three countries of Latin America: Brazil, Mexico, and Venezuela. The basic assumption is that the emergence of a suitably detected activity cascade is a precursor or a surrogate to a real protest event that will happen "on the ground." Our model supports the theoretical characterization of large cascades using spectral properties and uses properties of detected cascades to forecast events. Experimental results on many datasets, including the recent June 2013 protests in Brazil, demonstrate the effectiveness of our approach.

Forecasting Social Unrest Using Activity Cascades.

Directory of Open Access Journals (Sweden)

Jose Cadena

Full Text Available Social unrest is endemic in many societies, and recent news has drawn attention to happenings in Latin America, the Middle East, and Eastern Europe. Civilian populations mobilize, sometimes spontaneously and sometimes in an organized manner, to raise awareness of key issues or to demand changes in governing or other organizational structures. It is of key interest to social scientists and policy makers to forecast civil unrest using indicators observed on media such as Twitter, news, and blogs. We present an event forecasting model using a notion of activity cascades in Twitter (proposed by Gonzalez-Bailon et al., 2011 to predict the occurrence of protests in three countries of Latin America: Brazil, Mexico, and Venezuela. The basic assumption is that the emergence of a suitably detected activity cascade is a precursor or a surrogate to a real protest event that will happen "on the ground." Our model supports the theoretical characterization of large cascades using spectral properties and uses properties of detected cascades to forecast events. Experimental results on many datasets, including the recent June 2013 protests in Brazil, demonstrate the effectiveness of our approach.

DOWNWARD CATASTROPHE OF SOLAR MAGNETIC FLUX ROPES

Energy Technology Data Exchange (ETDEWEB)

Zhang, Quanhao; Wang, Yuming; Hu, Youqiu; Liu, Rui, E-mail: zhangqh@mail.ustc.edu.cn [CAS Key Laboratory of Geospace Environment, Department of Geophysics and Planetary Sciences, University of Science and Technology of China, Hefei 230026 (China)

2016-07-10

2.5-dimensional time-dependent ideal magnetohydrodynamic (MHD) models in Cartesian coordinates were used in previous studies to seek MHD equilibria involving a magnetic flux rope embedded in a bipolar, partially open background field. As demonstrated by these studies, the equilibrium solutions of the system are separated into two branches: the flux rope sticks to the photosphere for solutions at the lower branch but is suspended in the corona for those at the upper branch. Moreover, a solution originally at the lower branch jumps to the upper, as the related control parameter increases and reaches a critical value, and the associated jump is here referred to as an upward catastrophe. The present paper advances these studies in three aspects. First, the magnetic field is changed to be force-free; the system still experiences an upward catastrophe with an increase in each control parameter. Second, under the force-free approximation, there also exists a downward catastrophe, characterized by the jump of a solution from the upper branch to the lower. Both catastrophes are irreversible processes connecting the two branches of equilibrium solutions so as to form a cycle. Finally, the magnetic energy in the numerical domain is calculated. It is found that there exists a magnetic energy release for both catastrophes. The Ampère's force, which vanishes everywhere for force-free fields, appears only during the catastrophes and does positive work, which serves as a major mechanism for the energy release. The implications of the downward catastrophe and its relevance to solar activities are briefly discussed.

DOWNWARD CATASTROPHE OF SOLAR MAGNETIC FLUX ROPES

International Nuclear Information System (INIS)

Zhang, Quanhao; Wang, Yuming; Hu, Youqiu; Liu, Rui

2016-01-01

2.5-dimensional time-dependent ideal magnetohydrodynamic (MHD) models in Cartesian coordinates were used in previous studies to seek MHD equilibria involving a magnetic flux rope embedded in a bipolar, partially open background field. As demonstrated by these studies, the equilibrium solutions of the system are separated into two branches: the flux rope sticks to the photosphere for solutions at the lower branch but is suspended in the corona for those at the upper branch. Moreover, a solution originally at the lower branch jumps to the upper, as the related control parameter increases and reaches a critical value, and the associated jump is here referred to as an upward catastrophe. The present paper advances these studies in three aspects. First, the magnetic field is changed to be force-free; the system still experiences an upward catastrophe with an increase in each control parameter. Second, under the force-free approximation, there also exists a downward catastrophe, characterized by the jump of a solution from the upper branch to the lower. Both catastrophes are irreversible processes connecting the two branches of equilibrium solutions so as to form a cycle. Finally, the magnetic energy in the numerical domain is calculated. It is found that there exists a magnetic energy release for both catastrophes. The Ampère's force, which vanishes everywhere for force-free fields, appears only during the catastrophes and does positive work, which serves as a major mechanism for the energy release. The implications of the downward catastrophe and its relevance to solar activities are briefly discussed.

Catastrophic Antiphospholipid Syndrome

Directory of Open Access Journals (Sweden)

Rawhya R. El-Shereef

2016-01-01

Full Text Available This paper reports one case of successfully treated patients suffering from a rare entity, the catastrophic antiphospholipid syndrome (CAPS. Management of this patient is discussed in detail.

Realistic Affective Forecasting: The Role of Personality

Science.gov (United States)

Hoerger, Michael; Chapman, Ben; Duberstein, Paul

2016-01-01

Affective forecasting often drives decision making. Although affective forecasting research has often focused on identifying sources of error at the event level, the present investigation draws upon the ‘realistic paradigm’ in seeking to identify factors that similarly influence predicted and actual emotions, explaining their concordance across individuals. We hypothesized that the personality traits neuroticism and extraversion would account for variation in both predicted and actual emotional reactions to a wide array of stimuli and events (football games, an election, Valentine’s Day, birthdays, happy/sad film clips, and an intrusive interview). As hypothesized, individuals who were more introverted and neurotic anticipated, correctly, that they would experience relatively more unpleasant emotional reactions, and those who were more extraverted and less neurotic anticipated, correctly, that they would experience relatively more pleasant emotional reactions. Personality explained 30% of the concordance between predicted and actual emotional reactions. Findings suggest three purported personality processes implicated in affective forecasting, highlight the importance of individual-differences research in this domain, and call for more research on realistic affective forecasts. PMID:26212463

The Experimental Regional Ensemble Forecast System (ExREF): Its Use in NWS Forecast Operations and Preliminary Verification

Science.gov (United States)

Reynolds, David; Rasch, William; Kozlowski, Daniel; Burks, Jason; Zavodsky, Bradley; Bernardet, Ligia; Jankov, Isidora; Albers, Steve

2014-01-01

The Experimental Regional Ensemble Forecast (ExREF) system is a tool for the development and testing of new Numerical Weather Prediction (NWP) methodologies. ExREF is run in near-realtime by the Global Systems Division (GSD) of the NOAA Earth System Research Laboratory (ESRL) and its products are made available through a website, an ftp site, and via the Unidata Local Data Manager (LDM). The ExREF domain covers most of North America and has 9-km horizontal grid spacing. The ensemble has eight members, all employing WRF-ARW. The ensemble uses a variety of initial conditions from LAPS and the Global Forecasting System (GFS) and multiple boundary conditions from the GFS ensemble. Additionally, a diversity of physical parameterizations is used to increase ensemble spread and to account for the uncertainty in forecasting extreme precipitation events. ExREF has been a component of the Hydrometeorology Testbed (HMT) NWP suite in the 2012-2013 and 2013-2014 winters. A smaller domain covering just the West Coast was created to minimize band-width consumption for the NWS. This smaller domain has and is being distributed to the National Weather Service (NWS) Weather Forecast Office and California Nevada River Forecast Center in Sacramento, California, where it is ingested into the Advanced Weather Interactive Processing System (AWIPS I and II) to provide guidance on the forecasting of extreme precipitation events. This paper will review the cooperative effort employed by NOAA ESRL, NASA SPoRT (Short-term Prediction Research and Transition Center), and the NWS to facilitate the ingest and display of ExREF data utilizing the AWIPS I and II D2D and GFE (Graphical Software Editor) software. Within GFE is a very useful verification software package called BoiVer that allows the NWS to utilize the River Forecast Center's 4 km gridded QPE to compare with all operational NWP models 6-hr QPF along with the ExREF mean 6-hr QPF so the forecasters can build confidence in the use of the

Catastrophe theory and its application status in mechanical engineering

Directory of Open Access Journals (Sweden)

Jinge LIU

Full Text Available Catastrophe theory is a kind of mathematical method which aims to apply and interpret the discontinuous phenomenon. Since its emergence, it has been widely used to explain a variety of emergent phenomena in the fields of natural science, social science, management science and some other science and technology fields. Firstly, this paper introduces the theory of catastrophe in several aspects, such as its generation, radical principle, basic characteristics and development. Secondly, it summarizes the main applications of catastrophe theory in the field of mechanical engineering, focusing on the research progress of catastrophe theory in revealing catastrophe of rotor vibration state, analyzing friction and wear failure, predicting metal fracture, and so on. Finally, it advises that later development of catastrophe theory should pay more attention to the combination of itself with other traditional nonlinear theories and methods. This paper provides a beneficial reference to guide the application of catastrophe theory in mechanical engineering and related fields for later research.

Reply to "Comment on 'Nonparametric forecasting of low-dimensional dynamical systems' ".

Science.gov (United States)

Berry, Tyrus; Giannakis, Dimitrios; Harlim, John

2016-03-01

In this Reply we provide additional results which allow a better comparison of the diffusion forecast and the "past-noise" forecasting (PNF) approach for the El Niño index. We remark on some qualitative differences between the diffusion forecast and PNF, and we suggest an alternative use of the diffusion forecast for the purposes of forecasting the probabilities of extreme events.

Extensional rheometer based on viscoelastic catastrophes outline

DEFF Research Database (Denmark)

2014-01-01

The present invention relates to a method and a device for determining viscoelastic properties of a fluid. The invention resides inter alia in the generation of viscoelastic catastrophes in confined systems for use in the context of extensional rheology. The viscoelastic catastrophe is according ...... to the invention generated in a bistable fluid system, and the flow conditions for which the catastrophe occurs can be used as a fingerprint of the fluid's viscoelastic properties in extensional flow....

Space weather at Low Latitudes: Considerations to improve its forecasting

Science.gov (United States)

Chau, J. L.; Goncharenko, L.; Valladares, C. E.; Milla, M. A.

2013-05-01

In this work we present a summary of space weather events that are unique to low-latitude regions. Special emphasis will be devoted to events that occur during so-called quiet (magnetically) conditions. One of these events is the occurrence of nighttime F-region irregularities, also known Equatorial Spread F (ESF). When such irregularities occur navigation and communications systems get disrupted or perturbed. After more than 70 years of studies, many features of ESF irregularities (climatology, physical mechanisms, longitudinal dependence, time dependence, etc.) are well known, but so far they cannot be forecast on time scales of minutes to hours. We present a summary of some of these features and some of the efforts being conducted to contribute to their forecasting. In addition to ESF, we have recently identified a clear connection between lower atmospheric forcing and the low latitude variability, particularly during the so-called sudden stratospheric warming (SSW) events. During SSW events and magnetically quiet conditions, we have observed changes in total electron content (TEC) that are comparable to changes that occur during strong magnetically disturbed conditions. We present results from recent events as well as outline potential efforts to forecast the ionospheric effects during these events.

Robust seismicity forecasting based on Bayesian parameter estimation for epidemiological spatio-temporal aftershock clustering models.

Science.gov (United States)

Ebrahimian, Hossein; Jalayer, Fatemeh

2017-08-29

In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of seismicity forecasts play quite a crucial role in emergency decision-making and risk mitigation. Epidemic Type Aftershock Sequence (ETAS) models are frequently used for forecasting the spatio-temporal evolution of seismicity in the short-term. We propose robust forecasting of seismicity based on ETAS model, by exploiting the link between Bayesian inference and Markov Chain Monte Carlo Simulation. The methodology considers the uncertainty not only in the model parameters, conditioned on the available catalogue of events occurred before the forecasting interval, but also the uncertainty in the sequence of events that are going to happen during the forecasting interval. We demonstrate the methodology by retrospective early forecasting of seismicity associated with the 2016 Amatrice seismic sequence activities in central Italy. We provide robust spatio-temporal short-term seismicity forecasts with various time intervals in the first few days elapsed after each of the three main events within the sequence, which can predict the seismicity within plus/minus two standard deviations from the mean estimate within the few hours elapsed after the main event.

Chernobyl catastrophe: Information for people living in the contaminated areas

International Nuclear Information System (INIS)

Borisevich, Nikolaj

2001-01-01

The radioactive blow-outs after the Chernobyl Nuclear Power Plant catastrophe reached many states. The largest amount of them (according to experts' estimations - 70%) fell out on the Belarus territory. The estimation of radioecological, medico-biological, economic and social consequences of the Chernobyl catastrophe has shown that unimaginable damage was incurred on Belarus and its territory became the zone of ecological calamity. More than 14 years have passed since the Chernobyl NPP accident but some of the problems caused by the catastrophe have not been solved. This is bound up, first of all, with a high collective dosage absorbed by the population, with difficulties in forecasting and prophylactics of remote radiological effects, with ecological and economic crisis. The consequences of the disaster greatly affect all the aspects of vital activities of the affected regions and the state as a whole. Destructive tendencies have been revealed in all spheres of the life activity of people who experienced radiation effects. The processes of social adaptation and socio-psychological support of the population inhabiting the contaminated territory and resettled as well, require considerable optimisation. Negative factors of the Chernobyl catastrophe, which are significant for human health can be divided into two groups as follows: radiation-based, directly related to influence of ionising radiation and non radiation based, related to changes in habitat and prolonged psychological stress. The specific peculiarities of psychogenic disorders caused by the catastrophe are determined by the following reasons: insufficient knowledge of radiation effects; constant apprehension for the health and well-being of themselves and their families, especially children; unexpected change of the life stereotype (forced resettlement, the break of the former life, changing the place and the character of work, etc.); the necessity of constant keeping precaution measures and prophylactic

Forecasting sea fog on the coast of southern China

Science.gov (United States)

Huang, H.; Huang, B.; Liu, C.; Tu, J.; Wen, G.; Mao, W.

2016-12-01

Forecast sea fog is still full of challenges. We have performed the numerical forecasting of sea fog on the coast of southern China by using the operational meso-scale regional model GRAPES (Global/Regional assimilation and prediction system). The GRAPES model horizontal resolution was 3km and with 66 vertical levels. A total of 72 hours forecasting of sea fog was conducted with hourly outputs over the sea fog event. The results show that the model system can predict reasonable characteristics of typical sea fog events on the coast of southern China. The scope of sea fog coincides with the observations of meteorological stations, the observations of the Marine Meteorological Science Experiment Base (MMSEB) at Bohe, Maoming and satellite products of sea fog. The goal of this study is to establish an operational numerical forecasting model system of sea fog on the coast of southern China.

A global flash flood forecasting system

Science.gov (United States)

Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin

2016-04-01

The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial

Observing a catastrophic thermokarst lake drainage in northern Alaska

Science.gov (United States)

Jones, Benjamin M.; Arp, Christopher D.

2015-01-01

The formation and drainage of thermokarst lakes have reshaped ice-rich permafrost lowlands in the Arctic throughout the Holocene. North of Teshekpuk Lake, on the Arctic Coastal Plain of northern Alaska, thermokarst lakes presently occupy 22.5% of the landscape, and drained thermokarst lake basins occupy 61.8%. Analysis of remotely sensed imagery indicates that nine lakes (>10 ha) have drained in the 1,750 km2 study area between 1955 and 2014. The most recent lake drainage was observed using in situ data loggers providing information on the duration and magnitude of the event, and a nearby weather station provided information on the environmental conditions preceding the lake drainage. Lake 195 (L195), an 80 ha thermokarst lake with an estimated water volume of ~872,000 m3, catastrophically drained on 05 July 2014. Abundant winter snowfall and heavy early summer precipitation resulted in elevated lake water levels that likely promoted bank overtopping, thermo-erosion along an ice-wedge network, and formation of a 9 m wide, 2 m deep, and 70 m long drainage gully. The lake emptied in 36 hours, with 75% of the water volume loss occurring in the first ten hours. The observed peak discharge of the resultant flood was 25 m3/s, which is similar to that in northern Alaska river basins whose areas are more than two orders of magnitude larger. Our findings support the catastrophic nature of sudden lake drainage events and the mechanistic hypotheses developed by J. Ross Mackay.

Not all past events are equal: biased attention and emerging heuristics in children's past-to-future forecasting.

Science.gov (United States)

Lagattuta, Kristin Hansen; Sayfan, Liat

2013-01-01

Four- to 10-year-olds and adults (N = 265) responded to eight scenarios presented on an eye tracker. Each trial involved a character who encounters a perpetrator who had previously enacted positive (P), negative (N), or both types of actions toward him or her in varying sequences (NN, PP, PN, and NP). Participants predicted the character's thoughts about the likelihood of future events, emotion type and intensity, and decision to approach or avoid. All ages made more positive forecasts for PP > NP > PN > NN trials, with differentiation by past experience widening with age. Age-related increases in weighting the most recent past event also appeared in eye gaze. Individual differences in biased visual attention correlated with verbal judgments. Findings contribute to research on risk assessment, person perception, and heuristics in judgment and decision making. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

Myth and catastrophic reality: using cosmogonic mythology to identify cosmic impacts and massive plinian eruptions in holocene South America.

Energy Technology Data Exchange (ETDEWEB)

Masse, W. B. (William Bruce)

2004-01-01

Major natural catastrophes (e.g., 'universal' floods, fire, darkness, and sky falling down) are prominently reflected in traditional South American creation myths, cosmology, religion, and worldview. We are now beginning to recognize that cosmogonic myths represent a rich and largely untapped data set concerning the most dramatic natural events and processes experienced by each cultural group during the past several thousand years. Observational details regarding specific catastrophes are encoded in myth storylines, typically cast in terms of supernatural characters and actions. Not only are the myths amenable to scientific analysis, but also some sets of myths encode multiple catastrophes in meaningful relative chronological order. The present study considers more than 4200 myths, including more than 260 'universal' catastrophe myths from cultural groups throughout South America. These myths are examined in light of available geological, paleoenvironmental, archeological, and documentary evidence. Our analysis reveals three possible ultra-plinian volcanic eruptions, two in Columbia and the other in the Gran Chaco, the latter likely associated with a poorly dated late Holocene eruption of Nuevo Mundo in central Bolivia. Our analysis also identifies a set of traditions likely linked with the well-known Campo del Cielo iron meteorite impact in northern Argentina originally hypothesized to have occurred around 4000 years ago. Intriguingly, these traditions strongly suggest that the Campo del Cielo impact triggered widespread mass fires in the Gran Chaco region and possibly in the Brazilian Highlands. Several other potential cosmic impacts, distinct from Campo del Cielo, are hinted at in the mythology of other locations in South America. The numerous catastrophe myths in the Gran Chaco region exhibit the most coherent chronological sequence of any South American region. The sequence begins with a 'Great Flood,' by far the most widespread

Catastrophic Events Caused by Cosmic Objects

CERN Document Server

Adushkin, Vitaly

2008-01-01

Many times all of us could hear from mass media that an asteroid approached and swept past the Earth. Such an asteroid or comet will inevitably strike the planet some day. This volume considers hazards due to collisions with cosmic objects, particularly in light of recent investigations of impacts by the authors. Each chapter written by an expert contains an overview of an aspect and new findings in the field. The main hazardous effects – cratering, shock, aerial and seismic waves, fires, ejection of dust and soot, tsunami are described and numerically estimated. Numerical simulations of impacts and impact consequences have received much attention in the book. Fairly small impacting objects 50 -100 m in diameter pose a real threat to humanity and their influence on the atmosphere and ionosphere is emphasized. Especially vulnerable are industrially developed areas with dense population, almost all Europe is one of them. Special chapters are devoted to the famous 1908 Tunguska event and new results of its sim...

Salinity anomaly as a trigger for ENSO events.

Science.gov (United States)

Zhu, Jieshun; Huang, Bohua; Zhang, Rong-Hua; Hu, Zeng-Zhen; Kumar, Arun; Balmaseda, Magdalena A; Marx, Lawrence; Kinter, James L

2014-10-29

According to the classical theories of ENSO, subsurface anomalies in ocean thermal structure are precursors for ENSO events and their initial specification is essential for skillful ENSO forecast. Although ocean salinity in the tropical Pacific (particularly in the western Pacific warm pool) can vary in response to El Niño events, its effect on ENSO evolution and forecasts of ENSO has been less explored. Here we present evidence that, in addition to the passive response, salinity variability may also play an active role in ENSO evolution, and thus important in forecasting El Niño events. By comparing two forecast experiments in which the interannually variability of salinity in the ocean initial states is either included or excluded, the salinity variability is shown to be essential to correctly forecast the 2007/08 La Niña starting from April 2007. With realistic salinity initial states, the tendency to decay of the subsurface cold condition during the spring and early summer 2007 was interrupted by positive salinity anomalies in the upper central Pacific, which working together with the Bjerknes positive feedback, contributed to the development of the La Niña event. Our study suggests that ENSO forecasts will benefit from more accurate salinity observations with large-scale spatial coverage.

USA Nutrient managment forecasting via the "Fertilizer Forecaster": linking surface runnof, nutrient application and ecohydrology.

Science.gov (United States)

Drohan, Patrick; Buda, Anthony; Kleinman, Peter; Miller, Douglas; Lin, Henry; Beegle, Douglas; Knight, Paul

2017-04-01

USA and state nutrient management planning offers strategic guidance that strives to educate farmers and those involved in nutrient management to make wise management decisions. A goal of such programs is to manage hotspots of water quality degradation that threaten human and ecosystem health, water and food security. The guidance provided by nutrient management plans does not provide the day-to-day support necessary to make operational decisions, particularly when and where to apply nutrients over the short term. These short-term decisions on when and where to apply nutrients often make the difference between whether the nutrients impact water quality or are efficiently utilized by crops. Infiltrating rainfall events occurring shortly after broadcast nutrient applications are beneficial, given they will wash soluble nutrients into the soil where they are used by crops. Rainfall events that generate runoff shortly after nutrients are broadcast may wash off applied nutrients, and produce substantial nutrient losses from that site. We are developing a model and data based support tool for nutrient management, the Fertilizer Forecaster, which identifies the relative probability of runoff or infiltrating events in Pennsylvania (PA) landscapes in order to improve water quality. This tool will support field specific decisions by farmers and land managers on when and where to apply fertilizers and manures over 24, 48 and 72 hour periods. Our objectives are to: (1) monitor agricultural hillslopes in watersheds representing four of the five Physiographic Provinces of the Chesapeake Bay basin; (2) validate a high resolution mapping model that identifies soils prone to runoff; (3) develop an empirically based approach to relate state-of-the-art weather forecast variables to site-specific rainfall infiltration or runoff occurrence; (4) test the empirical forecasting model against alternative approaches to forecasting runoff occurrence; and (5) recruit farmers from the four

Forecasting the Seasonal Timing of Maine's Lobster Fishery

Directory of Open Access Journals (Sweden)

Katherine E. Mills

2017-11-01

Full Text Available The fishery for American lobster is currently the highest-valued commercial fishery in the United States, worth over US$620 million in dockside value in 2015. During a marine heat wave in 2012, the fishery was disrupted by the early warming of spring ocean temperatures and subsequent influx of lobster landings. This situation resulted in a price collapse, as the supply chain was not prepared for the early and abundant landings of lobsters. Motivated by this series of events, we have developed a forecast of when the Maine (USA lobster fishery will shift into its high volume summer landings period. The forecast uses a regression approach to relate spring ocean temperatures derived from four NERACOOS buoys along the coast of Maine to the start day of the high landings period of the fishery. Tested against conditions in past years, the forecast is able to predict the start day to within 1 week of the actual start, and the forecast can be issued 3–4 months prior to the onset of the high-landings period, providing valuable lead-time for the fishery and its associated supply chain to prepare for the upcoming season. Forecast results are conveyed in a probabilistic manner and are updated weekly over a 6-week forecasting period so that users can assess the certainty and consistency of the forecast and factor the uncertainty into their use of the information in a given year. By focusing on the timing of events, this type of seasonal forecast provides climate-relevant information to users at time scales that are meaningful for operational decisions. As climate change alters seasonal phenology and reduces the reliability of past experience as a guide for future expectations, this type of forecast can enable fishing industry participants to better adjust to and prepare for operating in the context of climate change.

Hydro-economic assessment of hydrological forecasting systems

Science.gov (United States)

Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

2012-01-01

SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

Manipulation of pain catastrophizing: An experimental study of healthy participants

Directory of Open Access Journals (Sweden)

Joel E Bialosky

2008-11-01

Full Text Available Joel E Bialosky1*, Adam T Hirsh2,3, Michael E Robinson2,3, Steven Z George1,3*1Department of Physical Therapy; 2Department of Clinical and Health Psychology; 3Center for Pain Research and Behavioral Health, University of Florida, Gainesville, Florida, USAAbstract: Pain catastrophizing is associated with the pain experience; however, causation has not been established. Studies which specifically manipulate catastrophizing are necessary to establish causation. The present study enrolled 100 healthy individuals. Participants were randomly assigned to repeat a positive, neutral, or one of three catastrophizing statements during a cold pressor task (CPT. Outcome measures of pain tolerance and pain intensity were recorded. No change was noted in catastrophizing immediately following the CPT (F(1,84 = 0.10, p = 0.75, partial η2 < 0.01 independent of group assignment (F(4,84 = 0.78, p = 0.54, partial η2 = 0.04. Pain tolerance (F(4 = 0.67, p = 0.62, partial η2 = 0.03 and pain intensity (F(4 = 0.73, p = 0.58, partial η2 = 0.03 did not differ by group. This study suggests catastrophizing may be difficult to manipulate through experimental pain procedures and repetition of specific catastrophizing statements was not sufficient to change levels of catastrophizing. Additionally, pain tolerance and pain intensity did not differ by group assignment. This study has implications for future studies attempting to experimentally manipulate pain catastrophizing.Keywords: pain, catastrophizing, experimental, cold pressor task, pain catastrophizing scale

Forecasting deflation, intrusion and eruption at inflating volcanoes

Science.gov (United States)

Blake, Stephen; Cortés, Joaquín A.

2018-01-01

A principal goal of volcanology is to successfully forecast the start of volcanic eruptions. This paper introduces a general forecasting method, which relies on a stream of monitoring data and a statistical description of a given threshold criterion for an eruption to start. Specifically we investigate the timing of intrusive and eruptive events at inflating volcanoes. The gradual inflation of the ground surface is a well-known phenomenon at many volcanoes and is attributable to pressurised magma accumulating within a shallow chamber. Inflation usually culminates in a rapid deflation event caused by magma escaping from the chamber to produce a shallow intrusion and, in some cases, a volcanic eruption. We show that the ground elevation during 15 inflation periods at Krafla volcano, Iceland, increased with time towards a limiting value by following a decaying exponential with characteristic timescale τ. The available data for Krafla, Kilauea and Mauna Loa volcanoes show that the duration of inflation (t*) is approximately equal to τ. The distribution of t* / τ values follows a log-logistic distribution in which the central 60% of the data lie between 0.99 deflation event starting during a specified time interval to be estimated. The time window in which there is a specified probability of deflation starting can also be forecast, and forecasts can be updated after each new deformation measurement. The method provides stronger forecasts than one based on the distribution of repose times alone and is transferable to other types of monitoring data and/or other patterns of pre-eruptive unrest.

Monitoring and forecasting local landslide hazard in the area of Longyearbyen, Svalbard - early progress and experiences from the Autumn 2016 events

Science.gov (United States)

Wang, Thea; Krøgli, Ingeborg; Boje, Søren; Colleuille, Hervé

2017-04-01

Since 2013 the Norwegian Water Resources and Energy Directorate (NVE) has operated a landslide early warning system (LEWS) for mainland Norway. The Svalbard islands, situated 800 km north of the Norwegian mainland, and 1200 km from the North Pole, are not part of the conventional early warning service. However, following the fatal snow avalanche event 19 Dec. 2015 in the settlement of Longyearbyen (78° north latitude), local authorities and the NVE have initiated monitoring of the hydro-meteorological conditions for the area of Longyearbyen, as an extraordinary precaution. Two operational forecasting teams from the NVE; the snow avalanche and the landslide hazard forecasters, perform hazard assessment related to snow avalanches, slush flows, debris flows, shallow slides and local flooding. This abstract will focus on recent experiences made by the landslide hazard team during the autumn 2016 landslide events, caused by a record setting wet and warm summer and autumn of 2016. The general concept of the Norwegian LEWS is based on frequency intervals of extreme hydro-meteorological conditions. This general concept has been transposed to the Longyearbyen area. Although the climate is considerably colder and drier than mainland Norway, experiences so far are positive and seem useful to the local authorities. Initially, the landslide hazard evaluation was intended to consider only slush flow hazard during the snow covered season. However, due to the extraordinary warm and wet summer and autumn 2016, the landslide hazard forecasters unexpectedly had to issue warnings for the local authorities due to increased risk of shallow landslides and debris flows. This was done in close cooperation with the Norwegian Meteorological Institute, who provided weather forecasts from the recently developed weather prediction model, AROME-Arctic. Two examples, from 14-15 Oct and 8-9 Nov 2016, will be given to demonstrate how the landslide hazard assessment for the Longyearbyen area is

Valuing Catastrophe Bonds Involving Credit Risks

Directory of Open Access Journals (Sweden)

Jian Liu

2014-01-01

Full Text Available Catastrophe bonds are the most important products in catastrophe risk securitization market. For the operating mechanism, CAT bonds may have a credit risk, so in this paper we consider the influence of the credit risk on CAT bonds pricing that is different from the other literature. We employ the Jarrow and Turnbull method to model the credit risks and get access to the general pricing formula using the Extreme Value Theory. Furthermore, we present an empirical pricing study of the Property Claim Services data, where the parameters in the loss function distribution are estimated by the MLE method and the default probabilities are deduced by the US financial market data. Then we get the catastrophe bonds value by the Monte Carlo method.

Does catastrophic thinking enhance oesophageal pain sensitivity?

DEFF Research Database (Denmark)

Martel, M O; Olesen, A E; Jørgensen, D

2016-01-01

that catastrophic thinking exerts an influence on oesophageal pain sensitivity, but not necessarily on the magnitude of acid-induced oesophageal sensitization. WHAT DOES THIS STUDY ADD?: Catastrophizing is associated with heightened pain sensitivity in the oesophagus. This was substantiated by assessing responses...

Two-Step Forecast of Geomagnetic Storm Using Coronal Mass Ejection and Solar Wind Condition

Science.gov (United States)

Kim, R.-S.; Moon, Y.-J.; Gopalswamy, N.; Park, Y.-D.; Kim, Y.-H.

2014-01-01

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz = -5 nT or Ey = 3 mV/m for t = 2 h for moderate storms with minimum Dst less than -50 nT) (i.e. Magnetic Field Magnitude, B (sub z) less than or equal to -5 nanoTeslas or duskward Electrical Field, E (sub y) greater than or equal to 3 millivolts per meter for time greater than or equal to 2 hours for moderate storms with Minimum Disturbance Storm Time, Dst less than -50 nanoTeslas) and a Dst model developed by Temerin and Li (2002, 2006) (TL [i.e. Temerin Li] model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90 percent) than the forecasts based on the TL model (87 percent). However, the latter produces better forecasts for 24 nonstorm events (88 percent), while the former correctly forecasts only 71 percent of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80 percent) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (n, i.e. cap operator - the intersection set that is comprised of all the elements that are common to both), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81 percent) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (?, i.e. cup operator - the union set that is comprised of all the elements of either or both

GDP-to-GTP exchange on the microtubule end can contribute to the frequency of catastrophe.

Science.gov (United States)

Piedra, Felipe-Andrés; Kim, Tae; Garza, Emily S; Geyer, Elisabeth A; Burns, Alexander; Ye, Xuecheng; Rice, Luke M

2016-11-07

Microtubules are dynamic polymers of αβ-tubulin that have essential roles in chromosome segregation and organization of the cytoplasm. Catastrophe-the switch from growing to shrinking-occurs when a microtubule loses its stabilizing GTP cap. Recent evidence indicates that the nucleotide on the microtubule end controls how tightly an incoming subunit will be bound (trans-acting GTP), but most current models do not incorporate this information. We implemented trans-acting GTP into a computational model for microtubule dynamics. In simulations, growing microtubules often exposed terminal GDP-bound subunits without undergoing catastrophe. Transient GDP exposure on the growing plus end slowed elongation by reducing the number of favorable binding sites on the microtubule end. Slower elongation led to erosion of the GTP cap and an increase in the frequency of catastrophe. Allowing GDP-to-GTP exchange on terminal subunits in simulations mitigated these effects. Using mutant αβ-tubulin or modified GTP, we showed experimentally that a more readily exchangeable nucleotide led to less frequent catastrophe. Current models for microtubule dynamics do not account for GDP-to-GTP exchange on the growing microtubule end, so our findings provide a new way of thinking about the molecular events that initiate catastrophe. © 2016 Piedra et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Catastrophic loss risks: An economic and legal analysis, and a model state statute

International Nuclear Information System (INIS)

Meyer, M.B.

1984-01-01

Catastrophic loss risk producing facilities or activities are defined as those human enterprises which are theoretically capable of producing some credible event which entails extremely large losses of human life, health, or property. Two examples of catastrophic loss risk producing facilities are examined, commercial nuclear power plants and LNG terminals. These two types of facilities appear to produce a type of externality in that they impose uncompensated loss risk costs on neighbors. Further, these two types of facilities may be quite dependent upon the subsidies implicit in these externalities for their continued economic operation. A model state statute is proposed which would use insurance premiums as an unbiased source of probability and outcome estimates in order to eliminate this externality and the resulting subsidy, and as a way of improving the present situation within certain economic limits

Development and testing of improved statistical wind power forecasting methods.

Energy Technology Data Exchange (ETDEWEB)

Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-12-06

(with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

Assessment of the regional economic impacts of catastrophic events: CGE analysis of resource loss and behavioral effects of an RDD attack scenario.

Science.gov (United States)

Giesecke, J A; Burns, W J; Barrett, A; Bayrak, E; Rose, A; Slovic, P; Suher, M

2012-04-01

We investigate the regional economic consequences of a hypothetical catastrophic event-attack via radiological dispersal device (RDD)-centered on the downtown Los Angeles area. We distinguish two routes via which such an event might affect regional economic activity: (i) reduction in effective resource supply (the resource loss effect) and (ii) shifts in the perceptions of economic agents (the behavioral effect). The resource loss effect relates to the physical destructiveness of the event, while the behavioral effect relates to changes in fear and risk perception. Both affect the size of the regional economy. RDD detonation causes little capital damage and few casualties, but generates substantial short-run resource loss via business interruption. Changes in fear and risk perception increase the supply cost of resources to the affected region, while simultaneously reducing demand for goods produced in the region. We use results from a nationwide survey, tailored to our RDD scenario, to inform our model values for behavioral effects. Survey results, supplemented by findings from previous research on stigmatized asset values, suggest that in the region affected by the RDD, households may require higher wages, investors may require higher returns, and customers may require price discounts. We show that because behavioral effects may have lingering long-term deleterious impacts on both the supply-cost of resources to a region and willingness to pay for regional output, they can generate changes in regional gross domestic product (GDP) much greater than those generated by resource loss effects. Implications for policies that have the potential to mitigate these effects are discussed. © 2011 Society for Risk Analysis.

Catastrophic shifts in vegetation-soil systems may unfold rapidly or slowly independent of the rate of change in the system driver

Science.gov (United States)

Karssenberg, Derek; Bierkens, Marc

2014-05-01

Complex systems may switch between contrasting stable states under gradual change of a driver. Such critical transitions often result in considerable long-term damage because strong hysteresis impedes reversion, and the transition becomes catastrophic. Critical transitions largely reduce our capability of forecasting future system states because it is hard to predict the timing of their occurrence [2]. Moreover, for many systems it is unknown how rapidly the critical transition unfolds when the tipping point has been reached. The rate of change during collapse, however, is important information because it determines the time available to take action to reverse a shift [1]. In this study we explore the rate of change during the degradation of a vegetation-soil system on a hillslope from a state with considerable vegetation cover and large soil depths, to a state with sparse vegetation and a bare rock or negligible soil depths. Using a distributed, stochastic model coupling hydrology, vegetation, weathering and water erosion, we derive two differential equations describing the vegetation and the soil system, and their interaction. Two stable states - vegetated and bare - are identified by means of analytical investigation, and it is shown that the change between these two states is a critical transition as indicated by hysteresis. Surprisingly, when the tipping point is reached under a very slow increase of grazing pressure, the transition between the vegetated and the bare state can either unfold rapidly, over a few years, or gradually, occurring over decennia up to millennia. These differences in the rate of change during the transient state are explained by differences in bedrock weathering rates. This finding emphasizes the considerable uncertainty associated with forecasting catastrophic shifts in ecosystems, which is due to both difficulties in forecasting the timing of the tipping point and the rate of change when the transition unfolds. References [1] Hughes

Assessment of storm forecast

DEFF Research Database (Denmark)

Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

Use and Communication of Probabilistic Forecasts.

Science.gov (United States)

Raftery, Adrian E

2016-12-01

Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? I review experience with five problems where probabilistic forecasting played an important role. This leads me to identify five types of potential users: Low Stakes Users, who don't need probabilistic forecasts; General Assessors, who need an overall idea of the uncertainty in the forecast; Change Assessors, who need to know if a change is out of line with expectatations; Risk Avoiders, who wish to limit the risk of an adverse outcome; and Decision Theorists, who quantify their loss function and perform the decision-theoretic calculations. This suggests that it is important to interact with users and to consider their goals. The cognitive research tells us that calibration is important for trust in probability forecasts, and that it is important to match the verbal expression with the task. The cognitive load should be minimized, reducing the probabilistic forecast to a single percentile if appropriate. Probabilities of adverse events and percentiles of the predictive distribution of quantities of interest seem often to be the best way to summarize probabilistic forecasts. Formal decision theory has an important role, but in a limited range of applications.

Use and Communication of Probabilistic Forecasts

Science.gov (United States)

Raftery, Adrian E.

2015-01-01

Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? I review experience with five problems where probabilistic forecasting played an important role. This leads me to identify five types of potential users: Low Stakes Users, who don’t need probabilistic forecasts; General Assessors, who need an overall idea of the uncertainty in the forecast; Change Assessors, who need to know if a change is out of line with expectatations; Risk Avoiders, who wish to limit the risk of an adverse outcome; and Decision Theorists, who quantify their loss function and perform the decision-theoretic calculations. This suggests that it is important to interact with users and to consider their goals. The cognitive research tells us that calibration is important for trust in probability forecasts, and that it is important to match the verbal expression with the task. The cognitive load should be minimized, reducing the probabilistic forecast to a single percentile if appropriate. Probabilities of adverse events and percentiles of the predictive distribution of quantities of interest seem often to be the best way to summarize probabilistic forecasts. Formal decision theory has an important role, but in a limited range of applications. PMID:28446941

Multicomponent ensemble models to forecast induced seismicity

Science.gov (United States)

Király-Proag, E.; Gischig, V.; Zechar, J. D.; Wiemer, S.

2018-01-01

In recent years, human-induced seismicity has become a more and more relevant topic due to its economic and social implications. Several models and approaches have been developed to explain underlying physical processes or forecast induced seismicity. They range from simple statistical models to coupled numerical models incorporating complex physics. We advocate the need for forecast testing as currently the best method for ascertaining if models are capable to reasonably accounting for key physical governing processes—or not. Moreover, operational forecast models are of great interest to help on-site decision-making in projects entailing induced earthquakes. We previously introduced a standardized framework following the guidelines of the Collaboratory for the Study of Earthquake Predictability, the Induced Seismicity Test Bench, to test, validate, and rank induced seismicity models. In this study, we describe how to construct multicomponent ensemble models based on Bayesian weightings that deliver more accurate forecasts than individual models in the case of Basel 2006 and Soultz-sous-Forêts 2004 enhanced geothermal stimulation projects. For this, we examine five calibrated variants of two significantly different model groups: (1) Shapiro and Smoothed Seismicity based on the seismogenic index, simple modified Omori-law-type seismicity decay, and temporally weighted smoothed seismicity; (2) Hydraulics and Seismicity based on numerically modelled pore pressure evolution that triggers seismicity using the Mohr-Coulomb failure criterion. We also demonstrate how the individual and ensemble models would perform as part of an operational Adaptive Traffic Light System. Investigating seismicity forecasts based on a range of potential injection scenarios, we use forecast periods of different durations to compute the occurrence probabilities of seismic events M ≥ 3. We show that in the case of the Basel 2006 geothermal stimulation the models forecast hazardous levels

Real time flood forecasting in the Upper Danube basin

Directory of Open Access Journals (Sweden)

Nester Thomas

2016-12-01

Full Text Available This paper reports on experience with developing the flood forecasting model for the Upper Danube basin and its operational use since 2006. The model system consists of hydrological and hydrodynamic components, and involves precipitation forecasts. The model parameters were estimated based on the dominant processes concept. Runoff data are assimilated in real time to update modelled soil moisture. An analysis of the model performance indicates 88% of the snow cover in the basin to be modelled correctly on more than 80% of the days. Runoff forecasting errors decrease with catchment area and increase with forecast lead time. The forecast ensemble spread is shown to be a meaningful indicator of the forecast uncertainty. During the 2013 flood, there was a tendency for the precipitation forecasts to underestimate event precipitation and for the runoff model to overestimate runoff generation which resulted in, overall, rather accurate runoff forecasts. It is suggested that the human forecaster plays an essential role in interpreting the model results and, if needed, adjusting them before issuing the forecasts to the general public.

Case studies of extended model-based flood forecasting: prediction of dike strength and flood impacts

Science.gov (United States)

Stuparu, Dana; Bachmann, Daniel; Bogaard, Tom; Twigt, Daniel; Verkade, Jan; de Bruijn, Karin; de Leeuw, Annemargreet

2017-04-01

Flood forecasts, warning and emergency response are important components in flood risk management. Most flood forecasting systems use models to translate weather predictions to forecasted discharges or water levels. However, this information is often not sufficient for real time decisions. A sound understanding of the reliability of embankments and flood dynamics is needed to react timely and reduce the negative effects of the flood. Where are the weak points in the dike system? When, how much and where the water will flow? When and where is the greatest impact expected? Model-based flood impact forecasting tries to answer these questions by adding new dimensions to the existing forecasting systems by providing forecasted information about: (a) the dike strength during the event (reliability), (b) the flood extent in case of an overflow or a dike failure (flood spread) and (c) the assets at risk (impacts). This work presents three study-cases in which such a set-up is applied. Special features are highlighted. Forecasting of dike strength. The first study-case focusses on the forecast of dike strength in the Netherlands for the river Rhine branches Waal, Nederrijn and IJssel. A so-called reliability transformation is used to translate the predicted water levels at selected dike sections into failure probabilities during a flood event. The reliability of a dike section is defined by fragility curves - a summary of the dike strength conditional to the water level. The reliability information enhances the emergency management and inspections of embankments. Ensemble forecasting. The second study-case shows the setup of a flood impact forecasting system in Dumfries, Scotland. The existing forecasting system is extended with a 2D flood spreading model in combination with the Delft-FIAT impact model. Ensemble forecasts are used to make use of the uncertainty in the precipitation forecasts, which is useful to quantify the certainty of a forecasted flood event. From global

From a Catastrophe Itself to Cata/strophic Reading. The Poetry of Charles Baudelaire in the Account of Jorge Semprúna L’écriture ou la vie

Directory of Open Access Journals (Sweden)

Judith Kasper

2015-01-01

Full Text Available This essay addresses the instable meaning of the term catastrophe over the course of history. The first part takes leave of the “the tiny fissures” in the continuous catastrophe noted by Walter Benjamin to develop a philology of the cata/strophe. This philology does not only register a given meaning (for instance, of the catastrophe, but intervenes actively as disruption. It insists on the strophe in the catastrophe, transforming catastrophe into cata/strophe that, in fatal situations, permits the poetic potential to become a dynamic force that can, at least on the linguistic level, open toward other dimensions without denying the catastrophe itself. The second part is dedicated to a reading of Jorge Semprún’s autobiographical novel L’écriture ou la vie from the perspective of this philological concept. It seeks to show how Semprún’s citing and reciting of Baudelaire’s strophes in the putrid atmosphere of the Buchenwald concentration camp literally produce, on the level of the signifiers, fresh air to breathe.

Geochemical and sedimentological signature of catastrophic saltwater inundations (tsunami), New Zealand

International Nuclear Information System (INIS)

Chague-Goff, C.; Goff, J.R.

1999-01-01

Three tidal marshes in Able Tasman National Par, New Zealand, were studied using geochemical, sedimentological and radiometric dating techniques. Charcoal and plant material samples were taken from one core in each inlet for 14 C analysis. radiocarbon ages were converted to dendrocalibrated years . All samples produced a terrestrial 13 C signal. Near surface samples were date d by measuring 137 Cs. A 1700 year record of catastrophic saltwater inundations (CSI) events (Tsunami) was produced. Up to four such events were identified, with ruptures of one or more of the Wellington, Wairarapa and Alpine Faults being the most likely tsunamigenic source. CSI signatures include: peaks in Fe and/or S, a peak in fines and contemporaneous or delayed peaks in organic content and/or loss on ignition (LOI). Geochemical data in association with grain size analyses proved to be a valuable tool in the interpretation of these events

Seasonal Drought Forecasting for Latin America Using the ECMWF S4 Forecast System

Directory of Open Access Journals (Sweden)

Hugo Carrão

2018-06-01

Full Text Available Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there are still not many studies of the feasibility of such a forecasts at continental level in the region. In this study, precipitation predictions from the European Centre for Medium Range Weather (ECMWF seasonal forecast system S4 are combined with observed precipitation data to generate forecasts of the standardized precipitation index (SPI for Latin America, and their skill is evaluated over the hindcast period 1981–2010. The value-added utility in using the ensemble S4 forecast to predict the SPI is identified by comparing the skill of its forecasts with a baseline skill based solely on their climatological characteristics. As expected, skill of the S4-generated SPI forecasts depends on the season, location, and the specific aggregation period considered (the 3- and 6-month SPI were evaluated. Added skill from the S4 for lead times equaling the SPI accumulation periods is primarily present in regions with high intra-annual precipitation variability, and is found mostly for the months at the end of the dry seasons for 3-month SPI, and half-yearly periods for 6-month SPI. The ECMWF forecast system behaves better than the climatology for clustered grid points in the North of South America, the Northeast of Argentina, Uruguay, southern Brazil and Mexico. The skillful regions are similar for the SPI3 and -6, but become reduced in extent for the severest SPI categories. Forecasting different magnitudes of meteorological drought intensity on a seasonal time scale still remains a challenge. However, the ECMWF S4 forecasting system does capture the occurrence of drought events for the aforementioned regions and seasons reasonably well. In the near term, the largest advances in the prediction of meteorological drought for Latin

An experimental system for flood risk forecasting at global scale

Science.gov (United States)

Alfieri, L.; Dottori, F.; Kalas, M.; Lorini, V.; Bianchi, A.; Hirpa, F. A.; Feyen, L.; Salamon, P.

2016-12-01

Global flood forecasting and monitoring systems are nowadays a reality and are being applied by an increasing range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasts, combining streamflow estimations with expected inundated areas and flood impacts. To this end, we have developed an experimental procedure for near-real time flood mapping and impact assessment based on the daily forecasts issued by the Global Flood Awareness System (GloFAS). The methodology translates GloFAS streamflow forecasts into event-based flood hazard maps based on the predicted flow magnitude and the forecast lead time and a database of flood hazard maps with global coverage. Flood hazard maps are then combined with exposure and vulnerability information to derive flood risk. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To further increase the reliability of the proposed methodology we integrated model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification of impact forecasts. The preliminary tests provided good results and showed the potential of the developed real-time operational procedure in helping emergency response and management. In particular, the link with social media is crucial for improving the accuracy of impact predictions.

Forecasting the Occurrence of Severe Haze Events in Asia using Machine Learning Algorithms

Science.gov (United States)

Wang, C.

2017-12-01

Particulate pollution has become a serious environmental issue of many Asian countries in recent decades, threatening human health and frequently causing low visibility or haze days that interrupt from working, outdoor, and school activities to air, road, and sea transportation. To ultimately prevent such severe haze to occur requires many difficult tasks to be accomplished, dealing with trade and negotiation, emission control, energy consumption, transportation, land and plantation management, among other, of all involved countries or parties. Whereas, before these difficult measures could finally take place, it would be more practical to reduce the economic loss by developing skills to predict the occurrence of such events in reasonable accuracy so that effective mitigation or adaptation measures could be implemented ahead of time. The "traditional" numerical models developed based on fluid dynamics and explicit or parameterized representations of physiochemical processes can be certainly used for this task. However, the significant and sophisticated spatiotemporal variabilities associated with these events, the propagation of numerical or parameterization errors through model integration, and the computational demand all pose serious challenges to the practice of using these models to accomplish this interdisciplinary task. On the other hand, large quantity of meteorological, hydrological, atmospheric aerosol and composition, and surface visibility data from in-situ observation, reanalysis, or satellite retrievals, have become available to the community. These data might still not sufficient for evaluating and improving certain important aspects of the "traditional" models. Nevertheless, it is likely that these data can already support the effort to develop alternative "task-oriented" and computationally efficient forecasting skill using deep machine learning technique to avoid directly dealing with the sophisticated interplays across multiple process layers. I

Short-range quantitative precipitation forecasting using Deep Learning approaches

Science.gov (United States)

Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Predicting short-range quantitative precipitation is very important for flood forecasting, early flood warning and other hydrometeorological purposes. This study aims to improve the precipitation forecasting skills using a recently developed and advanced machine learning technique named Long Short-Term Memory (LSTM). The proposed LSTM learns the changing patterns of clouds from Cloud-Top Brightness Temperature (CTBT) images, retrieved from the infrared channel of Geostationary Operational Environmental Satellite (GOES), using a sophisticated and effective learning method. After learning the dynamics of clouds, the LSTM model predicts the upcoming rainy CTBT events. The proposed model is then merged with a precipitation estimation algorithm termed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to provide precipitation forecasts. The results of merged LSTM with PERSIANN are compared to the results of an Elman-type Recurrent Neural Network (RNN) merged with PERSIANN and Final Analysis of Global Forecast System model over the states of Oklahoma, Florida and Oregon. The performance of each model is investigated during 3 storm events each located over one of the study regions. The results indicate the outperformance of merged LSTM forecasts comparing to the numerical and statistical baselines in terms of Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), RMSE and correlation coefficient especially in convective systems. The proposed method shows superior capabilities in short-term forecasting over compared methods.

Catastrophic primary antiphospholipid syndrome

International Nuclear Information System (INIS)

Kim, Dong Hun; Byun, Joo Nam; Ryu, Sang Wan

2006-01-01

Catastrophic antiphospholipid syndrome (CAPLS) was diagnosed in a 64-year-old male who was admitted to our hospital with dyspnea. The clinical and radiological examinations showed pulmonary thromboembolism, and so thromboembolectomy was performed. Abdominal distension rapidly developed several days later, and the abdominal computed tomography (CT) abdominal scan revealed thrombus within the superior mesenteric artery with small bowel and gall bladder distension. Cholecystectomy and jejunoileostomy were performed, and gall bladder necrosis and small bowel infarction were confirmed. The anticardiolipin antibody was positive. Anticoagulant agents and steroids were administered, but the patient expired 4 weeks after surgery due to acute respiratory distress syndrome (ARDS). We report here on a case of catastrophic APLS with manifestations of pulmonary thromboembolism, rapidly progressing GB necrosis and bowel infarction

Catastrophic primary antiphospholipid syndrome

Energy Technology Data Exchange (ETDEWEB)

Kim, Dong Hun; Byun, Joo Nam [Chosun University Hospital, Gwangju (Korea, Republic of); Ryu, Sang Wan [Miraero21 Medical Center, Gwangju (Korea, Republic of)

2006-09-15

Catastrophic antiphospholipid syndrome (CAPLS) was diagnosed in a 64-year-old male who was admitted to our hospital with dyspnea. The clinical and radiological examinations showed pulmonary thromboembolism, and so thromboembolectomy was performed. Abdominal distension rapidly developed several days later, and the abdominal computed tomography (CT) abdominal scan revealed thrombus within the superior mesenteric artery with small bowel and gall bladder distension. Cholecystectomy and jejunoileostomy were performed, and gall bladder necrosis and small bowel infarction were confirmed. The anticardiolipin antibody was positive. Anticoagulant agents and steroids were administered, but the patient expired 4 weeks after surgery due to acute respiratory distress syndrome (ARDS). We report here on a case of catastrophic APLS with manifestations of pulmonary thromboembolism, rapidly progressing GB necrosis and bowel infarction.

A laboratory analogue of the event horizon using slow light in an atomic medium.

Science.gov (United States)

Leonhardt, Ulf

2002-01-24

Singularities underlie many optical phenomena. The rainbow, for example, involves a particular type of singularity-a ray catastrophe-in which light rays become infinitely intense. In practice, the wave nature of light resolves these infinities, producing interference patterns. At the event horizon of a black hole, time stands still and waves oscillate with infinitely small wavelengths. However, the quantum nature of light results in evasion of the catastrophe and the emission of Hawking radiation. Here I report a theoretical laboratory analogue of an event horizon: a parabolic profile of the group velocity of light brought to a standstill in an atomic medium can cause a wave singularity similar to that associated with black holes. In turn, the quantum vacuum is forced to create photon pairs with a characteristic spectrum, a phenomenon related to Hawking radiation. The idea may initiate a theory of 'quantum' catastrophes, extending classical catastrophe theory.

Modeling, Forecasting and Mitigating Extreme Earthquakes

Science.gov (United States)

Ismail-Zadeh, A.; Le Mouel, J.; Soloviev, A.

2012-12-01

Recent earthquake disasters highlighted the importance of multi- and trans-disciplinary studies of earthquake risk. A major component of earthquake disaster risk analysis is hazards research, which should cover not only a traditional assessment of ground shaking, but also studies of geodetic, paleoseismic, geomagnetic, hydrological, deep drilling and other geophysical and geological observations together with comprehensive modeling of earthquakes and forecasting extreme events. Extreme earthquakes (large magnitude and rare events) are manifestations of complex behavior of the lithosphere structured as a hierarchical system of blocks of different sizes. Understanding of physics and dynamics of the extreme events comes from observations, measurements and modeling. A quantitative approach to simulate earthquakes in models of fault dynamics will be presented. The models reproduce basic features of the observed seismicity (e.g., the frequency-magnitude relationship, clustering of earthquakes, occurrence of extreme seismic events). They provide a link between geodynamic processes and seismicity, allow studying extreme events, influence of fault network properties on seismic patterns and seismic cycles, and assist, in a broader sense, in earthquake forecast modeling. Some aspects of predictability of large earthquakes (how well can large earthquakes be predicted today?) will be also discussed along with possibilities in mitigation of earthquake disasters (e.g., on 'inverse' forensic investigations of earthquake disasters).

High-resolution, multi-proxy characterization of the event deposit generated by the catastrophic events associated with the Mw 6.2 earthquake of 21 April 2007 in Aysén fjord (Chile)

Science.gov (United States)

De Batist, M. A.; Van Daele, M. E.; Cnudde, V.; Duyck, P.; Tjallingii, R. H.; Pino, M.; Urrutia, R.

2012-12-01

In 2007, a seismic swarm with more than 7000 recorded earthquakes affected the region around Aysén fjord, Chile (45°25'S). The series of seismic events reached a maximum on 21 April 2007, with an Mw 6.2 earthquake. Intensities as high as VIII to IX on the Modified Mercalli scale were reported around the epicenter. Multiple debris flows, rock slides and rock avalanches were triggered along the fjord's coastline, and several of these caused impact waves or tsunamis with wave heights of up to 6 m, which inundated the fjord shorelines and caused heavy damage and 10 casualties. In order to characterize in detail the imprint left by this series of catastrophic events in the sedimentary record of the fjord, we conducted a multi-disciplinary survey of the inner fjord region in December 2009. Multibeam bathymetry and high-resolution reflection seismic data reveal that large parts of the fjord basin floor, mostly at the foot of the fjord's steep underwater slopes, are covered by recent mass-wasting deposits or consist of mass-wasting-induced deformed basin-plain sediments. A series of short sediment cores collected throughout the inner fjord contain also the more distal deposits of this significant basin-wide mass-wasting event. By combining classical sedimentological techniques (i.e. grain-size analysis, LOI and magnetic susceptibility measurements, all at high resolution) with X-ray CT scanning and XRF scanning we were able to demonstrate that the event deposits encountered in the cores have a very complex signature and actually consist of a succession of several sub-deposits, comprising distal mass-flow deposits from different source areas (as evidenced by XRF-derived geochemical provenance indications) and with a different flow direction (as evidenced by CT-derived 3D flow-direction indications, such as imbricated rip-up mud clasts, cross and convolute laminations) and tsunami- or seiche-generated deposits. This allowed us to reconstruct the succession of sedimentary

Vaginismus: heightened harm avoidance and pain catastrophizing cognitions.

Science.gov (United States)

Borg, Charmaine; Peters, Madelon L; Schultz, Willibrord Weijmar; de Jong, Peter J

2012-02-01

Catastrophic appraisal of experienced pain may promote hypervigilance and intense pain, while the personality trait of harm avoidance (HA) might prevent the occurrence of correcting such experiences. Women inflicted with vaginismus may enter a self-perpetuating downward spiral of increasing avoidance of (anticipated) pain. In vaginismus the anticipation of pain may give rise to catastrophic pain ideation. This may establish hypervigilance toward painful sexual stimuli, which consequently results in negative appraisal of sexual cues. This process could impair genital and sexual responding, intensify pain and trigger avoidance, which in turn may contribute to the onset and persistence of symptoms in vaginismus and to certain extent also in dyspareunia. To investigate whether women suffering from vaginismus are characterized by heightened levels of habitual pain catastrophic cognitions, together with higher levels of HA. This study consisted of three groups: a lifelong vaginismus group (N = 35, mean age = 28.4; standard deviation [SD] = 5.8), a dyspareunia group (N = 33, mean age = 26.7; SD = 6.8), and women without sexual complaints (N = 54, mean age = 26.5; SD = 6.7). HA scale of Cloninger's tridimensional personality questionnaire, and the pain catastrophizing scale. Specifically women inflicted with vaginismus showed significantly heightened levels of catastrophic pain cognitions compared with the other two groups, as well as significant enhanced HA vs. the control group, and a trend vs. the dyspareunia group. Both traits were shown to have cumulative predictive validity for the presence of vaginismus. This study focused on the personality traits of catastrophizing pain cognitions and HA in women with lifelong vaginismus. Our findings showed that indeed, women suffering from vaginismus are characterized by trait of HA interwoven with habitual pain catastrophizing cognitions. This study could help in the refinement of the current conceptualization and might shed

Socioeconomic inequality in catastrophic health expenditure in Brazil.

Science.gov (United States)

Boing, Alexandra Crispim; Bertoldi, Andréa Dâmaso; Barros, Aluísio Jardim Dornellas de; Posenato, Leila Garcia; Peres, Karen Glazer

2014-08-01

To analyze the evolution of catastrophic health expenditure and the inequalities in such expenses, according to the socioeconomic characteristics of Brazilian families. Data from the National Household Budget 2002-2003 (48,470 households) and 2008-2009 (55,970 households) were analyzed. Catastrophic health expenditure was defined as excess expenditure, considering different methods of calculation: 10.0% and 20.0% of total consumption and 40.0% of the family's capacity to pay. The National Economic Indicator and schooling were considered as socioeconomic characteristics. Inequality measures utilized were the relative difference between rates, the rates ratio, and concentration index. The catastrophic health expenditure varied between 0.7% and 21.0%, depending on the calculation method. The lowest prevalences were noted in relation to the capacity to pay, while the highest, in relation to total consumption. The prevalence of catastrophic health expenditure increased by 25.0% from 2002-2003 to 2008-2009 when the cutoff point of 20.0% relating to the total consumption was considered and by 100% when 40.0% or more of the capacity to pay was applied as the cut-off point. Socioeconomic inequalities in the catastrophic health expenditure in Brazil between 2002-2003 and 2008-2009 increased significantly, becoming 5.20 times higher among the poorest and 4.17 times higher among the least educated. There was an increase in catastrophic health expenditure among Brazilian families, principally among the poorest and those headed by the least-educated individuals, contributing to an increase in social inequality.

Understanding catastrophizing from a misdirected problem-solving perspective.

Science.gov (United States)

Flink, Ida K; Boersma, Katja; MacDonald, Shane; Linton, Steven J

2012-05-01

The aim is to explore pain catastrophizing from a problem-solving perspective. The links between catastrophizing, problem framing, and problem-solving behaviour are examined through two possible models of mediation as inferred by two contemporary and complementary theoretical models, the misdirected problem solving model (Eccleston & Crombez, 2007) and the fear-anxiety-avoidance model (Asmundson, Norton, & Vlaeyen, 2004). In this prospective study, a general population sample (n= 173) with perceived problems with spinal pain filled out questionnaires twice; catastrophizing and problem framing were assessed on the first occasion and health care seeking (as a proxy for medically oriented problem solving) was assessed 7 months later. Two different approaches were used to explore whether the data supported any of the proposed models of mediation. First, multiple regressions were used according to traditional recommendations for mediation analyses. Second, a bootstrapping method (n= 1000 bootstrap resamples) was used to explore the significance of the indirect effects in both possible models of mediation. The results verified the concepts included in the misdirected problem solving model. However, the direction of the relations was more in line with the fear-anxiety-avoidance model. More specifically, the mediation analyses provided support for viewing catastrophizing as a mediator of the relation between biomedical problem framing and medically oriented problem-solving behaviour. These findings provide support for viewing catastrophizing from a problem-solving perspective and imply a need to examine and address problem framing and catastrophizing in back pain patients. ©2011 The British Psychological Society.

Forecasting metal prices: Do forecasters herd?

DEFF Research Database (Denmark)

Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

2013-01-01

We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

Nuclear war and other catastrophes. Civil and catastrophe protection in the Federal republic of Germany and the United Kingdom after 1945

International Nuclear Information System (INIS)

Diebel, Martin

2017-01-01

The book civil and catastrophe protection in the Federal republic of Germany and the United Kingdom after 1945 discusses the following issues: aerial defense and the atomic bomb (1945 - 1968), crises and catastrophes in the shadow of the bomb (1962 - 1978), civil defense and the comeback of the (nuclear) war (1976 - 1979), civil defense and the second ''Cold War'' (1979 - 1986), Chernobyl and the end of the Cold War (1979 - 1990), war, catastrophe and safety in the 20th century - a conclusion.

Risk allocation in a public-private catastrophe insurance system : an actuarial analysis of deductibles, stop-loss, and premiums

NARCIS (Netherlands)

Paudel, Y.; Botzen, W. J. W.; Aerts, J. C. J. H.; Dijkstra, T. K.

A public-private (PP) partnership could be a viable arrangement for providing insurance coverage for catastrophe events, such as floods and earthquakes. The objective of this paper is to obtain insights into efficient and practical allocations of risk in a PP insurance system. In particular, this

Risk allocation in a public-private catastrophe insurance system : An actuarial analysis of deductibles, stop-loss, and premiums

NARCIS (Netherlands)

Paudel, Y.; Botzen, W.J.W.; Dijkstra, Th.; Aerts, J.C.J.H.

2015-01-01

A public-private (PP) partnership could be a viable arrangement for providing insurance coverage for catastrophe events, such as floods and earthquakes. The objective of this paper is to obtain insights into efficient and practical allocations of risk in a PP insurance system. In particular, this

Six rules for accurate effective forecasting.

Science.gov (United States)

Saffo, Paul

2007-01-01

The primary goal of forecasting is to identify the full range of possibilities facing a company, society, or the world at large. In this article, Saffo demythologizes the forecasting process to help executives become sophisticated and participative consumers of forecasts, rather than passive absorbers. He illustrates how to use forecasts to at once broaden understanding of possibilities and narrow the decision space within which one must exercise intuition. The events of 9/11, for example, were a much bigger surprise than they should have been. After all, airliners flown into monuments were the stuff of Tom Clancy novels in the 1990s, and everyone knew that terrorists had a very personal antipathy toward the World Trade Center. So why was 9/11 such a surprise? What can executives do to avoid being blind-sided by other such wild cards, be they radical shifts in markets or the seemingly sudden emergence of disruptive technologies? In describing what forecasters are trying to achieve, Saffo outlines six simple, commonsense rules that smart managers should observe as they embark on a voyage of discovery with professional forecasters. Map a cone of uncertainty, he advises, look for the S curve, embrace the things that don't fit, hold strong opinions weakly, look back twice as far as you look forward, and know when not to make a forecast.

Web-Based Real Time Earthquake Forecasting and Personal Risk Management

Science.gov (United States)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

2012-12-01

Earthquake forecasts have been computed by a variety of countries and economies world-wide for over two decades. For the most part, forecasts have been computed for insurance, reinsurance and underwriters of catastrophe bonds. One example is the Working Group on California Earthquake Probabilities that has been responsible for the official California earthquake forecast since 1988. However, in a time of increasingly severe global financial constraints, we are now moving inexorably towards personal risk management, wherein mitigating risk is becoming the responsibility of individual members of the public. Under these circumstances, open access to a variety of web-based tools, utilities and information is a necessity. Here we describe a web-based system that has been operational since 2009 at www.openhazards.com and www.quakesim.org. Models for earthquake physics and forecasting require input data, along with model parameters. The models we consider are the Natural Time Weibull (NTW) model for regional earthquake forecasting, together with models for activation and quiescence. These models use small earthquakes ('seismicity-based models") to forecast the occurrence of large earthquakes, either through varying rates of small earthquake activity, or via an accumulation of this activity over time. These approaches use data-mining algorithms combined with the ANSS earthquake catalog. The basic idea is to compute large earthquake probabilities using the number of small earthquakes that have occurred in a region since the last large earthquake. Each of these approaches has computational challenges associated with computing forecast information in real time. Using 25 years of data from the ANSS California-Nevada catalog of earthquakes, we show that real-time forecasting is possible at a grid scale of 0.1o. We have analyzed the performance of these models using Reliability/Attributes and standard Receiver Operating Characteristic (ROC) tests. We show how the Reliability and

A survey on wind power ramp forecasting.

Energy Technology Data Exchange (ETDEWEB)

Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-02-23

The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

Ticket consumption forecast for Brazilian championship games

Directory of Open Access Journals (Sweden)

Adriana Bruscato Bortoluzzo

Full Text Available Abstract For the efficiency of sales and marketing management of athletic clubs, it is crucial to find a way to appropriately estimate the level of demand for sporting events. More precise estimates allow for an appropriate financial and operational plan and a higher quality of service delivered to the fans. The focus of this study is to analyze and forecast the ticket consumption for soccer games in Brazilian stadiums. We compare the results of the regression model with normally distributed errors (benchmark, the TOBIT model and the Gamma generalized linear model. The models include explanatory variables related to the economic environment, product quality, as well as monetary and non-monetary incentives that people are given to attend sporting events at stadiums. We show that most of these variables are statistically significant to explain the amount of fans that go to stadiums. We used different measures of accuracy to evaluate the performance of demand forecasts and concluded that Gamma generalized linear model presented better results to forecast the ticket consumption for Brazilian championship games, when compared to a benchmark.

Clinical Pain Catastrophizing in Women With Migraine and Obesity.

Science.gov (United States)

Bond, Dale S; Buse, Dawn C; Lipton, Richard B; Thomas, J Graham; Rathier, Lucille; Roth, Julie; Pavlovic, Jelena M; Evans, E Whitney; Wing, Rena R

2015-01-01

Obesity is related to migraine. Maladaptive pain coping strategies (eg, pain catastrophizing) may provide insight into this relationship. In women with migraine and obesity, we cross-sectionally assessed: (1) prevalence of clinical catastrophizing; (2) characteristics of those with and without clinical catastrophizing; and (3) associations of catastrophizing with headache features. Obese women migraineurs seeking weight loss treatment (n = 105) recorded daily migraine activity for 1 month via smartphone and completed the Pain Catastrophizing Scale (PCS). Clinical catastrophizing was defined as total PCS score ≥30. The six-item Headache Impact Test (HIT-6), 12-item Allodynia Symptom Checklist (ASC-12), Headache Management Self-Efficacy Scale (HMSE), and assessments for depression (Centers for Epidemiologic Studies Depression Scale) and anxiety (seven-item Generalized Anxiety Disorder Scale) were also administered. Using PCS scores and body mass index (BMI) as predictors in linear regression, we modeled a series of headache features (ie, headache days, HIT-6, etc) as outcomes. One quarter (25.7%; 95% confidence interval [CI] = 17.2-34.1%) of participants met criteria for clinical catastrophizing: they had higher BMI (37.9 ± 7.5 vs 34.4 ± 5.7 kg/m(2) , P = .035); longer migraine attack duration (160.8 ± 145.0 vs 97.5 ± 75.2 hours/month, P = .038); higher HIT-6 scores (68.7 ± 4.6 vs 64.5 ± 3.9, P duration (β = 0.390, P duration, higher pain sensitivity, greater headache impact, and lower headache management self-efficacy. In all participants, PCS scores were related to several migraine characteristics, above and beyond the effects of obesity. Prospective studies are needed to determine sequence and mechanisms of relationships between catastrophizing, obesity, and migraine. © 2015 American Headache Society.

Comparison of landslide forecasting services in Piedmont (Italy) and Norway, illustrated by events in late spring 2013

Science.gov (United States)

Devoli, Graziella; Tiranti, Davide; Cremonini, Roberto; Sund, Monica; Boje, Søren

2018-05-01

across the mountain regions. These secondary effects were effectively forecasted by the two landslide warning services, operating in different parts of Europe. The landslide risks were also properly communicated to the public some days in advance. This analysis has allowed the establishment of fruitful international collaboration between ARPA Piemonte and NVE and the future exchange of experiences, procedures and methods relating to similar events.

Heckling the Catastrophe. On the Holocaust Literary Criticism

Directory of Open Access Journals (Sweden)

Paweł Wolski

2015-01-01

Full Text Available The article discusses a special kind of narrative about the catastrophe, treated as a specific genre of writing: the theory of literature of the Holocaust. The article presents its two most significant (although not the only ones features: firstly, the conviction about its unusual character as compared to other genres/forms of writing, sometimes secretly described by such concepts as the uniqueness of the Holocaust (which metonymizes not only the event itself but also the narrations referring to it and, secondly, identifies all text-producing entities (narrator, author etc., simultaneously constituting the basic feature of the most important genre/modality of this kind of writing which is testimony. The article presents the examples of Polish and foreign scholars portraying this state of affairs.

Catastrophe Theory and Caustics

DEFF Research Database (Denmark)

Gravesen, Jens

1983-01-01

It is shown by elementary methods that in codimension two and under the assumption that light rays are straight lines, a caustic is the catastrophe set for a time function. The general case is also discussed....

Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

Science.gov (United States)

White, C. J.; Franks, S. W.; McEvoy, D.

2015-06-01

Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

The catastrophic antiphospholipid syndrome in children.

Science.gov (United States)

Go, Ellen J L; O'Neil, Kathleen M

2017-09-01

To review the difficult syndrome of catastrophic antiphospholipid syndrome, emphasizing new developments in the diagnosis, pathogenesis and treatment. Few recent publications directly address pediatric catastrophic antiphospholipid syndrome (CAPS). Most articles are case reports or are data from adult and pediatric registries. The major factors contributing to most pediatric catastrophic antiphospholipid syndrome include infection and the presence of antiphospholipid antibodies, but complement activation also is important in creating diffuse thrombosis in the microcirculation. Treatment of the acute emergency requires anticoagulation, suppression of the hyperinflammatory state and elimination of the triggering infection. Inhibition of complement activation appears to improve outcome in limited studies, and suppression of antiphospholipid antibody formation may be important in long-term management. CAPS, an antibody-mediated diffuse thrombotic disease of microvasculature, is rare in childhood but has high mortality (33-50%). It requires prompt recognition and aggressive multimodality treatment, including anticoagulation, anti-inflammatory therapy and elimination of inciting infection and pathogenic autoantibodies.

Orthogonality catastrophe and fractional exclusion statistics

Science.gov (United States)

Ares, Filiberto; Gupta, Kumar S.; de Queiroz, Amilcar R.

2018-02-01

We show that the N -particle Sutherland model with inverse-square and harmonic interactions exhibits orthogonality catastrophe. For a fixed value of the harmonic coupling, the overlap of the N -body ground state wave functions with two different values of the inverse-square interaction term goes to zero in the thermodynamic limit. When the two values of the inverse-square coupling differ by an infinitesimal amount, the wave function overlap shows an exponential suppression. This is qualitatively different from the usual power law suppression observed in the Anderson's orthogonality catastrophe. We also obtain an analytic expression for the wave function overlaps for an arbitrary set of couplings, whose properties are analyzed numerically. The quasiparticles constituting the ground state wave functions of the Sutherland model are known to obey fractional exclusion statistics. Our analysis indicates that the orthogonality catastrophe may be valid in systems with more general kinds of statistics than just the fermionic type.

Stochastic Catastrophe Analysis of Strategic Alliances' Coopetition Including Simulations%战略联盟竞合行为的随机突变分析与仿真

Institute of Scientific and Technical Information of China (English)

徐岩; 胡斌

2012-01-01

The evolution process of partners' strategies in strategic alliances with multi-firm was considered by evolutionary game theory perspective. A deterministic dynamical equation is developed, based on which, the Gaussian White noise is introduced to show the disturbance, and a stochastic dynamical equation is created. The catastrophe of strategic alliances that ranges cooperation to betrayal in the process is analyzed by means of stochastic catastrophe theory. The catastrophe set of control variables is found to explain and forecast the catastrophe of strategic alliances. To validate the correctness of the model, some numerical simulations are given in different scenarios, and it is evident from the illustrations that the behavior of the strategic alliances encounters catastrophe near the catastrophe set.%针对多成员战略联盟在不确定环境下策略的演化过程,借助演化博弈论建立了含有白噪声的随机动力学.利用随机突变理论来分析在不确定性条件下,联盟成员行为(竞争或合作)随着参数的连续变化在整体上发生突变的问题,给出了联盟发生突变的临界集,以此来解释和预测在不确定性环境下,战略联盟发生非计划性解体或者合作失败的突发性问题.对不同场景下的模型进行了数值仿真,结果表明,在临界集附近,联盟集体的行为发生了突变.

Valuation of Indonesian catastrophic earthquake bonds with generalized extreme value (GEV) distribution and Cox-Ingersoll-Ross (CIR) interest rate model

Science.gov (United States)

Gunardi, Setiawan, Ezra Putranda

2015-12-01

Indonesia is a country with high risk of earthquake, because of its position in the border of earth's tectonic plate. An earthquake could raise very high amount of damage, loss, and other economic impacts. So, Indonesia needs a mechanism for transferring the risk of earthquake from the government or the (reinsurance) company, as it could collect enough money for implementing the rehabilitation and reconstruction program. One of the mechanisms is by issuing catastrophe bond, `act-of-God bond', or simply CAT bond. A catastrophe bond issued by a special-purpose-vehicle (SPV) company, and then sold to the investor. The revenue from this transaction is joined with the money (premium) from the sponsor company and then invested in other product. If a catastrophe happened before the time-of-maturity, cash flow from the SPV to the investor will discounted or stopped, and the cash flow is paid to the sponsor company to compensate their loss because of this catastrophe event. When we consider the earthquake only, the amount of discounted cash flow could determine based on the earthquake's magnitude. A case study with Indonesian earthquake magnitude data show that the probability of maximum magnitude can model by generalized extreme value (GEV) distribution. In pricing this catastrophe bond, we assumed stochastic interest rate that following the Cox-Ingersoll-Ross (CIR) interest rate model. We develop formulas for pricing three types of catastrophe bond, namely zero coupon bonds, `coupon only at risk' bond, and `principal and coupon at risk' bond. Relationship between price of the catastrophe bond and CIR model's parameter, GEV's parameter, percentage of coupon, and discounted cash flow rule then explained via Monte Carlo simulation.

Paraboles et catastrophes

CERN Document Server

Thom, René

1983-01-01

René Thom, mathématicien français, membre de l'Académie des Sciences, s'est vu décerner en 1958 la médaille Field, équivalent du Prix Nobel en mathématiques, pour ses créations intellectuelles, la " théorie des catastrophes ", regard nouveau sur toutes les transformations qui adviennent de manière brusque, imprévisible, dramatique. Dans ces entretiens qui vont de la mathématique à l'embryologie, de la linguistique à l'anthropologie et à l'histoire, René Thom expose les grandes lignes de la théorie des catastrophes et passe en revue, avec un esprit à la fois critique et passionné, les grands thèmes scientifiques de notre époque, de la physique atomique à la biologie moléculaire, du " progrès " scientifique et technologique aux connexions complexes entre la société et la science. " Ce petit livre est une extraordinaire réussite en vulgarisation ". (Jean Largeault)

Catastrophe, Gender and Urban Experience, 1648–1920

DEFF Research Database (Denmark)

Employing a broad definition of catastrophe, this book examines how urban communities conceived, adapted to and were transformed by catastrophes. Competing views of gender figure in the telling and retelling of these trag- edies, which are mediated by myth and memory. This is a nuanced account...

Comparison of three different methods of perturbing the potential vorticity field in mesoscale forecasts of Mediterranean heavy precipitation events: PV-gradient, PV-adjoint and PV-satellite

Science.gov (United States)

Vich, M.; Romero, R.; Richard, E.; Arbogast, P.; Maynard, K.

2010-09-01

Heavy precipitation events occur regularly in the western Mediterranean region. These events often have a high impact on the society due to economic and personal losses. The improvement of the mesoscale numerical forecasts of these events can be used to prevent or minimize their impact on the society. In previous studies, two ensemble prediction systems (EPSs) based on perturbing the model initial and boundary conditions were developed and tested for a collection of high-impact MEDEX cyclonic episodes. These EPSs perturb the initial and boundary potential vorticity (PV) field through a PV inversion algorithm. This technique ensures modifications of all the meteorological fields without compromising the mass-wind balance. One EPS introduces the perturbations along the zones of the three-dimensional PV structure presenting the local most intense values and gradients of the field (a semi-objective choice, PV-gradient), while the other perturbs the PV field over the MM5 adjoint model calculated sensitivity zones (an objective method, PV-adjoint). The PV perturbations are set from a PV error climatology (PVEC) that characterizes typical PV errors in the ECMWF forecasts, both in intensity and displacement. This intensity and displacement perturbation of the PV field is chosen randomly, while its location is given by the perturbation zones defined in each ensemble generation method. Encouraged by the good results obtained by these two EPSs that perturb the PV field, a new approach based on a manual perturbation of the PV field has been tested and compared with the previous results. This technique uses the satellite water vapor (WV) observations to guide the correction of initial PV structures. The correction of the PV field intents to improve the match between the PV distribution and the WV image, taking advantage of the relation between dark and bright features of WV images and PV anomalies, under some assumptions. Afterwards, the PV inversion algorithm is applied to run

Catastrophizing Interferes with Cognitive Modulation of Pain in Women with Fibromyalgia.

Science.gov (United States)

Ellingson, Laura D; Stegner, Aaron J; Schwabacher, Isaac J; Lindheimer, Jacob B; Cook, Dane B

2018-02-21

Pain modulation is a critical function of the nociceptive system that includes the ability to engage descending pain control systems to maintain a functional balance between facilitation and inhibition of incoming sensory stimuli. Dysfunctional pain modulation is associated with increased risk for chronic pain and is characteristic of fibromyalgia (FM). Catastrophizing is also common in FM. However, its influence on pain modulation is poorly understood. To determine the role of catastrophizing on central nervous system processing during pain modulation in FM via examining brain responses and pain sensitivity during an attention-distraction paradigm. Twenty FM patients and 18 healthy controls (CO) underwent functional magnetic resonance imaging while receiving pain stimuli, administered alone and during distracting cognitive tasks. Pain ratings were assessed after each stimulus. Catastrophizing was assessed with the Pain Catastrophizing Scale (PCS). The ability to modulate pain during distraction varied among FM patients and was associated with catastrophizing. This was demonstrated by significant positive relationships between PCS scores and pain ratings (P modulation did not differ between FM and CO (P > 0.05). FM patients with higher levels of catastrophizing were less able to distract themselves from pain, indicative of catastrophizing-related impairments in pain modulation. These results suggest that the tendency to catastrophize interacts with attention-resource allocation and may represent a mechanism of chronic pain exacerbation and/or maintenance. Reducing catastrophizing may improve FM symptoms via improving central nervous system regulation of pain.

Recent Progress of Solar Weather Forecasting at Naoc

Science.gov (United States)

He, Han; Wang, Huaning; Du, Zhanle; Zhang, Liyun; Huang, Xin; Yan, Yan; Fan, Yuliang; Zhu, Xiaoshuai; Guo, Xiaobo; Dai, Xinghua

The history of solar weather forecasting services at National Astronomical Observatories, Chinese Academy of Sciences (NAOC) can be traced back to 1960s. Nowadays, NAOC is the headquarters of the Regional Warning Center of China (RWC-China), which is one of the members of the International Space Environment Service (ISES). NAOC is responsible for exchanging data, information and space weather forecasts of RWC-China with other RWCs. The solar weather forecasting services at NAOC cover short-term prediction (within two or three days), medium-term prediction (within several weeks), and long-term prediction (in time scale of solar cycle) of solar activities. Most efforts of the short-term prediction research are concentrated on the solar eruptive phenomena, such as flares, coronal mass ejections (CMEs) and solar proton events, which are the key driving sources of strong space weather disturbances. Based on the high quality observation data of the latest space-based and ground-based solar telescopes and with the help of artificial intelligence techniques, new numerical models with quantitative analyses and physical consideration are being developed for the predictions of solar eruptive events. The 3-D computer simulation technology is being introduced for the operational solar weather service platform to visualize the monitoring of solar activities, the running of the prediction models, as well as the presenting of the forecasting results. A new generation operational solar weather monitoring and forecasting system is expected to be constructed in the near future at NAOC.

A spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3‐ETAS): Toward an operational earthquake forecast

Science.gov (United States)

Field, Edward; Milner, Kevin R.; Hardebeck, Jeanne L.; Page, Morgan T.; van der Elst, Nicholas; Jordan, Thomas H.; Michael, Andrew J.; Shaw, Bruce E.; Werner, Maximillan J.

2017-01-01

We, the ongoing Working Group on California Earthquake Probabilities, present a spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3), with the goal being to represent aftershocks, induced seismicity, and otherwise triggered events as a potential basis for operational earthquake forecasting (OEF). Specifically, we add an epidemic‐type aftershock sequence (ETAS) component to the previously published time‐independent and long‐term time‐dependent forecasts. This combined model, referred to as UCERF3‐ETAS, collectively represents a relaxation of segmentation assumptions, the inclusion of multifault ruptures, an elastic‐rebound model for fault‐based ruptures, and a state‐of‐the‐art spatiotemporal clustering component. It also represents an attempt to merge fault‐based forecasts with statistical seismology models, such that information on fault proximity, activity rate, and time since last event are considered in OEF. We describe several unanticipated challenges that were encountered, including a need for elastic rebound and characteristic magnitude–frequency distributions (MFDs) on faults, both of which are required to get realistic triggering behavior. UCERF3‐ETAS produces synthetic catalogs of M≥2.5 events, conditioned on any prior M≥2.5 events that are input to the model. We evaluate results with respect to both long‐term (1000 year) simulations as well as for 10‐year time periods following a variety of hypothetical scenario mainshocks. Although the results are very plausible, they are not always consistent with the simple notion that triggering probabilities should be greater if a mainshock is located near a fault. Important factors include whether the MFD near faults includes a significant characteristic earthquake component, as well as whether large triggered events can nucleate from within the rupture zone of the mainshock. Because UCERF3‐ETAS has many sources of uncertainty, as

Tsunami Forecasting in the Atlantic Basin

Science.gov (United States)

Knight, W. R.; Whitmore, P.; Sterling, K.; Hale, D. A.; Bahng, B.

2012-12-01

The mission of the West Coast and Alaska Tsunami Warning Center (WCATWC) is to provide advance tsunami warning and guidance to coastal communities within its Area-of-Responsibility (AOR). Predictive tsunami models, based on the shallow water wave equations, are an important part of the Center's guidance support. An Atlantic-based counterpart to the long-standing forecasting ability in the Pacific known as the Alaska Tsunami Forecast Model (ATFM) is now developed. The Atlantic forecasting method is based on ATFM version 2 which contains advanced capabilities over the original model; including better handling of the dynamic interactions between grids, inundation over dry land, new forecast model products, an optional non-hydrostatic approach, and the ability to pre-compute larger and more finely gridded regions using parallel computational techniques. The wide and nearly continuous Atlantic shelf region presents a challenge for forecast models. Our solution to this problem has been to develop a single unbroken high resolution sub-mesh (currently 30 arc-seconds), trimmed to the shelf break. This allows for edge wave propagation and for kilometer scale bathymetric feature resolution. Terminating the fine mesh at the 2000m isobath keeps the number of grid points manageable while allowing for a coarse (4 minute) mesh to adequately resolve deep water tsunami dynamics. Higher resolution sub-meshes are then included around coastal forecast points of interest. The WCATWC Atlantic AOR includes eastern U.S. and Canada, the U.S. Gulf of Mexico, Puerto Rico, and the Virgin Islands. Puerto Rico and the Virgin Islands are in very close proximity to well-known tsunami sources. Because travel times are under an hour and response must be immediate, our focus is on pre-computing many tsunami source "scenarios" and compiling those results into a database accessible and calibrated with observations during an event. Seismic source evaluation determines the order of model pre

Forecast Based Financing for Managing Weather and Climate Risks to Reduce Potential Disaster Impacts

Science.gov (United States)

Arrighi, J.

2017-12-01

There is a critical window of time to reduce potential impacts of a disaster after a forecast for heightened risk is issued and before an extreme event occurs. The concept of Forecast-based Financing focuses on this window of opportunity. Through advanced preparation during system set-up, tailored methodologies are used to 1) analyze a range of potential extreme event forecasts, 2) identify emergency preparedness measures that can be taken when factoring in forecast lead time and inherent uncertainty and 3) develop standard operating procedures that are agreed on and tied to guaranteed funding sources to facilitate emergency measures led by the Red Cross or government actors when preparedness measures are triggered. This presentation will focus on a broad overview of the current state of theory and approaches used in developing a forecast-based financing systems - with a specific focus on hydrologic events, case studies of success and challenges in various contexts where this approach is being piloted, as well as what is on the horizon to be further explored and developed from a research perspective as the application of this approach continues to expand.

Using subseasonal-to-seasonal (S2S extreme rainfall forecasts for extended-range flood prediction in Australia

Directory of Open Access Journals (Sweden)

C. J. White

2015-06-01

Full Text Available Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal. Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

Task Force on Catastrophic Antiphospholipid Syndrome (APS) and Non-criteria APS Manifestations (I): catastrophic APS, APS nephropathy and heart valve lesions.

Science.gov (United States)

Cervera, R; Tektonidou, M G; Espinosa, G; Cabral, A R; González, E B; Erkan, D; Vadya, S; Adrogué, H E; Solomon, M; Zandman-Goddard, G; Shoenfeld, Y

2011-02-01

The objectives of the 'Task Force on Catastrophic Antiphospholipid Syndrome (APS) and Non-criteria APS Manifestations' were to assess the clinical utility of the international consensus statement on classification criteria and treatment guidelines for the catastrophic APS, to identify and grade the studies that analyse the relationship between the antiphospholipid antibodies and the non-criteria APS manifestations and to present the current evidence regarding the accuracy of these non-criteria APS manifestations for the detection of patients with APS. This article summarizes the studies analysed on the catastrophic APS, APS nephropathy and heart valve lesions, and presents the recommendations elaborated by the Task Force after this analysis.

Space Weather Forecasting and Research at the Community Coordinated Modeling Center

Science.gov (United States)

Aronne, M.

2015-12-01

The Space Weather Research Center (SWRC), within the Community Coordinated Modeling Center (CCMC), provides experimental research forecasts and analysis for NASA's robotic mission operators. Space weather conditions are monitored to provide advance warning and forecasts based on observations and modeling using the integrated Space Weather Analysis Network (iSWA). Space weather forecasters come from a variety of backgrounds, ranging from modelers to astrophysicists to undergraduate students. This presentation will discuss space weather operations and research from an undergraduate perspective. The Space Weather Research, Education, and Development Initiative (SW REDI) is the starting point for many undergraduate opportunities in space weather forecasting and research. Space weather analyst interns play an active role year-round as entry-level space weather analysts. Students develop the technical and professional skills to forecast space weather through a summer internship that includes a two week long space weather boot camp, mentorship, poster session, and research opportunities. My unique development of research projects includes studying high speed stream events as well as a study of 20 historic, high-impact solar energetic particle events. This unique opportunity to combine daily real-time analysis with related research prepares students for future careers in Heliophysics.

Improving weather forecasts for wind energy applications

Science.gov (United States)

Kay, Merlinde; MacGill, Iain

2010-08-01

Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms-1 and around 25 ms-1. A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

Improving weather forecasts for wind energy applications

International Nuclear Information System (INIS)

Kay, Merlinde; MacGill, Iain

2010-01-01

Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms -1 and around 25 ms -1 . A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

Catastrophic risks and insurance in farm-level decision making

NARCIS (Netherlands)

Ogurtsov, V.

2008-01-01

Keywords: risk perception, risk attitude, catastrophic risk, insurance, farm characteristics, farmer personal characteristics, utility-efficient programming, arable farming, dairy farming

Catastrophic risks can cause severe cash flow problems for farmers or even result into their

Valuation of Indonesian catastrophic earthquake bonds with generalized extreme value (GEV) distribution and Cox-Ingersoll-Ross (CIR) interest rate model

International Nuclear Information System (INIS)

Gunardi,; Setiawan, Ezra Putranda

2015-01-01

Indonesia is a country with high risk of earthquake, because of its position in the border of earth’s tectonic plate. An earthquake could raise very high amount of damage, loss, and other economic impacts. So, Indonesia needs a mechanism for transferring the risk of earthquake from the government or the (reinsurance) company, as it could collect enough money for implementing the rehabilitation and reconstruction program. One of the mechanisms is by issuing catastrophe bond, ‘act-of-God bond’, or simply CAT bond. A catastrophe bond issued by a special-purpose-vehicle (SPV) company, and then sold to the investor. The revenue from this transaction is joined with the money (premium) from the sponsor company and then invested in other product. If a catastrophe happened before the time-of-maturity, cash flow from the SPV to the investor will discounted or stopped, and the cash flow is paid to the sponsor company to compensate their loss because of this catastrophe event. When we consider the earthquake only, the amount of discounted cash flow could determine based on the earthquake’s magnitude. A case study with Indonesian earthquake magnitude data show that the probability of maximum magnitude can model by generalized extreme value (GEV) distribution. In pricing this catastrophe bond, we assumed stochastic interest rate that following the Cox-Ingersoll-Ross (CIR) interest rate model. We develop formulas for pricing three types of catastrophe bond, namely zero coupon bonds, ‘coupon only at risk’ bond, and ‘principal and coupon at risk’ bond. Relationship between price of the catastrophe bond and CIR model’s parameter, GEV’s parameter, percentage of coupon, and discounted cash flow rule then explained via Monte Carlo simulation

Valuation of Indonesian catastrophic earthquake bonds with generalized extreme value (GEV) distribution and Cox-Ingersoll-Ross (CIR) interest rate model

Energy Technology Data Exchange (ETDEWEB)

Gunardi,; Setiawan, Ezra Putranda [Mathematics Department, Gadjah Mada University (Indonesia)

2015-12-22

Indonesia is a country with high risk of earthquake, because of its position in the border of earth’s tectonic plate. An earthquake could raise very high amount of damage, loss, and other economic impacts. So, Indonesia needs a mechanism for transferring the risk of earthquake from the government or the (reinsurance) company, as it could collect enough money for implementing the rehabilitation and reconstruction program. One of the mechanisms is by issuing catastrophe bond, ‘act-of-God bond’, or simply CAT bond. A catastrophe bond issued by a special-purpose-vehicle (SPV) company, and then sold to the investor. The revenue from this transaction is joined with the money (premium) from the sponsor company and then invested in other product. If a catastrophe happened before the time-of-maturity, cash flow from the SPV to the investor will discounted or stopped, and the cash flow is paid to the sponsor company to compensate their loss because of this catastrophe event. When we consider the earthquake only, the amount of discounted cash flow could determine based on the earthquake’s magnitude. A case study with Indonesian earthquake magnitude data show that the probability of maximum magnitude can model by generalized extreme value (GEV) distribution. In pricing this catastrophe bond, we assumed stochastic interest rate that following the Cox-Ingersoll-Ross (CIR) interest rate model. We develop formulas for pricing three types of catastrophe bond, namely zero coupon bonds, ‘coupon only at risk’ bond, and ‘principal and coupon at risk’ bond. Relationship between price of the catastrophe bond and CIR model’s parameter, GEV’s parameter, percentage of coupon, and discounted cash flow rule then explained via Monte Carlo simulation.

Catastrophic avalanches and methods of their control

Directory of Open Access Journals (Sweden)

N. A. Volodicheva

2014-01-01

Full Text Available Definition of such phenomenon as “catastrophic avalanche” is presented in this arti-cle. Several situations with releases of catastrophic avalanches in mountains of Caucasus, Alps, and Central Asia are investigated. Materials of snow-avalanche ob-servations performed since 1960s at the Elbrus station of the Lomonosov Moscow State University (Central Caucasus were used for this work. Complex-valued measures of engineering protection demonstrating different efficiencies are consid-ered.

Pricing catastrophic bonds for earthquakes in Mexico

OpenAIRE

Cabrera, Brenda López

2006-01-01

After the occurrence of a natural disaster, the reconstruction can be financed with catastrophic bonds (CAT bonds) or reinsurance. For insurers, reinsurers and other corporations CAT bonds provide multi year protection without the credit risk present in reinsurance. For investors CAT bonds offer attractive returns and reduction of portfolio risk, since CAT bonds defaults are uncorrelated with defaults of other securities. As the study of natural catastrophe models plays an important role in t...

Locally adapted fish populations maintain small-scale genetic differentiation despite perturbation by a catastrophic flood event.

Science.gov (United States)

Plath, Martin; Hermann, Bernd; Schröder, Christiane; Riesch, Rüdiger; Tobler, Michael; García de León, Francisco J; Schlupp, Ingo; Tiedemann, Ralph

2010-08-23

Local adaptation to divergent environmental conditions can promote population genetic differentiation even in the absence of geographic barriers and hence, lead to speciation. Perturbations by catastrophic events, however, can distort such parapatric ecological speciation processes. Here, we asked whether an exceptionally strong flood led to homogenization of gene pools among locally adapted populations of the Atlantic molly (Poecilia mexicana, Poeciliidae) in the Cueva del Azufre system in southern Mexico, where two strong environmental selection factors (darkness within caves and/or presence of toxic H2S in sulfidic springs) drive the diversification of P. mexicana. Nine nuclear microsatellites as well as heritable female life history traits (both as a proxy for quantitative genetics and for trait divergence) were used as markers to compare genetic differentiation, genetic diversity, and especially population mixing (immigration and emigration) before and after the flood. Habitat type (i.e., non-sulfidic surface, sulfidic surface, or sulfidic cave), but not geographic distance was the major predictor of genetic differentiation. Before and after the flood, each habitat type harbored a genetically distinct population. Only a weak signal of individual dislocation among ecologically divergent habitat types was uncovered (with the exception of slightly increased dislocation from the Cueva del Azufre into the sulfidic creek, El Azufre). By contrast, several lines of evidence are indicative of increased flood-induced dislocation within the same habitat type, e.g., between different cave chambers of the Cueva del Azufre. The virtual absence of individual dislocation among ecologically different habitat types indicates strong natural selection against migrants. Thus, our current study exemplifies that ecological speciation in this and other systems, in which extreme environmental factors drive speciation, may be little affected by temporary perturbations, as adaptations

An Operational Short-Term Forecasting System for Regional Hydropower Management

Science.gov (United States)

Gronewold, A.; Labuhn, K. A.; Calappi, T. J.; MacNeil, A.

2017-12-01

The Niagara River is the natural outlet of Lake Erie and drains four of the five Great lakes. The river is used to move commerce and is home to both sport fishing and tourism industries. It also provides nearly 5 million kilowatts of hydropower for approximately 3.9 million homes. Due to a complex international treaty and the necessity of balancing water needs for an extensive tourism industry, the power entities operating on the river require detailed and accurate short-term river flow forecasts to maximize power output. A new forecast system is being evaluated that takes advantage of several previously independent components including the NOAA Lake Erie operational Forecast System (LEOFS), a previously developed HEC-RAS model, input from the New York Power Authority(NYPA) and Ontario Power Generation (OPG) and lateral flow forecasts for some of the tributaries provided by the NOAA Northeast River Forecast Center (NERFC). The Corps of Engineers updated the HEC-RAS model of the upper Niagara River to use the output forcing from LEOFS and a planned Grass Island Pool elevation provided by the power entities. The entire system has been integrated at the NERFC; it will be run multiple times per day with results provided to the Niagara River Control Center operators. The new model helps improve discharge forecasts by better accounting for dynamic conditions on Lake Erie. LEOFS captures seiche events on the lake that are often several meters of displacement from still water level. These seiche events translate into flow spikes that HEC-RAS routes downstream. Knowledge of the peak arrival time helps improve operational decisions at the Grass Island Pool. This poster will compare and contrast results from the existing operational flow forecast and the new integrated LEOFS/HEC-RAS forecast. This additional model will supply the Niagara River Control Center operators with multiple forecasts of flow to help improve forecasting under a wider variety of conditions.

Rare event techniques applied in the Rasmussen study

International Nuclear Information System (INIS)

Vesely, W.E.

1977-01-01

The Rasmussen Study estimated public risks from commercial nuclear power plant accidents, and therefore the statistics of rare events had to be treated. Two types of rare events were specifically handled, those rare events which were probabilistically rare events and those which were statistically rare events. Four techniques were used to estimate probabilities of rare events. These techniques were aggregating data samples, discretizing ''continuous'' events, extrapolating from minor to catastrophic severities, and decomposing events using event trees and fault trees. In aggregating or combining data the goal was to enlarge the data sample so that the rare event was no longer rare, i.e., so that the enlarged data sample contained one or more occurrences of the event of interest. This aggregation gave rise to random variable treatments of failure rates, occurrence frequencies, and other characteristics estimated from data. This random variable treatment can be interpreted as being comparable to an empirical Bayes technique or a Bayesian technique. In the discretizing event technique, events of a detailed nature were grouped together into a grosser event for purposes of analysis as well as for data collection. The treatment of data characteristics as random variables helped to account for the uncertainties arising from this discretizing. In the severity extrapolation technique a severity variable was associated with each event occurrence for the purpose of predicting probabilities of catastrophic occurrences. Tail behaviors of distributions therefore needed to be considered. Finally, event trees and fault trees were used to express accident occurrences and system failures in terms of more basic events for which data existed. Common mode failures and general dependencies therefore needed to be treated. 2 figures

Stagewise cognitive development: an application of catastrophe theory.

Science.gov (United States)

van der Maas, H L; Molenaar, P C

1992-07-01

In this article an overview is given of traditional methodological approaches to stagewise cognitive developmental research. These approaches are evaluated and integrated on the basis of catastrophe theory. In particular, catastrophe theory specifies a set of common criteria for testing the discontinuity hypothesis proposed by Piaget. Separate criteria correspond to distinct methods used in cognitive developmental research. Such criteria are, for instance, the detection of spurts in development, bimodality of test scores, and increased variability of responses during transitional periods. When a genuine stage transition is present, these criteria are expected to be satisfied. A revised catastrophe model accommodating these criteria is proposed for the stage transition in cognitive development from the preoperational to the concrete operational stage.

Should catastrophic risks be included in a regulated competitive health insurance market?

Science.gov (United States)

van de Ven, W P; Schut, F T

1994-11-01

In 1988 the Dutch government launched a proposal for a national health insurance based on regulated competition. The mandatory benefits package should be offered by competing insurers and should cover both non-catastrophic risks (like hospital care, physician services and drugs) and catastrophic risks (like several forms of expensive long-term care). However, there are two arguments to exclude some of the catastrophic risks from the competitive insurance market, at least during the implementation process of the reforms. Firstly, the prospects for a workable system of risk-adjusted payments to the insurers that should take away the incentives for cream skimming are, at least during the next 5 years, more favorable for the non-catastrophic risks than for the catastrophic risks. Secondly, even if a workable system of risk-adjusted payments can be developed, the problem of quality skimping may be relevant for some of the catastrophic risks, but not for non-catastrophic risks. By 'quality skimping' we mean the reduction of the quality of care to a level which is below the minimum level that is acceptable to society. After 5 years of health care reforms in the Netherlands new insights have resulted in a growing support to confine the implementation of the reforms to the non-catastrophic risks. In drawing (and redrawing) the exact boundaries between different regulatory regimes for catastrophic and non-catastrophic risks, the expected benefits of a cost-effective substitution of care have to be weighted against the potential harm caused by cream skimming and quality skimping.

Indirect Catastrophic Injuries in Olympic Styles of Wrestling in Iran

OpenAIRE

Kordi, Ramin; Ziaee, Vahid; Rostami, Mohsen; Wallace, W. Angus

2011-01-01

Background: Data on indirect catastrophic injuries in wrestling are scarce. Objectives: To develop a profile of indirect catastrophic injuries in international styles of wrestling and to describe possible risk factors. Study Design: Retrospective case series; Level of evidence, 3. Methods: Indirect catastrophic injuries that occurred in wrestling clubs in Iran from July 1998 to June 2005 were identified by contacting several sources. The cases were retrospectively reviewed. Results: The injur...

Foretelling Flares and Solar Energetic Particle Events: the FORSPEF tool

Science.gov (United States)

Anastasiadis, Anastasios; Papaioannou, Athanasios; Sandberg, Ingmar; Georgoulis, Manolis K.; Tziotziou, Kostas; Jiggens, Piers

2017-04-01

A novel integrated prediction system, for both solar flares (SFs) and solar energetic particle (SEP) events is being presented. The Forecasting Solar Particle Events and Flares (FORSPEF) provides forecasting of solar eruptive events, such as SFs with a projection to coronal mass ejections (CMEs) (occurrence and velocity) and the likelihood of occurrence of a SEP event. In addition, FORSPEF, also provides nowcasting of SEP events based on actual SF and CME near real-time data, as well as the complete SEP profile (peak flux, fluence, rise time, duration) per parent solar event. The prediction of SFs relies on a morphological method: the effective connected magnetic field strength (Beff); it is based on an assessment of potentially flaring active-region (AR) magnetic configurations and it utilizes sophisticated analysis of a large number of AR magnetograms. For the prediction of SEP events new methods have been developed for both the likelihood of SEP occurrence and the expected SEP characteristics. In particular, using the location of the flare (longitude) and the flare size (maximum soft X-ray intensity), a reductive statistical method has been implemented. Moreover, employing CME parameters (velocity and width), proper functions per width (i.e. halo, partial halo, non-halo) and integral energy (E>30, 60, 100 MeV) have been identified. In our technique warnings are issued for all > C1.0 soft X-ray flares. The prediction time in the forecasting scheme extends to 24 hours with a refresh rate of 3 hours while the respective prediction time for the nowcasting scheme depends on the availability of the near real-time data and falls between 15-20 minutes for solar flares and 6 hours for CMEs. We present the modules of the FORSPEF system, their interconnection and the operational set up. The dual approach in the development of FORPSEF (i.e. forecasting and nowcasting scheme) permits the refinement of predictions upon the availability of new data that characterize changes on

Weather and forecasting at Wilkins ice runway, Antarctica

International Nuclear Information System (INIS)

Carpentier, Scott

2010-01-01

Aviation forecasts for Wilkins ice runway in East Antarctica are developed within the conceptual framework of flow against a single dome shaped hill. Forecast challenges include the sudden onset of blizzards associated with the formation of an internal gravity wave; frontal weather; transient wake vortices and mesoscale lows; temperature limitations on runway use; and snow and fog events. These key weather aspects are presented within the context of synoptic to local scale climatologies and numerical weather prediction models.

Comparison of landslide forecasting services in Piedmont (Italy and Norway, illustrated by events in late spring 2013

Directory of Open Access Journals (Sweden)

G. Devoli

2018-05-01

the system moves across the mountain regions. These secondary effects were effectively forecasted by the two landslide warning services, operating in different parts of Europe. The landslide risks were also properly communicated to the public some days in advance. This analysis has allowed the establishment of fruitful international collaboration between ARPA Piemonte and NVE and the future exchange of experiences, procedures and methods relating to similar events.

Reactor accidents and nuclear catastrophes

International Nuclear Information System (INIS)

Kirchhoff, R.; Linde, H.J.

1979-01-01

Assuming some preliminary knowledge of the fundamentals of atomic physics, the book describes the effects of ionizing radiation on the human organism. In order to assess the potential hazards of reactor accidents and the extent of a nuclear catastrophe, the technology of power generation in nuclear power stations is presented together with its potential dangers as well as the physical and medical processes occurring during a nuclear weapons explosion. The special medical aspects are presented which range from first aid in the case of a catastrophe to the accute radiation syndrome, the treatment of burns to the therapy of late radiolesions. Finally, it is confirmed that the treatment of radiation injured persons does not give rise to basically new medical problems. (orig./HP) [de

Monitoring and forecasting Etna volcanic plumes

Directory of Open Access Journals (Sweden)

S. Scollo

2009-09-01

Full Text Available In this paper we describe the results of a project ongoing at the Istituto Nazionale di Geofisica e Vulcanologia (INGV. The objective is to develop and implement a system for monitoring and forecasting volcanic plumes of Etna. Monitoring is based at present by multispectral infrared measurements from the Spin Enhanced Visible and Infrared Imager on board the Meteosat Second Generation geosynchronous satellite, visual and thermal cameras, and three radar disdrometers able to detect ash dispersal and fallout. Forecasting is performed by using automatic procedures for: i downloading weather forecast data from meteorological mesoscale models; ii running models of tephra dispersal, iii plotting hazard maps of volcanic ash dispersal and deposition for certain scenarios and, iv publishing the results on a web-site dedicated to the Italian Civil Protection. Simulations are based on eruptive scenarios obtained by analysing field data collected after the end of recent Etna eruptions. Forecasting is, hence, supported by plume observations carried out by the monitoring system. The system was tested on some explosive events occurred during 2006 and 2007 successfully. The potentiality use of monitoring and forecasting Etna volcanic plumes, in a way to prevent threats to aviation from volcanic ash, is finally discussed.

Bayesian quantitative precipitation forecasts in terms of quantiles

Science.gov (United States)

Bentzien, Sabrina; Friederichs, Petra

2014-05-01

Ensemble prediction systems (EPS) for numerical weather predictions on the mesoscale are particularly developed to obtain probabilistic guidance for high impact weather. An EPS not only issues a deterministic future state of the atmosphere but a sample of possible future states. Ensemble postprocessing then translates such a sample of forecasts into probabilistic measures. This study focus on probabilistic quantitative precipitation forecasts in terms of quantiles. Quantiles are particular suitable to describe precipitation at various locations, since no assumption is required on the distribution of precipitation. The focus is on the prediction during high-impact events and related to the Volkswagen Stiftung funded project WEX-MOP (Mesoscale Weather Extremes - Theory, Spatial Modeling and Prediction). Quantile forecasts are derived from the raw ensemble and via quantile regression. Neighborhood method and time-lagging are effective tools to inexpensively increase the ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Since an EPS provides a large amount of potentially informative predictors, a variable selection is required in order to obtain a stable statistical model. A Bayesian formulation of quantile regression allows for inference about the selection of predictive covariates by the use of appropriate prior distributions. Moreover, the implementation of an additional process layer for the regression parameters accounts for spatial variations of the parameters. Bayesian quantile regression and its spatially adaptive extension is illustrated for the German-focused mesoscale weather prediction ensemble COSMO-DE-EPS, which runs (pre)operationally since December 2010 at the German Meteorological Service (DWD). Objective out-of-sample verification uses the quantile score (QS), a weighted absolute error between quantile forecasts and observations. The QS is a proper scoring function and can be decomposed into

Forecasting electricity spot-prices using linear univariate time-series models

International Nuclear Information System (INIS)

Cuaresma, Jesus Crespo; Hlouskova, Jaroslava; Kossmeier, Stephan; Obersteiner, Michael

2004-01-01

This paper studies the forecasting abilities of a battery of univariate models on hourly electricity spot prices, using data from the Leipzig Power Exchange. The specifications studied include autoregressive models, autoregressive-moving average models and unobserved component models. The results show that specifications, where each hour of the day is modelled separately present uniformly better forecasting properties than specifications for the whole time-series, and that the inclusion of simple probabilistic processes for the arrival of extreme price events can lead to improvements in the forecasting abilities of univariate models for electricity spot prices. (Author)

Frost Monitoring and Forecasting Using MODIS Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa

Science.gov (United States)

Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh

2014-01-01

Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. MODIS Land Surface Temperature (LST) data, derived from NASA's Terra and Aqua satellites, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.

Microtubule catastrophe and rescue.

Science.gov (United States)

Gardner, Melissa K; Zanic, Marija; Howard, Jonathon

2013-02-01

Microtubules are long cylindrical polymers composed of tubulin subunits. In cells, microtubules play an essential role in architecture and motility. For example, microtubules give shape to cells, serve as intracellular transport tracks, and act as key elements in important cellular structures such as axonemes and mitotic spindles. To accomplish these varied functions, networks of microtubules in cells are very dynamic, continuously remodeling through stochastic length fluctuations at the ends of individual microtubules. The dynamic behavior at the end of an individual microtubule is termed 'dynamic instability'. This behavior manifests itself by periods of persistent microtubule growth interrupted by occasional switching to rapid shrinkage (called microtubule 'catastrophe'), and then by switching back from shrinkage to growth (called microtubule 'rescue'). In this review, we summarize recent findings which provide new insights into the mechanisms of microtubule catastrophe and rescue, and discuss the impact of these findings in regards to the role of microtubule dynamics inside of cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Pressure Effects Analysis of National Ignition Facility Capacitor Module Events

International Nuclear Information System (INIS)

Brereton, S; Ma, C; Newton, M; Pastrnak, J; Price, D; Prokosch, D

1999-01-01

Capacitors and power conditioning systems required for the National Ignition Facility (NIF) have experienced several catastrophic failures during prototype demonstration. These events generally resulted in explosion, generating a dramatic fireball and energetic shrapnel, and thus may present a threat to the walls of the capacitor bay that houses the capacitor modules. The purpose of this paper is to evaluate the ability of the capacitor bay walls to withstand the overpressure generated by the aforementioned events. Two calculations are described in this paper. The first one was used to estimate the energy release during a fireball event and the second one was used to estimate the pressure in a capacitor module during a capacitor explosion event. Both results were then used to estimate the subsequent overpressure in the capacitor bay where these events occurred. The analysis showed that the expected capacitor bay overpressure was less than the pressure tolerance of the walls. To understand the risk of the above events in NIF, capacitor module failure probabilities were also calculated. This paper concludes with estimates of the probability of single module failure and multi-module failures based on the number of catastrophic failures in the prototype demonstration facility

Pain catastrophizing predicts verbal expression among children with chronic pain and their mothers

Directory of Open Access Journals (Sweden)

Shelby L Langer

2016-03-01

Full Text Available This study examined intra- and inter-personal associations between pain catastrophizing and verbal expression in 70 children with recurrent abdominal pain and their mothers. Participants independently completed the Pain Catastrophizing Scale. Mothers and children then talked about the child’s pain. Speech was categorized using a linguistic analysis program. Catastrophizing was positively associated with the use of negative emotion words by both mothers and children. In addition, mothers’ catastrophizing was positively associated with both mothers’ and children’s anger word usage, whereas children’s catastrophizing was inversely associated with mothers’ anger word usage. Findings extend the literature on behavioral and interpersonal aspects of catastrophizing.

Risky Business: Development, Communication and Use of Hydroclimatic Forecasts

Science.gov (United States)

Lall, U.

2012-12-01

Inter-seasonal and longer hydroclimatic forecasts have been made increasingly in the last two decades following the increase in ENSO activity since the early 1980s and the success in seasonal ENSO forecasting. Yet, the number of examples of systematic use of these forecasts and their incorporation into water systems operation continue to be few. This may be due in part to the limited skill in such forecasts over much of the world, but is also likely due to the limited evolution of methods and opportunities to "safely" use uncertain forecasts. There has been a trend to rely more on "physically based" rather than "physically informed" empirical forecasts, and this may in part explain the limited success in developing usable products in more locations. Given the limited skill, forecasters have tended to "dumb" down their forecasts - either formally or subjectively shrinking the forecasts towards climatology, or reducing them to tercile forecasts that serve to obscure the potential information in the forecast. Consequently, the potential utility of such forecasts for decision making is compromised. Water system operating rules are often designed to be robust in the face of historical climate variability, and consequently are adapted to the potential conditions that a forecast seeks to inform. In such situations, there is understandable reluctance by managers to use the forecasts as presented, except in special cases where an alternate course of action is pragmatically appealing in any case. In this talk, I review opportunities to present targeted forecasts for use with decision systems that directly address climate risk and the risk induced by unbiased yet uncertain forecasts, focusing especially on extreme events and water allocation in a competitive environment. Examples from Brazil and India covering surface and ground water conjunctive use strategies that could potentially be insured and lead to improvements over the traditional system operation and resource

The Impact of Weather Forecasts of Various Lead Times on Snowmaking Decisions Made for the 2010 Vancouver Olympic Winter Games

Science.gov (United States)

Doyle, Chris

2014-01-01

The Vancouver 2010 Winter Olympics were held from 12 to 28 February 2010, and the Paralympic events followed 2 weeks later. During the Games, the weather posed a grave threat to the viability of one venue and created significant complications for the event schedule at others. Forecasts of weather with lead times ranging from minutes to days helped organizers minimize disruptions to sporting events and helped ensure all medal events were successfully completed. Of comparable importance, however, were the scenarios and forecasts of probable weather for the winter in advance of the Games. Forecasts of mild conditions at the time of the Games helped the Games' organizers mitigate what would have been very serious potential consequences for at least one venue. Snowmaking was one strategy employed well in advance of the Games to prepare for the expected conditions. This short study will focus on how operational decisions were made by the Games' organizers on the basis of both climatological and snowmaking forecasts during the pre-Games winter. An attempt will be made to quantify, economically, the value of some of the snowmaking forecasts made for the Games' operators. The results obtained indicate that although the economic value of the snowmaking forecast was difficult to determine, the Games' organizers valued the forecast information greatly. This suggests that further development of probabilistic forecasts for applications like pre-Games snowmaking would be worthwhile.

Electrical streaming potential precursors to catastrophic earthquakes in China

Directory of Open Access Journals (Sweden)

F. Qian

1997-06-01

Full Text Available The majority of anomalies in self-potential at 7 stations within 160 km from the epicentre showed a similar pattern of rapid onset and slow decay during and before the M 7.8 Tangshan earthquake of 1976. Considering that some of these anomalies associated with episodical spouting from boreholes or the increase in pore pressure in wells, observed anomalies are streaming potential generated by local events of sudden movements and diffusion process of high-pressure fluid in parallel faults. These transient events triggered by tidal forces exhibited a periodic nature and the statistical phenomenon to migrate towards the epicentre about one month before the earthquake. As a result of events, the pore pressure reached its final equilibrium state and was higher than that in the initial state in a large enough section of the fault region. Consequently, local effective shear strength of the material in the fault zone decreased and finally the catastrophic earthquake was induced. Similar phenomena also occurred one month before the M 7.3 Haichen earthquake of 1975. Therefore, a short term earthquake prediction can be made by electrical measurements, which are the kind of geophysical measurements most closely related to pore fluid behaviors of the deep crust.

Single Event Burnout in DC-DC Converters for the LHC Experiments

Energy Technology Data Exchange (ETDEWEB)

Claudio H. Rivetta et al.

2001-09-24

High voltage transistors in DC-DC converters are prone to catastrophic Single Event Burnout in the LHC radiation environment. This paper presents a systematic methodology to analyze single event effects sensitivity in converters and proposes solutions based on de-rating input voltage and output current or voltage.

Recent advances in flood forecasting and flood risk assessment

Directory of Open Access Journals (Sweden)

G. Arduino

2005-01-01

Full Text Available Recent large floods in Europe have led to increased interest in research and development of flood forecasting systems. Some of these events have been provoked by some of the wettest rainfall periods on record which has led to speculation that such extremes are attributable in some measure to anthropogenic global warming and represent the beginning of a period of higher flood frequency. Whilst current trends in extreme event statistics will be difficult to discern, conclusively, there has been a substantial increase in the frequency of high floods in the 20th century for basins greater than 2x105 km2. There is also increasing that anthropogenic forcing of climate change may lead to an increased probability of extreme precipitation and, hence, of flooding. There is, therefore, major emphasis on the improvement of operational flood forecasting systems in Europe, with significant European Community spending on research and development on prototype forecasting systems and flood risk management projects. This Special Issue synthesises the most relevant scientific and technological results presented at the International Conference on Flood Forecasting in Europe held in Rotterdam from 3-5 March 2003. During that meeting 150 scientists, forecasters and stakeholders from four continents assembled to present their work and current operational best practice and to discuss future directions of scientific and technological efforts in flood prediction and prevention. The papers presented at the conference fall into seven themes, as follows.

The Catalan version of the Pain Catastrophizing Scale: a useful instrument to assess catastrophic thinking in whiplash patients.

Science.gov (United States)

Miró, Jordi; Nieto, Rubén; Huguet, Anna

2008-05-01

The main aims of this work were to test the psychometric properties of the Catalan version of the Pain Catastrophizing Scale (PCS) and to assess the usefulness of the scale when used with whiplash patients. This article reports results from 2 complementary studies. In the first one, the PCS was administered to 280 students and 146 chronic pain patients to examine the psychometric properties of a new Catalan version of the instrument. A confirmatory factor analysis supported a second-order structure, in which 3 second-order factors (ie, rumination, helplessness, and magnification) load in a higher-order factor (ie, catastrophizing). The reliability of the Catalan version was supported by an acceptable internal consistency and test-retest values. Validity was supported by the correlations found among the PCS and pain intensity, pain interference, and depression. The objective of the second study was to evaluate the PCS when used with whiplash patients. In this second study, 141 patients with whiplash disorders participated. In general, the psychometric properties of the PCS were found appropriate, with factor analysis supporting the structure described in patients with chronic pain. Our data suggest that the PCS is a good instrument to assess catastrophic thinking in whiplash patients. The usefulness of the PCS in whiplash disorders has been explored in this study. Results of our work show that the PCS can be a very useful tool to assess catastrophic thinking about pain in whiplash patients.

Controlling extreme events on complex networks

Science.gov (United States)

Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng

2014-08-01

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

The Art and Science of Long-Range Space Weather Forecasting

Science.gov (United States)

Hathaway, David H.; Wilson, Robert M.

2006-01-01

Long-range space weather forecasts are akin to seasonal forecasts of terrestrial weather. We don t expect to forecast individual events but we do hope to forecast the underlying level of activity important for satellite operations and mission pl&g. Forecasting space weather conditions years or decades into the future has traditionally been based on empirical models of the solar cycle. Models for the shape of the cycle as a function of its amplitude become reliable once the amplitude is well determined - usually two to three years after minimum. Forecasting the amplitude of a cycle well before that time has been more of an art than a science - usually based on cycle statistics and trends. Recent developments in dynamo theory -the theory explaining the generation of the Sun s magnetic field and the solar activity cycle - have now produced models with predictive capabilities. Testing these models with historical sunspot cycle data indicates that these predictions may be highly reliable one, or even two, cycles into the future.

Early warnings of extreme winds using the ECMWF Extreme Forecast Index

DEFF Research Database (Denmark)

Petroliagis, Thomas I.; Pinson, Pierre

2014-01-01

The European FP7 SafeWind Project aims at developing research towards a European vision of wind power forecasting, which requires advanced meteorological support concerning extreme wind events. This study is focused mainly on early warnings of extreme winds in the early medium-range. Three synoptic...... regimes. Overall, it becomes clear that the first indications of an extreme wind event might come from the ECMWF deterministic and/or probabilistic components capturing very intense weather systems (possible windstorms) in the medium term. For early warnings, all available EPS Extreme Forecast Index (EFI......) formulations were used, by linking daily maximum wind speeds to EFI values for different forecast horizons. From all possible EFI schemes deployed for issuing early warnings, the highest skill was found for the Gust Factor formulation (EFI-10FGI). Using EFI-10FGI, the corresponding 99% threshold could provide...

Energy operations and planning decision support for systems using weather forecast information

International Nuclear Information System (INIS)

Altalo, M.G.

2004-01-01

Hydroelectric utilities deal with uncertainties on a regular basis. These include uncertainties in weather, policy and markets. This presentation outlined regional studies to define uncertainty, sources of uncertainty and their affect on power managers, power marketers, power insurers and end users. Solutions to minimize uncertainties include better forecasting and better business processes to mobilize action. The main causes of uncertainty in energy operations and planning include uncaptured wind, precipitation and wind events. Load model errors also contribute to uncertainty in energy operations. This presentation presented the results of a 2002-2003 study conducted by the National Oceanic and Atmospheric Administration (NOAA) on the impact uncertainties in northeast energy weather forecasts. The study demonstrated the cost of seabreeze error on transmission and distribution. The impact of climate scale events were also presented along with energy demand implications. It was suggested that energy planners should incorporate climate change parameters into planning, and that models should include probability distribution forecasts and ensemble forecasting methods that incorporate microclimate estimates. It was also suggested that seabreeze, lake effect, fog, afternoon thunderstorms and frontal passage should be incorporated into forecasts. tabs., figs

A critical look at catastrophe risk assessments

CERN Document Server

Kent, A

2004-01-01

Recent papers by Busza et al. (BJSW) and Dar et al. (DDH) argue that astrophysical data can be used to establish bounds on the risk of a catastrophe in forthcoming collider experiments. The safety case set out by BJSW does not rely on these bounds, but on theoretical arguments, which BJSW find sufficiently compelling. However, DDH and other commentators (initially including BJSW) have suggested that the astrophysical bounds alone do give sufficient reassurance. This seems unsupportable when the bounds are expressed in terms of expected cost. For example, DDH's main bound, $p_{\\rm catastrophe} < 2 \\times 10^{-8}$, implies only that the expectation value of the number of deaths is bounded by 120. We thus reappraise the DDH and BJSW risk bounds by comparing risk policy in other areas. We find that requiring a catastrophe risk of no higher than 10^{-15} is necessary to be consistent with established policy for risk optimisation from radiation hazards, even if highly risk tolerant assumptions are made. A respec...

[Bioethics in catastrophe situations such as earthquakes].

Science.gov (United States)

León, C Francisco Javier

2012-01-01

A catastrophe of the magnitude of the earthquake and tsunami that hit Chile not long ago, forces us to raise some questions that we will try to answer from a philosophical, ethical and responsibility viewpoints. An analysis of the basic principles of bioethics is also justified. A natural catastrophe is not, by itself, moral or immoral, fair or unfair. However, its consequences could certainly be regarded as such, depending on whether they could have been prevented or mitigated. We will identify those individuals, who have the ethical responsibility to attend the victims and the ethical principles that must guide the tasks of healthcare and psychological support teams. The minimal indispensable actions to obtain an adequate social and legal protection of vulnerable people, must be defined according to international guidelines. These reflections are intended to improve the responsibility of the State and all the community, to efficiently prevent and repair the material and psychological consequences of such a catastrophe.

Pain Catastrophizing Correlates with Early Mild Traumatic Brain Injury Outcome

Directory of Open Access Journals (Sweden)

Geneviève Chaput

2016-01-01

Full Text Available Background. Identifying which patients are most likely to be at risk of chronic pain and other postconcussion symptoms following mild traumatic brain injury (MTBI is a difficult clinical challenge. Objectives. To examine the relationship between pain catastrophizing, defined as the exaggerated negative appraisal of a pain experience, and early MTBI outcome. Methods. This cross-sectional design included 58 patients diagnosed with a MTBI. In addition to medical chart review, postconcussion symptoms were assessed by self-report at 1 month (Time 1 and 8 weeks (Time 2 after MTBI. Pain severity, psychological distress, level of functionality, and pain catastrophizing were measured by self-report at Time 2. Results. The pain catastrophizing subscales of rumination, magnification, and helplessness were significantly correlated with pain severity (r=.31 to .44, number of postconcussion symptoms reported (r=.35 to .45, psychological distress (r=.57 to .67, and level of functionality (r=-.43 to -.29. Pain catastrophizing scores were significantly higher for patients deemed to be at high risk of postconcussion syndrome (6 or more symptoms reported at both Time 1 and Time 2. Conclusions. Higher levels of pain catastrophizing were related to adverse early MTBI outcomes. The early detection of pain catastrophizing may facilitate goal-oriented interventions to prevent or minimize the development of chronic pain and other postconcussion symptoms.

THE 9TH INTERNATIONAL WORKSHOP "PHYSICS AND FORECASTING OF ROCK DESTRUCTION"

Directory of Open Access Journals (Sweden)

V. V. Ruzhich

2014-01-01

Full Text Available   The 9th International Workshop “Physics and Forecasting of Rock Destruction” was held in the Institute of the Earth’s Crust, SB RAS, in Irkutsk on 02–06 September 2013. The article reviews the main events of this scientific forum and briefly describes its discussion results concerning prediction / forecasting of dynamic destruction of rocks due to loading in various regimes and scales. Also reviewed are options for improvement of forecast methods and their application to practice. 

The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

Science.gov (United States)

Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

2010-09-01

Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events

Oceanic sources of predictability for MJO propagation across the Maritime Continent in a subset of S2S forecast models

Science.gov (United States)

DeMott, C. A.; Klingaman, N. P.

2017-12-01

Skillful prediction of the Madden-Julian oscillation (MJO) passage across the Maritime Continent (MC) has important implications for global forecasts of high-impact weather events, such as atmospheric rivers and heat waves. The North American teleconnection response to the MJO is strongest when MJO convection is located in the western Pacific Ocean, but many climate and forecast models are deficient in their simulation of MC-crossing MJO events. Compared to atmosphere-only general circulation models (AGCMs), MJO simulation skill generally improves with the addition of ocean feedbacks in coupled GCMs (CGCMs). Using observations, previous studies have noted that the degree of ocean coupling may vary considerably from one MJO event to the next. The coupling mechanisms may be linked to the presence of ocean Equatorial Rossby waves, the sign and amplitude of Equatorial surface currents, and the upper ocean temperature and salinity profiles. In this study, we assess the role of ocean feedbacks to MJO prediction skill using a subset of CGCMs participating in the Subseasonal-to-Seasonal (S2S) Project database. Oceanic observational and reanalysis datasets are used to characterize the upper ocean background state for observed MJO events that do and do not propagate beyond the MC. The ability of forecast models to capture the oceanic influence on the MJO is first assessed by quantifying SST forecast skill. Next, a set of previously developed air-sea interaction diagnostics is applied to model output to measure the role of SST perturbations on the forecast MJO. The "SST effect" in forecast MJO events is compared to that obtained from reanalysis data. Leveraging all ensemble members of a given forecast helps disentangle oceanic model biases from atmospheric model biases, both of which can influence the expression of ocean feedbacks in coupled forecast systems. Results of this study will help identify areas of needed model improvement for improved MJO forecasts.

House Price Forecasts, Forecaster Herding, and the Recent Crisis

DEFF Research Database (Denmark)

Stadtmann, Georg; Pierdzioch; Ruelke

2013-01-01

We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

On forecasting ionospheric total electron content responses to high-speed solar wind streams

Directory of Open Access Journals (Sweden)

Meng Xing

2016-01-01

Full Text Available Conditions in the ionosphere have become increasingly important to forecast, since more and more spaceborne and ground-based technological systems rely on ionospheric weather. Here we explore the feasibility of ionospheric forecasts with the current generation of physics-based models. In particular, we focus on total electron content (TEC predictions using the Global Ionosphere-Thermosphere Model (GITM. Simulations are configured in a forecast mode and performed for four typical high-speed-stream events during 2007–2012. The simulated TECs are quantified through a metric, which divides the globe into a number of local regions and robustly differentiates between quiet and disturbed periods. Proposed forecast products are hourly global maps color-coded by the TEC disturbance level of each local region. To assess the forecasts, we compare the simulated TEC disturbances with global TEC maps derived from Global Positioning System (GPS satellite observations. The forecast performance is found to be merely acceptable, with a large number of regions where the observed variations are not captured by the simulations. Examples of model-data agreements and disagreements are investigated in detail, aiming to understand the model behavior and improve future forecasts. For one event, we identify two adjacent regions with similar TEC observations but significant differences in how local chemistry versus plasma transport contribute to electron density changes in the simulation. Suggestions for further analysis are described.

Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

Science.gov (United States)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

Forecasting Nike’s Sales using Facebook Data

DEFF Research Database (Denmark)

Boldt, Linda Camilla; Vinayagamoorthy, Vinothan; Winder, Florian

2016-01-01

the method of social set analysis from the domain of computational social science to model sales from Big Social Data. The dataset consists of (a) selection of Nike’s Facebook pages with the number of likes, comments, posts etc. that have been registered for each page per day and (b) business data in terms......This paper tests whether accurate sales forecasts for Nike are possible from Facebook data and how events related to Nike affect the activity on Nike’s Facebook pages. The paper draws from the AIDA sales framework (Awareness, Interest, Desire,and Action) from the domain of marketing and employs...... of quarterly global sales figures published in Nike’s financial reports. An event study is also conducted using the Social Set Visualizer (SoSeVi). The findings suggest that Facebook data does have informational value. Some of the simple regression models have a high forecasting accuracy. The multiple...

House Price Forecasts, Forecaster Herding, and the Recent Crisis

Directory of Open Access Journals (Sweden)

Christian Pierdzioch

2012-11-01

Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

A forecasting model of gaming revenues in Clark County, Nevada

International Nuclear Information System (INIS)

Edwards, B.; Bando, A.; Bassett, G.; Rosen, A.; Carlson, J.; Meenan, C.

1992-01-01

This paper describes the Western Area Gaining and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. It is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry, an identify the exogenous variables that affect gaming revenues. This model will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming related economic activity resulting from future events like the siting of a permanent high-level radioactive waste repository at Yucca Mountain

A forecasting model of gaming revenues in Clark County, Nevada

International Nuclear Information System (INIS)

Edwards, B.; Bando, A.; Basset, G.; Rosen, A.; Meenan, C.; Carlson, J.

1992-01-01

This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. It is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry, and identify the exogenous variables that affect gaming revenues. This model will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming related economic activity resulting from future events like the siting of a permanent high-level radioactive waste repository at Yucca Mountain

A forecasting model of gaming revenues in Clark County, Nevada

Energy Technology Data Exchange (ETDEWEB)

Edwards, B.; Bando, A.; Bassett, G.; Rosen, A. [Argonne National Lab., IL (United States); Carlson, J.; Meenan, C. [Science Applications International Corp., Las Vegas, NV (United States)

1992-04-01

This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. It is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry, an identify the exogenous variables that affect gaming revenues. This model will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming related economic activity resulting from future events like the siting of a permanent high-level radioactive waste repository at Yucca Mountain.

Using HPC within an operational forecasting configuration

Science.gov (United States)

Jagers, H. R. A.; Genseberger, M.; van den Broek, M. A. F. H.

2012-04-01

Various natural disasters are caused by high-intensity events, for example: extreme rainfall can in a short time cause major damage in river catchments, storms can cause havoc in coastal areas. To assist emergency response teams in operational decisions, it's important to have reliable information and predictions as soon as possible. This starts before the event by providing early warnings about imminent risks and estimated probabilities of possible scenarios. In the context of various applications worldwide, Deltares has developed an open and highly configurable forecasting and early warning system: Delft-FEWS. Finding the right balance between simulation time (and hence prediction lead time) and simulation accuracy and detail is challenging. Model resolution may be crucial to capture certain critical physical processes. Uncertainty in forcing conditions may require running large ensembles of models; data assimilation techniques may require additional ensembles and repeated simulations. The computational demand is steadily increasing and data streams become bigger. Using HPC resources is a logical step; in different settings Delft-FEWS has been configured to take advantage of distributed computational resources available to improve and accelerate the forecasting process (e.g. Montanari et al, 2006). We will illustrate the system by means of a couple of practical applications including the real-time dynamic forecasting of wind driven waves, flow of water, and wave overtopping at dikes of Lake IJssel and neighboring lakes in the center of The Netherlands. Montanari et al., 2006. Development of an ensemble flood forecasting system for the Po river basin, First MAP D-PHASE Scientific Meeting, 6-8 November 2006, Vienna, Austria.

Does a more skilful meteorological input lead to a more skilful flood forecast at seasonal timescales?

Science.gov (United States)

Neumann, Jessica; Arnal, Louise; Magnusson, Linus; Cloke, Hannah

2017-04-01

Seasonal river flow forecasts are important for many aspects of the water sector including flood forecasting, water supply, hydropower generation and navigation. In addition to short term predictions, seasonal forecasts have the potential to realise higher benefits through more optimal and consistent decisions. Their operational use however, remains a challenge due to uncertainties posed by the initial hydrologic conditions (e.g. soil moisture, groundwater levels) and seasonal climate forcings (mainly forecasts of precipitation and temperature), leading to a decrease in skill with increasing lead times. Here we present a stakeholder-led case study for the Thames catchment (UK), currently being undertaken as part of the H2020 IMPREX project. The winter of 2013-14 was the wettest on record in the UK; driven by 12 major Atlantic depressions, the Thames catchment was subject to compound (concurrent) flooding from fluvial and groundwater sources. Focusing on the 2013-14 floods, this study aims to see whether increased skill in meteorological input translates through to more accurate forecasting of compound flood events at seasonal timescales in the Thames catchment. An earlier analysis of the ECMWF System 4 (S4) seasonal meteorological forecasts revealed that it did not skilfully forecast the extreme event of winter 2013-14. This motivated the implementation of an atmospheric experiment by the ECMWF to force the S4 to more accurately represent the low-pressure weather conditions prevailing in winter 2013-14 [1]. Here, we used both the standard and the "improved" S4 seasonal meteorological forecasts to force the EFAS (European Flood Awareness System) LISFLOOD hydrological model. Both hydrological forecasts were started on the 1st of November 2013 and run for 4 months of lead time to capture the peak of the 2013-14 flood event. Comparing the seasonal hydrological forecasts produced with both meteorological forcing data will enable us to assess how the improved meteorology

Catastrophic household expenditure on health in Nepal: a cross-sectional survey.

Science.gov (United States)

Saito, Eiko; Gilmour, Stuart; Rahman, Md Mizanur; Gautam, Ghan Shyam; Shrestha, Pradeep Krishna; Shibuya, Kenji

2014-10-01

To determine the incidence of - and illnesses commonly associated with - catastrophic household expenditure on health in Nepal. We did a cross-sectional population-based survey in five municipalities of Kathmandu Valley between November 2011 and January 2012. For each household surveyed, out-of-pocket spending on health in the previous 30 days that exceeded 10% of the household's total expenditure over the same period was considered to be catastrophic. We estimated the incidence and intensity of catastrophic health expenditure. We identified the illnesses most commonly associated with such expenditure using a Poisson regression model and assessed the distribution of expenditure by economic quintile of households using the concentration index. Overall, 284 of the 1997 households studied in Kathmandu, i.e. 13.8% after adjustment by sampling weight, reported catastrophic health expenditure in the 30 days before the survey. After adjusting for confounders, this expenditure was found to be associated with injuries, particularly those resulting from road traffic accidents. Catastrophic expenditure by households in the poorest quintile were associated with at least one episode of diabetes, asthma or heart disease. In an urban area of Nepal, catastrophic household expenditure on health was mostly associated with injuries and noncommunicable diseases such as diabetes and asthma. Throughout Nepal, interventions for the control and management of noncommunicable diseases and the prevention of road traffic accidents should be promoted. A phased introduction of health insurance should also reduce the incidence of catastrophic household expenditure.

a system approach to the long term forecasting of the climat data in baikal region

Science.gov (United States)

Abasov, N.; Berezhnykh, T.

2003-04-01

The Angara river running from Baikal with a cascade of hydropower plants built on it plays a peculiar role in economy of the region. With view of high variability of water inflow into the rivers and lakes (long-term low water periods and catastrophic floods) that is due to climatic peculiarities of the water resource formation, a long-term forecasting is developed and applied for risk decreasing at hydropower plants. Methodology and methods of long-term forecasting of natural-climatic processes employs some ideas of the research schools by Academician I.P.Druzhinin and Prof. A.P.Reznikhov and consists in detailed investigation of cause-effect relations, finding out physical analogs and their application to formalized methods of long-term forecasting. They are divided into qualitative (background method; method of analogs based on solar activity), probabilistic and approximative methods (analog-similarity relations; discrete-continuous model). These forecasting methods have been implemented in the form of analytical aids of the information-forecasting software "GIPSAR" that provides for some elements of artificial intelligence. Background forecasts of the runoff of the Ob, the Yenisei, the Angara Rivers in the south of Siberia are based on space-time regularities that were revealed on taking account of the phase shifts in occurrence of secular maxima and minima on integral-difference curves of many-year hydrological processes in objects compared. Solar activity plays an essential role in investigations of global variations of climatic processes. Its consideration in the method of superimposed epochs has allowed a conclusion to be made on the higher probability of the low-water period in the actual inflow to Lake Baikal that takes place on the increasing branch of solar activity of its 11-year cycle. The higher probability of a high-water period is observed on the decreasing branch of solar activity from the 2nd to the 5th year after its maximum. Probabilistic method

Forecasting Italian seismicity through a spatio-temporal physical model: importance of considering time-dependency and reliability of the forecast

Directory of Open Access Journals (Sweden)

Amir Hakimhashemi

2010-11-01

Full Text Available We apply here a forecasting model to the Italian region for the spatio-temporal distribution of seismicity based on a smoothing Kernel function, Coulomb stress variations, and a rate-and-state friction law. We tested the feasibility of this approach, and analyzed the importance of introducing time-dependency in forecasting future events. The change in seismicity rate as a function of time was estimated by calculating the Coulomb stress change imparted by large earthquakes. We applied our approach to the region of Italy, and used all of the cataloged earthquakes that occurred up to 2006 to generate the reference seismicity rate. For calculation of the time-dependent seismicity rate changes, we estimated the rate-and-state stress transfer imparted by all of the ML≥4.0 earthquakes that occurred during 2007 and 2008. To validate the results, we first compared the reference seismicity rate with the distribution of ML≥1.8 earthquakes since 2007, using both a non-declustered and a declustered catalog. A positive correlation was found, and all of the forecast earthquakes had locations within 82% and 87% of the study area with the highest seismicity rate, respectively. Furthermore, 95% of the forecast earthquakes had locations within 27% and 47% of the study area with the highest seismicity rate, respectively. For the time-dependent seismicity rate changes, the number of events with locations in the regions with a seismicity rate increase was 11% more than in the regions with a seismicity rate decrease.

Short-Term Wind Speed Forecasting for Power System Operations

KAUST Repository

Zhu, Xinxin

2012-04-01

The emphasis on renewable energy and concerns about the environment have led to large-scale wind energy penetration worldwide. However, there are also significant challenges associated with the use of wind energy due to the intermittent and unstable nature of wind. High-quality short-term wind speed forecasting is critical to reliable and secure power system operations. This article begins with an overview of the current status of worldwide wind power developments and future trends. It then reviews some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented. © 2012 The Authors. International Statistical Review © 2012 International Statistical Institute.

Non-seismic tsunamis: filling the forecast gap

Science.gov (United States)

Moore, C. W.; Titov, V. V.; Spillane, M. C.

2015-12-01

Earthquakes are the generation mechanism in over 85% of tsunamis. However, non-seismic tsunamis, including those generated by meteorological events, landslides, volcanoes, and asteroid impacts, can inundate significant area and have a large far-field effect. The current National Oceanographic and Atmospheric Administration (NOAA) tsunami forecast system falls short in detecting these phenomena. This study attempts to classify the range of effects possible from these non-seismic threats, and to investigate detection methods appropriate for use in a forecast system. Typical observation platforms are assessed, including DART bottom pressure recorders and tide gauges. Other detection paths include atmospheric pressure anomaly algorithms for detecting meteotsunamis and the early identification of asteroids large enough to produce a regional hazard. Real-time assessment of observations for forecast use can provide guidance to mitigate the effects of a non-seismic tsunami.

Catastrophic Failure and Critical Scaling Laws of Fiber Bundle Material

Directory of Open Access Journals (Sweden)

Shengwang Hao

2017-05-01

Full Text Available This paper presents a spring-fiber bundle model used to describe the failure process induced by energy release in heterogeneous materials. The conditions that induce catastrophic failure are determined by geometric conditions and energy equilibrium. It is revealed that the relative rates of deformation of, and damage to the fiber bundle with respect to the boundary controlling displacement ε0 exhibit universal power law behavior near the catastrophic point, with a critical exponent of −1/2. The proportion of the rate of response with respect to acceleration exhibits a linear relationship with increasing displacement in the vicinity of the catastrophic point. This allows for the prediction of catastrophic failure immediately prior to failure by extrapolating the trajectory of this relationship as it asymptotes to zero. Monte Carlo simulations are completed and these two critical scaling laws are confirmed.

A severe blizzard event in Romania – a case study

Directory of Open Access Journals (Sweden)

F. Georgescu

2009-04-01

Full Text Available During winter cold strong winds associated with snowfalls are not unusual for South and Southeastern Romania. The episode of 2–4 January 2008 was less usual due to its intensity and persistence. It happened after a long period (autumn 2006–autumn 2007 of mainly southerly circulations inducing warm weather, when the absolute record of the maximum temperature was registered. The important snowfalls and snowdrifts, leading to a consistent snow layer (up to 100 cm, produced serious transport and electricity supply perturbations.

Since this atypical local weather event was not correctly represented by the operational numerical forecasts, several cross-comparison numerical simulations were performed to analyze the relative role of the coupler/coupling models and to compare two ways of process-scale uncertainties mitigation: optimizing the forecast range and performing ensemble forecast through the perturbation of the lateral boundary conditions. The results underline, for this case, the importance of physical parametrization package on the first place and secondary, the importance of the model horizontal resolution. The resolution increase is beneficial only in the local process representation; on larger scale it may either improve or decrease the accuracy effect, depending on the specified nudging between large-scale and small-scale information. The event capture is likely to be favored by two elements: a more appropriate time-scale of the event's physics and the quality of the transmitted large-scale information. Concerning the time scale, the statistics on skill as a function of forecast range are shown to be a useful tool in order to increase the accuracy of the numerical simulations. Ensembles forecasting versus resolution increase experiments indicate, for such atypical events, an interesting supply in the forecast accuracy through the ensemble method when applied to correct the minimum skill of the deterministic forecast.

Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change

Science.gov (United States)

Storer, Luke N.; Williams, Paul D.; Gill, Philip G.

2018-03-01

Atmospheric turbulence is a major hazard in the aviation industry and can cause injuries to passengers and crew. Understanding the physical and dynamical generation mechanisms of turbulence aids with the development of new forecasting algorithms and, therefore, reduces the impact that it has on the aviation industry. The scope of this paper is to review the dynamics of aviation turbulence, its response to climate change, and current forecasting methods at the cruising altitude of aircraft. Aviation-affecting turbulence comes from three main sources: vertical wind shear instabilities, convection, and mountain waves. Understanding these features helps researchers to develop better turbulence diagnostics. Recent research suggests that turbulence will increase in frequency and strength with climate change, and therefore, turbulence forecasting may become more important in the future. The current methods of forecasting are unable to predict every turbulence event, and research is ongoing to find the best solution to this problem by combining turbulence predictors and using ensemble forecasts to increase skill. The skill of operational turbulence forecasts has increased steadily over recent decades, mirroring improvements in our understanding. However, more work is needed—ideally in collaboration with the aviation industry—to improve observations and increase forecast skill, to help maintain and enhance aviation safety standards in the future.

The Effectiveness of Catastrophe Bonds in Portfolio Diversification

OpenAIRE

Mariani, Massimo; Amoruso, Paola

2016-01-01

The rapid growth of catastrophe bonds in financial markets is due to increasing environmental disasters and consequent economic losses, barely covered by insurance and reinsurance companies. These securities represent an effective solution, allowing the risk transfer to the capital market. The objective of this paper is to prove real advantages of the investor who operates in this market segment, in terms of portfolio diversification. The present work indeed shows how investing in catastrophe...

Forecasting the heavy rainfall during Himalayan flooding—June 2013

Directory of Open Access Journals (Sweden)

Anumeha Dube

2014-08-01

Verification of the synoptic features in forecasts of the two models suggests that NCUM accurately captures the circulation features as compared to T574. Further verification of this event is carried out based on the contiguous rain area (CRA technique. CRA verification is used in computing the total mean square error (MSE which is based on displacement, volume and pattern errors. This verification technique also, confirms the better skill of NCUM over T574 in terms of forecast peak rainfall amounts, volume and average rain rate, lower MSE and root mean square error (RMSE as well as having higher hit rates and lower misses and false alarm rates for different rainfall thresholds from Day 1 to Day 5 forecasts.

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-23

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

An application of Mean Escape Time and metapopulation on forestry catastrophe insurance

Science.gov (United States)

Li, Jiangcheng; Zhang, Chunmin; Liu, Jifa; Li, Zhen; Yang, Xuan

2018-04-01

A forestry catastrophe insurance model due to forestry pest infestations and disease epidemics is developed by employing metapopulation dynamics and statistics properties of Mean Escape Time (MET). The probability of outbreak of forestry catastrophe loss and the catastrophe loss payment time with MET are respectively investigated. Forestry loss data in China is used for model simulation. Experimental results are concluded as: (1) The model with analytical results is shown to be a better fit; (2) Within the condition of big area of patches and structure of patches, high system factor, low extinction rate, high multiplicative noises, and additive noises with a high cross-correlated strength range, an outbreak of forestry catastrophe loss or catastrophe loss payment due to forestry pest infestations and disease epidemics could occur; (3) An optimal catastrophe loss payment time MET due to forestry pest infestations and disease epidemics can be identified by taking proper value of multiplicative noises and limits the additive noises on a low range of value, and cross-correlated strength at a high range of value.

Continental and global scale flood forecasting systems

NARCIS (Netherlands)

Emerton, Rebecca E.; Stephens, Elisabeth M.; Pappenberger, Florian; Pagano, Thomas P.; Weerts, A.H.; Wood, A.; Salamon, Peter; Brown, James D.; Hjerdt, Niclas; Donnelly, Chantal; Baugh, Calum A.; Cloke, Hannah L.

2016-01-01

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not

Pan-European stochastic flood event set

Science.gov (United States)

Kadlec, Martin; Pinto, Joaquim G.; He, Yi; Punčochář, Petr; Kelemen, Fanni D.; Manful, Desmond; Palán, Ladislav

2017-04-01

Impact Forecasting (IF), the model development center of Aon Benfield, has been developing a large suite of catastrophe flood models on probabilistic bases for individual countries in Europe. Such natural catastrophes do not follow national boundaries: for example, the major flood in 2016 was responsible for the Europe's largest insured loss of USD3.4bn and affected Germany, France, Belgium, Austria and parts of several other countries. Reflecting such needs, IF initiated a pan-European flood event set development which combines cross-country exposures with country based loss distributions to provide more insightful data to re/insurers. Because the observed discharge data are not available across the whole Europe in sufficient quantity and quality to permit a detailed loss evaluation purposes, a top-down approach was chosen. This approach is based on simulating precipitation from a GCM/RCM model chain followed by a calculation of discharges using rainfall-runoff modelling. IF set up this project in a close collaboration with Karlsruhe Institute of Technology (KIT) regarding the precipitation estimates and with University of East Anglia (UEA) in terms of the rainfall-runoff modelling. KIT's main objective is to provide high resolution daily historical and stochastic time series of key meteorological variables. A purely dynamical downscaling approach with the regional climate model COSMO-CLM (CCLM) is used to generate the historical time series, using re-analysis data as boundary conditions. The resulting time series are validated against the gridded observational dataset E-OBS, and different bias-correction methods are employed. The generation of the stochastic time series requires transfer functions between large-scale atmospheric variables and regional temperature and precipitation fields. These transfer functions are developed for the historical time series using reanalysis data as predictors and bias-corrected CCLM simulated precipitation and temperature as

Purchase of Catastrophe Insurance by Dutch Dairy and Arable Farmers

NARCIS (Netherlands)

Ogurtsov, V.; Asseldonk, van M.A.P.M.; Huirne, R.B.M.

2009-01-01

This article analyzed the impact of risk perception, risk attitude, and other farmer personal and farm characteristics on the actual purchase of catastrophe insurance by Dutch dairy and arable farmers. The specific catastrophe insurance types considered were hail–fire–storm insurance for buildings,

Creep and slip: Seismic precursors to the Nuugaatsiaq landslide (Greenland)

Science.gov (United States)

Poli, Piero

2017-09-01

Precursory signals to material's failure are predicted by numerical models and observed in laboratory experiments or using field data. These precursory signals are a marker of slip acceleration on weak regions, such as crustal faults. Observation of these precursory signals of catastrophic natural events, such as earthquakes and landslides, is necessary for improving our knowledge about the physics of the nucleation process. Furthermore, observing such precursory signals may help to forecast these catastrophic events or reduce their hazard. I report here the observation of seismic precursors to the Nuugaatsiaq landslide in Greenland. Time evolution of the detected precursors implies that an aseismic slip event is taking place for hours before the landslide, with an exponential increase of slip velocity. Furthermore, time evolution of the precursory signals' amplitude sheds light on the evolution of the fault physics during the nucleation process.

Ascertaining the impact of catastrophic events on dengue outbreak: The 2014 gas explosions in Kaohsiung, Taiwan

Science.gov (United States)

2017-01-01

Infectious disease outbreaks often occur in the aftermath of catastrophic events, either natural or man-made. While natural disasters such as typhoons/hurricanes, flooding and earthquakes have been known to increase the risk of infectious disease outbreak, the impact of anthropogenic disasters is less well-understood. Kaohsiung City is located in southern Taiwan, where most dengue outbreaks had occurred in the past two decades. It is also the center of petrochemical industry in Taiwan with pipelines running underneath city streets. Multiple underground gas explosions occurred in Kaohsiung in the evening of July 31, 2014 due to chemical leaks in the pipelines. The explosions caused 32 deaths, including five firefighters and two volunteer firefighters, and injured 321 persons. Historically, dengue outbreaks in southern Taiwan occurred mostly in small numbers of around 2000 cases or less, except in 2002 with over 5000 cases. However, in the months after the gas explosions, the city reported 14528 lab-confirmed dengue cases from August to December. To investigate the possible impact, if any, of the gas explosions on this record-breaking dengue outbreak, a simple mathematical model, the Richards model, is utilized to study the temporal patterns of the spread of dengue in the districts of Kaohsiung in the proximity of the explosion sites and to pinpoint the waves of infections that had occurred in each district in the aftermath of the gas explosions. The reproduction number of each wave in each district is also computed. In the aftermath of the gas explosions, early waves occurred 4–5 days (which coincides with the minimum of human intrinsic incubation period for dengue) later in districts with multiple waves. The gas explosions likely impacted the timing of the waves, but their impact on the magnitude of the 2014 outbreak remains unclear. The modeling suggests the need for public health surveillance and preparedness in the aftermath of future disasters. PMID:28520740

Short-term Inundation Forecasting for Tsunamis Version 4.0 Brings Forecasting Speed, Accuracy, and Capability Improvements to NOAA's Tsunami Warning Centers

Science.gov (United States)

Sterling, K.; Denbo, D. W.; Eble, M. C.

2016-12-01

Short-term Inundation Forecasting for Tsunamis (SIFT) software was developed by NOAA's Pacific Marine Environmental Laboratory (PMEL) for use in tsunami forecasting and has been used by both U.S. Tsunami Warning Centers (TWCs) since 2012, when SIFTv3.1 was operationally accepted. Since then, advancements in research and modeling have resulted in several new features being incorporated into SIFT forecasting. Following the priorities and needs of the TWCs, upgrades to SIFT forecasting were implemented into SIFTv4.0, scheduled to become operational in October 2016. Because every minute counts in the early warning process, two major time saving features were implemented in SIFT 4.0. To increase processing speeds and generate high-resolution flooding forecasts more quickly, the tsunami propagation and inundation codes were modified to run on Graphics Processing Units (GPUs). To reduce time demand on duty scientists during an event, an automated DART inversion (or fitting) process was implemented. To increase forecasting accuracy, the forecasted amplitudes and inundations were adjusted to include dynamic tidal oscillations, thereby reducing the over-estimates of flooding common in SIFTv3.1 due to the static tide stage conservatively set at Mean High Water. Further improvements to forecasts were gained through the assimilation of additional real-time observations. Cabled array measurements from Bottom Pressure Recorders (BPRs) in the Oceans Canada NEPTUNE network are now available to SIFT for use in the inversion process. To better meet the needs of harbor masters and emergency managers, SIFTv4.0 adds a tsunami currents graphical product to the suite of disseminated forecast results. When delivered, these new features in SIFTv4.0 will improve the operational tsunami forecasting speed, accuracy, and capabilities at NOAA's Tsunami Warning Centers.

The Henetus wave forecast system in the Adriatic Sea

Directory of Open Access Journals (Sweden)

L. Bertotti

2011-11-01

Full Text Available We describe the Henetus wave forecast system in the Adriatic Sea. Operational since 1996, the system is continuously upgraded, especially through the correction of the input ECMWF wind fields. As these fields are of progressively improved quality with the increasing resolution of the meteorological model, the correction needs to be correspondingly updated. This ensures a practically constant quality of the Henetus results in the Adriatic Sea since 1996. After suitable and extended validation of the quality of the results at different forecast ranges, the operational range has been recently extended to five days. The Henetus results are used also to improve the tidal forecast on the Venetian coasts and the Venice lagoon, particularly during the most severe events. Extensive statistics on the model performance are provided, both as analysis and forecast, by comparing the model results versus both satellite and buoy data.

Spatiotemporal drought forecasting using nonlinear models

Science.gov (United States)

Vasiliades, Lampros; Loukas, Athanasios

2010-05-01

Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

A probabilistic strategy for parametric catastrophe insurance

Science.gov (United States)

Figueiredo, Rui; Martina, Mario; Stephenson, David; Youngman, Benjamin

2017-04-01

Economic losses due to natural hazards have shown an upward trend since 1980, which is expected to continue. Recent years have seen a growing worldwide commitment towards the reduction of disaster losses. This requires effective management of disaster risk at all levels, a part of which involves reducing financial vulnerability to disasters ex-ante, ensuring that necessary resources will be available following such events. One way to achieve this is through risk transfer instruments. These can be based on different types of triggers, which determine the conditions under which payouts are made after an event. This study focuses on parametric triggers, where payouts are determined by the occurrence of an event exceeding specified physical parameters at a given location, or at multiple locations, or over a region. This type of product offers a number of important advantages, and its adoption is increasing. The main drawback of parametric triggers is their susceptibility to basis risk, which arises when there is a mismatch between triggered payouts and the occurrence of loss events. This is unavoidable in said programmes, as their calibration is based on models containing a number of different sources of uncertainty. Thus, a deterministic definition of the loss event triggering parameters appears flawed. However, often for simplicity, this is the way in which most parametric models tend to be developed. This study therefore presents an innovative probabilistic strategy for parametric catastrophe insurance. It is advantageous as it recognizes uncertainties and minimizes basis risk while maintaining a simple and transparent procedure. A logistic regression model is constructed here to represent the occurrence of loss events based on certain loss index variables, obtained through the transformation of input environmental variables. Flood-related losses due to rainfall are studied. The resulting model is able, for any given day, to issue probabilities of occurrence of loss

Usages des TIC et rapports a l’incertitude en situation de catastrophes naturelles

Directory of Open Access Journals (Sweden)

Claire Brossaud

2008-11-01

Full Text Available Cet article montre comment des professionnels et des sinistrés qui ont été confrontés à des catastrophes naturelles sur trois territoires distincts - la tempête à Limoges en 1999, les inondations à Abbeville (2001 et à Bourg-en-Bresse (2005 - ont construit une histoire commune du risque au moyen des technologies de l’information et de la communication (TIC : Internet, téléphone portable, bases de données, outils de travail partagés, etc. Les usages des TIC sont d’abord resitués concrètement avant, pendant et après les événements dans un contexte historique où les sciences et techniques sont de plus en plus sollicitées pour réduire les incertitudes liées aux menaces sanitaires et écologiques. On voit ensuite s’élaborer une culture du risque sur la base de compétences socio-cognitives et relationnelles particulières face aux événements et à leur prise en charge technologique. Nous examinons en dernier ressort le rôle des TIC dans l’apprentissage d’une argumentation et d’une délibération collective sur les catastrophes, notamment grâce à la mise en place d’outils dédiés à l’étude sur le site http://www.technorisque.net.This article shows how professionnals and disaster victims involved in natural catastrophes in three different areas - Limoges storm in 1999, Abbeville and Bourg-en-Bresse floods in 2001 and 2005 – built a commun risk story with Information and communication technologies (ICT : Internet, mobiles, data bases, groupware, etc. At first, ICT uses are concretely approached before, during and after the events in a historic context where sciences and technology are growing up to reduce uncertainties of medical and ecological threats. Then, in the second part of this article, a risk culture is supported by socio-cognitive and relationnal competences towards events and their technological holding. At last, we examine ICT place in a collective argumentation and deliberation about the

Protocols of a catastrophe

International Nuclear Information System (INIS)

Stscherbak, J.

1988-01-01

In unusually frank terms the author, a journalist and epidemiologist, describes the catastrophe of Chernobyl as the 'most pathetic and important' experience of the Soviet people after World War II. Documents, interviews and statements of persons concerned trace the disaster of those days that surpasses imagination and describe how individual persons witnessed the coming true of visions of terror. (orig./HSCH) [de

Cosmic Catastrophes

Science.gov (United States)

Wheeler, J. Craig

2014-08-01

Preface; 1. Setting the stage: star formation and hydrogen burning in single stars; 2. Stellar death: the inexorable grip of gravity; 3. Dancing with stars: binary stellar evolution; 4. Accretion disks: flat stars; 5. White Dwarfs: quantum dots; 6. Supernovae: stellar catastrophes; 7. Supernova 1987A: lessons and enigmas; 8. Neutron stars: atoms with attitude; 9. Black holes in theory: into the abyss; 10. Black holes in fact: exploring the reality; 11. Gamma-ray bursts, black holes and the universe: long, long ago and far, far away; 12. Supernovae and the universe; 13. Worm holes and time machines: tunnels in space and time; 14. Beyond: the frontiers; Index.

Short-Term fo F2 Forecast: Present Day State of Art

Science.gov (United States)

Mikhailov, A. V.; Depuev, V. H.; Depueva, A. H.

An analysis of the F2-layer short-term forecast problem has been done. Both objective and methodological problems prevent us from a deliberate F2-layer forecast issuing at present. An empirical approach based on statistical methods may be recommended for practical use. A forecast method based on a new aeronomic index (a proxy) AI has been proposed and tested over selected 64 severe storm events. The method provides an acceptable prediction accuracy both for strongly disturbed and quiet conditions. The problems with the prediction of the F2-layer quiet-time disturbances as well as some other unsolved problems are discussed

Predicting emergency department volume using forecasting methods to create a "surge response" for noncrisis events.

Science.gov (United States)

Chase, Valerie J; Cohn, Amy E M; Peterson, Timothy A; Lavieri, Mariel S

2012-05-01

This study investigated whether emergency department (ED) variables could be used in mathematical models to predict a future surge in ED volume based on recent levels of use of physician capacity. The models may be used to guide decisions related to on-call staffing in non-crisis-related surges of patient volume. A retrospective analysis was conducted using information spanning July 2009 through June 2010 from a large urban teaching hospital with a Level I trauma center. A comparison of significance was used to assess the impact of multiple patient-specific variables on the state of the ED. Physician capacity was modeled based on historical physician treatment capacity and productivity. Binary logistic regression analysis was used to determine the probability that the available physician capacity would be sufficient to treat all patients forecasted to arrive in the next time period. The prediction horizons used were 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 8 hours, and 12 hours. Five consecutive months of patient data from July 2010 through November 2010, similar to the data used to generate the models, was used to validate the models. Positive predictive values, Type I and Type II errors, and real-time accuracy in predicting noncrisis surge events were used to evaluate the forecast accuracy of the models. The ratio of new patients requiring treatment over total physician capacity (termed the care utilization ratio [CUR]) was deemed a robust predictor of the state of the ED (with a CUR greater than 1 indicating that the physician capacity would not be sufficient to treat all patients forecasted to arrive). Prediction intervals of 30 minutes, 8 hours, and 12 hours performed best of all models analyzed, with deviances of 1.000, 0.951, and 0.864, respectively. A 95% significance was used to validate the models against the July 2010 through November 2010 data set. Positive predictive values ranged from 0.738 to 0.872, true positives ranged from 74% to 94%, and

Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

Science.gov (United States)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

2017-04-01

reliability diagram. This study covers 10 nordic watersheds. We show that forecast performance according to the CRPS varies with lead-time but also with the period of the year. The raw forecasts from the ECMWF System4 display important biases for both temperature and precipitation, which need to be corrected. The linear scaling method is used for this purpose and is found effective. Bias correction improves forecasts performance, especially during the summer when the precipitations are over-estimated. According to the CRPS, bias corrected forecasts from System4 show performances comparable to those of the ESP system. However, the Ignorance score, which penalizes the lack of calibration (under-dispersive forecasts in this case) more severely than the CRPS, provides a different outlook for the comparison of the two systems. In fact, according to the Ignorance score, the ESP system outperforms forecasts based on System4 in most cases. This illustrates that the joint use of several metrics is crucial to assess the quality of a forecasts system thoroughly. Globally, ESP provide reliable forecasts which can be over-dispersed whereas bias corrected ECMWF System4 forecasts are sharper but at the risk of missing events.

Assessing flood forecast uncertainty with fuzzy arithmetic

Directory of Open Access Journals (Sweden)

de Bruyn Bertrand

2016-01-01

Full Text Available Providing forecasts for flow rates and water levels during floods have to be associated with uncertainty estimates. The forecast sources of uncertainty are plural. For hydrological forecasts (rainfall-runoff performed using a deterministic hydrological model with basic physics, two main sources can be identified. The first obvious source is the forcing data: rainfall forecast data are supplied in real time by meteorological forecasting services to the Flood Forecasting Service within a range between a lowest and a highest predicted discharge. These two values define an uncertainty interval for the rainfall variable provided on a given watershed. The second source of uncertainty is related to the complexity of the modeled system (the catchment impacted by the hydro-meteorological phenomenon, the number of variables that may describe the problem and their spatial and time variability. The model simplifies the system by reducing the number of variables to a few parameters. Thus it contains an intrinsic uncertainty. This model uncertainty is assessed by comparing simulated and observed rates for a large number of hydro-meteorological events. We propose a method based on fuzzy arithmetic to estimate the possible range of flow rates (and levels of water making a forecast based on possible rainfalls provided by forcing and uncertainty model. The model uncertainty is here expressed as a range of possible values. Both rainfall and model uncertainties are combined with fuzzy arithmetic. This method allows to evaluate the prediction uncertainty range. The Flood Forecasting Service of Oise and Aisne rivers, in particular, monitors the upstream watershed of the Oise at Hirson. This watershed’s area is 310 km2. Its response time is about 10 hours. Several hydrological models are calibrated for flood forecasting in this watershed and use the rainfall forecast. This method presents the advantage to be easily implemented. Moreover, it permits to be carried out

Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

Science.gov (United States)

Jha, Sanjeev K.; Shrestha, Durga L.; Stadnyk, Tricia A.; Coulibaly, Paulin

2018-03-01

Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP) models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs) are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP), developed in Australia (Robertson et al., 2013; Shrestha et al., 2015), has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS) Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS), from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

Coupled atmosphere-ocean-wave simulations of a storm event over the Gulf of Lion and Balearic Sea

Science.gov (United States)

Renault, Lionel; Chiggiato, Jacopo; Warner, John C.; Gomez, Marta; Vizoso, Guillermo; Tintore, Joaquin

2012-01-01

The coastal areas of the North-Western Mediterranean Sea are one of the most challenging places for ocean forecasting. This region is exposed to severe storms events that are of short duration. During these events, significant air-sea interactions, strong winds and large sea-state can have catastrophic consequences in the coastal areas. To investigate these air-sea interactions and the oceanic response to such events, we implemented the Coupled Ocean-Atmosphere-Wave-Sediment Transport Modeling System simulating a severe storm in the Mediterranean Sea that occurred in May 2010. During this event, wind speed reached up to 25 m.s-1 inducing significant sea surface cooling (up to 2°C) over the Gulf of Lion (GoL) and along the storm track, and generating surface waves with a significant height of 6 m. It is shown that the event, associated with a cyclogenesis between the Balearic Islands and the GoL, is relatively well reproduced by the coupled system. A surface heat budget analysis showed that ocean vertical mixing was a major contributor to the cooling tendency along the storm track and in the GoL where turbulent heat fluxes also played an important role. Sensitivity experiments on the ocean-atmosphere coupling suggested that the coupled system is sensitive to the momentum flux parameterization as well as air-sea and air-wave coupling. Comparisons with available atmospheric and oceanic observations showed that the use of the fully coupled system provides the most skillful simulation, illustrating the benefit of using a fully coupled ocean-atmosphere-wave model for the assessment of these storm events.

Earthquake focal mechanism forecasting in Italy for PSHA purposes

Science.gov (United States)

Roselli, Pamela; Marzocchi, Warner; Mariucci, Maria Teresa; Montone, Paola

2018-01-01

In this paper, we put forward a procedure that aims to forecast focal mechanism of future earthquakes. One of the primary uses of such forecasts is in probabilistic seismic hazard analysis (PSHA); in fact, aiming at reducing the epistemic uncertainty, most of the newer ground motion prediction equations consider, besides the seismicity rates, the forecast of the focal mechanism of the next large earthquakes as input data. The data set used to this purpose is relative to focal mechanisms taken from the latest stress map release for Italy containing 392 well-constrained solutions of events, from 1908 to 2015, with Mw ≥ 4 and depths from 0 down to 40 km. The data set considers polarity focal mechanism solutions until to 1975 (23 events), whereas for 1976-2015, it takes into account only the Centroid Moment Tensor (CMT)-like earthquake focal solutions for data homogeneity. The forecasting model is rooted in the Total Weighted Moment Tensor concept that weighs information of past focal mechanisms evenly distributed in space, according to their distance from the spatial cells and magnitude. Specifically, for each cell of a regular 0.1° × 0.1° spatial grid, the model estimates the probability to observe a normal, reverse, or strike-slip fault plane solution for the next large earthquakes, the expected moment tensor and the related maximum horizontal stress orientation. These results will be available for the new PSHA model for Italy under development. Finally, to evaluate the reliability of the forecasts, we test them with an independent data set that consists of some of the strongest earthquakes with Mw ≥ 3.9 occurred during 2016 in different Italian tectonic provinces.

CLUJ-NAPOCA PRECIPITATION FORECAST USING WSR-98D DOPPLER RADAR

Directory of Open Access Journals (Sweden)

Narcis MAIER

2011-11-01

Full Text Available CLUJ-NAPOCA precipitation forecast using WSR-98D Doppler radar. Forecasting inundations requires accurate spatial and temporal estimation of rainfalls in an area. Depending on the Z-R relationship (reflectivity-precipitation rate, the thresholds, maximum reflectivity data processing, VIL, cloud height or speed, provided by the WSR-98D affects the estimated precipitation used in the prediction of inundations. How much precipitation receives a watershed during an extreme event and what response will result depends on the basin hydrographic characteristics. A study of summer weather events between the years 2004-2008 and a new method in establishing relations between the radar estimated and recorded precipitations led to the determination of new relations between them which will balance the connections between them.

Fukushinobyl, the impossible catastrophe

International Nuclear Information System (INIS)

Boceno, Laurent

2012-01-01

With the emergence of variety of health and environmental crisis or catastrophes (Seveso, Bhopal, Chernobyl, AIDS, contaminated blood, mad cow, influenzas), the author proposes thoughts about the fact that it seems we are not in the era of industrial societies any longer, but in that of societies of risk. He more particularly focuses on Chernobyl and Fukushima to analyse how a social framework is built up to integrate forms of institutionalisation of multifaceted vulnerability, these institutional logics becoming latent social pathologies. In this respect, he more particularly discusses the catastrophic share of nuclear. He shows how what can be considered as a risk is socialised, dissimulated by priority, and then addresses the management of consequences of Chernobyl and how it is used to address the Japanese present situation. He notably outlines a kind of collusion between the WHO and the IAEA about nuclear issues. In his respect, he recalls a statement made by the WHO saying that, from a mental health point of view, the most satisfying solution for the future of pacific uses of nuclear energy would be the emergence of a new generation who would have learned to cope with ignorance and uncertainty

An assessment of the ECMWF tropical cyclone ensemble forecasting system and its use for insurance loss predictions

Science.gov (United States)

Aemisegger, F.; Martius, O.; Wüest, M.

2010-09-01

Tropical cyclones (TC) are amongst the most impressive and destructive weather systems of Earth's atmosphere. The costs related to such intense natural disasters have been rising in recent years and may potentially continue to increase in the near future due to changes in magnitude, timing, duration or location of tropical storms. This is a challenging situation for numerical weather prediction, which should provide a decision basis for short term protective measures through high quality medium range forecasts on the one hand. On the other hand, the insurance system bears great responsibility in elaborating proactive plans in order to face these extreme events that individuals cannot manage independently. Real-time prediction and early warning systems are needed in the insurance sector in order to face an imminent hazard and minimise losses. Early loss estimates are important in order to allocate capital and to communicate to investors. The ECMWF TC identification algorithm delivers information on the track and intensity of storms based on the ensemble forecasting system. This provides a physically based framework to assess the uncertainty in the forecast of a specific event. The performance of the ECMWF TC ensemble forecasts is evaluated in terms of cyclone intensity and location in this study and the value of such a physically-based quantification of uncertainty in the meteorological forecast for the estimation of insurance losses is assessed. An evaluation of track and intensity forecasts of hurricanes in the North Atlantic during the years 2005 to 2009 is carried out. Various effects are studied like the differences in forecasts over land or sea, as well as links between storm intensity and forecast error statistics. The value of the ECMWF TC forecasting system for the global re-insurer Swiss Re was assessed by performing insurance loss predictions using their in-house loss model for several case studies of particularly devastating events. The generally known

Forecast Combinations

OpenAIRE

Timmermann, Allan G

2005-01-01

Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

Dynamical systems V bifurcation theory and catastrophe theory

CERN Document Server

1994-01-01

Bifurcation theory and catastrophe theory are two of the best known areas within the field of dynamical systems. Both are studies of smooth systems, focusing on properties that seem to be manifestly non-smooth. Bifurcation theory is concerned with the sudden changes that occur in a system when one or more parameters are varied. Examples of such are familiar to students of differential equations, from phase portraits. Moreover, understanding the bifurcations of the differential equations that describe real physical systems provides important information about the behavior of the systems. Catastrophe theory became quite famous during the 1970's, mostly because of the sensation caused by the usually less than rigorous applications of its principal ideas to "hot topics", such as the characterization of personalities and the difference between a "genius" and a "maniac". Catastrophe theory is accurately described as singularity theory and its (genuine) applications. The authors of this book, the first printing of w...

Effects of Cognitive-Behavioral Therapy (CBT) on Brain Connectivity Supporting Catastrophizing in Fibromyalgia.

Science.gov (United States)

Lazaridou, Asimina; Kim, Jieun; Cahalan, Christine M; Loggia, Marco L; Franceschelli, Olivia; Berna, Chantal; Schur, Peter; Napadow, Vitaly; Edwards, Robert R

2017-03-01

Fibromyalgia (FM) is a chronic, common pain disorder characterized by hyperalgesia. A key mechanism by which cognitive-behavioral therapy (CBT) fosters improvement in pain outcomes is via reductions in hyperalgesia and pain-related catastrophizing, a dysfunctional set of cognitive-emotional processes. However, the neural underpinnings of these CBT effects are unclear. Our aim was to assess CBT's effects on the brain circuitry underlying hyperalgesia in FM patients, and to explore the role of treatment-associated reduction in catastrophizing as a contributor to normalization of pain-relevant brain circuitry and clinical improvement. In total, 16 high-catastrophizing FM patients were enrolled in the study and randomized to 4 weeks of individual treatment with either CBT or a Fibromyalgia Education (control) condition. Resting state functional magnetic resonance imaging scans evaluated functional connectivity between key pain-processing brain regions at baseline and posttreatment. Clinical outcomes were assessed at baseline, posttreatment, and 6-month follow-up. Catastrophizing correlated with increased resting state functional connectivity between S1 and anterior insula. The CBT group showed larger reductions (compared with the education group) in catastrophizing at posttreatment (PCBT produced significant reductions in both pain and catastrophizing at the 6-month follow-up (PCBT group also showed reduced resting state connectivity between S1 and anterior/medial insula at posttreatment; these reductions in resting state connectivity were associated with concurrent treatment-related reductions in catastrophizing. The results add to the growing support for the clinically important associations between S1-insula connectivity, clinical pain, and catastrophizing, and suggest that CBT may, in part via reductions in catastrophizing, help to normalize pain-related brain responses in FM.

Forecaster Behaviour and Bias in Macroeconomic Forecasts

OpenAIRE

Roy Batchelor

2007-01-01

This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

West-WRF Sensitivity to Sea Surface Temperature Boundary Condition in California Precipitation Forecasts of AR Related Events

Science.gov (United States)

Zhang, X.; Cornuelle, B. D.; Martin, A.; Weihs, R. R.; Ralph, M.

2017-12-01

We evaluated the merit in coastal precipitation forecasts by inclusion of high resolution sea surface temperature (SST) from blended satellite and in situ observations as a boundary condition (BC) to the Weather Research and Forecast (WRF) mesoscale model through simple perturbation tests. Our sensitivity analyses shows that the limited improvement of watershed scale precipitation forecast is credible. When only SST BC is changed, there is an uncertainty introduced because of artificial model state equilibrium and the nonlinear nature of the WRF model system. With the change of SST on the order of a fraction of a degree centigrade, we found that the part of random perturbation forecast response is saturated after 48 hours when it reaches to the order magnitude of the linear response. It is important to update the SST at a shorter time period, so that the independent excited nonlinear modes can cancel each other. The uncertainty in our SST configuration is quantitatively equivalent to adding to a spatially uncorrelated Guasian noise of zero mean and 0.05 degree of standard deviation to the SST. At this random noise perturbation magnitude, the ensemble average behaves well within a convergent range. It is also found that the sensitivity of forecast changes in response to SST changes. This is measured by the ratio of the spatial variability of mean of the ensemble perturbations over the spatial variability of the corresponding forecast. The ratio is about 10% for surface latent heat flux, 5 % for IWV, and less than 1% for surface pressure.

Catastrophic antiphospholipid syndrome mimicking a malignant pancreatic tumour--a case report

NARCIS (Netherlands)

van Wissen, S.; Bastiaansen, B. A. J.; Stroobants, A. K.; van den Dool, E. J.; Idu, M. M.; Levi, M. [=Marcel M.; Stroes, E. S. G.

2008-01-01

The catastrophic antiphospholipid syndrome is characterised by rapid onset thromboses, often resistant to conventional anticoagulant treatment, and resulting in life threatening multiple organ dysfunction. The diagnosis of catastrophic antiphospholipid syndrome may be difficult, predominantly due to

High-resolution simulation and forecasting of Jeddah floods using WRF version 3.5

KAUST Repository

Deng, Liping

2013-12-01

Modeling flash flood events in arid environments is a difficult but important task that has impacts on both water resource related issues and also emergency management and response. The challenge is often related to adequately describing the precursor intense rainfall events that cause these flood responses, as they are generally poorly simulated and forecast. Jeddah, the second largest city in the Kingdom of Saudi Arabia, has suffered from a number of flash floods over the last decade, following short-intense rainfall events. The research presented here focuses on examining four historic Jeddah flash floods (Nov. 25-26 2009, Dec. 29-30 2010, Jan. 14-15 2011 and Jan. 25-26 2011) and investigates the feasibility of using numerical weather prediction models to achieve a more realistic simulation of these flood-producing rainfall events. The Weather Research and Forecasting (WRF) model (version 3.5) is used to simulate precipitation and meteorological conditions via a high-resolution inner domain (1-km) around Jeddah. A range of different convective closure and microphysics parameterization, together with high-resolution (4-km) sea surface temperature data are employed. Through examining comparisons between the WRF model output and in-situ, radar and satellite data, the characteristics and mechanism producing the extreme rainfall events are discussed and the capacity of the WRF model to accurately forecast these rainstorms is evaluated.

High-resolution simulation and forecasting of Jeddah floods using WRF version 3.5

KAUST Repository

Deng, Liping; McCabe, Matthew; Stenchikov, Georgiy L.; Evans, Jason; Kucera, Paul

2013-01-01

Modeling flash flood events in arid environments is a difficult but important task that has impacts on both water resource related issues and also emergency management and response. The challenge is often related to adequately describing the precursor intense rainfall events that cause these flood responses, as they are generally poorly simulated and forecast. Jeddah, the second largest city in the Kingdom of Saudi Arabia, has suffered from a number of flash floods over the last decade, following short-intense rainfall events. The research presented here focuses on examining four historic Jeddah flash floods (Nov. 25-26 2009, Dec. 29-30 2010, Jan. 14-15 2011 and Jan. 25-26 2011) and investigates the feasibility of using numerical weather prediction models to achieve a more realistic simulation of these flood-producing rainfall events. The Weather Research and Forecasting (WRF) model (version 3.5) is used to simulate precipitation and meteorological conditions via a high-resolution inner domain (1-km) around Jeddah. A range of different convective closure and microphysics parameterization, together with high-resolution (4-km) sea surface temperature data are employed. Through examining comparisons between the WRF model output and in-situ, radar and satellite data, the characteristics and mechanism producing the extreme rainfall events are discussed and the capacity of the WRF model to accurately forecast these rainstorms is evaluated.

Forecast combinations

OpenAIRE

Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

2010-01-01

We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks

Science.gov (United States)

Clune, Jeff

2017-01-01

A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when learning new information erases previously learned information. Catastrophic forgetting occurs in artificial neural networks (ANNs), which have fueled most recent advances in AI. A recent paper proposed that catastrophic forgetting in ANNs can be reduced by promoting modularity, which can limit forgetting by isolating task information to specific clusters of nodes and connections (functional modules). While the prior work did show that modular ANNs suffered less from catastrophic forgetting, it was not able to produce ANNs that possessed task-specific functional modules, thereby leaving the main theory regarding modularity and forgetting untested. We introduce diffusion-based neuromodulation, which simulates the release of diffusing, neuromodulatory chemicals within an ANN that can modulate (i.e. up or down regulate) learning in a spatial region. On the simple diagnostic problem from the prior work, diffusion-based neuromodulation 1) induces task-specific learning in groups of nodes and connections (task-specific localized learning), which 2) produces functional modules for each subtask, and 3) yields higher performance by eliminating catastrophic forgetting. Overall, our results suggest that diffusion-based neuromodulation promotes task-specific localized learning and functional modularity, which can help solve the challenging, but important problem of catastrophic forgetting. PMID:29145413

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks.

Directory of Open Access Journals (Sweden)

Roby Velez

Full Text Available A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when learning new information erases previously learned information. Catastrophic forgetting occurs in artificial neural networks (ANNs, which have fueled most recent advances in AI. A recent paper proposed that catastrophic forgetting in ANNs can be reduced by promoting modularity, which can limit forgetting by isolating task information to specific clusters of nodes and connections (functional modules. While the prior work did show that modular ANNs suffered less from catastrophic forgetting, it was not able to produce ANNs that possessed task-specific functional modules, thereby leaving the main theory regarding modularity and forgetting untested. We introduce diffusion-based neuromodulation, which simulates the release of diffusing, neuromodulatory chemicals within an ANN that can modulate (i.e. up or down regulate learning in a spatial region. On the simple diagnostic problem from the prior work, diffusion-based neuromodulation 1 induces task-specific learning in groups of nodes and connections (task-specific localized learning, which 2 produces functional modules for each subtask, and 3 yields higher performance by eliminating catastrophic forgetting. Overall, our results suggest that diffusion-based neuromodulation promotes task-specific localized learning and functional modularity, which can help solve the challenging, but important problem of catastrophic forgetting.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

Science.gov (United States)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

Catastrophes in nature and society mathematical modeling of complex systems

CERN Document Server

Khlebopros, Rem G; Fet, Abram I

2007-01-01

Many people are concerned about crises leading to disasters in nature, in social and economic life. The book offers a popular account of the causative mechanisms of critical states and breakdown in a broad range of natural and cultural systems - which obey the same laws - and thus makes the reader aware of the origin of catastrophic events and the ways to avoid and mitigate their negative consequences. The authors apply a single mathematical approach to investigate the revolt of cancer cells that destroy living organisms and population outbreaks that upset natural ecosystems, the balance between biosphere and global climate interfered lately by industry, the driving mechanisms of market and related economic and social phenomena, as well as the electoral system the proper use of which is an arduous accomplishment of democracy.

Lupus-Negative Libman-Sacks Endocarditis Complicated by Catastrophic Antiphospholipid Syndrome.

Science.gov (United States)

Murtaza, Ghulam; Iskandar, Joy; Humphrey, Tara; Adhikari, Sujeen; Kuruvilla, Aneesh

2017-04-01

Libman-Sacks endocarditis is characterized by sterile and verrucous lesions that predominantly affect the aortic and mitral valves. In most cases, patients do not have significant valvular dysfunction. However, patients with significant valvular dysfunction may present with serious complications such as cardiac failure, arrhythmias, and thromboembolic events. Recently, association of Libman-Sacks endocarditis with antiphospholipid antibody syndrome (APS) has been made. APS is most commonly defined by venous and arterial thrombosis, recurrent pregnancy loss, and thrombocytopenia. While the syndrome can be a primary syndrome, it is usually secondary to systemic lupus erythematosus. Catastrophic antiphospholipid syndrome (CAPS) can be a life-threatening presentation of APS and can occur in 1% of patients with antiphospholipid syndrome. We present a very rare case of a young female patient with lupus-negative Libman-Sacks endocarditis complicated by CAPS.

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-07-26

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.

Application of Flood Nomograph for Flood Forecasting in Urban Areas

Directory of Open Access Journals (Sweden)

Eui Hoon Lee

2018-01-01

Full Text Available Imperviousness has increased due to urbanization, as has the frequency of extreme rainfall events by climate change. Various countermeasures, such as structural and nonstructural measures, are required to prepare for these effects. Flood forecasting is a representative nonstructural measure. Flood forecasting techniques have been developed for the prevention of repetitive flood damage in urban areas. It is difficult to apply some flood forecasting techniques using training processes because training needs to be applied at every usage. The other flood forecasting techniques that use rainfall data predicted by radar are not appropriate for small areas, such as single drainage basins. In this study, a new flood forecasting technique is suggested to reduce flood damage in urban areas. The flood nomograph consists of the first flooding nodes in rainfall runoff simulations with synthetic rainfall data at each duration. When selecting the first flooding node, the initial amount of synthetic rainfall is 1 mm, which increases in 1 mm increments until flooding occurs. The advantage of this flood forecasting technique is its simple application using real-time rainfall data. This technique can be used to prepare a preemptive response in the process of urban flood management.

Laboratory tests of catastrophic disruption of rotating bodies

Science.gov (United States)

Morris, A. J. W.; Burchell, M. J.

2017-11-01

The results of catastrophic disruption experiments on static and rotating targets are reported. The experiments used cement spheres of diameter 10 cm as the targets. Impacts were by mm sized stainless steel spheres at speeds of between 1 and 7.75 km s-1. Energy densities (Q) in the targets ranged from 7 to 2613 J kg-1. The experiments covered both the cratering and catastrophic disruption regimes. For static, i.e. non-rotating targets the critical energy density for disruption (Q*, the value of Q when the largest surviving target fragment has a mass equal to one half of the pre-impact target mass) was Q* = 1447 ± 90 J kg-1. For rotating targets (median rotation frequency of 3.44 Hz) we found Q* = 987 ± 349 J kg-1, a reduction of 32% in the mean value. This lower value of Q* for rotating targets was also accompanied by a larger scatter on the data, hence the greater uncertainty. We suggest that in some cases the rotating targets behaved as static targets, i.e. broke up with the same catastrophic disruption threshold, but in other cases the rotation helped the break up causing a lower catastrophic disruption threshold, hence both the lower value of Q* and the larger scatter on the data. The fragment mass distributions after impact were similar in both the static and rotating target experiments with similar slopes.

Pricing Zero-Coupon Catastrophe Bonds Using EVT with Doubly Stochastic Poisson Arrivals

Directory of Open Access Journals (Sweden)

Zonggang Ma

2017-01-01

Full Text Available The frequency and severity of climate abnormal change displays an irregular upward cycle as global warming intensifies. Therefore, this paper employs a doubly stochastic Poisson process with Black Derman Toy (BDT intensity to describe the catastrophic characteristics. By using the Property Claim Services (PCS loss index data from 2001 to 2010 provided by the US Insurance Services Office (ISO, the empirical result reveals that the BDT arrival rate process is superior to the nonhomogeneous Poisson and lognormal intensity process due to its smaller RMSE, MAE, MRPE, and U and larger E and d. Secondly, to depict extreme features of catastrophic risks, this paper adopts the Peak Over Threshold (POT in extreme value theory (EVT to characterize the tail characteristics of catastrophic loss distribution. And then the loss distribution is analyzed and assessed using a quantile-quantile (QQ plot to visually check whether the PCS index observations meet the generalized Pareto distribution (GPD assumption. Furthermore, this paper derives a pricing formula for zero-coupon catastrophe bonds with a stochastic interest rate environment and aggregate losses generated by a compound doubly stochastic Poisson process under the forward measure. Finally, simulation results verify pricing model predictions and show how catastrophic risks and interest rate risk affect the prices of zero-coupon catastrophe bonds.

Coupling meteorological and hydrological models for flood forecasting

Directory of Open Access Journals (Sweden)

Bartholmes

2005-01-01

Full Text Available This paper deals with the problem of analysing the coupling of meteorological meso-scale quantitative precipitation forecasts with distributed rainfall-runoff models to extend the forecasting horizon. Traditionally, semi-distributed rainfall-runoff models have been used for real time flood forecasting. More recently, increased computer capabilities allow the utilisation of distributed hydrological models with mesh sizes from tenths of metres to a few kilometres. On the other hand, meteorological models, providing the quantitative precipitation forecast, tend to produce average values on meshes ranging from slightly less than 10 to 200 kilometres. Therefore, to improve the quality of flood forecasts, the effects of coupling the meteorological and the hydrological models at different scales were analysed. A distributed hydrological model (TOPKAPI was developed and calibrated using a 1x1 km mesh for the case of the river Po closed at Ponte Spessa (catchment area c. 37000 km2. The model was then coupled with several other European meteorological models ranging from the Limited Area Models (provided by DMI and DWD with resolutions from 0.0625° * 0.0625°, to the ECMWF ensemble predictions with a resolution of 1.85° * 1.85°. Interesting results, describing the coupled model behaviour, are available for a meteorological extreme event in Northern Italy (Nov. 1994. The results demonstrate the poor reliability of the quantitative precipitation forecasts produced by meteorological models presently available; this is not resolved using the Ensemble Forecasting technique, when compared with results obtainable with measured rainfall.

Probabilistic short-term forecasting of eruption rate at Kīlauea Volcano using a physics-based model

Science.gov (United States)

Anderson, K. R.

2016-12-01

Deterministic models of volcanic eruptions yield predictions of future activity conditioned on uncertainty in the current state of the system. Physics-based eruption models are well-suited for deterministic forecasting as they can relate magma physics with a wide range of observations. Yet, physics-based eruption forecasting is strongly limited by an inadequate understanding of volcanic systems, and the need for eruption models to be computationally tractable. At Kīlauea Volcano, Hawaii, episodic depressurization-pressurization cycles of the magma system generate correlated, quasi-exponential variations in ground deformation and surface height of the active summit lava lake. Deflations are associated with reductions in eruption rate, or even brief eruptive pauses, and thus partly control lava flow advance rates and associated hazard. Because of the relatively well-understood nature of Kīlauea's shallow magma plumbing system, and because more than 600 of these events have been recorded to date, they offer a unique opportunity to refine a physics-based effusive eruption forecasting approach and apply it to lava eruption rates over short (hours to days) time periods. A simple physical model of the volcano ascribes observed data to temporary reductions in magma supply to an elastic reservoir filled with compressible magma. This model can be used to predict the evolution of an ongoing event, but because the mechanism that triggers events is unknown, event durations are modeled stochastically from previous observations. A Bayesian approach incorporates diverse data sets and prior information to simultaneously estimate uncertain model parameters and future states of the system. Forecasts take the form of probability distributions for eruption rate or cumulative erupted volume at some future time. Results demonstrate the significant uncertainties that still remain even for short-term eruption forecasting at a well-monitored volcano - but also the value of a physics

Financing Losses from Catastrophic Risks

Science.gov (United States)

2008-11-01

often held in the form of bonds, the interest on which is subject to corporate income tax , which reduces the net earnings to each insurer’s shareholders...course; it is a basic feature of the corporate income tax . But, as explained above, catastrophe insurance is distinguished from other types of

Seasonal forecasts of the summer 2016 Yangtze River basin rainfall

OpenAIRE

Bett, Philip E.; Scaife, Adam A.; Li, Chaofan; Hewitt, Chris; Golding, Nicola; Zhang, Peiqun; Dunstone, Nick; Smith, Doug M.; Thornton, Hazel E.; Lu, Riyu; Ren, Hong-Li

2017-01-01

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used direc...

Discharge data assimilation in a distributed hydrologic model for flood forecasting purposes

Science.gov (United States)

Ercolani, G.; Castelli, F.

2017-12-01

Flood early warning systems benefit from accurate river flow forecasts, and data assimilation may improve their reliability. However, the actual enhancement that can be obtained in the operational practice should be investigated in detail and quantified. In this work we assess the benefits that the simultaneous assimilation of discharge observations at multiple locations can bring to flow forecasting through a distributed hydrologic model. The distributed model, MOBIDIC, is part of the operational flood forecasting chain of Tuscany Region in Central Italy. The assimilation system adopts a mixed variational-Monte Carlo approach to update efficiently initial river flow, soil moisture, and a parameter related to runoff production. The evaluation of the system is based on numerous hindcast experiments of real events. The events are characterized by significant rainfall that resulted in both high and relatively low flow in the river network. The area of study is the main basin of Tuscany Region, i.e. Arno river basin, which extends over about 8300 km2 and whose mean annual precipitation is around 800 mm. Arno's mainstream, with its nearly 240 km length, passes through major Tuscan cities, as Florence and Pisa, that are vulnerable to floods (e.g. flood of November 1966). The assimilation tests follow the usage of the model in the forecasting chain, employing the operational resolution in both space and time (500 m and 15 minutes respectively) and releasing new flow forecasts every 6 hours. The assimilation strategy is evaluated in respect to open loop simulations, i.e. runs that do not exploit discharge observations through data assimilation. We compare hydrographs in their entirety, as well as classical performance indexes, as error on peak flow and Nash-Sutcliffe efficiency. The dependence of performances on lead time and location is assessed. Results indicate that the operational forecasting chain can benefit from the developed assimilation system, although with a

A hybrid spatiotemporal drought forecasting model for operational use

Science.gov (United States)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

Science.gov (United States)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

Forecasting solar proton event with artificial neural network

Science.gov (United States)

Gong, J.; Wang, J.; Xue, B.; Liu, S.; Zou, Z.

Solar proton event (SPE), relatively rare but popular in solar maximum, can bring hazard situation to spacecraft. As a special event, SPE always accompanies flare, which is also called proton flare. To produce such an eruptive event, large amount energy must be accumulated within the active region. So we can investigate the character of the active region and its evolving trend, together with other such as cm radio emission and soft X-ray background to evaluate the potential of SEP in chosen area. In order to summarize the omen of SPEs in the active regions behind the observed parameters, we employed AI technology. Full connecting neural network was chosen to fulfil this job. After constructing the network, we train it with 13 parameters that was able to exhibit the character of active regions and their evolution trend. More than 80 sets of event parameter were defined to teach the neural network to identify whether an active region was potential of SPE. Then we test this model with a data base consisting SPE and non-SPE cases that was not used to train the neural network. The result showed that 75% of the choice by the model was right.

Application of a serial extended forecast experiment using the ECMWF model to interpret the predictive skill of tropical intraseasonal variability

Energy Technology Data Exchange (ETDEWEB)

Agudelo, P.A.; Hoyos, C.D.; Webster, P.J.; Curry, J.A. [Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA (United States)

2009-05-15

The extended-range forecast skill of the ECMWF operational forecast model is evaluated during tropical intraseasonal oscillation (ISO) events in the Indo-West Pacific warm pool. The experiment consists of ensemble extended serial forecasts including winter and summer ISO cases. The forecasts are compared with the ERA-40 analyses. The analysis focuses on understanding the origin of forecast errors by studying the vertical structure of relevant dynamical and moist convective features associated with the ISO. The useful forecast time scale for circulation anomalies is in average 13 days during winter compared to 7-8 days during summer. The forecast skill is not stationary and presents evidence of a flow-dependent nature, with states of the coupled system corresponding to long-lived convective envelopes associated with the ISO for which the skill is always low regardless of the starting date of the forecast. The model is not able to forecast skillfully the generation of specific humidity anomalies and results indicate that the convective processes in the model are associated with the erosion of the ISO forecast skill in the model. Circulation-associated anomalies are forecast better than moist convective associated anomalies. The model tends to generate a more stable atmosphere, limiting the model's capability to reproduce deep convective events, resulting in smaller humidity and circulation anomalies in the forecasts compared to those in ERA-40. (orig.)

Real-time forecasting of the April 11, 2012 Sumatra tsunami

Science.gov (United States)

Wang, Dailin; Becker, Nathan C.; Walsh, David; Fryer, Gerard J.; Weinstein, Stuart A.; McCreery, Charles S.; ,

2012-01-01

The April 11, 2012, magnitude 8.6 earthquake off the northern coast of Sumatra generated a tsunami that was recorded at sea-level stations as far as 4800 km from the epicenter and at four ocean bottom pressure sensors (DARTs) in the Indian Ocean. The governments of India, Indonesia, Sri Lanka, Thailand, and Maldives issued tsunami warnings for their coastlines. The United States' Pacific Tsunami Warning Center (PTWC) issued an Indian Ocean-wide Tsunami Watch Bulletin in its role as an Interim Service Provider for the region. Using an experimental real-time tsunami forecast model (RIFT), PTWC produced a series of tsunami forecasts during the event that were based on rapidly derived earthquake parameters, including initial location and Mwp magnitude estimates and the W-phase centroid moment tensor solutions (W-phase CMTs) obtained at PTWC and at the U. S. Geological Survey (USGS). We discuss the real-time forecast methodology and how successive, real-time tsunami forecasts using the latest W-phase CMT solutions improved the accuracy of the forecast.

Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast

Directory of Open Access Journals (Sweden)

Junfei Chen

2012-01-01

Full Text Available Drought is part of natural climate variability and ranks the first natural disaster in the world. Drought forecasting plays an important role in mitigating impacts on agriculture and water resources. In this study, a drought forecast model based on the random forest method is proposed to predict the time series of monthly standardized precipitation index (SPI. We demonstrate model application by four stations in the Haihe river basin, China. The random-forest- (RF- based forecast model has consistently shown better predictive skills than the ARIMA model for both long and short drought forecasting. The confidence intervals derived from the proposed model generally have good coverage, but still tend to be conservative to predict some extreme drought events.

Short-term wind power combined forecasting based on error forecast correction

International Nuclear Information System (INIS)

Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

2016-01-01

Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

Economic assessment of flood forecasts for a risk-averse decision-maker

Science.gov (United States)

Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier-Filion, Thomas-Charles

2017-04-01

A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. It has also been suggested in past studies that ensemble forecasts might possess a greater economic value than deterministic forecasts. However, the vast majority of recent hydro-economic literature is based on the cost-loss ratio framework, which might be appealing for its simplicity and intuitiveness. One important drawback of the cost-loss ratio is that it implicitly assumes a risk-neutral decision maker. By definition, a risk-neutral individual is indifferent to forecasts' sharpness: as long as forecasts agree with observations on average, the risk-neutral individual is satisfied. A risk-averse individual, however, is sensitive to the level of precision (sharpness) of forecasts. This person is willing to pay to increase his or her certainty about future events. In fact, this is how insurance companies operate: the probability of seeing one's house burn down is relatively low, so the expected cost related to such event is also low. However, people are willing to buy insurance to avoid the risk, however small, of loosing everything. Similarly, in a context where people's safety and property is at stake, the typical decision maker is more risk-averse than risk-neutral. Consequently, the cost-loss ratio is not the most appropriate tool to assess the economic value of flood forecasts. This presentation describes a more realistic framework for assessing the economic value of such forecasts for flood mitigation purposes. Borrowing from economics, the Constant Absolute Risk Aversion utility function (CARA) is the central tool of this new framework. Utility functions allow explicitly accounting for the level of risk aversion of the decision maker and fully exploiting the information related to ensemble forecasts' uncertainty. Three concurrent ensemble streamflow forecasting systems are compared in terms of quality (comparison with

Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

Directory of Open Access Journals (Sweden)

S. K. Jha

2018-03-01

Full Text Available Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP, developed in Australia (Robertson et al., 2013; Shrestha et al., 2015, has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS, from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

Catastrophizing and Depressive Symptoms as Prospective Predictors of Outcomes Following Total Knee Replacement

Directory of Open Access Journals (Sweden)

Robert R Edwards

2009-01-01

Full Text Available Several recent reports suggest that pain-related catastrophizing is a risk factor for poor acute pain outcomes following surgical interventions. However, it has been less clear whether levels of catastrophizing influence longer-term postoperative outcomes. Data were analyzed from a relatively small number (n=43 of patients who underwent total knee replacement and were followed for 12 months after their surgery. Previous research has suggested that high levels of both catastrophizing and depression are associated with elevated acute postoperative pain complaints among patients undergoing knee surgery. In this sample, catastrophizing and depression at each of the assessment points were studied as prospective predictors of pain (both global pain ratings and pain at night at the subsequent assessment point over the course of one year. The predictive patterns differed somewhat across measures of pain reporting; depressive symptoms were unique predictors of greater global pain complaints, while catastrophizing was a specific and unique predictor of elevated nighttime pain. While surgical outcomes following total knee replacement are, on average, quite good, a significant minority of patients continue to experience long-term pain. The present findings suggest that high levels of catastrophizing and depression may promote enhanced pain levels, indicating that interventions designed to reduce catastrophizing and depressive symptoms may have the potential to further improve joint replacement outcomes.

Improvement of the plan of measures for cases of catastrophes corresponding to radiological accidents

International Nuclear Information System (INIS)

Jerez Vegueria, Pablo F.; Lopez Forteza; Yamil; Diaz Guerra, Pedro I.

2003-01-01

In the year 1988 the Plan of Measures for Cases of Catastrophe (PMCC) it was focused basically to the Central Electronuclear of Juragua and the Center of Investigations Nuclear both in construction in that moment. In Cuba, with the Ordinance Law Not. 170 of the System of Civil Defense of 1997 assign the EMNDC the responsibility for the address and coordination of the material resources and humans to make in front of any catastrophe type, including the emergencies radiological. However the radiological events that could happen in rest of those practical with ionizing radiations that were carried out in the country they were not contemplated in the old conception of planning of emergency of the PMCC. In the year 2001 the CNSN and EMNDC begin a revision of the national planning from the answer to radiological emergencies developing new conceptions of planning, preparation and answer to radiological emergencies using for it categories of planning recommended by the IAEA in new technical documents emitted to the effect. Presently work is exposed the new philosophy of planning and national answer that it sustains the current Annex radiological Accidents of the PMCC

Fuel cycle forecasting - there are forecasts and there are forecasts

International Nuclear Information System (INIS)

Puechl, K.H.

1975-01-01

The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

Fuel cycle forecasting - there are forecasts and there are forecasts

Energy Technology Data Exchange (ETDEWEB)

Puechl, K H

1975-12-01

The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

ENSO-based probabilistic forecasts of March-May U.S. tornado and hail activity

Science.gov (United States)

Lepore, Chiara; Tippett, Michael K.; Allen, John T.

2017-09-01

Extended logistic regression is used to predict March-May severe convective storm (SCS) activity based on the preceding December-February (DJF) El Niño-Southern Oscillation (ENSO) state. The spatially resolved probabilistic forecasts are verified against U.S. tornado counts, hail events, and two environmental indices for severe convection. The cross-validated skill is positive for roughly a quarter of the U.S. Overall, indices are predicted with more skill than are storm reports, and hail events are predicted with more skill than tornado counts. Skill is higher in the cool phase of ENSO (La Niña like) when overall SCS activity is higher. SCS forecasts based on the predicted DJF ENSO state from coupled dynamical models initialized in October of the previous year extend the lead time with only a modest reduction in skill compared to forecasts based on the observed DJF ENSO state.

Thermal catastrophe in the plasma sheet boundary layer

International Nuclear Information System (INIS)

Smith, R.A.; Goertz, C.K.; Grossmann, W.

1986-01-01

This letter presents a first step towards a substorm model including particle heating and transport in the plasma sheet boundary layer (PSBL). The heating mechanism discussed is resonant absorption of Alfven waves. For some assumed MHD perturbation incident from the tail lobes onto the plasma sheet, the local heating rate in the PSBL has the form of a resonance function of the one-fluid plasma temperature. Balancing the local heating by convective transport of the heated plasma toward the central plasma sheet, and ''equation of state'' is found for the steady-state PSBL whose solution has the form of a mathematical catastrophe: at a critical value of a parameter containing the incident power flux, the local density, and the convection velocity, the equilibrium temperature jumps discontinuously. Associating this temperature increase with the abrupt onset of the substorm expansion phase, the catastrophe model indicates at least three ways in which the onset may be triggered. Several other consequences related to substorm dynamics are suggested by the simple catastrophe model

International Aftershock Forecasting: Lessons from the Gorkha Earthquake

Science.gov (United States)

Michael, A. J.; Blanpied, M. L.; Brady, S. R.; van der Elst, N.; Hardebeck, J.; Mayberry, G. C.; Page, M. T.; Smoczyk, G. M.; Wein, A. M.

2015-12-01

Following the M7.8 Gorhka, Nepal, earthquake of April 25, 2015 the USGS issued a series of aftershock forecasts. The initial impetus for these forecasts was a request from the USAID Office of US Foreign Disaster Assistance to support their Disaster Assistance Response Team (DART) which coordinated US Government disaster response, including search and rescue, with the Government of Nepal. Because of the possible utility of the forecasts to people in the region and other response teams, the USGS released these forecasts publicly through the USGS Earthquake Program web site. The initial forecast used the Reasenberg and Jones (Science, 1989) model with generic parameters developed for active deep continental regions based on the Garcia et al. (BSSA, 2012) tectonic regionalization. These were then updated to reflect a lower productivity and higher decay rate based on the observed aftershocks, although relying on teleseismic observations, with a high magnitude-of-completeness, limited the amount of data. After the 12 May M7.3 aftershock, the forecasts used an Epidemic Type Aftershock Sequence model to better characterize the multiple sources of earthquake clustering. This model provided better estimates of aftershock uncertainty. These forecast messages were crafted based on lessons learned from the Christchurch earthquake along with input from the U.S. Embassy staff in Kathmandu. Challenges included how to balance simple messaging with forecasts over a variety of time periods (week, month, and year), whether to characterize probabilities with words such as those suggested by the IPCC (IPCC, 2010), how to word the messages in a way that would translate accurately into Nepali and not alarm the public, and how to present the probabilities of unlikely but possible large and potentially damaging aftershocks, such as the M7.3 event, which had an estimated probability of only 1-in-200 for the week in which it occurred.

Origins of forecast skill of weather and climate events on verifiable time scales

CSIR Research Space (South Africa)

Landman, WA

2012-07-01

Full Text Available specific location between the predictor or the predictand and their respective canonical component time series (rj and sk) Barnett, T. P., and Preisendorfer, R. W. 1987: Origins and levels of monthly and seasonal forecast skill for United States air...

Photography and nuclear catastrophe. The visual representation of the occurrences in Hiroshima/Nagasaki and Chernobyl

International Nuclear Information System (INIS)

Buerkner, Daniel

2014-01-01

The dissertation project seeks to analyse the photographic positions that deal with the atomic bomb attacks on Hiroshima and Nagasaki and the accident of the nuclear power plant in Chernobyl. This focus includes press photographs of the events as well as artistic, documentary and touristic images that take an approach towards the disasters often years after and hereby form iconographic or material references to the events. The study reveals central strategies for photographic images of atomic catastrophes, be they of military or civil nature. It is the inability to visualize non-visible nuclear rays or the complexity of processes on an atomic level that has turned out to be crucial. This incapacity of making images, a paradigm of invisibility, substantially coins the cultural role of the events. The question of how a society deals with these abstract potentials of nuclear technology has turned out to be always anew of high relevance in regard to ecological, social and technological policies of images.

Sensitivity of a Simulated Derecho Event to Model Initial Conditions

Science.gov (United States)

Wang, Wei

2014-05-01

Since 2003, the MMM division at NCAR has been experimenting cloud-permitting scale weather forecasting using Weather Research and Forecasting (WRF) model. Over the years, we've tested different model physics, and tried different initial and boundary conditions. Not surprisingly, we found that the model's forecasts are more sensitive to the initial conditions than model physics. In 2012 real-time experiment, WRF-DART (Data Assimilation Research Testbed) at 15 km was employed to produce initial conditions for twice-a-day forecast at 3 km. On June 29, this forecast system captured one of the most destructive derecho event on record. In this presentation, we will examine forecast sensitivity to different model initial conditions, and try to understand the important features that may contribute to the success of the forecast.

Cyclone track forecasting based on satellite images using artificial neural networks

OpenAIRE

Kovordanyi, Rita; Roy, Chandan

2009-01-01

Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on sate...

What Should Be the Relationship between the National Guard and United States Northern Command in Civil Support Operations Following Catastrophic Events?

Science.gov (United States)

2006-09-01

catastrophe such as the New Madrid earthquake or pandemic influenza scenarios that required a standard military response across the states, this construct...the next crisis. D. LITERATURE REVIEW USNORTHCOM is a relatively new organization so there is not an abundance of existing literature that...Brigadier General (Retired) Raymond E. Bell proposes making a National Guard general officer the commander of USNORTHCOM. He also suggests the National

Forecasting Housing Approvals in Australia: Do Forecasters Herd?

DEFF Research Database (Denmark)

Stadtmann, Georg; Pierdzioch; Rülke

2012-01-01

Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

Experiences from coordinated national-level landslide and flood forecasting in Norway

Science.gov (United States)

Krøgli, Ingeborg; Fleig, Anne; Glad, Per; Dahl, Mads-Peter; Devoli, Graziella; Colleuille, Hervé

2015-04-01

While flood forecasting at national level is quite well established and operational in many countries worldwide, landslide forecasting at national level is still seldom. Examples of coordinated flood and landslide forecasting are even rarer. Most of the time flood and landslide forecasters work separately (investigating, defining thresholds, and developing models) and most of the time without communication with each other. One example of coordinated operational early warning systems (EWS) for flooding and shallow landslides is found at the Norwegian Water Resources and Energy Directorate (NVE) in Norway. In this presentation we give an introduction to the two separate but tightly collaborative EWSs and to the coordination of these. The two EWSs are being operated from the same office, every day using similar hydro-meteorological prognosis and hydrological models. Prognosis and model outputs on e.g. discharge, snow melt, soil water content and exceeded landslide thresholds are evaluated in a web based decision-making tool (xgeo.no). The experts performing forecasts are hydrologists, geologists and physical geographers. A similar warning scale, based on colors (green, yellow, orange and red) is used for both EWSs, however thresholds for flood and landslide warning levels are defined differently. Also warning areas may not necessary be the same for both hazards and depending on the specific meteorological event, duration of the warning periods can differ. We present how knowledge, models and tools, but also human and economic resources are being shared between the two EWSs. Moreover, we discuss challenges faced in the communication of warning messages using recent flood and landslide events as examples.

Evaluating the Predictability of South-East Asian Floods Using ECMWF and GloFAS Forecasts

Science.gov (United States)

Pillosu, F. M.

2017-12-01

Between July and September 2017, the monsoon season caused widespread heavy rainfall and severe floods across countries in South-East Asia, notably in India, Nepal and Bangladesh, with deadly consequences. According to the U.N., in Bangladesh 140 people lost their lives and 700,000 homes were destroyed; in Nepal at least 143 people died, and more than 460,000 people were forced to leave their homes; in India there were 726 victims of flooding and landslides, 3 million people were affected by the monsoon floods and 2000 relief camps were established. Monsoon season happens regularly every year in South Asia, but local authorities reported the last monsoon season as the worst in several years. What made the last monsoon season particularly severe in certain regions? Are these causes clear from the forecasts? Regarding the meteorological characterization of the event, an analysis of forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF) for different lead times (from seasonal to short range) will be shown to evaluate how far in advance this event was predicted and start discussion on what were the factors that led to such a severe event. To illustrate hydrological aspects, forecasts from the Global Flood Awareness System (GloFAS) will be shown. GloFAS is developed at ECMWF in co-operation with the European Commission's Joint Research Centre (JRC) and with the support of national authorities and research institutions such as the University of Reading. It will become operational at the end of 2017 as part of the Copernicus Emergency Management Service. GloFAS couples state-of-the-art weather forecasts with a hydrological model to provide a cross-border system with early flood guidance information to help humanitarian agencies and national hydro-meteorological services to strengthen and improve forecasting capacity, preparedness and mitigation of natural hazards. In this case GloFAS has shown good potential to become a useful tool for better and

Catastrophizing and perceived injustice: risk factors for the transition to chronicity after whiplash injury.

Science.gov (United States)

Sullivan, Michael J L; Adams, Heather; Martel, Marc-Olivier; Scott, Whitney; Wideman, Timothy

2011-12-01

The article will summarize research that has supported the role of pain catastrophizing and perceived injustice as risk factors for problematic recovery after whiplash injury. This article focuses on two psychological variables that have been shown to impact on recovery trajectories after whiplash injury; namely pain catastrophizing and perceived injustice. Research has shown that psychological variables play a role in determining the trajectory of recovery after whiplash injury. This article will focus on two psychological variables that have been shown to impact on recovery trajectories after whiplash injury; namely pain catastrophizing and perceived injustice. The article will summarize research that has supported the role of pain catastrophizing and perceived injustice as risk factors for problematic recovery after whiplash injury. Several investigations have shown that measures of catastrophizing and perceived injustice prospectively predict problematic trajectories of recovery after whiplash injury. Basic research points to the potential roles of expectancies, attention, coping and endogenous opioid dysregulation as possible avenues through which catastrophizing might heighten the probability of the persistence of pain after whiplash injury. Although research has yet to systematically address the mechanisms by which perceived injustice might contribute to prolonged disability in individuals with whiplash injuries, there are grounds for suggesting the potential contributions of catastrophizing, pain behavior and anger. A challenge for future research will be the development and evaluation of risk factor-targeted interventions aimed at reducing catastrophizing and perceived injustice to improve recovery trajectories after whiplash injury.

Forecasting freight flows

DEFF Research Database (Denmark)

Lyk-Jensen, Stéphanie

2011-01-01

Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

Topographic precursors and geological structures of deep-seated catastrophic landslides caused by Typhoon Talas

Science.gov (United States)

Chigira, Masahiro; Tsou, Ching-Ying; Matsushi, Yuki; Hiraishi, Narumi; Matsuzawa, Makoto

2013-11-01

Typhoon Talas crossed the Japanese Islands between 2 and 5 September 2011, causing more than 70 deep-seated catastrophic landslides in a Jurassic to Paleogene-lower Miocene accretion complex. Detailed examination of the topographic features of 10 large landslides before the event, recorded on 1-m DEMs based on airborne laser scanner surveys, showed that all landslides had small scarps near their future crowns prior to the slide, and one landslide had linear depressions along its future crown as precursor topographic features. These scarps and linear depressions were caused by gravitational slope deformation that preceded the catastrophic failure. Although the scarps may have been enlarged by degradation, their sizes relative to the whole slopes suggest that minimal slope deformation had occurred in the period immediately before the catastrophic failure. The scarp ratio, defined as the ratio of length of a scarp to that of the whole slope both measured along the slope line, ranged from 5% to 21%. Careful examination of aerial photographs from another four large landslides, for which no high-resolution DEMs were available, suggested that they also developed scarps at their heads beforehand. Twelve of the 14 landslides we surveyed in the field had sliding surfaces with wedge-shaped discontinuities that consisted of faults and bedding, suggesting that the buildup of pore pressure occurs readily on wedge-shaped discontinuities in a gravitationally deformed rock body. Most of the faults were undulatory and were probably thrust faults that formed during accretion. Other types of gravitational deformation were also active; e.g., flexural toppling and buckling were observed to have preceded one landslide.

Complexities, Catastrophes and Cities: Emergency Dynamics in Varying Scenarios and Urban Topologies

Science.gov (United States)

Narzisi, Giuseppe; Mysore, Venkatesh; Byeon, Jeewoong; Mishra, Bud

Complex Systems are often characterized by agents capable of interacting with each other dynamically, often in non-linear and non-intuitive ways. Trying to characterize their dynamics often results in partial differential equations that are difficult, if not impossible, to solve. A large city or a city-state is an example of such an evolving and self-organizing complex environment that efficiently adapts to different and numerous incremental changes to its social, cultural and technological infrastructure [1]. One powerful technique for analyzing such complex systems is Agent-Based Modeling (ABM) [9], which has seen an increasing number of applications in social science, economics and also biology. The agent-based paradigm facilitates easier transfer of domain specific knowledge into a model. ABM provides a natural way to describe systems in which the overall dynamics can be described as the result of the behavior of populations of autonomous components: agents, with a fixed set of rules based on local information and possible central control. As part of the NYU Center for Catastrophe Preparedness and Response (CCPR1), we have been exploring how ABM can serve as a powerful simulation technique for analyzing large-scale urban disasters. The central problem in Disaster Management is that it is not immediately apparent whether the current emergency plans are robust against such sudden, rare and punctuated catastrophic events.

Catastrophizing and Causal Beliefs in Whiplash

NARCIS (Netherlands)

Buitenhuis, J.; de Jong, P. J.; Jaspers, J. P. C.; Groothoff, J. W.

2008-01-01

Study Design. Prospective cohort study. Objective. This study investigates the role of pain catastrophizing and causal beliefs with regard to severity and persistence of neck complaints after motor vehicle accidents. Summary of Background Data. In previous research on low back pain, somatoform

Waterspout Forecasting Method Over the Eastern Adriatic Using a High-Resolution Numerical Weather Model

Science.gov (United States)

Renko, Tanja; Ivušić, Sarah; Telišman Prtenjak, Maja; Šoljan, Vinko; Horvat, Igor

2018-03-01

In this study, a synoptic and mesoscale analysis was performed and Szilagyi's waterspout forecasting method was tested on ten waterspout events in the period of 2013-2016. Data regarding waterspout occurrences were collected from weather stations, an online survey at the official website of the National Meteorological and Hydrological Service of Croatia and eyewitness reports from newspapers and the internet. Synoptic weather conditions were analyzed using surface pressure fields, 500 hPa level synoptic charts, SYNOP reports and atmospheric soundings. For all observed waterspout events, a synoptic type was determined using the 500 hPa geopotential height chart. The occurrence of lightning activity was determined from the LINET lightning database, and waterspouts were divided into thunderstorm-related and "fair weather" ones. Mesoscale characteristics (with a focus on thermodynamic instability indices) were determined using the high-resolution (500 m grid length) mesoscale numerical weather model and model results were compared with the available observations. Because thermodynamic instability indices are usually insufficient for forecasting waterspout activity, the performance of the Szilagyi Waterspout Index (SWI) was tested using vertical atmospheric profiles provided by the mesoscale numerical model. The SWI successfully forecasted all waterspout events, even the winter events. This indicates that the Szilagyi's waterspout prognostic method could be used as a valid prognostic tool for the eastern Adriatic.

Robust forecast comparison

OpenAIRE

Jin, Sainan; Corradi, Valentina; Swanson, Norman

2015-01-01

Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

Staged decision making based on probabilistic forecasting

Science.gov (United States)

Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

2016-04-01

Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

Science.gov (United States)

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

Nonlinear physics: Catastrophe, chaos and complexity

International Nuclear Information System (INIS)

Arecchi, F.T.

1992-01-01

Currently in the world of physics, there is open debate on the role of the three C's - catastrophe, chaos and complexity. Seen as new ideas or paradigms, incapable of being harmonized within the realm of traditional physics, these terms seem to be creating turmoil in the classical physics establishment whose foundations date back to the early seventeenth century. This paper first defines catastrophe, chaos and complexity and shows how these terms are all connected to nonlinear dynamics and how they have long since been present within scientific treatises. It also evidences the relationship of the three C's with the concept of organization, inappropriately called self-organization, and with recognition and decisional strategies of cognitive systems. Relevant to natural science, the development of these considerations is necessitating the re-examination of the role and capabilities of human knowledge and a return to inter-disciplinary scientific-philosophical debate

UCERF3: A new earthquake forecast for California's complex fault system

Science.gov (United States)

Field, Edward H.; ,

2015-01-01

With innovations, fresh data, and lessons learned from recent earthquakes, scientists have developed a new earthquake forecast model for California, a region under constant threat from potentially damaging events. The new model, referred to as the third Uniform California Earthquake Rupture Forecast, or "UCERF" (http://www.WGCEP.org/UCERF3), provides authoritative estimates of the magnitude, location, and likelihood of earthquake fault rupture throughout the state. Overall the results confirm previous findings, but with some significant changes because of model improvements. For example, compared to the previous forecast (Uniform California Earthquake Rupture Forecast 2), the likelihood of moderate-sized earthquakes (magnitude 6.5 to 7.5) is lower, whereas that of larger events is higher. This is because of the inclusion of multifault ruptures, where earthquakes are no longer confined to separate, individual faults, but can occasionally rupture multiple faults simultaneously. The public-safety implications of this and other model improvements depend on several factors, including site location and type of structure (for example, family dwelling compared to a long-span bridge). Building codes, earthquake insurance products, emergency plans, and other risk-mitigation efforts will be updated accordingly. This model also serves as a reminder that damaging earthquakes are inevitable for California. Fortunately, there are many simple steps residents can take to protect lives and property.

Catastrophic floods may pave the way for increased genetic diversity in endemic artesian spring snail populations.

Directory of Open Access Journals (Sweden)

Jessica Worthington Wilmer

Full Text Available The role of disturbance in the promotion of biological heterogeneity is widely recognised and occurs at a variety of ecological and evolutionary scales. However, within species, the impact of disturbances that decimate populations are neither predicted nor known to result in conditions that promote genetic diversity. Directly examining the population genetic consequences of catastrophic disturbances however, is rarely possible, as it requires both longitudinal genetic data sets and serendipitous timing. Our long-term study of the endemic aquatic invertebrates of the artesian spring ecosystem of arid central Australia has presented such an opportunity. Here we show a catastrophic flood event, which caused a near total population crash in an aquatic snail species (Fonscochlea accepta endemic to this ecosystem, may have led to enhanced levels of within species genetic diversity. Analyses of individuals sampled and genotyped from the same springs sampled both pre (1988-1990 and post (1995, 2002-2006 a devastating flood event in 1992, revealed significantly higher allelic richness, reduced temporal population structuring and greater effective population sizes in nearly all post flood populations. Our results suggest that the response of individual species to disturbance and severe population bottlenecks is likely to be highly idiosyncratic and may depend on both their ecology (whether they are resilient or resistant to disturbance and the stability of the environmental conditions (i.e. frequency and intensity of disturbances in which they have evolved.

Communications en cas de catastrophe faisant appel aux TIC pour ...

International Development Research Centre (IDRC) Digital Library (Canada)

Communications en cas de catastrophe faisant appel aux TIC pour les collectivités vulnérables des Caraïbes. De récents événements survenus dans les Caraïbes ont mis en relief les insuffisances des mesures régionales et nationales de préparation aux catastrophes. On manque particulièrement de systèmes d'alerte ...

Catastrophic phase transitions and early warnings in a spatial ecological model