An assessment of temporal effect on extreme rainfall estimates

NASA Astrophysics Data System (ADS)

Das, Samiran; Zhu, Dehua; Chi-Han, Cheng

2018-06-01

This study assesses the temporal behaviour in terms of inter-decadal variability of extreme daily rainfall of stated return period relevant for hydrologic risk analysis using a novel regional parametric approach. The assessment is carried out based on annual maximum daily rainfall series of 180 meteorological stations of Yangtze River Basin over a 50-year period (1961-2010). The outcomes of the analysis reveal that while there were effects present indicating higher quantile values when estimated from data of the 1990s, it is found not to be noteworthy to exclude the data of any decade from the extreme rainfall estimation process for hydrologic risk analysis.

The end of trend-estimation for extreme floods under climate change?

NASA Astrophysics Data System (ADS)

Schulz, Karsten; Bernhardt, Matthias

2016-04-01

An increased risk of flood events is one of the major threats under future climate change conditions. Therefore, many recent studies have investigated trends in flood extreme occurences using historic long-term river discharge data as well as simulations from combined global/regional climate and hydrological models. Severe floods are relatively rare events and the robust estimation of their probability of occurrence requires long time series of data (6). Following a method outlined by the IPCC research community, trends in extreme floods are calculated based on the difference of discharge values exceeding e.g. a 100-year level (Q100) between two 30-year windows, which represents prevailing conditions in a reference and a future time period, respectively. Following this approach, we analysed multiple, synthetically derived 2,000-year trend-free, yearly maximum runoff data generated using three different extreme value distributions (EDV). The parameters were estimated from long term runoff data of four large European watersheds (Danube, Elbe, Rhine, Thames). Both, Q100-values estimated from 30-year moving windows, as well as the subsequently derived trends showed enormous variations with time: for example, estimating the Extreme Value (Gumbel) - distribution for the Danube data, trends of Q100 in the synthetic time-series range from -4,480 to 4,028 m³/s per 100 years (Q100 =10,071m³/s, for reference). Similar results were found when applying other extreme value distributions (Weibull, and log-Normal) to all of the watersheds considered. This variability or "background noise" of estimating trends in flood extremes makes it almost impossible to significantly distinguish any real trend in observed as well as modelled data when such an approach is applied. These uncertainties, even though known in principle are hardly addressed and discussed by the climate change impact community. Any decision making and flood risk management, including the dimensioning of flood

A non-stationary cost-benefit based bivariate extreme flood estimation approach

NASA Astrophysics Data System (ADS)

Qi, Wei; Liu, Junguo

2018-02-01

Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis.

PubMed

Quintela-del-Río, Alejandro; Francisco-Fernández, Mario

2011-02-01

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multiscale Measurement of Extreme Response Style

ERIC Educational Resources Information Center

Bolt, Daniel M.; Newton, Joseph R.

2011-01-01

This article extends a methodological approach considered by Bolt and Johnson for the measurement and control of extreme response style (ERS) to the analysis of rating data from multiple scales. Specifically, it is shown how the simultaneous analysis of item responses across scales allows for more accurate identification of ERS, and more effective…

Extreme Response Style: Which Model Is Best?

ERIC Educational Resources Information Center

Leventhal, Brian

2017-01-01

More robust and rigorous psychometric models, such as multidimensional Item Response Theory models, have been advocated for survey applications. However, item responses may be influenced by construct-irrelevant variance factors such as preferences for extreme response options. Through empirical and simulation methods, this study evaluates the use…

Extreme Quantile Estimation in Binary Response Models

DTIC Science & Technology

1990-03-01

in Cancer Research," Biometria , VoL 66, pp. 307-316. Hsi, B.P. [1969], ’The Multiple Sample Up-and-Down Method in Bioassay," Journal of the American...New Method of Estimation," Biometria , VoL 53, pp. 439-454. Wetherill, G.B. [1976], Sequential Methods in Statistics, London: Chapman and Hall. Wu, C.FJ

Response spectrum method for extreme wave loading with higher order components of drag force

NASA Astrophysics Data System (ADS)

Reza, Tabeshpour Mohammad; Mani, Fatemi Dezfouli; Ali, Dastan Diznab Mohammad; Saied, Mohajernasab; Saied, Seif Mohammad

2017-03-01

Response spectra of fixed offshore structures impacted by extreme waves are investigated based on the higher order components of the nonlinear drag force. In this way, steel jacket platforms are simplified as a mass attached to a light cantilever cylinder and their corresponding deformation response spectra are estimated by utilizing a generalized single degree of freedom system. Based on the wave data recorded in the Persian Gulf region, extreme wave loading conditions corresponding to different return periods are exerted on the offshore structures. Accordingly, the effect of the higher order components of the drag force is considered and compared to the linearized state for different sea surface levels. When the fundamental period of the offshore structure is about one third of the main period of wave loading, the results indicate the linearized drag term is not capable of achieving a reliable deformation response spectrum.

Challenges estimating the return period of extreme floods for reinsurance applications

NASA Astrophysics Data System (ADS)

Raven, Emma; Busby, Kathryn; Liu, Ye

2013-04-01

Mapping and modelling extreme natural events is fundamental within the insurance and reinsurance industry for assessing risk. For example, insurers might use a 1 in 100-year flood hazard map to set the annual premium of a property, whilst a reinsurer might assess the national scale loss associated with the 1 in 200-year return period for capital and regulatory requirements. Using examples from a range of international flood projects, we focus on exploring how to define what the n-year flood looks like for predictive uses in re/insurance applications, whilst considering challenges posed by short historical flow records and the spatial and temporal complexities of flood. First, we shall explore the use of extreme value theory (EVT) statistics for extrapolating data beyond the range of observations in a marginal analysis. In particular, we discuss how to estimate the return period of historical flood events and explore the impact that a range of statistical decisions have on these estimates. Decisions include: (1) selecting which distribution type to apply (e.g. generalised Pareto distribution (GPD) vs. generalised extreme value distribution (GEV)); (2) if former, the choice of the threshold above which the GPD is fitted to the data; and (3) the necessity to perform a cluster analysis to group flow peaks to temporally represent individual flood events. Second, we summarise a specialised multivariate extreme value model, which combines the marginal analysis above with dependence modelling to generate industry standard event sets containing thousands of simulated, equi-probable floods across a region/country. These events represent the typical range of anticipated flooding across a region and can be used to estimate the largest or most widespread events that are expected to occur. Finally, we summarise how a reinsurance catastrophe model combines the event set with detailed flood hazard maps to estimate the financial cost of floods; both the full event set and also

Flood frequency estimates and documented and potential extreme peak discharges in Oklahoma

USGS Publications Warehouse

Tortorelli, Robert L.; McCabe, Lan P.

2001-01-01

Knowledge of the magnitude and frequency of floods is required for the safe and economical design of highway bridges, culverts, dams, levees, and other structures on or near streams; and for flood plain management programs. Flood frequency estimates for gaged streamflow sites were updated, documented extreme peak discharges for gaged and miscellaneous measurement sites were tabulated, and potential extreme peak discharges for Oklahoma streamflow sites were estimated. Potential extreme peak discharges, derived from the relation between documented extreme peak discharges and contributing drainage areas, can provide valuable information concerning the maximum peak discharge that could be expected at a stream site. Potential extreme peak discharge is useful in conjunction with flood frequency analysis to give the best evaluation of flood risk at a site. Peak discharge and flood frequency for selected recurrence intervals from 2 to 500 years were estimated for 352 gaged streamflow sites. Data through 1999 water year were used from streamflow-gaging stations with at least 8 years of record within Oklahoma or about 25 kilometers into the bordering states of Arkansas, Kansas, Missouri, New Mexico, and Texas. These sites were in unregulated basins, and basins affected by regulation, urbanization, and irrigation. Documented extreme peak discharges and associated data were compiled for 514 sites in and near Oklahoma, 352 with streamflow-gaging stations and 162 at miscellaneous measurements sites or streamflow-gaging stations with short record, with a total of 671 measurements.The sites are fairly well distributed statewide, however many streams, large and small, have never been monitored. Potential extreme peak-discharge curves were developed for streamflow sites in hydrologic regions of the state based on documented extreme peak discharges and the contributing drainage areas. Two hydrologic regions, east and west, were defined using 98 degrees 15 minutes longitude as the

Stream Response to an Extreme Defoliation Event

NASA Astrophysics Data System (ADS)

Gold, A.; Loffredo, J.; Addy, K.; Bernhardt, E. S.; Berdanier, A. B.; Schroth, A. W.; Inamdar, S. P.; Bowden, W. B.

2017-12-01

Extreme climatic events are known to profoundly impact stream flow and stream fluxes. These events can also exert controls on insect outbreaks, which may create marked changes in stream characteristics. The invasive Gypsy Moth (Lymantria dispar dispar) experiences episodic infestations based on extreme climatic conditions within the northeastern U.S. In most years, gypsy moth populations are kept in check by diseases. In 2016 - after successive years of unusually warm, dry spring and summer weather -gypsy moth caterpillars defoliated over half of Rhode Island's 160,000 forested ha. No defoliation of this magnitude had occurred for more than 30 years. We examined one RI headwater stream's response to the defoliation event in 2016 compared with comparable data in 2014 and 2015. Stream temperature and flow was gauged continuously by USGS and dissolved oxygen (DO) was measured with a YSI EXO2 sonde every 30 minutes during a series of deployments in the spring, summer and fall from 2014-2016. We used the single station, open channel method to estimate stream metabolism metrics. We also assessed local climate and stream temperature data from 2009-2016. We observed changes in stream responses during the defoliation event that suggest changes in ET, solar radiation and heat flux. Although the summer of 2016 had more drought stress (PDSI) than previous years, stream flow occurred throughout the summer, in contrast to several years with lower drought stress when stream flow ceased. Air temperature in 2016 was similar to prior years, but stream temperature was substantially higher than the prior seven years, likely due to the loss of canopy shading. DO declined dramatically in 2016 compared to prior years - more than the rising stream temperatures would indicate. Gross Primary Productivity was significantly higher during the year of the defoliation, indicating more total fixation of inorganic carbon from photo-autotrophs. In 2016, Ecosystem Respiration was also higher and Net

Response Styles in Rating Scales: Simultaneous Modeling of Content-Related Effects and the Tendency to Middle or Extreme Categories

ERIC Educational Resources Information Center

Tutz, Gerhard; Berger, Moritz

2016-01-01

Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…

Response of Simple, Model Systems to Extreme Conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ewing, Rodney C.; Lang, Maik

2015-07-30

The focus of the research was on the application of high-pressure/high-temperature techniques, together with intense energetic ion beams, to the study of the behavior of simple oxide systems (e.g., SiO 2, GeO 2, CeO 2, TiO 2, HfO 2, SnO 2, ZnO and ZrO 2) under extreme conditions. These simple stoichiometries provide unique model systems for the analysis of structural responses to pressure up to and above 1 Mbar, temperatures of up to several thousands of kelvin, and the extreme energy density generated by energetic heavy ions (tens of keV/atom). The investigations included systematic studies of radiation- and pressure-induced amorphizationmore » of high P-T polymorphs. By studying the response of simple stoichiometries that have multiple structural “outcomes”, we have established the basic knowledge required for the prediction of the response of more complex structures to extreme conditions. We especially focused on the amorphous state and characterized the different non-crystalline structure-types that result from the interplay of radiation and pressure. For such experiments, we made use of recent technological developments, such as the perforated diamond-anvil cell and in situ investigation using synchrotron x-ray sources. We have been particularly interested in using extreme pressures to alter the electronic structure of a solid prior to irradiation. We expected that the effects of modified band structure would be evident in the track structure and morphology, information which is much needed to describe theoretically the fundamental physics of track-formation. Finally, we investigated the behavior of different simple-oxide, composite nanomaterials (e.g., uncoated nanoparticles vs. core/shell systems) under coupled, extreme conditions. This provided insight into surface and boundary effects on phase stability under extreme conditions.« less

From Drought to Flood: Biological Responses of Large River Salmonids and Emergent Management Challenges Under California's Extreme Hydroclimatic Variability

NASA Astrophysics Data System (ADS)

Anderson, C.

2017-12-01

California's hydroclimatic regime is characterized by extreme interannual variability including periodic, multi-year droughts and winter flooding sequences. Statewide, water years 2012-2016 were characterized by extreme drought followed by likely one of the wettest years on record in water year 2017. Similar drought-flood patterns have occurred multiple times both in the contemporary empirical record and reconstructed climate records. Both the extreme magnitude and rapid succession of these hydroclimatic periods pose difficult challenges for water managers and regulatory agencies responsible for providing instream flows to protect and recover threatened and endangered fish species. Principal among these riverine fish species are federally listed winter-run and spring-run Chinook salmon (Oncorhynchus tshawytscha), Central Valley steelhead (Oncorhynchus mykiss), and the pelagic species Delta smelt (Hypomesus transpacificus). Poor instream conditions from 2012-2016 resulted in extremely low abundance estimates and poor overall fish health, and while fish monitoring results from water year 2017 are too preliminary to draw substantive conclusions, early indicators show continued downward population trends despite the historically wet conditions. This poster evaluates California's hydroclimatic conditions over the past decade and quantifies resultant impacts of the 2012-2016 drought and the extremely wet 2017 water year to both adult escapement and juvenile production estimates in California's major inland salmon rivers over that same time span. We will also examine local, state, and federal regulatory actions both in response to the extreme hydroclimatic variability and in preparation for future drought-flood sequences.

Tropical precipitation extremes: Response to SST-induced warming in aquaplanet simulations

NASA Astrophysics Data System (ADS)

Bhattacharya, Ritthik; Bordoni, Simona; Teixeira, João.

2017-04-01

Scaling of tropical precipitation extremes in response to warming is studied in aquaplanet experiments using the global Weather Research and Forecasting (WRF) model. We show how the scaling of precipitation extremes is highly sensitive to spatial and temporal averaging: while instantaneous grid point extreme precipitation scales more strongly than the percentage increase (˜7% K-1) predicted by the Clausius-Clapeyron (CC) relationship, extremes for zonally and temporally averaged precipitation follow a slight sub-CC scaling, in agreement with results from Climate Model Intercomparison Project (CMIP) models. The scaling depends crucially on the employed convection parameterization. This is particularly true when grid point instantaneous extremes are considered. These results highlight how understanding the response of precipitation extremes to warming requires consideration of dynamic changes in addition to the thermodynamic response. Changes in grid-scale precipitation, unlike those in convective-scale precipitation, scale linearly with the resolved flow. Hence, dynamic changes include changes in both large-scale and convective-scale motions.

Bias-correction of PERSIANN-CDR Extreme Precipitation Estimates Over the United States

NASA Astrophysics Data System (ADS)

Faridzad, M.; Yang, T.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Ground-based precipitation measurements can be sparse or even nonexistent over remote regions which make it difficult for extreme event analysis. PERSIANN-CDR (CDR), with 30+ years of daily rainfall information, provides an opportunity to study precipitation for regions where ground measurements are limited. In this study, the use of CDR annual extreme precipitation for frequency analysis of extreme events over limited/ungauged basins is explored. The adjustment of CDR is implemented in two steps: (1) Calculated CDR bias correction factor at limited gauge locations based on the linear regression analysis of gauge and CDR annual maxima precipitation; and (2) Extend the bias correction factor to the locations where gauges are not available. The correction factors are estimated at gauge sites over various catchments, elevation zones, and climate regions and the results were generalized to ungauged sites based on regional and climatic similarity. Case studies were conducted on 20 basins with diverse climate and altitudes in the Eastern and Western US. Cross-validation reveals that the bias correction factors estimated on limited calibration data can be extended to regions with similar characteristics. The adjusted CDR estimates also outperform gauge interpolation on validation sites consistently. It is suggested that the CDR with bias adjustment has a potential for study frequency analysis of extreme events, especially for regions with limited gauge observations.

Estimation of local extreme suspended sediment concentrations in California Rivers.

PubMed

Tramblay, Yves; Saint-Hilaire, André; Ouarda, Taha B M J; Moatar, Florentina; Hecht, Barry

2010-09-01

The total amount of suspended sediment load carried by a stream during a year is usually transported during one or several extreme events related to high river flow and intense rainfall, leading to very high suspended sediment concentrations (SSCs). In this study quantiles of SSC derived from annual maximums and the 99th percentile of SSC series are considered to be estimated locally in a site-specific approach using regional information. Analyses of relationships between physiographic characteristics and the selected indicators were undertaken using the localities of 5-km radius draining of each sampling site. Multiple regression models were built to test the regional estimation for these indicators of suspended sediment transport. To assess the accuracy of the estimates, a Jack-Knife re-sampling procedure was used to compute the relative bias and root mean square error of the models. Results show that for the 19 stations considered in California, the extreme SSCs can be estimated with 40-60% uncertainty, depending on the presence of flow regulation in the basin. This modelling approach is likely to prove functional in other Mediterranean climate watersheds since they appear useful in California, where geologic, climatic, physiographic, and land-use conditions are highly variable. Copyright 2010 Elsevier B.V. All rights reserved.

Assigning historic responsibility for extreme weather events

NASA Astrophysics Data System (ADS)

Otto, Friederike E. L.; Skeie, Ragnhild B.; Fuglestvedt, Jan S.; Berntsen, Terje; Allen, Myles R.

2017-11-01

Recent scientific advances make it possible to assign extreme events to human-induced climate change and historical emissions. These developments allow losses and damage associated with such events to be assigned country-level responsibility.

TRMM rainfall estimative coupled with Bell (1969) methodology for extreme rainfall characterization

NASA Astrophysics Data System (ADS)

Schiavo Bernardi, E.; Allasia, D.; Basso, R.; Freitas Ferreira, P.; Tassi, R.

2015-06-01

The lack of rainfall data in Brazil, and, in particular, in Rio Grande do Sul State (RS), hinders the understanding of the spatial and temporal distribution of rainfall, especially in the case of the more complex extreme events. In this context, rainfall's estimation from remote sensors is seen as alternative to the scarcity of rainfall gauges. However, as they are indirect measures, such estimates needs validation. This paper aims to verify the applicability of the Tropical Rainfall Measuring Mission (TRMM) satellite information for extreme rainfall determination in RS. The analysis was accomplished at different temporal scales that ranged from 5 min to daily rainfall while spatial distribution of rainfall was investigated by means of regionalization. An initial test verified TRMM rainfall estimative against measured rainfall at gauges for 1998-2013 period considering different durations and return periods (RP). Results indicated that, for the RP of 2, 5, 10 and 15 years, TRMM overestimated on average 24.7% daily rainfall. As TRMM minimum time-steps is 3 h, in order to verify shorter duration rainfall, the TRMM data were adapted to fit Bell's (1969) generalized IDF formula (based on the existence of similarity between the mechanisms of extreme rainfall events as they are associated to convective cells). Bell`s equation error against measured precipitation was around 5-10%, which varied based on location, RP and duration while the coupled BELL+TRMM error was around 10-35%. However, errors were regionally distributed, allowing a correction to be implemented that reduced by half these values. These findings in turn permitted the use of TRMM+Bell estimates to improve the understanding of spatiotemporal distribution of extreme hydrological rainfall events.

A new hydrological model for estimating extreme floods in the Alps

NASA Astrophysics Data System (ADS)

Receanu, R. G.; Hertig, J.-A.; Fallot, J.-M.

2012-04-01

Protection against flooding is very important for a country like Switzerland with a varied topography and many rivers and lakes. Because of the potential danger caused by extreme precipitation, structural and functional safety of large dams must be guaranteed to withstand the passage of an extreme flood. We introduce a new distributed hydrological model to calculate the PMF from a PMP which is spatially and temporally distributed using clouds. This model has permitted the estimation of extreme floods based on the distributed PMP and the taking into account of the specifics of alpine catchments, in particular the small size of the basins, the complex topography, the large lakes, snowmelt and glaciers. This is an important evolution compared to other models described in the literature, as they mainly use a uniform distribution of extreme precipitation all over the watershed. This paper presents the results of calculation with the developed rainfall-runoff model, taking into account measured rainfall and comparing results to observed flood events. This model includes three parts: surface runoff, underground flow and melting snow. Two Swiss watersheds are studied, for which rainfall data and flow rates are available for a considerably long period, including several episodes of heavy rainfall with high flow events. From these events, several simulations are performed to estimate the input model parameters such as soil roughness and average width of rivers in case of surface runoff. Following the same procedure, the parameters used in the underground flow simulation are also estimated indirectly, since direct underground flow and exfiltration measurements are difficult to obtain. A sensitivity analysis of the parameters is performed at the first step to define more precisely the boundary and initial conditions. The results for the two alpine basins, validated with the Nash equation, show a good correlation between the simulated and observed flows. This good correlation

An "Ensemble Approach" to Modernizing Extreme Precipitation Estimation for Dam Safety Decision-Making

NASA Astrophysics Data System (ADS)

Cifelli, R.; Mahoney, K. M.; Webb, R. S.; McCormick, B.

2017-12-01

To ensure structural and operational safety of dams and other water management infrastructure, water resources managers and engineers require information about the potential for heavy precipitation. The methods and data used to estimate extreme rainfall amounts for managing risk are based on 40-year-old science and in need of improvement. The need to evaluate new approaches based on the best science available has led the states of Colorado and New Mexico to engage a body of scientists and engineers in an innovative "ensemble approach" to updating extreme precipitation estimates. NOAA is at the forefront of one of three technical approaches that make up the "ensemble study"; the three approaches are conducted concurrently and in collaboration with each other. One approach is the conventional deterministic, "storm-based" method, another is a risk-based regional precipitation frequency estimation tool, and the third is an experimental approach utilizing NOAA's state-of-the-art High Resolution Rapid Refresh (HRRR) physically-based dynamical weather prediction model. The goal of the overall project is to use the individual strengths of these different methods to define an updated and broadly acceptable state of the practice for evaluation and design of dam spillways. This talk will highlight the NOAA research and NOAA's role in the overarching goal to better understand and characterizing extreme precipitation estimation uncertainty. The research led by NOAA explores a novel high-resolution dataset and post-processing techniques using a super-ensemble of hourly forecasts from the HRRR model. We also investigate how this rich dataset may be combined with statistical methods to optimally cast the data in probabilistic frameworks. NOAA expertise in the physical processes that drive extreme precipitation is also employed to develop careful testing and improved understanding of the limitations of older estimation methods and assumptions. The process of decision making in the

A modified estimation distribution algorithm based on extreme elitism.

PubMed

Gao, Shujun; de Silva, Clarence W

2016-12-01

An existing estimation distribution algorithm (EDA) with univariate marginal Gaussian model was improved by designing and incorporating an extreme elitism selection method. This selection method highlighted the effect of a few top best solutions in the evolution and advanced EDA to form a primary evolution direction and obtain a fast convergence rate. Simultaneously, this selection can also keep the population diversity to make EDA avoid premature convergence. Then the modified EDA was tested by means of benchmark low-dimensional and high-dimensional optimization problems to illustrate the gains in using this extreme elitism selection. Besides, no-free-lunch theorem was implemented in the analysis of the effect of this new selection on EDAs. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

(When and where) Do extreme climate events trigger extreme ecosystem responses? - Development and initial results of a holistic analysis framework

NASA Astrophysics Data System (ADS)

Hauber, Eva K.; Donner, Reik V.

2015-04-01

In the context of ongoing climate change, extremes are likely to increase in magnitude and frequency. One of the most important consequences of these changes is that the associated ecological risks and impacts are potentially rising as well. In order to better anticipate and understand these impacts, it therefore becomes more and more crucial to understand the general connection between climate extremes and the response and functionality of ecosystems. Among other region of the world, Europe presents an excellent test case for studies concerning the interaction between climate and biosphere, since it lies in the transition region between cold polar and warm tropical air masses and thus covers a great variety of different climatic zones and associated terrestrial ecosystems. The large temperature differences across the continent make this region particularly interesting for investigating the effects of climate change on biosphere-climate interactions. However, previously used methods for defining an extreme event typically disregard the necessity of taking seasonality as well as seasonal variance appropriately into account. Furthermore, most studies have focused on the impacts of individual extreme events instead of considering a whole inventory of extremes with their respective spatio-temporal extents. In order to overcome the aforementioned research gaps, this work introduces a new approach to studying climate-biosphere interactions associated with extreme events, which comprises three consecutive steps: (1) Since Europe exhibits climatic conditions characterized by marked seasonality, a novel method is developed to define extreme events taking into account the seasonality in all quantiles of the probability distribution of the respective variable of interest. This is achieved by considering kernel density estimates individually for each observation date during the year, including the properly weighted information from adjacent dates. By this procedure, we obtain

Integrating plant ecological responses to climate extremes from individual to ecosystem levels.

PubMed

Felton, Andrew J; Smith, Melinda D

2017-06-19

Climate extremes will elicit responses from the individual to the ecosystem level. However, only recently have ecologists begun to synthetically assess responses to climate extremes across multiple levels of ecological organization. We review the literature to examine how plant responses vary and interact across levels of organization, focusing on how individual, population and community responses may inform ecosystem-level responses in herbaceous and forest plant communities. We report a high degree of variability at the individual level, and a consequential inconsistency in the translation of individual or population responses to directional changes in community- or ecosystem-level processes. The scaling of individual or population responses to community or ecosystem responses is often predicated upon the functional identity of the species in the community, in particular, the dominant species. Furthermore, the reported stability in plant community composition and functioning with respect to extremes is often driven by processes that operate at the community level, such as species niche partitioning and compensatory responses during or after the event. Future research efforts would benefit from assessing ecological responses across multiple levels of organization, as this will provide both a holistic and mechanistic understanding of ecosystem responses to increasing climatic variability.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation

NASA Astrophysics Data System (ADS)

Byun, K.; Hamlet, A. F.

2017-12-01

There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.

Estimating the Extreme Behaviors of Students Performance Using Quantile Regression--Evidences from Taiwan

ERIC Educational Resources Information Center

Chen, Sheng-Tung; Kuo, Hsiao-I.; Chen, Chi-Chung

2012-01-01

The two-stage least squares approach together with quantile regression analysis is adopted here to estimate the educational production function. Such a methodology is able to capture the extreme behaviors of the two tails of students' performance and the estimation outcomes have important policy implications. Our empirical study is applied to the…

Optimal regionalization of extreme value distributions for flood estimation

NASA Astrophysics Data System (ADS)

Asadi, Peiman; Engelke, Sebastian; Davison, Anthony C.

2018-01-01

Regionalization methods have long been used to estimate high return levels of river discharges at ungauged locations on a river network. In these methods, discharge measurements from a homogeneous group of similar, gauged, stations are used to estimate high quantiles at a target location that has no observations. The similarity of this group to the ungauged location is measured in terms of a hydrological distance measuring differences in physical and meteorological catchment attributes. We develop a statistical method for estimation of high return levels based on regionalizing the parameters of a generalized extreme value distribution. The group of stations is chosen by optimizing over the attribute weights of the hydrological distance, ensuring similarity and in-group homogeneity. Our method is applied to discharge data from the Rhine basin in Switzerland, and its performance at ungauged locations is compared to that of other regionalization methods. For gauged locations we show how our approach improves the estimation uncertainty for long return periods by combining local measurements with those from the chosen group.

Comparison of different statistical methods for estimation of extreme sea levels with wave set-up contribution

NASA Astrophysics Data System (ADS)

Kergadallan, Xavier; Bernardara, Pietro; Benoit, Michel; Andreewsky, Marc; Weiss, Jérôme

2013-04-01

Estimating the probability of occurrence of extreme sea levels is a central issue for the protection of the coast. Return periods of sea level with wave set-up contribution are estimated here in one site : Cherbourg in France in the English Channel. The methodology follows two steps : the first one is computation of joint probability of simultaneous wave height and still sea level, the second one is interpretation of that joint probabilities to assess a sea level for a given return period. Two different approaches were evaluated to compute joint probability of simultaneous wave height and still sea level : the first one is multivariate extreme values distributions of logistic type in which all components of the variables become large simultaneously, the second one is conditional approach for multivariate extreme values in which only one component of the variables have to be large. Two different methods were applied to estimate sea level with wave set-up contribution for a given return period : Monte-Carlo simulation in which estimation is more accurate but needs higher calculation time and classical ocean engineering design contours of type inverse-FORM in which the method is simpler and allows more complex estimation of wave setup part (wave propagation to the coast for example). We compare results from the two different approaches with the two different methods. To be able to use both Monte-Carlo simulation and design contours methods, wave setup is estimated with an simple empirical formula. We show advantages of the conditional approach compared to the multivariate extreme values approach when extreme sea-level occurs when either surge or wave height is large. We discuss the validity of the ocean engineering design contours method which is an alternative when computation of sea levels is too complex to use Monte-Carlo simulation method.

Crop insurance evaluation in response to extreme events

NASA Astrophysics Data System (ADS)

Moriondo, Marco; Ferrise, Roberto; Bindi, Marco

2013-04-01

Crop yield insurance has been indicated as a tool to manage the uncertainties of crop yields (Sherrick et al., 2004) but the changes in crop yield variability as expected in the near future should be carefully considered for a better quantitative assessment of farmer's revenue risk and insurance values in a climatic change regime (Moriondo et al., 2011). Under this point of view, mechanistic crop growth models coupled to the output of General/Regional Circulation Models (GCMs, RCMs) offer a valuable tool to evaluate crop responses to climatic change and this approach has been extensively used to describe crop yield distribution in response to climatic change considering changes in both mean climate and variability. In this work, we studied the effect of a warmer climate on crop yield distribution of durum wheat (Triticum turgidum L. subsp durum) in order to assess the economic significance of climatic change in a risk decision context. Specifically, the outputs of 6 RCMs (Tmin, Tmax, Rainfall, Global Radiation) (van der Linden and Mitchell 2009) have been statistically downscaled by a stochastic weather generator over eight sites across the Mediterranean basin and used to feed the crop growth model Sirius Quality. Three time slices were considered i) the present period PP (average of the period 1975-1990, [CO2]=350 ppm), 2020 (average of the period 2010-2030, SRES scenario A1b, [CO2]=415 ppm) and 2040 (average of the period 2030-2050, SRES scenario A1b, [CO2]=480 ppm). The effect of extreme climate events (i.e. heat stress at anthesis stage) was also considered. The outputs of these simulations were used to estimate the expected payout per hectare from insurance triggered when yields fall below a specific threshold defined as "the insured yield". For each site, the threshold was calculated as a fraction (70%) of the median of yield distribution under PP that represents the percentage of median yield above which indemnity payments are triggered. The results

Responsiveness of SF-36 and Lower Extremity Functional Scale for assessing outcomes in traumatic injuries of lower extremities.

PubMed

Pan, Shin-Liang; Liang, Huey-Wen; Hou, Wen-Hsuan; Yeh, Tian-Shin

2014-11-01

To assess the responsiveness of one generic questionnaire, Medical Outcomes Study Short Form-36 (SF-36), and one region-specific outcome measure, Lower Extremity Functional Scale (LEFS), in patients with traumatic injuries of lower extremities. A prospective and observational study of patients after traumatic injuries of lower extremities. Assessments were performed at baseline and 3 months later. In-patients and out-patients in two university hospitals in Taiwan. A convenience sample of 109 subjects were evaluated and 94 (86%) were followed. Not applicable. Assessments of responsiveness with distribution-based approach (effect size, standardized response mean [SRM], minimal detectable change) and anchor-based approach (receiver's operating curve analysis, ROC analysis). LEFS and physical component score (PCS) of SF-36 were all responsive to global improvement, with fair-to-good accuracy in discriminating between participants with and without improvement. The area under curve gained by ROC analysis for LEFS and SF-36 PCS was similar (0.65 vs. 0.70, p=0.26). Our findings revealed comparable responsiveness of LEFS and PCS of SF-36 in a sample of subjects with traumatic injuries of lower limbs. Either type of functional measure would be suitable for use in clinical trials where improvement in function was an endpoint of interest. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mangrove species' responses to winter air temperature extremes in China

USGS Publications Warehouse

Chen, Luzhen; Wang, Wenqing; Li, Qingshun Q.; Zhang, Yihui; Yang, Shengchang; Osland, Michael J.; Huang, Jinliang; Peng, Congjiao

2017-01-01

The global distribution and diversity of mangrove forests is greatly influenced by the frequency and intensity of winter air temperature extremes. However, our understanding of how different mangrove species respond to winter temperature extremes has been lacking because extreme freezing and chilling events are, by definition, relatively uncommon and also difficult to replicate experimentally. In this study, we investigated species-specific variation in mangrove responses to winter temperature extremes in China. In 10 sites that span a latitudinal gradient, we quantified species-specific damage and recovery following a chilling event, for mangrove species within and outside of their natural range (i.e., native and non-native species, respectively). To characterize plant stress, we measured tree defoliation and chlorophyll fluorescence approximately one month following the chilling event. To quantify recovery, we measured chlorophyll fluorescence approximately nine months after the chilling event. Our results show high variation in the geographic- and species-specific responses of mangroves to winter temperature extremes. While many species were sensitive to the chilling temperatures (e.g., Bruguiera sexangula and species in the Sonneratia and Rhizophora genera), the temperatures during this event were not cold enough to affect certain species (e.g., Kandelia obovata, Aegiceras corniculatum, Avicennia marina, and Bruguiera gymnorrhiza). As expected, non-native species were less tolerant of winter temperature extremes than native species. Interestingly, tidal inundation modulated the effects of chilling. In comparison with other temperature-controlled mangrove range limits across the world, the mangrove range limit in China is unique due to the combination of the following three factors: (1) Mangrove species diversity is comparatively high; (2) winter air temperature extremes, rather than means, are particularly intense and play an important ecological

Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

NASA Astrophysics Data System (ADS)

Costa, Veber; Fernandes, Wilson

2017-11-01

Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods

The Relationship between Spatial and Temporal Magnitude Estimation of Scientific Concepts at Extreme Scales

NASA Astrophysics Data System (ADS)

Price, Aaron; Lee, H.

2010-01-01

Many astronomical objects, processes, and events exist and occur at extreme scales of spatial and temporal magnitudes. Our research draws upon the psychological literature, replete with evidence of linguistic and metaphorical links between the spatial and temporal domains, to compare how students estimate spatial and temporal magnitudes associated with objects and processes typically taught in science class.. We administered spatial and temporal scale estimation tests, with many astronomical items, to 417 students enrolled in 12 undergraduate science courses. Results show that while the temporal test was more difficult, students’ overall performance patterns between the two tests were mostly similar. However, asymmetrical correlations between the two tests indicate that students think of the extreme ranges of spatial and temporal scales in different ways, which is likely influenced by their classroom experience. When making incorrect estimations, students tended to underestimate the difference between the everyday scale and the extreme scales on both tests. This suggests the use of a common logarithmic mental number line for both spatial and temporal magnitude estimation. However, there are differences between the two tests in the errors student make in the everyday range. Among the implications discussed is the use of spatio-temporal reference frames, instead of smooth bootstrapping, to help students maneuver between scales of magnitude and the use of logarithmic transformations between reference frames. Implications for astronomy range from learning about spectra to large scale galaxy structure.

Uncertainties in extreme surge level estimates from observational records.

PubMed

van den Brink, H W; Können, G P; Opsteegh, J D

2005-06-15

Ensemble simulations with a total length of 7540 years are generated with a climate model, and coupled to a simple surge model to transform the wind field over the North Sea to the skew surge level at Delfzijl, The Netherlands. The 65 constructed surge records, each with a record length of 116 years, are analysed with the generalized extreme value (GEV) and the generalized Pareto distribution (GPD) to study both the model and sample uncertainty in surge level estimates with a return period of 104 years, as derived from 116-year records. The optimal choice of the threshold, needed for an unbiased GPD estimate from peak over threshold (POT) values, cannot be determined objectively from a 100-year dataset. This fact, in combination with the sensitivity of the GPD estimate to the threshold, and its tendency towards too low estimates, leaves the application of the GEV distribution to storm-season maxima as the best approach. If the GPD analysis is applied, then the exceedance rate, lambda, chosen should not be larger than 4. The climate model hints at the existence of a second population of very intense storms. As the existence of such a second population can never be excluded from a 100-year record, the estimated 104-year wind-speed from such records has always to be interpreted as a lower limit.

Estimating extreme river discharges in Europe through a Bayesian network

NASA Astrophysics Data System (ADS)

Paprotny, Dominik; Morales-Nápoles, Oswaldo

2017-06-01

Large-scale hydrological modelling of flood hazards requires adequate extreme discharge data. In practise, models based on physics are applied alongside those utilizing only statistical analysis. The former require enormous computational power, while the latter are mostly limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian networks (BNs), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables representing the geographical characteristics of their catchments. Annual maxima of daily discharges from more than 1800 river gauges (stations with catchment areas ranging from 1.4 to 807 000 km2) were collected, together with information on terrain, land use and local climate. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe and better than a comparable global statistical model. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and remains the same in a split-sample validation. Though discharge prediction under climate change is not the main scope of this paper, the BN was applied to a large domain covering all sizes of rivers in the continent both for present and future climate, as an example. Results show substantial variation in the influence of climate change on river discharges. The model can be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

Estimates of peak flood discharge for 21 sites in the Front Range in Colorado in response to extreme rainfall in September 2013

USGS Publications Warehouse

Moody, John A.

2016-03-21

Extreme rainfall in September 2013 caused destructive floods in part of the Front Range in Boulder County, Colorado. Erosion from these floods cut roads and isolated mountain communities for several weeks, and large volumes of eroded sediment were deposited downstream, which caused further damage of property and infrastructures. Estimates of peak discharge for these floods and the associated rainfall characteristics will aid land and emergency managers in the future. Several methods (an ensemble) were used to estimate peak discharge at 21 measurement sites, and the ensemble average and standard deviation provided a final estimate of peak discharge and its uncertainty. Because of the substantial erosion and deposition of sediment, an additional estimate of peak discharge was made based on the flow resistance caused by sediment transport effects.Although the synoptic-scale rainfall was extreme (annual exceedance probability greater than 1,000 years, about 450 millimeters in 7 days) for these mountains, the resulting peak discharges were not. Ensemble average peak discharges per unit drainage area (unit peak discharge, [Qu]) for the floods were 1–2 orders of magnitude less than those for the maximum worldwide floods with similar drainage areas and had a wide range of values (0.21–16.2 cubic meters per second per square kilometer [m3 s-1 km-2]). One possible explanation for these differences was that the band of high-accumulation, high-intensity rainfall was narrow (about 50 kilometers wide), oriented nearly perpendicular to the predominant drainage pattern of the mountains, and therefore entire drainage areas were not subjected to the same range of extreme rainfall. A linear relation (coefficient of determination [R2]=0.69) between Qu and the rainfall intensity (ITc, computed for a time interval equal to the time-of-concentration for the drainage area upstream from each site), had the form: Qu=0.26(ITc-8.6), where the coefficient 0.26 can be considered to be an

Using Kriging with a heterogeneous measurement error to improve the accuracy of extreme precipitation return level estimation

NASA Astrophysics Data System (ADS)

Yin, Shui-qing; Wang, Zhonglei; Zhu, Zhengyuan; Zou, Xu-kai; Wang, Wen-ting

2018-07-01

Extreme precipitation can cause flooding and may result in great economic losses and deaths. The return level is a commonly used measure of extreme precipitation events and is required for hydrological engineer designs, including those of sewerage systems, dams, reservoirs and bridges. In this paper, we propose a two-step method to estimate the return level and its uncertainty for a study region. In the first step, we use the generalized extreme value distribution, the L-moment method and the stationary bootstrap to estimate the return level and its uncertainty at the site with observations. In the second step, a spatial model incorporating the heterogeneous measurement errors and covariates is trained to estimate return levels at sites with no observations and to improve the estimates at sites with limited information. The proposed method is applied to the daily rainfall data from 273 weather stations in the Haihe river basin of North China. We compare the proposed method with two alternatives: the first one is based on the ordinary Kriging method without measurement error, and the second one smooths the estimated location and scale parameters of the generalized extreme value distribution by the universal Kriging method. Results show that the proposed method outperforms its counterparts. We also propose a novel approach to assess the two-step method by comparing it with the at-site estimation method with a series of reduced length of observations. Estimates of the 2-, 5-, 10-, 20-, 50- and 100-year return level maps and the corresponding uncertainties are provided for the Haihe river basin, and a comparison with those released by the Hydrology Bureau of Ministry of Water Resources of China is made.

Estimating extreme stream temperatures by the standard deviate method

NASA Astrophysics Data System (ADS)

Bogan, Travis; Othmer, Jonathan; Mohseni, Omid; Stefan, Heinz

2006-02-01

It is now widely accepted that global climate warming is taking place on the earth. Among many other effects, a rise in air temperatures is expected to increase stream temperatures indefinitely. However, due to evaporative cooling, stream temperatures do not increase linearly with increasing air temperatures indefinitely. Within the anticipated bounds of climate warming, extreme stream temperatures may therefore not rise substantially. With this concept in mind, past extreme temperatures measured at 720 USGS stream gauging stations were analyzed by the standard deviate method. In this method the highest stream temperatures are expressed as the mean temperature of a measured partial maximum stream temperature series plus its standard deviation multiplied by a factor KE (standard deviate). Various KE-values were explored; values of KE larger than 8 were found physically unreasonable. It is concluded that the value of KE should be in the range from 7 to 8. A unit error in estimating KE translates into a typical stream temperature error of about 0.5 °C. Using a logistic model for the stream temperature/air temperature relationship, a one degree error in air temperature gives a typical error of 0.16 °C in stream temperature. With a projected error in the enveloping standard deviate dKE=1.0 (range 0.5-1.5) and an error in projected high air temperature d Ta=2 °C (range 0-4 °C), the total projected stream temperature error is estimated as d Ts=0.8 °C.

Extreme startle and photomyoclonic response in severe hypocalcaemia.

PubMed

Moccia, Marcello; Erro, Roberto; Nicolella, Elvira; Striano, Pasquale; Striano, Salvatore

2014-03-01

We report the case of 62-year-old woman referred to our department because of a clinical suspicion of tonic-clonic seizures. Clinical examination revealed an exaggerated startle reflex, EEG showed a photomyoclonic response, and blood tests indicated severe hypocalcaemia. Additional clinical data, treatment strategies, and long-term follow-up visits were reported. The present report discusses the difficulties in distinguishing between epileptic and non-epileptic startles, and shows, for the first time, exaggerated startle reflex and extreme photomyoclonic response due to severe hypocalcaemia.

Modeling short duration extreme precipitation patterns using copula and generalized maximum pseudo-likelihood estimation with censoring

NASA Astrophysics Data System (ADS)

Bargaoui, Zoubeida Kebaili; Bardossy, Andràs

2015-10-01

The paper aims to develop researches on the spatial variability of heavy rainfall events estimation using spatial copula analysis. To demonstrate the methodology, short time resolution rainfall time series from Stuttgart region are analyzed. They are constituted by rainfall observations on continuous 30 min time scale recorded over a network composed by 17 raingages for the period July 1989-July 2004. The analysis is performed aggregating the observations from 30 min up to 24 h. Two parametric bivariate extreme copula models, the Husler-Reiss model and the Gumbel model are investigated. Both involve a single parameter to be estimated. Thus, model fitting is operated for every pair of stations for a giving time resolution. A rainfall threshold value representing a fixed rainfall quantile is adopted for model inference. Generalized maximum pseudo-likelihood estimation is adopted with censoring by analogy with methods of univariate estimation combining historical and paleoflood information with systematic data. Only pairs of observations greater than the threshold are assumed as systematic data. Using the estimated copula parameter, a synthetic copula field is randomly generated and helps evaluating model adequacy which is achieved using Kolmogorov Smirnov distance test. In order to assess dependence or independence in the upper tail, the extremal coefficient which characterises the tail of the joint bivariate distribution is adopted. Hence, the extremal coefficient is reported as a function of the interdistance between stations. If it is less than 1.7, stations are interpreted as dependent in the extremes. The analysis of the fitted extremal coefficients with respect to stations inter distance highlights two regimes with different dependence structures: a short spatial extent regime linked to short duration intervals (from 30 min to 6 h) with an extent of about 8 km and a large spatial extent regime related to longer rainfall intervals (from 12 h to 24 h) with an

Diabetic Driving Studies-Part 1: Brake Response Time in Diabetic Drivers With Lower Extremity Neuropathy.

PubMed

Meyr, Andrew J; Spiess, Kerianne E

Although the effect of lower extremity pathology and surgical intervention on automobile driving function has been a topic of contemporary interest, we are unaware of any analysis of the effect of lower extremity diabetic sensorimotor neuropathy on driving performance. The objective of the present case-control investigation was to assess the mean brake response time in diabetic drivers with lower extremity neuropathy compared with that of a control group and a brake response safety threshold. The driving performances of participants were evaluated using a computerized driving simulator with specific measurement of the mean brake response time and frequency of abnormally delayed brake responses. We analyzed a control group of 25 active drivers with neither diabetes nor lower extremity neuropathy and an experimental group of 25 active drivers with type 2 diabetes and lower extremity neuropathy. The experimental group demonstrated a 37.89% slower mean brake response time (0.757 ± 0.180 versus 0.549 ± 0.076 second; p < .001), with abnormally delayed responses occurring at a greater frequency (57.5% versus 3.5%; p < .001). Independent of a comparative statistical analysis, the observed mean brake response time in the experimental group was slower than the reported safety brake response threshold of 0.70 second. The results of the present investigation provide original data with respect to abnormally delayed brake responses in diabetic patients with lower extremity neuropathy and might raise the potential for impaired driving function in this population. Copyright © 2017 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Replica and extreme-value analysis of the Jarzynski free-energy estimator

NASA Astrophysics Data System (ADS)

Palassini, Matteo; Ritort, Felix

2008-03-01

We analyze the Jarzynski estimator of free-energy differences from nonequilibrium work measurements. By a simple mapping onto Derrida's Random Energy Model, we obtain a scaling limit for the expectation of the bias of the estimator. We then derive analytical approximations in three different regimes of the scaling parameter x = log(N)/W, where N is the number of measurements and W the mean dissipated work. Our approach is valid for a generic distribution of the dissipated work, and is based on a replica symmetry breaking scheme for x >> 1, the asymptotic theory of extreme value statistics for x << 1, and a direct approach for x near one. The combination of the three analytic approximations describes well Monte Carlo data for the expectation value of the estimator, for a wide range of values of N, from N=1 to large N, and for different work distributions. Based on these results, we introduce improved free-energy estimators and discuss the application to the analysis of experimental data.

Streamflow response to increasing precipitation extremes altered by forest management

NASA Astrophysics Data System (ADS)

Kelly, Charlene N.; McGuire, Kevin J.; Miniat, Chelcy Ford; Vose, James M.

2016-04-01

Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the impact of the interaction between forest management and precipitation. We use daily long-term data from paired watersheds that have undergone forest harvest or species conversion. We find that interactive effects of climate change, represented by changes in observed precipitation trends, and forest management regime, significantly alter expected streamflow most often during extreme events, ranging from a decrease of 59% to an increase of 40% in streamflow, depending upon management. Our results suggest that vegetation might be managed to compensate for hydrologic responses due to climate change to help mitigate effects of extreme changes in precipitation.

Using damage data to estimate the risk from summer convective precipitation extremes

NASA Astrophysics Data System (ADS)

Schroeer, Katharina; Tye, Mari

2017-04-01

model to test whether the relationship between extreme rainfall events and damages is robust enough to estimate a potential underrepresentation of high intensity rainfall events in ungauged areas. Risk-relevant factors of socio-economic vulnerability, land cover, streamflow data, and weather type information are included to improve and sharpen the analysis. Within this study, we first aim to identify which rainfall events are most damaging and which factors affect the damages - seen as a proxy for the vulnerability - related to summer convective rainfall extremes in different catchment types. Secondly, we aim to detect potentially unreported damaging rainfall events and estimate the likelihood of such cases. We anticipate this damage perspective on summertime extreme convective precipitation to be beneficial for risk assessment, uncertainty management, and decision making with respect to weather and climate extremes on the regional-to-local level.

Observations and estimates of wave-driven water level extremes at the Marshall Islands

NASA Astrophysics Data System (ADS)

Merrifield, M. A.; Becker, J. M.; Ford, M.; Yao, Y.

2014-10-01

Wave-driven extreme water levels are examined for coastlines protected by fringing reefs using field observations obtained in the Republic of the Marshall Islands. The 2% exceedence water level near the shoreline due to waves is estimated empirically for the study sites from breaking wave height at the outer reef and by combining separate contributions from setup, sea and swell, and infragravity waves, which are estimated based on breaking wave height and water level over the reef flat. Although each component exhibits a tidal dependence, they sum to yield a 2% exceedence level that does not. A hindcast based on the breaking wave height parameterization is used to assess factors leading to flooding at Roi-Namur caused by an energetic swell event during December 2008. Extreme water levels similar to December 2008 are projected to increase significantly with rising sea level as more wave and tide events combine to exceed inundation threshold levels.

Multi-catchment rainfall-runoff simulation for extreme flood estimation

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel

2017-04-01

The SCHADEX method (Paquet et al., 2013) is a reference method in France for the estimation of extreme flood for dam design. The method is based on a semi-continuous rainfall-runoff simulation process: hundreds of different rainy events, randomly drawn up to extreme values, are simulated independently in the hydrological conditions of each day when a rainy event has been actually observed. This allows generating an exhaustive set of crossings between precipitation and soil saturation hazards, and to build a complete distribution of flood discharges up to extreme quantiles. The hydrological model used within SCHADEX, the MORDOR model (Garçon, 1996), is a lumped model, which implies that hydrological processes, e.g. rainfall and soil saturation, are supposed to be homogeneous throughout the catchment. Snow processes are nevertheless represented in relation with altitude. This hypothesis of homogeneity is questionable especially as the size of the catchment increases, or in areas of highly contrasted climatology (like mountainous areas). Conversely, modeling the catchment with a fully distributed approach would cause different problems, in particular distributing the rainfall-runoff model parameters trough space, and within the SCHADEX stochastic framework, generating extreme rain fields with credible spatio-temporal features. An intermediate solution is presented here. It provides a better representation of the hydro-climatic diversity of the studied catchment (especially regarding flood processes) while keeping the SCHADEX simulation framework. It consists in dividing the catchment in several, more homogeneous sub-catchments. Rainfall-runoff models are parameterized individually for each of them, using local discharge data if available. A first SCHADEX simulation is done at the global scale, which allows assigning a probability to each simulated event, mainly based on the global areal rainfall drawn for the event (see Paquet el al., 2013 for details). Then the

Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments

DOE PAGES

Wilcox, Kevin R.; Shi, Zheng; Gherardi, Laureano A.; ...

2017-04-02

Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitationmore » changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. Here, we used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. Finally, this highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into

Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments.

PubMed

Wilcox, Kevin R; Shi, Zheng; Gherardi, Laureano A; Lemoine, Nathan P; Koerner, Sally E; Hoover, David L; Bork, Edward; Byrne, Kerry M; Cahill, James; Collins, Scott L; Evans, Sarah; Gilgen, Anna K; Holub, Petr; Jiang, Lifen; Knapp, Alan K; LeCain, Daniel; Liang, Junyi; Garcia-Palacios, Pablo; Peñuelas, Josep; Pockman, William T; Smith, Melinda D; Sun, Shanghua; White, Shannon R; Yahdjian, Laura; Zhu, Kai; Luo, Yiqi

2017-10-01

Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change

Asymmetrical Responses of Ecosystem Processes to Positive Versus Negative Precipitation Extremes: a Replicated Regression Experimental Approach

NASA Astrophysics Data System (ADS)

Felton, A. J.; Smith, M. D.

2016-12-01

Heightened climatic variability due to atmospheric warming is forecast to increase the frequency and severity of climate extremes. In particular, changes to interannual variability in precipitation, characterized by increases in extreme wet and dry years, are likely to impact virtually all terrestrial ecosystem processes. However, to date experimental approaches have yet to explicitly test how ecosystem processes respond to multiple levels of climatic extremity, limiting our understanding of how ecosystems will respond to forecast increases in the magnitude of climate extremes. Here we report the results of a replicated regression experimental approach, in which we imposed 9 and 11 levels of growing season precipitation amount and extremity in mesic grassland during 2015 and 2016, respectively. Each level corresponded to a specific percentile of the long-term record, which produced a large gradient of soil moisture conditions that ranged from extreme wet to extreme dry. In both 2015 and 2016, asymptotic responses to water availability were observed for soil respiration. This asymmetry was driven in part by transitions between soil moisture versus temperature constraints on respiration as conditions became increasingly dry versus increasingly wet. In 2015, aboveground net primary production (ANPP) exhibited asymmetric responses to precipitation that largely mirrored those of soil respiration. In total, our results suggest that in this mesic ecosystem, these two carbon cycle processes were more sensitive to extreme drought than to extreme wet years. Future work will assess ANPP responses for 2016, soil nutrient supply and physiological responses of the dominant plant species. Future efforts are needed to compare our findings across a diverse array of ecosystem types, and in particular how the timing and magnitude of precipitation events may modify the response of ecosystem processes to increasing magnitudes of precipitation extremes.

Phenology of mixed woody-herbaceous ecosystems following extreme events: net and differential responses.

PubMed

Rich, Paul M; Breshears, David D; White, Amanda B

2008-02-01

Ecosystem responses to key climate drivers are reflected in phenological dynamics such as the timing and degree of "green-up" that integrate responses over spatial scales from individual plants to ecosystems. This integration is clearest in ecosystems dominated by a single species or life form, such as seasonally dynamic grasslands or more temporally constant evergreen forests. Yet many ecosystems have substantial contribution of cover from both herbaceous and woody evergreen plants. Responses of mixed woody-herbaceous ecosystems to climate are of increasing concern due to their extensive nature, the potential for such systems to yield more complex responses than those dominated by a single life form, and projections that extreme climate and weather events will increase in frequency and intensity with global warming. We present responses of a mixed woody-herbaceous ecosystem type to an extreme event: regional-scale piñon pine mortality following an extended drought and the subsequent herbaceous green-up following the first wet period after the drought. This example highlights how reductions in greenness of the slower, more stable evergreen woody component can rapidly be offset by increases associated with resources made available to the relatively more responsive herbaceous component. We hypothesize that such two-phase phenological responses to extreme events are characteristic of many mixed woody-herbaceous ecosystems.

Combining Radar and Daily Precipitation Data to Estimate Meaningful Sub-daily Precipitation Extremes

NASA Astrophysics Data System (ADS)

Pegram, G. G. S.; Bardossy, A.

2016-12-01

Short duration extreme rainfalls are important for design. The purpose of this presentation is not to improve the day by day estimation of precipitation, but to obtain reasonable statistics for the subdaily extremes at gauge locations. We are interested specifically in daily and sub-daily extreme values of precipitation at gauge locations. We do not employ the common procedure of using time series of control station to determine the missing data values in a target. We are interested in individual rare events, not sequences. The idea is to use radar to disaggregate daily totals to sub-daily amounts. In South Arica, an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. Using this valuable set of data, we are only interested in rare extremes, therefore small to medium values of rainfall depth were neglected, leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprised about 50% of each annual rainfall total. The method presented here uses radar for disaggregating daily gauge totals in subdaily intervals down to 15 minutes in order to extract the maxima of sub-hourly through to daily rainfall at each of 37 selected radar pixels [1 km square in plan] which contained one of the 45 pluviometers not masked out by the radar foot-print. The pluviometer data were aggregated to daily totals, to act as if they were daily read gauges; their only other task was to help in the cross-validation exercise. The extrema were obtained as quantiles by ordering the 12 daily maxima of each interval per year. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the gauge and radar extremes, by matching their ranks, which we found to be stable and meaningful in cross-validation tests. We provide and

A probabilistic storm transposition approach for estimating exceedance probabilities of extreme precipitation depths

NASA Astrophysics Data System (ADS)

Foufoula-Georgiou, E.

1989-05-01

A storm transposition approach is investigated as a possible tool of assessing the frequency of extreme precipitation depths, that is, depths of return period much greater than 100 years. This paper focuses on estimation of the annual exceedance probability of extreme average precipitation depths over a catchment. The probabilistic storm transposition methodology is presented, and the several conceptual and methodological difficulties arising in this approach are identified. The method is implemented and is partially evaluated by means of a semihypothetical example involving extreme midwestern storms and two hypothetical catchments (of 100 and 1000 mi2 (˜260 and 2600 km2)) located in central Iowa. The results point out the need for further research to fully explore the potential of this approach as a tool for assessing the probabilities of rare storms, and eventually floods, a necessary element of risk-based analysis and design of large hydraulic structures.

Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

NASA Astrophysics Data System (ADS)

Bárdossy, András; Pegram, Geoffrey

2017-01-01

The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the paper is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the subdaily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. Additionally a statistical procedure not based on a matching day by day correction is tested. In this last procedure as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest L radar based days. Of course, the timings of radar and gauge maxima can be different, so the method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated relatively continuously at

Combining Empirical and Stochastic Models for Extreme Floods Estimation

NASA Astrophysics Data System (ADS)

Zemzami, M.; Benaabidate, L.

2013-12-01

Hydrological models can be defined as physical, mathematical or empirical. The latter class uses mathematical equations independent of the physical processes involved in the hydrological system. The linear regression and Gradex (Gradient of Extreme values) are classic examples of empirical models. However, conventional empirical models are still used as a tool for hydrological analysis by probabilistic approaches. In many regions in the world, watersheds are not gauged. This is true even in developed countries where the gauging network has continued to decline as a result of the lack of human and financial resources. Indeed, the obvious lack of data in these watersheds makes it impossible to apply some basic empirical models for daily forecast. So we had to find a combination of rainfall-runoff models in which it would be possible to create our own data and use them to estimate the flow. The estimated design floods would be a good choice to illustrate the difficulties facing the hydrologist for the construction of a standard empirical model in basins where hydrological information is rare. The construction of the climate-hydrological model, which is based on frequency analysis, was established to estimate the design flood in the Anseghmir catchments, Morocco. The choice of using this complex model returns to its ability to be applied in watersheds where hydrological information is not sufficient. It was found that this method is a powerful tool for estimating the design flood of the watershed and also other hydrological elements (runoff, volumes of water...).The hydrographic characteristics and climatic parameters were used to estimate the runoff, water volumes and design flood for different return periods.

Flood risk assessment in France: comparison of extreme flood estimation methods (EXTRAFLO project, Task 7)

NASA Astrophysics Data System (ADS)

Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.

2013-12-01

In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example

Estimating the impact of extreme climatic events on riverine sediment transport: new tools and methods

NASA Astrophysics Data System (ADS)

Lajeunesse, E.; Delacourt, C.; Allemand, P.; Limare, A.; Dessert, C.; Ammann, J.; Grandjean, P.

2010-12-01

A series of recent works have underlined that the flux of material exported outside of a watershed is dramatically increased during extreme climatic events, such as storms, tropical cyclones and hurricanes [Dadson et al., 2003 and 2004; Hilton et al., 2008]. Indeed the exceptionally high rainfall rates reached during these events trigger runoff and landsliding which destabilize slopes and accumulate a significant amount of sediments in flooded rivers. This observation raises the question of the control that extreme climatic events might exert on the denudation rate and the morphology of watersheds. Addressing this questions requires to measure sediment transport in flooded rivers. However most conventional sediment monitoring technics rely on manned operated measurements which cannot be performed during extreme climatic events. Monitoring riverine sediment transport during extreme climatic events remains therefore a challenging issue because of the lack of instruments and methodologies adapted to such extreme conditions. In this paper, we present a new methodology aimed at estimating the impact of extreme events on sediment transport in rivers. Our approach relies on the development of two instruments. The first one is an in-situ optical instrument, based on a LISST-25X sensor, capable of measuring both the water level and the concentration of suspended matter in rivers with a time step going from one measurement every hour at low flow to one measurement every 2 minutes during a flood. The second instrument is a remote controlled drone helicopter used to acquire high resolution stereophotogrammetric images of river beds used to compute DEMs and to estimate how flash floods impact the granulometry and the morphology of the river. These two instruments were developed and tested during a 1.5 years field survey performed from june 2007 to january 2009 on the Capesterre river located on Basse-Terre island (Guadeloupe archipelago, Lesser Antilles Arc).

Maternal Responses and Development of Communication Skills in Extremely Preterm Infants

ERIC Educational Resources Information Center

Benassi, Erika; Guarini, Annalisa; Savini, Silvia; Iverson, Jana Marie; Caselli, Maria Cristina; Alessandroni, Rosina; Faldella, Giacomo; Sansavini, Alessandra

2018-01-01

The present study examined maternal responses to infants' spontaneous communicative behaviors in a sample of 20 extremely-low-gestational-age (ELGA) infants and 20 full-term (FT) infants during 30 minutes of play interaction when infants were 12 months of age. Relations between maternal responses and infants' communication skills at 12 and 24…

The Individual Consistency of Acquiescence and Extreme Response Style in Self-Report Questionnaires

ERIC Educational Resources Information Center

Weijters, Bert; Geuens, Maggie; Schillewaert, Niels

2010-01-01

The severity of bias in respondents' self-reports due to acquiescence response style (ARS) and extreme response style (ERS) depends strongly on how consistent these response styles are over the course of a questionnaire. In the literature, different alternative hypotheses on response style (in)consistency circulate. Therefore, nine alternative…

Community Response and Engagement During Extreme Water Events in Saskatchewan, Canada and Queensland, Australia

NASA Astrophysics Data System (ADS)

McMartin, Dena W.; Sammel, Alison J.; Arbuthnott, Katherine

2018-01-01

Technology alone cannot address the challenges of how societies, communities, and individuals understand water accessibility, water management, and water consumption, particularly under extreme conditions like floods and droughts. At the community level, people are increasingly aware challenges related to responses to and impacts of extreme water events. This research begins with an assessment of social and political capacities of communities in two Commonwealth jurisdictions, Queensland, Australia and Saskatchewan, Canada, in response to major flooding events. The research further reviews how such capacities impact community engagement to address and mitigate risks associated with extreme water events and provides evidence of key gaps in skills, understanding, and agency for addressing impacts at the community level. Secondary data were collected using template analysis to elucidate challenges associated with education (formal and informal), social and political capacity, community ability to respond appropriately, and formal government responses to extreme water events in these two jurisdictions. The results indicate that enhanced community engagement alongside elements of an empowerment model can provide avenues for identifying and addressing community vulnerability to negative impacts of flood and drought.

Observed and simulated hydrologic response for a first-order catchment during extreme rainfall 3 years after wildfire disturbance

USGS Publications Warehouse

Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.

2016-01-01

Hydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., <1 ha) in Colorado, USA that had previously been burned by a wildfire in 2010. We compared measurements of soil-hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire-affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil-hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire-affected headwater catchment by the infiltration-excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil-hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil-hydraulic property parameterizations produced longer duration but lower peak-flow infiltration-excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near-channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.

Extreme Mean and Its Applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.

1979-01-01

Extreme value statistics obtained from normally distributed data are considered. An extreme mean is defined as the mean of p-th probability truncated normal distribution. An unbiased estimate of this extreme mean and its large sample distribution are derived. The distribution of this estimate even for very large samples is found to be nonnormal. Further, as the sample size increases, the variance of the unbiased estimate converges to the Cramer-Rao lower bound. The computer program used to obtain the density and distribution functions of the standardized unbiased estimate, and the confidence intervals of the extreme mean for any data are included for ready application. An example is included to demonstrate the usefulness of extreme mean application.

Maximum likelihood estimation of correction for dilution bias in simple linear regression using replicates from subjects with extreme first measurements.

PubMed

Berglund, Lars; Garmo, Hans; Lindbäck, Johan; Svärdsudd, Kurt; Zethelius, Björn

2008-09-30

The least-squares estimator of the slope in a simple linear regression model is biased towards zero when the predictor is measured with random error. A corrected slope may be estimated by adding data from a reliability study, which comprises a subset of subjects from the main study. The precision of this corrected slope depends on the design of the reliability study and estimator choice. Previous work has assumed that the reliability study constitutes a random sample from the main study. A more efficient design is to use subjects with extreme values on their first measurement. Previously, we published a variance formula for the corrected slope, when the correction factor is the slope in the regression of the second measurement on the first. In this paper we show that both designs improve by maximum likelihood estimation (MLE). The precision gain is explained by the inclusion of data from all subjects for estimation of the predictor's variance and by the use of the second measurement for estimation of the covariance between response and predictor. The gain of MLE enhances with stronger true relationship between response and predictor and with lower precision in the predictor measurements. We present a real data example on the relationship between fasting insulin, a surrogate marker, and true insulin sensitivity measured by a gold-standard euglycaemic insulin clamp, and simulations, where the behavior of profile-likelihood-based confidence intervals is examined. MLE was shown to be a robust estimator for non-normal distributions and efficient for small sample situations. Copyright (c) 2008 John Wiley & Sons, Ltd.

Rainfall extremes from TRMM data and the Metastatistical Extreme Value Distribution

NASA Astrophysics Data System (ADS)

Zorzetto, Enrico; Marani, Marco

2017-04-01

A reliable quantification of the probability of weather extremes occurrence is essential for designing resilient water infrastructures and hazard mitigation measures. However, it is increasingly clear that the presence of inter-annual climatic fluctuations determines a substantial long-term variability in the frequency of occurrence of extreme events. This circumstance questions the foundation of the traditional extreme value theory, hinged on stationary Poisson processes or on asymptotic assumptions to derive the Generalized Extreme Value (GEV) distribution. We illustrate here, with application to daily rainfall, a new approach to extreme value analysis, the Metastatistical Extreme Value Distribution (MEVD). The MEVD relaxes the above assumptions and is based on the whole distribution of daily rainfall events, thus allowing optimal use of all available observations. Using a global dataset of rain gauge observations, we show that the MEVD significantly outperforms the Generalized Extreme Value distribution, particularly for long average recurrence intervals and when small samples are available. The latter property suggests MEVD to be particularly suited for applications to satellite rainfall estimates, which only cover two decades, thus making extreme value estimation extremely challenging. Here we apply MEVD to the TRMM TMPA 3B42 product, an 18-year dataset of remotely-sensed daily rainfall providing a quasi-global coverage. Our analyses yield a global scale mapping of daily rainfall extremes and of their distributional tail properties, bridging the existing large gaps in ground-based networks. Finally, we illustrate how our global-scale analysis can provide insight into how properties of local rainfall regimes affect tail estimation uncertainty when using the GEV or MEVD approach. We find a dependence of the estimation uncertainty, for both the GEV- and MEV-based approaches, on the average annual number and on the inter-annual variability of rainy days. In

Value-at-risk estimation with wavelet-based extreme value theory: Evidence from emerging markets

NASA Astrophysics Data System (ADS)

Cifter, Atilla

2011-06-01

This paper introduces wavelet-based extreme value theory (EVT) for univariate value-at-risk estimation. Wavelets and EVT are combined for volatility forecasting to estimate a hybrid model. In the first stage, wavelets are used as a threshold in generalized Pareto distribution, and in the second stage, EVT is applied with a wavelet-based threshold. This new model is applied to two major emerging stock markets: the Istanbul Stock Exchange (ISE) and the Budapest Stock Exchange (BUX). The relative performance of wavelet-based EVT is benchmarked against the Riskmetrics-EWMA, ARMA-GARCH, generalized Pareto distribution, and conditional generalized Pareto distribution models. The empirical results show that the wavelet-based extreme value theory increases predictive performance of financial forecasting according to number of violations and tail-loss tests. The superior forecasting performance of the wavelet-based EVT model is also consistent with Basel II requirements, and this new model can be used by financial institutions as well.

Extreme Response Style and the Measurement of Intra-Individual Variability

ERIC Educational Resources Information Center

Deng, Sien

2017-01-01

Psychologists have become increasingly interested in the intra-individual variability of psychological measures as a meaningful distinguishing characteristic of persons. Assessments of intra-individual variability are frequently based on the repeated administration of self-report rating scale instruments, and extreme response style (ERS) has the…

Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

NASA Astrophysics Data System (ADS)

Pegram, Geoff; Bardossy, Andras; Sinclair, Scott

2017-04-01

The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this presentation we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the presentation is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to un-sampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the sub-daily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. In addition, a statistical procedure not based on a matching day by day correction is tested. In this last procedure, as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these 12 day maxima is first interpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest 12 radar based days in each year. Of course, the timings of radar and gauge maxima can be different, so the new method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated

Long-Term Geomagnetically Induced Current Observations From New Zealand: Peak Current Estimates for Extreme Geomagnetic Storms

NASA Astrophysics Data System (ADS)

Rodger, Craig J.; Mac Manus, Daniel H.; Dalzell, Michael; Thomson, Alan W. P.; Clarke, Ellen; Petersen, Tanja; Clilverd, Mark A.; Divett, Tim

2017-11-01

Geomagnetically induced current (GIC) observations made in New Zealand over 14 years show induction effects associated with a rapidly varying horizontal magnetic field (dBH/dt) during geomagnetic storms. This study analyzes the GIC observations in order to estimate the impact of extreme storms as a hazard to the power system in New Zealand. Analysis is undertaken of GIC in transformer number six in Islington, Christchurch (ISL M6), which had the highest observed currents during the 6 November 2001 storm. Using previously published values of 3,000 nT/min as a representation of an extreme storm with 100 year return period, induced currents of 455 A were estimated for Islington (with the 95% confidence interval range being 155-605 A). For 200 year return periods using 5,000 nT/min, current estimates reach 755 A (confidence interval range 155-910 A). GIC measurements from the much shorter data set collected at transformer number 4 in Halfway Bush, Dunedin, (HWB T4), found induced currents to be consistently a factor of 3 higher than at Islington, suggesting equivalent extreme storm effects of 460-1,815 A (100 year return) and 460-2,720 A (200 year return). An estimate was undertaken of likely failure levels for single-phase transformers, such as HWB T4 when it failed during the 6 November 2001 geomagnetic storm, identifying that induced currents of 100 A can put such transformer types at risk of damage. Detailed modeling of the New Zealand power system is therefore required to put this regional analysis into a global context.

Estimating return periods of extreme values from relatively short time series of winds

NASA Astrophysics Data System (ADS)

Jonasson, Kristjan; Agustsson, Halfdan; Rognvaldsson, Olafur; Arfeuille, Gilles

2013-04-01

An important factor for determining the prospect of individual wind farm sites is the frequency of extreme winds at hub height. Here, extreme winds are defined as the value of the highest 10 minutes averaged wind speed with a 50 year return period, i.e. annual exceeding probability of 2% (Rodrigo, 2010). A frequently applied method to estimate winds in the lowest few hundred meters above ground is to extrapolate observed 10-meter winds logarithmically to higher altitudes. Recent study by Drechsel et al. (2012) showed however that this methodology is not as accurate as interpolating simulated results from the global ECMWF numerical weather prediction (NWP) model to the desired height. Observations of persistent low level jets near Colima in SW-Mexico also show that the logarithmic approach can give highly inaccurate results for some regions (Arfeuille et al., 2012). To address these shortcomings of limited, and/or poorly representative, observations and extrapolations of winds one can use NWP models to dynamically scale down relatively coarse resolution atmospheric analysis. In the case of limited computing resources one has typically to make a compromise between spatial resolution and the duration of the simulated period, both of which can limit the quality of the wind farm siting. A common method to estimate maximum winds is to fit an extreme value distribution (e.g. Gumbel, gev or Pareto) to the maximum values of each year of available data, or the tail of these values. If data are only available for a short period, e.g. 10 or 15 years, then this will give a rather inaccurate estimate. It is possible to deal with this problem by utilizing monthly or weekly maxima, but this introduces new problems: seasonal variation, autocorrelation of neighboring values, and increased discrepancy between data and fitted distribution. We introduce a new method to estimate return periods of extreme values of winds at hub height from relatively short time series of winds, simulated

The dichotomous response of flood and storm extremes to rising global temperatures

NASA Astrophysics Data System (ADS)

Sharma, A.; Wasko, C.

2017-12-01

Rising temperature have resulted in increases in short-duration rainfall extremes across the world. Additionally it has been shown (doi:10.1038/ngeo2456) that storms will intensify, causing derived flood peaks to rise even more. This leads us to speculate that flood peaks will increase as a result, complying with the storyline presented in past IPCC reports. This talk, however, shows that changes in flood extremes are much more complex. Using global data on extreme flow events, the study conclusively shows that while the very extreme floods may be rising as a result of storm intensification, the more frequent flood events are decreasing in magnitude. The study argues that changes in the magnitude of floods are a function of changes in storm patterns and as well as pre-storm or antecedent conditions. It goes on to show that while changes in storms dominate for the most extreme events and over smaller, more urbanised catchments, changes in pre-storm conditions are the driving factor in modulating flood peaks in large rural catchments. The study concludes by providing recommendations on how future flood design should proceed, arguing that current practices (or using a design storm to estimate floods) are flawed and need changing.

Estimation of resist sensitivity for extreme ultraviolet lithography using an electron beam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oyama, Tomoko Gowa, E-mail: ohyama.tomoko@qst.go.jp; Oshima, Akihiro; Tagawa, Seiichi, E-mail: tagawa@sanken.osaka-u.ac.jp

2016-08-15

It is a challenge to obtain sufficient extreme ultraviolet (EUV) exposure time for fundamental research on developing a new class of high sensitivity resists for extreme ultraviolet lithography (EUVL) because there are few EUV exposure tools that are very expensive. In this paper, we introduce an easy method for predicting EUV resist sensitivity by using conventional electron beam (EB) sources. If the chemical reactions induced by two ionizing sources (EB and EUV) are the same, the required absorbed energies corresponding to each required exposure dose (sensitivity) for the EB and EUV would be almost equivalent. Based on this theory, wemore » calculated the resist sensitivities for the EUV/soft X-ray region. The estimated sensitivities were found to be comparable to the experimentally obtained sensitivities. It was concluded that EB is a very useful exposure tool that accelerates the development of new resists and sensitivity enhancement processes for 13.5 nm EUVL and 6.x nm beyond-EUVL (BEUVL).« less

Estimating Single-Trial Responses in EEG

NASA Technical Reports Server (NTRS)

Shah, A. S.; Knuth, K. H.; Truccolo, W. A.; Mehta, A. D.; Fu, K. G.; Johnston, T. A.; Ding, M.; Bressler, S. L.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

A non-stationary cost-benefit analysis approach for extreme flood estimation to explore the nexus of 'Risk, Cost and Non-stationarity'

NASA Astrophysics Data System (ADS)

Qi, Wei

2017-11-01

Cost-benefit analysis is commonly used for engineering planning and design problems in practice. However, previous cost-benefit based design flood estimation is based on stationary assumption. This study develops a non-stationary cost-benefit based design flood estimation approach. This approach integrates a non-stationary probability distribution function into cost-benefit analysis, and influence of non-stationarity on expected total cost (including flood damage and construction costs) and design flood estimation can be quantified. To facilitate design flood selections, a 'Risk-Cost' analysis approach is developed, which reveals the nexus of extreme flood risk, expected total cost and design life periods. Two basins, with 54-year and 104-year flood data respectively, are utilized to illustrate the application. It is found that the developed approach can effectively reveal changes of expected total cost and extreme floods in different design life periods. In addition, trade-offs are found between extreme flood risk and expected total cost, which reflect increases in cost to mitigate risk. Comparing with stationary approaches which generate only one expected total cost curve and therefore only one design flood estimation, the proposed new approach generate design flood estimation intervals and the 'Risk-Cost' approach selects a design flood value from the intervals based on the trade-offs between extreme flood risk and expected total cost. This study provides a new approach towards a better understanding of the influence of non-stationarity on expected total cost and design floods, and could be beneficial to cost-benefit based non-stationary design flood estimation across the world.

Extreme flood estimation by the SCHADEX method in a snow-driven catchment: application to Atnasjø (Norway)

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel; Lawrence, Deborah

2013-04-01

The SCHADEX method for extreme flood estimation was developed by Paquet et al. (2006, 2013), and since 2008, it is the reference method used by Electricité de France (EDF) for dam spillway design. SCHADEX is a so-called "semi-continuous" stochastic simulation method in that flood events are simulated on an event basis and are superimposed on a continuous simulation of the catchment saturation hazard usingrainfall-runoff modelling. The MORDOR hydrological model (Garçon, 1999) has thus far been used for the rainfall-runoff modelling. MORDOR is a conceptual, lumped, reservoir model with daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt, and routing. The model has been intensively used at EDF for more than 15 years, in particular for inflow forecasts for French mountainous catchments. SCHADEX has now also been applied to the Atnasjø catchment (463 km²), a well-documented inland catchment in south-central Norway, dominated by snowmelt flooding during spring/early summer. To support this application, a weather pattern classification based on extreme rainfall was first established for Norway (Fleig, 2012). This classification scheme was then used to build a Multi-Exponential Weather Pattern distribution (MEWP), as introduced by Garavaglia et al. (2010) for extreme rainfall estimation. The MORDOR model was then calibrated relative to daily discharge data for Atnasjø. Finally, a SCHADEX simulation was run to build a daily discharge distribution with a sufficient number of simulations for assessing the extreme quantiles. Detailed results are used to illustrate how SCHADEX handles the complex and interacting hydrological processes driving flood generation in this snow driven catchment. Seasonal and monthly distributions, as well as statistics for several thousand simulated events reaching a 1000 years return level

Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures

EPA Pesticide Factsheets

This is a presentation titled Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures that was given for the National Center for Environmental Economics

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

Response Strength in Extreme Multiple Schedules

PubMed Central

McLean, Anthony P; Grace, Randolph C; Nevin, John A

2012-01-01

Four pigeons were trained in a series of two-component multiple schedules. Reinforcers were scheduled with random-interval schedules. The ratio of arranged reinforcer rates in the two components was varied over 4 log units, a much wider range than previously studied. When performance appeared stable, prefeeding tests were conducted to assess resistance to change. Contrary to the generalized matching law, logarithms of response ratios in the two components were not a linear function of log reinforcer ratios, implying a failure of parameter invariance. Over a 2 log unit range, the function appeared linear and indicated undermatching, but in conditions with more extreme reinforcer ratios, approximate matching was observed. A model suggested by McLean (1991), originally for local contrast, predicts these changes in sensitivity to reinforcer ratios somewhat better than models by Herrnstein (1970) and by Williams and Wixted (1986). Prefeeding tests of resistance to change were conducted at each reinforcer ratio, and relative resistance to change was also a nonlinear function of log reinforcer ratios, again contrary to conclusions from previous work. Instead, the function suggests that resistance to change in a component may be determined partly by the rate of reinforcement and partly by the ratio of reinforcers to responses. PMID:22287804

Spatial dependence of extreme rainfall

NASA Astrophysics Data System (ADS)

Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

2017-05-01

This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

NASA Astrophysics Data System (ADS)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2018-03-01

Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

An extreme ultraviolet telescope with no soft X-ray response

NASA Technical Reports Server (NTRS)

Finley, David S.; Jelinsky, Patrick; Bowyer, Stuart; Malina, Roger F.

1986-01-01

While EUV grazing incidence telescopes of conventional design exhibit a substantial X-ray response as well as an extreme UV response, and existing bandpass filters for the transmission of radiation longward of 400 A also transmit soft X-rays, the grazing incidence telescope presented suppresses this soft X-ray throughput through the incorporation of a Wolter Schwarzschild Type II mirror with large graze angles. The desirable features of an EUV photometric survey telescope are retained. An instrument of this design will be flown on the EUE mission, in order to make a survey of the sky at wavelengths longer than 400 A.

Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jiali; Han, Yuefeng; Stein, Michael L.

2016-02-10

The Weather Research and Forecast (WRF) model downscaling skill in extreme maximum daily temperature is evaluated by using the generalized extreme value (GEV) distribution. While the GEV distribution has been used extensively in climatology and meteorology for estimating probabilities of extreme events, accurately estimating GEV parameters based on data from a single pixel can be difficult, even with fairly long data records. This work proposes a simple method assuming that the shape parameter, the most difficult of the three parameters to estimate, does not vary over a relatively large region. This approach is applied to evaluate 31-year WRF-downscaled extreme maximummore » temperature through comparison with North American Regional Reanalysis (NARR) data. Uncertainty in GEV parameter estimates and the statistical significance in the differences of estimates between WRF and NARR are accounted for by conducting bootstrap resampling. Despite certain biases over parts of the United States, overall, WRF shows good agreement with NARR in the spatial pattern and magnitudes of GEV parameter estimates. Both WRF and NARR show a significant increase in extreme maximum temperature over the southern Great Plains and southeastern United States in January and over the western United States in July. The GEV model shows clear benefits from the regionally constant shape parameter assumption, for example, leading to estimates of the location and scale parameters of the model that show coherent spatial patterns.« less

General circulation model response to production-limited fossil fuel emission estimates.

NASA Astrophysics Data System (ADS)

Bowman, K. W.; Rutledge, D.; Miller, C.

2008-12-01

The differences in emissions scenarios used to drive IPCC climate projections are the largest sources of uncertainty in future temperature predictions. These estimates are critically dependent on oil, gas, and coal production where the extremal variations in fossil fuel production used in these scenarios is roughly 10:1 after 2100. The development of emission scenarios based on production-limited fossil fuel estimates, i.e., total fossil fuel reserves can be reliably predicted from cumulative production, offers the opportunity to significantly reduce this uncertainty. We present preliminary results of the response of the NASA GISS atmospheric general circulation model to input forcings constrained by production-limited cumulative future fossil-fuel CO2 emissions estimates that reach roughly 500 GtC by 2100, which is significantly lower than any of the IPCC emission scenarios. For climate projections performed from 1958 through 2400 and a climate sensitivity of 5C/2xCO2, the change in globally averaged annual mean temperature relative to fixed CO2 does not exceed 3C with most changes occurring at high latitudes. We find that from 2100-2400 other input forcings such as increased in N2O play an important role in maintaining increase surface temperatures.

A random sampling approach for robust estimation of tissue-to-plasma ratio from extremely sparse data.

PubMed

Chu, Hui-May; Ette, Ene I

2005-09-02

his study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naïve data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.

Extremity movements help occupational therapists identify stress responses in preterm infants in the neonatal intensive care unit: a systematic review.

PubMed

Holsti, Liisa; Grunau, Ruth E

2007-06-01

Accurate assessment and treatment of pain and stress in preterm infants in neonatal intensive care units (NICU) is vital because pain and stress responses have been linked to long-term alterations in development in this population. To review the evidence of specific extremity movements in preterm infants as observed during stressful procedures. Five on-line databases were searched for relevant studies. For each study, levels of evidence were determined and effect size estimates were calculated. Each study was also evaluated for specific factors that presented potential threats to its validity. Eighteen studies were identified and seven comprised the review. The combined sample included 359 preterm infants. Six specific movements were associated with painful and intrusive procedures. A set of specific extremity movements, when combined with other reliable biobehavioural measures of pain and stress, can form the basis for future research and development of a clinical stress scale for preterm infants.

Detection of photosynthetic responses of cool-temperate forests following extreme climate events using Bayesian inversion

NASA Astrophysics Data System (ADS)

Toda, M.; Knohl, A.; Herbst, M.; Keenan, T. F.; Yokozawa, M.

2016-12-01

The increase in extreme climate events associated with ongoing global warming may create severe damage to terrestrial ecosystems, changing plant structure and the eco-physiological functions that regulate ecosystem carbon exchange. However, most damage is usually due to moderate, rather than catastrophic, disturbances. The nature of plant functional responses to such disturbances, and the resulting effects on the terrestrial carbon cycle, remain poorly understood. To unravel the scientific question, tower-based eddy covariance data in the cool-temperate forests were used to constrain plant eco-physiological parameters in a persimoneous ecosystem model that may have affected carbon dynamics following extreme climate events using the statistic Bayesian inversion approach. In the present study, we raised two types of extreme events relevant for cool-temperate regions, i.e. a typhoon with mechanistic foliage destraction and a heat wave with severe drought. With appropriate evaluation of parameter and predictive uncertainties, the inversion analysis shows annual trajectory of activated photosynthetic responses following climate extremes compared the pre-disturbance state in each forest. We address that forests with moderate disturbance show substantial and rapid photosynthetic recovery, enhanced productivity, and, thus, ecosystem carbon exchange, although the effect of extreme climatic events varies depending on the stand successional phase and the type, intensity, timing and legacy of the disturbance.

Use of heat to estimate streambed fluxes during extreme hydrologic events

USGS Publications Warehouse

Barlow, Jeannie R.B.; Coupe, Richard H.

2009-01-01

Using heat as a tracer, quantitative estimates of streambed fluxes and the critical stage for flow reversal were calculated for high‐flow events that occurred on the Bogue Phalia (a tributary of the Mississippi River) following the 2005 Hurricanes Katrina and Rita. In June 2005, piezometers were installed in the Bogue Phalia upstream from the stream gage near Leland, Mississippi, to monitor temperature. Even with the hurricanes, precipitation in the Bogue Phalia Basin for the months of June to October 2005 was below normal, and consequently, streamflow was below the long‐term average. Temperature profiles from the piezometers indicate that the Bogue Phalia was a gaining stream during most of this time, but relatively static streambed temperatures suggested long‐term data was warranted for heat‐based estimates of flux. However, the hurricanes caused a pair of sharp rises in stream stage over short periods of time, increasing the potential for rapid heat‐based modeling and for identification of the critical stage for flow reversal into the streambed. Heat‐based modeling fits of simulated‐to‐measured sediment temperatures show that once a critical stage was surpassed, flow direction reversed into the streambed. Results of this study demonstrate the ability to constrain estimates of streambed water flux and the critical stage of flow reversal, with little available groundwater head data, by using heat as a tracer during extreme stage events.

Sexual dimorphism in epigenomic responses of stem cells to extreme fetal growth.

PubMed

Delahaye, Fabien; Wijetunga, N Ari; Heo, Hye J; Tozour, Jessica N; Zhao, Yong Mei; Greally, John M; Einstein, Francine H

2014-10-10

Extreme fetal growth is associated with increased susceptibility to a range of adult diseases through an unknown mechanism of cellular memory. We tested whether heritable epigenetic processes in long-lived CD34(+) haematopoietic stem/progenitor cells showed evidence for re-programming associated with the extremes of fetal growth. Here we show that both fetal growth restriction and over-growth are associated with global shifts towards DNA hypermethylation, targeting cis-regulatory elements in proximity to genes involved in glucose homeostasis and stem cell function. We find a sexually dimorphic response; intrauterine growth restriction is associated with substantially greater epigenetic dysregulation in males, whereas large for gestational age growth predominantly affects females. The findings are consistent with extreme fetal growth interacting with variable fetal susceptibility to influence cellular ageing and metabolic characteristics through epigenetic mechanisms, potentially generating biomarkers that could identify infants at higher risk for chronic disease later in life.

Estimating neural response functions from fMRI

PubMed Central

Kumar, Sukhbinder; Penny, William

2014-01-01

This paper proposes a methodology for estimating Neural Response Functions (NRFs) from fMRI data. These NRFs describe non-linear relationships between experimental stimuli and neuronal population responses. The method is based on a two-stage model comprising an NRF and a Hemodynamic Response Function (HRF) that are simultaneously fitted to fMRI data using a Bayesian optimization algorithm. This algorithm also produces a model evidence score, providing a formal model comparison method for evaluating alternative NRFs. The HRF is characterized using previously established “Balloon” and BOLD signal models. We illustrate the method with two example applications based on fMRI studies of the auditory system. In the first, we estimate the time constants of repetition suppression and facilitation, and in the second we estimate the parameters of population receptive fields in a tonotopic mapping study. PMID:24847246

Antarctic climate change: extreme events disrupt plastic phenotypic response in Adélie penguins.

PubMed

Lescroël, Amélie; Ballard, Grant; Grémillet, David; Authier, Matthieu; Ainley, David G

2014-01-01

In the context of predicted alteration of sea ice cover and increased frequency of extreme events, it is especially timely to investigate plasticity within Antarctic species responding to a key environmental aspect of their ecology: sea ice variability. Using 13 years of longitudinal data, we investigated the effect of sea ice concentration (SIC) on the foraging efficiency of Adélie penguins (Pygoscelis adeliae) breeding in the Ross Sea. A 'natural experiment' brought by the exceptional presence of giant icebergs during 5 consecutive years provided unprecedented habitat variation for testing the effects of extreme events on the relationship between SIC and foraging efficiency in this sea-ice dependent species. Significant levels of phenotypic plasticity were evident in response to changes in SIC in normal environmental conditions. Maximum foraging efficiency occurred at relatively low SIC, peaking at 6.1% and decreasing with higher SIC. The 'natural experiment' uncoupled efficiency levels from SIC variations. Our study suggests that lower summer SIC than currently observed would benefit the foraging performance of Adélie penguins in their southernmost breeding area. Importantly, it also provides evidence that extreme climatic events can disrupt response plasticity in a wild seabird population. This questions the predictive power of relationships built on past observations, when not only the average climatic conditions are changing but the frequency of extreme climatic anomalies is also on the rise.

Antarctic Climate Change: Extreme Events Disrupt Plastic Phenotypic Response in Adélie Penguins

PubMed Central

Lescroël, Amélie; Ballard, Grant; Grémillet, David; Authier, Matthieu; Ainley, David G.

2014-01-01

In the context of predicted alteration of sea ice cover and increased frequency of extreme events, it is especially timely to investigate plasticity within Antarctic species responding to a key environmental aspect of their ecology: sea ice variability. Using 13 years of longitudinal data, we investigated the effect of sea ice concentration (SIC) on the foraging efficiency of Adélie penguins (Pygoscelis adeliae) breeding in the Ross Sea. A ‘natural experiment’ brought by the exceptional presence of giant icebergs during 5 consecutive years provided unprecedented habitat variation for testing the effects of extreme events on the relationship between SIC and foraging efficiency in this sea-ice dependent species. Significant levels of phenotypic plasticity were evident in response to changes in SIC in normal environmental conditions. Maximum foraging efficiency occurred at relatively low SIC, peaking at 6.1% and decreasing with higher SIC. The ‘natural experiment’ uncoupled efficiency levels from SIC variations. Our study suggests that lower summer SIC than currently observed would benefit the foraging performance of Adélie penguins in their southernmost breeding area. Importantly, it also provides evidence that extreme climatic events can disrupt response plasticity in a wild seabird population. This questions the predictive power of relationships built on past observations, when not only the average climatic conditions are changing but the frequency of extreme climatic anomalies is also on the rise. PMID:24489657

Nonlocal response in plasmonic waveguiding with extreme light confinement

NASA Astrophysics Data System (ADS)

Toscano, Giuseppe; Raza, Søren; Yan, Wei; Jeppesen, Claus; Xiao, Sanshui; Wubs, Martijn; Jauho, Antti-Pekka; Bozhevolnyi, Sergey I.; Mortensen, N. Asger

2013-07-01

We present a novel wave equation for linearized plasmonic response, obtained by combining the coupled real-space differential equations for the electric field and current density. Nonlocal dynamics are fully accounted for, and the formulation is very well suited for numerical implementation, allowing us to study waveguides with subnanometer cross-sections exhibiting extreme light confinement. We show that groove and wedge waveguides have a fundamental lower limit in their mode confinement, only captured by the nonlocal theory. The limitation translates into an upper limit for the corresponding Purcell factors, and thus has important implications for quantum plasmonics.

Representing Extremes in Agricultural Models

NASA Technical Reports Server (NTRS)

Ruane, Alex

2015-01-01

AgMIP and related projects are conducting several activities to understand and improve crop model response to extreme events. This involves crop model studies as well as the generation of climate datasets and scenarios more capable of capturing extremes. Models are typically less responsive to extreme events than we observe, and miss several forms of extreme events. Models also can capture interactive effects between climate change and climate extremes. Additional work is needed to understand response of markets and economic systems to food shocks. AgMIP is planning a Coordinated Global and Regional Assessment of Climate Change Impacts on Agricultural Production and Food Security with an aim to inform the IPCC Sixth Assessment Report.

Effects of Arm Ergometry Exercise on the Reaction, Movement and Response Times of the Lower Extremities.

ERIC Educational Resources Information Center

Israel, Richard G.

A study determined the effects of fatigue produced in the upper extremities on the reaction time, movement time, and response time of the lower extremities in 30 male subjects, 19-25 years old. Each subject participated in a 10 trial practice session one day prior to the experiment and immediately preceding the pre-test. The pre-test consisted of…

Using Annual Data to Estimate the Public Health Impact of Extreme Temperatures.

PubMed

Goggins, William B; Yang, Chunyuh; Hokama, Tomiko; Law, Lewis S K; Chan, Emily Y Y

2015-07-01

Short-term associations between both hot and cold ambient temperatures and higher mortality have been found worldwide. Few studies have examined these associations on longer time scales. Age-standardized mortality rates (ASMRs) were calculated for 1976-2012 for Hong Kong SAR, People's Republic of China, defining "annual" time periods in 2 ways: from May through April of the following year and from November through October. Annual frequency and severity of extreme temperatures were summarized by using a degree-days approach with extreme heat expressed as annual degree-days >29.3°C and cold as annual degree-days <27.5°C. For example, a day with a mean temperature of 25.0°C contributes 2.5 cold degree-days to the annual total. Generalized additive models were used to estimate the association between annual hot and cold degree-days and the ASMR, with adjustment for long-term trends. Increases of 10 hot or 200 cold degree-days in an annual period, the approximate interquartile ranges for these variables, were significantly (all P's ≤ 0.011) associated with 1.9% or 3.1% increases, respectively, in the annual ASMR for the May-April analyses and with 2.2% or 2.8% increases, respectively, in the November-October analyses. Associations were stronger for noncancer and elderly mortality. Mortality increases associated with extreme temperature are not simply due to short-term forward displacement of deaths that would have occurred anyway within a few weeks. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Ergonomic stressors and upper extremity disorders in vehicle manufacturing: cross sectional exposure-response trends

PubMed Central

Punnett, L.

1998-01-01

OBJECTIVE: To evaluate the association between upper extremity soft tissue disorders and exposure to preventable ergonomic stressors in vehicle manufacturing operations. METHODS: A cross sectional study was conducted in one vehicle stamping plant and one engine assembly plant. A standardised physical examination of the upper extremities was performed on all subjects. An interviewer administered questionnaire obtained data on demographics, work history, musculoskeletal symptoms, non-occupational covariates, and psycho-physical (relative intensity) ratings of ergonomic stressors. The primary exposure score was computed by summing the responses to the psychophysical exposure items. Multivariate regression analysis was used to model the prevalence of disorders of the shoulders or upper arms, wrists or hands, and all upper extremity regions (each defined both by symptoms and by physical examination plus symptoms) as a function of exposure quartile. RESULTS: A total of 1315 workers (85% of the target population) was examined. The prevalence of symptom disorders was 22% for the wrists or hands and 15% for the shoulders or upper arms; cases defined on the basis of a physical examination were about 80% as frequent. Disorders of the upper extremities, shoulders, and wrists or hands all increased markedly with exposure score, after adjustment for plant, acute injury, sex, body mass index, systemic disease, and seniority. CONCLUSIONS: Musculoskeletal disorders of the upper extremities were strongly associated with exposure to combined ergonomic stressors. The exposure- response trend was very similar for symptom cases and for physical examination cases. It is important to evaluate all dimensions of ergonomic exposure in epidemiological studies, as exposures often occur in combination in actual workplaces.   PMID:9764102

Contributions of Dynamic and Thermodynamic Scaling in Subdaily Precipitation Extremes in India

NASA Astrophysics Data System (ADS)

Ali, Haider; Mishra, Vimal

2018-03-01

Despite the importance of subdaily precipitation extremes for urban areas, the role of dynamic and thermodynamic scaling in changes in precipitation extremes in India remains poorly constrained. Here we estimate contributions from thermodynamic and dynamic scaling on changes in subdaily precipitation extremes for 23 urban locations in India. Subdaily precipitation extremes have become more intense during the last few decades. Moreover, we find a twofold rise in the frequency of subdaily precipitation extremes during 1979-2015, which is faster than the increase in daily precipitation extremes. The contribution of dynamic scaling in this rise in the frequency and intensity of subdaily precipitation extremes is higher than the thermodynamic scaling. Moreover, half-hourly precipitation extremes show higher contributions from the both thermodynamic ( 10%/K) and dynamic ( 15%/K) scaling than daily (6%/K and 9%/K, respectively) extremes indicating the role of warming on the rise in the subdaily precipitation extremes in India. Our findings have implications for better understanding the dynamic response of precipitation extremes under the warming climate over India.

Responses of tree species to heat waves and extreme heat events.

PubMed

Teskey, Robert; Wertin, Timothy; Bauweraerts, Ingvar; Ameye, Maarten; McGuire, Mary Anne; Steppe, Kathy

2015-09-01

The number and intensity of heat waves has increased, and this trend is likely to continue throughout the 21st century. Often, heat waves are accompanied by drought conditions. It is projected that the global land area experiencing heat waves will double by 2020, and quadruple by 2040. Extreme heat events can impact a wide variety of tree functions. At the leaf level, photosynthesis is reduced, photooxidative stress increases, leaves abscise and the growth rate of remaining leaves decreases. In some species, stomatal conductance increases at high temperatures, which may be a mechanism for leaf cooling. At the whole plant level, heat stress can decrease growth and shift biomass allocation. When drought stress accompanies heat waves, the negative effects of heat stress are exacerbated and can lead to tree mortality. However, some species exhibit remarkable tolerance to thermal stress. Responses include changes that minimize stress on photosynthesis and reductions in dark respiration. Although there have been few studies to date, there is evidence of within-species genetic variation in thermal tolerance, which could be important to exploit in production forestry systems. Understanding the mechanisms of differing tree responses to extreme temperature events may be critically important for understanding how tree species will be affected by climate change. © 2014 John Wiley & Sons Ltd.

Forest tree responses to extreme drought and some biotic events: Towards a selection according to hazard tolerance?

NASA Astrophysics Data System (ADS)

Bréda, Nathalie; Badeau, Vincent

2008-09-01

The aim of this paper is to illustrate how some extreme events could affect forest ecosystems. Forest tree response can be analysed using dendroecological methods, as tree-ring widths are strongly controlled by climatic or biotic events. Years with such events induce similar tree responses and are called pointer years. They can result from extreme climatic events like frost, a heat wave, spring water logging, drought or insect damage… Forest tree species showed contrasting responses to climatic hazards, depending on their sensitivity to water shortage or temperature hardening, as illustrated from our dendrochronological database. For foresters, a drought or a pest disease is an extreme event if visible and durable symptoms are induced (leaf discolouration, leaf loss, perennial organs mortality, tree dieback and mortality). These symptoms here are shown, lagging one or several years behind a climatic or biotic event, from forest decline cases in progress since the 2003 drought or attributed to previous severe droughts or defoliations in France. Tree growth or vitality recovery is illustrated, and the functional interpretation of the long lasting memory of trees is discussed. A coupled approach linking dendrochronology and ecophysiology helps in discussing vulnerability of forest stands, and suggests management advices in order to mitigate extreme drought and cope with selective mortality.

Endothelial cells of extremely premature infants display impaired immune response after proinflammatory stimulation.

PubMed

Wisgrill, Lukas; Muck, Martina; Wessely, Isabelle; Berger, Angelika; Spittler, Andreas; Förster-Waldl, Elisabeth; Sadeghi, Kambis

2018-01-01

BackgroundEndothelial cells (ECs) exert immunological functions such as production of proinflammatory cytokines/chemokines as well as facilitation of extravasation of immune cells into infected tissue. Limited data are available on the functionality of ECs from extremely preterm neonates during infection. Accordingly, the aim of our study was to investigate the immune response of premature ECs after proinflammatory stimulation.MethodsCell adhesion receptors' expression and function, nuclear factor 'kappa-light-chain-enhancer' of activated B-cells (NFκB) signaling, and chemokine production were analyzed in umbilical cord ECs from extremely preterm and term neonates after proinflammatory stimulation.ResultsP-selectin and E-selectin surface expression as well as NFκB signaling were lower after lipopolysaccharide (LPS) stimulation in premature ECs. Preterm ECs exhibited lower, but significant, cell-adhesive functions after LPS stimulation compared with term ECs. CCL2/CXCL8 chemokine secretion was significantly upregulated after proinflammatory stimulation in both groups. CXCL10 production was significantly increased in term but not in preterm ECs upon stimulation with tumor necrosis factor compared with unstimulated ECs.ConclusionExtremely premature ECs showed partly reduced expression levels and function of cell adhesion molecules. Both NFκB signaling and chemokine/cytokine production were reduced in premature ECs. The diminished endothelial proinflammatory immune response might result in impaired infection control of preterm newborns rendering them prone to severe infection.

No phenotypic plasticity in nest-site selection in response to extreme flooding events.

PubMed

Bailey, Liam D; Ens, Bruno J; Both, Christiaan; Heg, Dik; Oosterbeek, Kees; van de Pol, Martijn

2017-06-19

Phenotypic plasticity is a crucial mechanism for responding to changes in climatic means, yet we know little about its role in responding to extreme climatic events (ECEs). ECEs may lack the reliable cues necessary for phenotypic plasticity to evolve; however, this has not been empirically tested. We investigated whether behavioural plasticity in nest-site selection allows a long-lived shorebird ( Haematopus ostralegus ) to respond to flooding. We collected longitudinal nest elevation data on individuals over two decades, during which time flooding events have become increasingly frequent. We found no evidence that individuals learn from flooding experiences, showing nest elevation change consistent with random nest-site selection. There was also no evidence of phenotypic plasticity in response to potential environmental cues (lunar nodal cycle and water height). A small number of individuals, those nesting near an artificial sea wall, did show an increase in nest elevation over time; however, there is no conclusive evidence this occurred in response to ECEs. Our study population showed no behavioural plasticity in response to changing ECE patterns. More research is needed to determine whether this pattern is consistent across species and types of ECEs. If so, ECEs may pose a major challenge to the resilience of wild populations.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Decoupling of microbial carbon, nitrogen, and phosphorus cycling in response to extreme temperature events

PubMed Central

Mooshammer, Maria; Hofhansl, Florian; Frank, Alexander H.; Wanek, Wolfgang; Hämmerle, Ieda; Leitner, Sonja; Schnecker, Jörg; Wild, Birgit; Watzka, Margarete; Keiblinger, Katharina M.; Zechmeister-Boltenstern, Sophie; Richter, Andreas

2017-01-01

Predicted changes in the intensity and frequency of climate extremes urge a better mechanistic understanding of the stress response of microbially mediated carbon (C) and nutrient cycling processes. We analyzed the resistance and resilience of microbial C, nitrogen (N), and phosphorus (P) cycling processes and microbial community composition in decomposing plant litter to transient, but severe, temperature disturbances, namely, freeze-thaw and heat. Disturbances led temporarily to a more rapid cycling of C and N but caused a down-regulation of P cycling. In contrast to the fast recovery of the initially stimulated C and N processes, we found a slow recovery of P mineralization rates, which was not accompanied by significant changes in community composition. The functional and structural responses to the two distinct temperature disturbances were markedly similar, suggesting that direct negative physical effects and costs associated with the stress response were comparable. Moreover, the stress response of extracellular enzyme activities, but not that of intracellular microbial processes (for example, respiration or N mineralization), was dependent on the nutrient content of the resource through its effect on microbial physiology and community composition. Our laboratory study provides novel insights into the mechanisms of microbial functional stress responses that can serve as a basis for field studies and, in particular, illustrates the need for a closer integration of microbial C-N-P interactions into climate extremes research. PMID:28508070

Use of historical information in extreme surge frequency estimation: case of the marine flooding on the La Rochelle site in France

NASA Astrophysics Data System (ADS)

Hamdi, Y.; Bardet, L.; Duluc, C.-M.; Rebour, V.

2014-09-01

Nuclear power plants located in the French Atlantic coast are designed to be protected against extreme environmental conditions. The French authorities remain cautious by adopting a strict policy of nuclear plants flood prevention. Although coastal nuclear facilities in France are designed to very low probabilities of failure (e.g. 1000 year surge), exceptional surges (outliers induced by exceptional climatic events) had shown that the extreme sea levels estimated with the current statistical approaches could be underestimated. The estimation of extreme surges then requires the use of a statistical analysis approach having a more solid theoretical motivation. This paper deals with extreme surge frequency estimation using historical information (HI) about events occurred before the systematic record period. It also contributes to addressing the problem of the presence of outliers in data sets. The frequency models presented in the present paper have been quite successful in the field of hydrometeorology and river flooding but they have not been applied to sea levels data sets to prevent marine flooding. In this work, we suggest two methods of incorporating the HI: the Peaks-Over-Threshold method with HI (POTH) and the Block Maxima method with HI (BMH). Two kinds of historical data can be used in the POTH method: classical Historical Maxima (HMax) data, and Over a Threshold Supplementary (OTS) data. In both cases, the data are structured in historical periods and can be used only as complement to the main systematic data. On the other hand, in the BMH method, the basic hypothesis in statistical modeling of HI is that at least one threshold of perception exists for the whole period (historical and systematic) and that during a giving historical period preceding the period of tide gauging, only information about surges above this threshold have been recorded or archived. The two frequency models were applied to a case study from France, at the La Rochelle site where

Use of historical information in extreme-surge frequency estimation: the case of marine flooding on the La Rochelle site in France

NASA Astrophysics Data System (ADS)

Hamdi, Y.; Bardet, L.; Duluc, C.-M.; Rebour, V.

2015-07-01

Nuclear power plants located in the French Atlantic coast are designed to be protected against extreme environmental conditions. The French authorities remain cautious by adopting a strict policy of nuclear-plants flood prevention. Although coastal nuclear facilities in France are designed to very low probabilities of failure (e.g., 1000-year surge), exceptional surges (outliers induced by exceptional climatic events) have shown that the extreme sea levels estimated with the current statistical approaches could be underestimated. The estimation of extreme surges then requires the use of a statistical analysis approach having a more solid theoretical motivation. This paper deals with extreme-surge frequency estimation using historical information (HI) about events occurred before the systematic record period. It also contributes to addressing the problem of the presence of outliers in data sets. The frequency models presented in the present paper have been quite successful in the field of hydrometeorology and river flooding but they have not been applied to sea level data sets to prevent marine flooding. In this work, we suggest two methods of incorporating the HI: the peaks-over-threshold method with HI (POTH) and the block maxima method with HI (BMH). Two kinds of historical data can be used in the POTH method: classical historical maxima (HMax) data, and over-a-threshold supplementary (OTS) data. In both cases, the data are structured in historical periods and can be used only as complement to the main systematic data. On the other hand, in the BMH method, the basic hypothesis in statistical modeling of HI is that at least one threshold of perception exists for the whole period (historical and systematic) and that during a giving historical period preceding the period of tide gauging, only information about surges above this threshold have been recorded or archived. The two frequency models were applied to a case study from France, at the La Rochelle site where

Estimating glacier response times and disequilibrium in a changing climate

NASA Astrophysics Data System (ADS)

Christian, J. E.; Koutnik, M.; Roe, G.

2017-12-01

Glaciers respond to climate variations according to a characteristic timescale that, for most mountain glaciers, is on the order of 10—100 years. An important consequence of this multi-decadal memory is that a glacier's transient response to a climate trend exhibits a persistent lag behind the equilibrium response. In the context of anthropogenic warming, this means that most glaciers are currently well out of equilibrium, and that a substantial amount of retreat is committed even without further warming. The degree of disequilibrium depends fundamentally on the glacier response timescale, making it an important parameter to constrain. A common and robust metric for the response timescale is τ=H/bt, where H and bt are characteristic values for ice thickness and the terminus mass-balance rate, respectively. However, sparse observations, climate variability, and glacier disequilibrium make it difficult to define these characteristic values. We compare several sources of uncertainty that will affect estimates of the response timescale and thus the degree of disequilibrium. Ice thickness is poorly constrained for many glaciers, which bears directly on estimates of the response timescale. However, errors may also arise from estimating thickness and mass-balance rates in a variable climate. We assess how noisy mass balance and observed terminus fluctuations introduce sampling errors into estimates of the glacier's response timescale and the expected equilibrium response to a climate change. Additionally, the instantaneous value of τ evolves during sustained warming as the glacier thins and retreats. Perhaps counterintuitively, τ can increase if retreat into higher elevations exceeds thinning. This has implications for estimating the timescale based on currently observed geometry and mass balance. We use shallow-ice and 3-stage linear models to explore these effects with synthetic glacier geometries and climate forcings. In this way, we can diagnose the geometric and

Adrenocortical stress responses influence an invasive vertebrate's fitness in an extreme environment

PubMed Central

Jessop, Tim S.; Letnic, Mike; Webb, Jonathan K.; Dempster, Tim

2013-01-01

Continued range expansion into physiologically challenging environments requires invasive species to maintain adaptive phenotypic performance. The adrenocortical stress response, governed in part by glucocorticoid hormones, influences physiological and behavioural responses of vertebrates to environmental stressors. However, any adaptive role of this response in invasive populations that are expanding into extreme environments is currently unclear. We experimentally manipulated the adrenocortical stress response of invasive cane toads (Rhinella marina) to investigate its effect on phenotypic performance and fitness at the species' range front in the Tanami Desert, Australia. Here, toads are vulnerable to overheating and dehydration during the annual hot–dry season and display elevated plasma corticosterone levels indicative of severe environmental stress. By comparing unmanipulated control toads with toads whose adrenocortical stress response was manipulated to increase acute physiological stress responsiveness, we found that control toads had significantly reduced daily evaporative water loss and higher survival relative to the experimental animals. The adrenocortical stress response hence appears essential in facilitating complex phenotypic performance and setting fitness trajectories of individuals from invasive species during range expansion. PMID:23945686

Estimation of mean response via effective balancing score

PubMed Central

Hu, Zonghui; Follmann, Dean A.; Wang, Naisyin

2015-01-01

Summary We introduce effective balancing scores for estimation of the mean response under a missing at random mechanism. Unlike conventional balancing scores, the effective balancing scores are constructed via dimension reduction free of model specification. Three types of effective balancing scores are introduced: those that carry the covariate information about the missingness, the response, or both. They lead to consistent estimation with little or no loss in efficiency. Compared to existing estimators, the effective balancing score based estimator relieves the burden of model specification and is the most robust. It is a near-automatic procedure which is most appealing when high dimensional covariates are involved. We investigate both the asymptotic and the numerical properties, and demonstrate the proposed method in a study on Human Immunodeficiency Virus disease. PMID:25797955

Whole-body heating decreases skin vascular response to low orthostatic stress in the lower extremities.

PubMed

Yamazaki, Fumio; Nakayama, Yoshiro; Sone, Ryoko

2006-04-01

To elucidate the influence of heat stress on cutaneous vascular response in the lower extremities during orthostatic stress, a head-up tilt (HUT) test at angles of 15 degrees, 30 degrees, 45 degrees, and 60 degrees for 4 min each was conducted under normothermic control conditions followed by whole-body heat stress produced by a hot water-perfused suit in healthy volunteers. Skin blood flows (SkBF) in the forearm, thigh, and calf were monitored using laser-Doppler flowmetry throughout the experiment. Furthermore, to elucidate the effects of increased core and local skin temperatures on the local vascular response in calf skin under increasing orthostatic stress, the thigh was occluded at 20, 30, 50, 70, and 80 mmHg with a cuff in both the normothermic condition and the whole-body or local heating condition. Significant decreases in forearm SkBF during HUT were observed at an angle of 60 degrees during normothermia and at 30 degrees or more during heating. SkBF in the thigh and calf was decreased significantly by HUT at 15 degrees and above during normothermia, and there was no significant reduction of SkBF in these sites during HUT at the lower angles (15 degrees -45 degrees ) during whole-body heating. Significant decreases of calf SkBF were observed at cuff pressures of 20 mmHg and above during normothermia and of 30 mmHg and above during whole-body and local heating, respectively. These results suggest that SkBF in the lower extremities shows a marked reduction compared with the upper extremities during low orthostatic stress in normothermia, and the enhanced skin vasoconstrictor response in the lower extremities is diminished by both whole-body and local heat stress.

Probabilistic forecasting of extreme weather events based on extreme value theory

NASA Astrophysics Data System (ADS)

Van De Vyver, Hans; Van Schaeybroeck, Bert

2016-04-01

Extreme events in weather and climate such as high wind gusts, heavy precipitation or extreme temperatures are commonly associated with high impacts on both environment and society. Forecasting extreme weather events is difficult, and very high-resolution models are needed to describe explicitly extreme weather phenomena. A prediction system for such events should therefore preferably be probabilistic in nature. Probabilistic forecasts and state estimations are nowadays common in the numerical weather prediction community. In this work, we develop a new probabilistic framework based on extreme value theory that aims to provide early warnings up to several days in advance. We consider the combined events when an observation variable Y (for instance wind speed) exceeds a high threshold y and its corresponding deterministic forecasts X also exceeds a high forecast threshold y. More specifically two problems are addressed:} We consider pairs (X,Y) of extreme events where X represents a deterministic forecast, and Y the observation variable (for instance wind speed). More specifically two problems are addressed: Given a high forecast X=x_0, what is the probability that Y>y? In other words: provide inference on the conditional probability: [ Pr{Y>y|X=x_0}. ] Given a probabilistic model for Problem 1, what is the impact on the verification analysis of extreme events. These problems can be solved with bivariate extremes (Coles, 2001), and the verification analysis in (Ferro, 2007). We apply the Ramos and Ledford (2009) parametric model for bivariate tail estimation of the pair (X,Y). The model accommodates different types of extremal dependence and asymmetry within a parsimonious representation. Results are presented using the ensemble reforecast system of the European Centre of Weather Forecasts (Hagedorn, 2008). Coles, S. (2001) An Introduction to Statistical modelling of Extreme Values. Springer-Verlag.Ferro, C.A.T. (2007) A probability model for verifying deterministic

Normalization Strategies for Enhancing Spatio-Temporal Analysis of Social Media Responses during Extreme Events: A Case Study based on Analysis of Four Extreme Events using Socio-Environmental Data Explorer (SEDE)

NASA Astrophysics Data System (ADS)

Ajayakumar, J.; Shook, E.; Turner, V. K.

2017-10-01

With social media becoming increasingly location-based, there has been a greater push from researchers across various domains including social science, public health, and disaster management, to tap in the spatial, temporal, and textual data available from these sources to analyze public response during extreme events such as an epidemic outbreak or a natural disaster. Studies based on demographics and other socio-economic factors suggests that social media data could be highly skewed based on the variations of population density with respect to place. To capture the spatio-temporal variations in public response during extreme events we have developed the Socio-Environmental Data Explorer (SEDE). SEDE collects and integrates social media, news and environmental data to support exploration and assessment of public response to extreme events. For this study, using SEDE, we conduct spatio-temporal social media response analysis on four major extreme events in the United States including the "North American storm complex" in December 2015, the "snowstorm Jonas" in January 2016, the "West Virginia floods" in June 2016, and the "Hurricane Matthew" in October 2016. Analysis is conducted on geo-tagged social media data from Twitter and warnings from the storm events database provided by National Centers For Environmental Information (NCEI) for analysis. Results demonstrate that, to support complex social media analyses, spatial and population-based normalization and filtering is necessary. The implications of these results suggests that, while developing software solutions to support analysis of non-conventional data sources such as social media, it is quintessential to identify the inherent biases associated with the data sources, and adapt techniques and enhance capabilities to mitigate the bias. The normalization strategies that we have developed and incorporated to SEDE will be helpful in reducing the population bias associated with social media data and will be useful

The Effect of Low Survey Response Rates on Estimates of Alcohol Consumption in a General Population Survey

PubMed Central

Meiklejohn, Jessica; Connor, Jennie; Kypri, Kypros

2012-01-01

Background Response rates for surveys of alcohol use are declining for all modes of administration (postal, telephone, face-to-face). Low response rates may result in estimates that are biased by selective non-response. We examined non-response bias in the NZ GENACIS survey, a postal survey of a random electoral roll sample, with a response rate of 49.5% (n = 1924). Our aim was to estimate the magnitude of non-response bias in estimating the prevalence of current drinking and heavy episodic (binge) drinking. Methods We used the “continuum of resistance” model to guide the investigation. In this model the likelihood of response by sample members is related to the amount of effort required from the researchers to elicit a response. First, the demographic characteristics of respondents and non-respondents were compared. Second, respondents who returned their questionnaire before the first reminder (early), before the second reminder (intermediate) or after the second reminder (late) were compared by demographic characteristics, 12-month prevalence of drinking and prevalence of binge drinking. Results Demographic characteristics and prevalence of binge drinking were significantly different between late respondents and early/intermediate respondents, with the demographics of early and intermediate respondents being similar to people who refused to participate while late respondents were similar to all other non-respondents. Assuming non-respondents who did not actively refuse to participate had the same drinking patterns as late respondents, the prevalence of binge drinking amongst current drinkers was underestimated. Adjusting the prevalence of binge drinkers amongst current drinkers using population weights showed that this method of adjustment still resulted in an underestimate of the prevalence. Conclusions The findings suggest non-respondents who did not actively refuse to participate are likely to have similar or more extreme drinking behaviours than late

Regional Frequency and Uncertainty Analysis of Extreme Precipitation in Bangladesh

NASA Astrophysics Data System (ADS)

Mortuza, M. R.; Demissie, Y.; Li, H. Y.

2014-12-01

Increased frequency of extreme precipitations, especially those with multiday durations, are responsible for recent urban floods and associated significant losses of lives and infrastructures in Bangladesh. Reliable and routinely updated estimation of the frequency of occurrence of such extreme precipitation events are thus important for developing up-to-date hydraulic structures and stormwater drainage system that can effectively minimize future risk from similar events. In this study, we have updated the intensity-duration-frequency (IDF) curves for Bangladesh using daily precipitation data from 1961 to 2010 and quantified associated uncertainties. Regional frequency analysis based on L-moments is applied on 1-day, 2-day and 5-day annual maximum precipitation series due to its advantages over at-site estimation. The regional frequency approach pools the information from climatologically similar sites to make reliable estimates of quantiles given that the pooling group is homogeneous and of reasonable size. We have used Region of influence (ROI) approach along with homogeneity measure based on L-moments to identify the homogenous pooling groups for each site. Five 3-parameter distributions (i.e., Generalized Logistic, Generalized Extreme value, Generalized Normal, Pearson Type Three, and Generalized Pareto) are used for a thorough selection of appropriate models that fit the sample data. Uncertainties related to the selection of the distributions and historical data are quantified using the Bayesian Model Averaging and Balanced Bootstrap approaches respectively. The results from this study can be used to update the current design and management of hydraulic structures as well as in exploring spatio-temporal variations of extreme precipitation and associated risk.

The Role of Air-sea Coupling in the Response of Climate Extremes to Aerosols

NASA Astrophysics Data System (ADS)

Mahajan, S.

2017-12-01

Air-sea interactions dominate the climate of surrounding regions and thus also modulate the climate response to local and remote aerosol forcings. To clearly isolate the role of air-sea coupling in the climate response to aerosols, we conduct experiments with a full complexity atmosphere model that is coupled to a series of ocean models progressively increasing in complexity. The ocean models range from a data ocean model with prescribed SSTs, to a slab ocean model that only allows thermodynamic interactions, to a full dynamic ocean model. In a preliminary study, we have conducted single forcing experiments with black carbon aerosols in an atmosphere GCM coupled to a data ocean model and a slab ocean model. We find that while black carbon aerosols can intensify mean and extreme summer monsoonal precipitation over the Indian sub-continent, air-sea coupling can dramatically modulate this response. Black carbon aerosols in the vicinity of the Arabian Sea result in an increase of sea surface temperatures there in the slab ocean model, which intensify the low-level Somali Jet. The associated increase in moisture transport into Western India enhances the mean as well as extreme precipitation. In prescribed SST experiments, where SSTs are not allowed to respond BC aerosols, the response is muted. We will present results from a hierarchy of GCM simulations that investigate the role of air-sea coupling in the climate response to aerosols in more detail.

Most robust estimate of the Transient Climate Response yet?

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Venema, Victor; Schurer, Andrew

2017-04-01

Estimates of the Transient Climate Response often lack a coherent hemispheric or otherwise spatio-temporal representation. In the light of recent work that highlights the importance of inhomogeneous forcing considerations (Shindell et al 2014; Marvel et al 2015) and tas/tos-related inaccuracies (Richardson et al. 2016), here we present results from a well-tested two-box response model that takes these effects carefully into account. All external forcing data are updated based on latest emission estimates as well as recent TSI and volcanic AOD estimates. So are observed GMST data which include data for the entire year of 2016. Hence we also provide one of the first TCR estimates taking the latest El Nino into account. We demonstrate that short-term climate variability is not going to change the TCR estimate beyond very minor fluctuations. The method is therefore shown to be robust within surprisingly small uncertainty estimates. Using PMIP3 and an extended ensemble of HadCM3 simulations (Euro500; Schurer et al. 2014) GCM simulations for the pre-industrial period, we test the fast and slow response time constants that are tailored for observational data (Ripdal 2012). We also test the hemispheric response as well as the response over land and ocean separately. The TCR/ECS ratio is taken from a selected sub-set of CMIP5 simulations. The selection criteria is the best spatiotemporal match over 4 different time periods between 1860 and 2010. We will argue that this procedure should also be standard procedure to estimate ECS from observations, rather than relying on OHC estimates only. Finally, the demonstrate that PMIP3-type simulations that are initialised at least a century before 1850 (as is the standard initialisation for CMIP5-type simulations) are to be preferred. Remaining long-term radiative imbalance due to strong volcanic eruptions (e.g. Gleckler et al. 2006) tend to make CMIP5-type simulations slightly more sensitive to forcing, which leads to detectable

Evolution caused by extreme events.

PubMed

Grant, Peter R; Grant, B Rosemary; Huey, Raymond B; Johnson, Marc T J; Knoll, Andrew H; Schmitt, Johanna

2017-06-19

Extreme events can be a major driver of evolutionary change over geological and contemporary timescales. Outstanding examples are evolutionary diversification following mass extinctions caused by extreme volcanism or asteroid impact. The evolution of organisms in contemporary time is typically viewed as a gradual and incremental process that results from genetic change, environmental perturbation or both. However, contemporary environments occasionally experience strong perturbations such as heat waves, floods, hurricanes, droughts and pest outbreaks. These extreme events set up strong selection pressures on organisms, and are small-scale analogues of the dramatic changes documented in the fossil record. Because extreme events are rare, almost by definition, they are difficult to study. So far most attention has been given to their ecological rather than to their evolutionary consequences. We review several case studies of contemporary evolution in response to two types of extreme environmental perturbations, episodic (pulse) or prolonged (press). Evolution is most likely to occur when extreme events alter community composition. We encourage investigators to be prepared for evolutionary change in response to rare events during long-term field studies.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Bivariate extreme value distributions

NASA Technical Reports Server (NTRS)

Elshamy, M.

1992-01-01

In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given.

Behavioural, ecological and evolutionary responses to extreme climatic events: challenges and directions.

PubMed

van de Pol, Martijn; Jenouvrier, Stéphanie; Cornelissen, Johannes H C; Visser, Marcel E

2017-06-19

More extreme climatic events (ECEs) are among the most prominent consequences of climate change. Despite a long-standing recognition of the importance of ECEs by paleo-ecologists and macro-evolutionary biologists, ECEs have only recently received a strong interest in the wider ecological and evolutionary community. However, as with many rapidly expanding fields, it lacks structure and cohesiveness, which strongly limits scientific progress. Furthermore, due to the descriptive and anecdotal nature of many ECE studies it is still unclear what the most relevant questions and long-term consequences are of ECEs. To improve synthesis, we first discuss ways to define ECEs that facilitate comparison among studies. We then argue that biologists should adhere to more rigorous attribution and mechanistic methods to assess ECE impacts. Subsequently, we discuss conceptual and methodological links with climatology and disturbance-, tipping point- and paleo-ecology. These research fields have close linkages with ECE research, but differ in the identity and/or the relative severity of environmental factors. By summarizing the contributions to this theme issue we draw parallels between behavioural, ecological and evolutionary ECE studies, and suggest that an overarching challenge is that most empirical and theoretical evidence points towards responses being highly idiosyncratic, and thus predictability being low. Finally, we suggest a roadmap based on the proposition that an increased focus on the mechanisms behind the biological response function will be crucial for increased understanding and predictability of the impacts of ECE.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Behavioural, ecological and evolutionary responses to extreme climatic events: challenges and directions

PubMed Central

2017-01-01

More extreme climatic events (ECEs) are among the most prominent consequences of climate change. Despite a long-standing recognition of the importance of ECEs by paleo-ecologists and macro-evolutionary biologists, ECEs have only recently received a strong interest in the wider ecological and evolutionary community. However, as with many rapidly expanding fields, it lacks structure and cohesiveness, which strongly limits scientific progress. Furthermore, due to the descriptive and anecdotal nature of many ECE studies it is still unclear what the most relevant questions and long-term consequences are of ECEs. To improve synthesis, we first discuss ways to define ECEs that facilitate comparison among studies. We then argue that biologists should adhere to more rigorous attribution and mechanistic methods to assess ECE impacts. Subsequently, we discuss conceptual and methodological links with climatology and disturbance-, tipping point- and paleo-ecology. These research fields have close linkages with ECE research, but differ in the identity and/or the relative severity of environmental factors. By summarizing the contributions to this theme issue we draw parallels between behavioural, ecological and evolutionary ECE studies, and suggest that an overarching challenge is that most empirical and theoretical evidence points towards responses being highly idiosyncratic, and thus predictability being low. Finally, we suggest a roadmap based on the proposition that an increased focus on the mechanisms behind the biological response function will be crucial for increased understanding and predictability of the impacts of ECE. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483865

Diabetic Driving Studies-Part 2: A Comparison of Brake Response Time Between Drivers With Diabetes With and Without Lower Extremity Sensorimotor Neuropathy.

PubMed

Spiess, Kerianne E; Sansosti, Laura E; Meyr, Andrew J

We have previously demonstrated an abnormally delayed mean brake response time and an increased frequency of abnormally delayed brake responses in a group of neuropathic drivers with diabetes compared with a control group of drivers with neither diabetes nor lower extremity neuropathy. The objective of the present case-control study was to compare the mean brake response time between 2 groups of drivers with diabetes with and without lower extremity sensorimotor neuropathy. The braking performances of the participants were evaluated using a computerized driving simulator with specific measurement of the mean brake response time and the frequency of the abnormally delayed brake responses. We compared a control group of 25 active drivers with type 2 diabetes without lower extremity neuropathy and an experimental group of 25 active drivers with type 2 diabetes and lower extremity neuropathy from an urban U.S. podiatric medical clinic. The experimental group demonstrated an 11.49% slower mean brake response time (0.757 ± 0.180 versus 0.679 ± 0.120 second; p < .001), with abnormally delayed reactions occurring at a greater frequency (57.5% versus 35.0%; p < .001). Independent of a comparative statistical analysis, diabetic drivers with neuropathy demonstrated a mean brake response time slower than a suggested safety threshold of 0.70 second, and diabetic drivers without neuropathy demonstrated a mean brake response time faster than this threshold. The results of the present investigation provide evidence that the specific onset of lower extremity sensorimotor neuropathy associated with diabetes appears to impart a negative effect on automobile brake responses. Copyright © 2017 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Improving simulated long-term responses of vegetation to temperature and precipitation extremes using the ACME land model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Warren, J.; Guha, A.

2017-12-01

While carbon and energy fluxes in current Earth system models generally have reasonable instantaneous responses to extreme temperature and precipitation events, they often do not adequately represent the long-term impacts of these events. For example, simulated net primary productivity (NPP) may decrease during an extreme heat wave or drought, but may recover rapidly to pre-event levels following the conclusion of the extreme event. However, field measurements indicate that long-lasting damage to leaves and other plant components often occur, potentially affecting the carbon and energy balance for months after the extreme event. The duration and frequency of such extreme conditions is likely to shift in the future, and therefore it is critical for Earth system models to better represent these processes for more accurate predictions of future vegetation productivity and land-atmosphere feedbacks. Here we modify the structure of the Accelerated Climate Model for Energy (ACME) land surface model to represent long-term impacts and test the improved model against observations from experiments that applied extreme conditions in growth chambers. Additionally, we test the model against eddy covariance measurements that followed extreme conditions at selected locations in North America, and against satellite-measured vegetation indices following regional extreme events.

A new mean estimator using auxiliary variables for randomized response models

NASA Astrophysics Data System (ADS)

Ozgul, Nilgun; Cingi, Hulya

2013-10-01

Randomized response models are commonly used in surveys dealing with sensitive questions such as abortion, alcoholism, sexual orientation, drug taking, annual income, tax evasion to ensure interviewee anonymity and reduce nonrespondents rates and biased responses. Starting from the pioneering work of Warner [7], many versions of RRM have been developed that can deal with quantitative responses. In this study, new mean estimator is suggested for RRM including quantitative responses. The mean square error is derived and a simulation study is performed to show the efficiency of the proposed estimator to other existing estimators in RRM.

Republic of Georgia estimates for prevalence of drug use: Randomized response techniques suggest under-estimation.

PubMed

Kirtadze, Irma; Otiashvili, David; Tabatadze, Mzia; Vardanashvili, Irina; Sturua, Lela; Zabransky, Tomas; Anthony, James C

2018-06-01

Validity of responses in surveys is an important research concern, especially in emerging market economies where surveys in the general population are a novelty, and the level of social control is traditionally higher. The Randomized Response Technique (RRT) can be used as a check on response validity when the study aim is to estimate population prevalence of drug experiences and other socially sensitive and/or illegal behaviors. To apply RRT and to study potential under-reporting of drug use in a nation-scale, population-based general population survey of alcohol and other drug use. For this first-ever household survey on addictive substances for the Country of Georgia, we used the multi-stage probability sampling of 18-to-64-year-old household residents of 111 urban and 49 rural areas. During the interviewer-administered assessments, RRT involved pairing of sensitive and non-sensitive questions about drug experiences. Based upon the standard household self-report survey estimate, an estimated 17.3% [95% confidence interval, CI: 15.5%, 19.1%] of Georgian household residents have tried cannabis. The corresponding RRT estimate was 29.9% [95% CI: 24.9%, 34.9%]. The RRT estimates for other drugs such as heroin also were larger than the standard self-report estimates. We remain unsure about what is the "true" value for prevalence of using illegal psychotropic drugs in the Republic of Georgia study population. Our RRT results suggest that standard non-RRT approaches might produce 'under-estimates' or at best, highly conservative, lower-end estimates. Copyright © 2018 Elsevier B.V. All rights reserved.

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

Evaluation of Piloted Inputs for Onboard Frequency Response Estimation

NASA Technical Reports Server (NTRS)

Grauer, Jared A.; Martos, Borja

2013-01-01

Frequency response estimation results are presented using piloted inputs and a real-time estimation method recently developed for multisine inputs. A nonlinear simulation of the F-16 and a Piper Saratoga research aircraft were subjected to different piloted test inputs while the short period stabilator/elevator to pitch rate frequency response was estimated. Results show that the method can produce accurate results using wide-band piloted inputs instead of multisines. A new metric is introduced for evaluating which data points to include in the analysis and recommendations are provided for applying this method with piloted inputs.

Estimation of Graded Response Model Parameters Using MULTILOG.

ERIC Educational Resources Information Center

Baker, Frank B.

1997-01-01

Describes an idiosyncracy of the MULTILOG (D. Thissen, 1991) parameter estimation process discovered during a simulation study involving the graded response model. A misordering reflected in boundary function location parameter estimates resulted in a large negative contribution to the true score followed by a large positive contribution. These…

Robust Estimation of Latent Ability in Item Response Models

ERIC Educational Resources Information Center

Schuster, Christof; Yuan, Ke-Hai

2011-01-01

Because of response disturbances such as guessing, cheating, or carelessness, item response models often can only approximate the "true" individual response probabilities. As a consequence, maximum-likelihood estimates of ability will be biased. Typically, the nature and extent to which response disturbances are present is unknown, and, therefore,…

Extreme precipitation depths for Texas, excluding the Trans-Pecos region

USGS Publications Warehouse

Lanning-Rush, Jennifer; Asquith, William H.; Slade, Raymond M.

1998-01-01

Storm durations of 1, 2, 3, 4, 5, and 6 days were investigated for this report. The extreme precipitation depth for a particular area is estimated from an “extreme precipitation curve” (an upper limit or envelope curve developed from graphs of extreme precipitation depths for each climatic region). The extreme precipitation curves were determined using precipitation depth-duration information from a subset (24 “extreme” storms) of 213 “notable” storms documented throughout Texas. The extreme precipitation curves can be used to estimate extreme precipitation depth for a particular area. The extreme precipitation depth represents a limiting depth, which can provide useful comparative information for more quantitative analyses.

USACE Extreme Sea levels

DTIC Science & Technology

2014-03-14

with expected changes due to climate change. (tropicals and extra-tropicals) Ivan provided some good information on work being done on tropical...Pattiaratchi, C., Jensen, J., 2013. Estimating extreme water level probabilities: a comparison of the direct methods and recommendations for best practise ...sites: site-by-site analyses. Proudman Oceanographic Laboratory , Internal Document, No. 65, 229pp. Dixon, M.J., Tawn, J.A. (1995) Extreme sea-levels

Extreme Value Analysis of hydro meteorological extremes in the ClimEx Large-Ensemble

NASA Astrophysics Data System (ADS)

Wood, R. R.; Martel, J. L.; Willkofer, F.; von Trentini, F.; Schmid, F. J.; Leduc, M.; Frigon, A.; Ludwig, R.

2017-12-01

Many studies show an increase in the magnitude and frequency of hydrological extreme events in the course of climate change. However the contribution of natural variability to the magnitude and frequency of hydrological extreme events is not yet settled. A reliable estimate of extreme events is from great interest for water management and public safety. In the course of the ClimEx Project (www.climex-project.org) a new single-model large-ensemble was created by dynamically downscaling the CanESM2 large-ensemble with the Canadian Regional Climate Model version 5 (CRCM5) for an European Domain and a Northeastern North-American domain. By utilizing the ClimEx 50-Member Large-Ensemble (CRCM5 driven by CanESM2 Large-Ensemble) a thorough analysis of natural variability in extreme events is possible. Are the current extreme value statistical methods able to account for natural variability? How large is the natural variability for e.g. a 1/100 year return period derived from a 50-Member Large-Ensemble for Europe and Northeastern North-America? These questions should be answered by applying various generalized extreme value distributions (GEV) to the ClimEx Large-Ensemble. Hereby various return levels (5-, 10-, 20-, 30-, 60- and 100-years) based on various lengths of time series (20-, 30-, 50-, 100- and 1500-years) should be analyzed for the maximum one day precipitation (RX1d), the maximum three hourly precipitation (RX3h) and the streamflow for selected catchments in Europe. The long time series of the ClimEx Ensemble (7500 years) allows us to give a first reliable estimate of the magnitude and frequency of certain extreme events.

Model methodology for estimating pesticide concentration extremes based on sparse monitoring data

USGS Publications Warehouse

Vecchia, Aldo V.

2018-03-22

This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.

Thermal reactionomes reveal divergent responses to thermal extremes in warm and cool-climate ant species.

PubMed

Stanton-Geddes, John; Nguyen, Andrew; Chick, Lacy; Vincent, James; Vangala, Mahesh; Dunn, Robert R; Ellison, Aaron M; Sanders, Nathan J; Gotelli, Nicholas J; Cahan, Sara Helms

2016-03-02

The distributions of species and their responses to climate change are in part determined by their thermal tolerances. However, little is known about how thermal tolerance evolves. To test whether evolutionary extension of thermal limits is accomplished through enhanced cellular stress response (enhanced response), constitutively elevated expression of protective genes (genetic assimilation) or a shift from damage resistance to passive mechanisms of thermal stability (tolerance), we conducted an analysis of the reactionome: the reaction norm for all genes in an organism's transcriptome measured across an experimental gradient. We characterized thermal reactionomes of two common ant species in the eastern U.S, the northern cool-climate Aphaenogaster picea and the southern warm-climate Aphaenogaster carolinensis, across 12 temperatures that spanned their entire thermal breadth. We found that at least 2 % of all genes changed expression with temperature. The majority of upregulation was specific to exposure to low temperatures. The cool-adapted A. picea induced expression of more genes in response to extreme temperatures than did A. carolinensis, consistent with the enhanced response hypothesis. In contrast, under high temperatures the warm-adapted A. carolinensis downregulated many of the genes upregulated in A. picea, and required more extreme temperatures to induce down-regulation in gene expression, consistent with the tolerance hypothesis. We found no evidence for a trade-off between constitutive and inducible gene expression as predicted by the genetic assimilation hypothesis. These results suggest that increases in upper thermal limits may require an evolutionary shift in response mechanism away from damage repair toward tolerance and prevention.

A Rasch-validated version of the upper extremity functional index for interval-level measurement of upper extremity function.

PubMed

Hamilton, Clayon B; Chesworth, Bert M

2013-11-01

The original 20-item Upper Extremity Functional Index (UEFI) has not undergone Rasch validation. The purpose of this study was to determine whether Rasch analysis supports the UEFI as a measure of a single construct (ie, upper extremity function) and whether a Rasch-validated UEFI has adequate reproducibility for individual-level patient evaluation. This was a secondary analysis of data from a repeated-measures study designed to evaluate the measurement properties of the UEFI over a 3-week period. Patients (n=239) with musculoskeletal upper extremity disorders were recruited from 17 physical therapy clinics across 4 Canadian provinces. Rasch analysis of the UEFI measurement properties was performed. If the UEFI did not fit the Rasch model, misfitting patients were deleted, items with poor response structure were corrected, and misfitting items and redundant items were deleted. The impact of differential item functioning on the ability estimate of patients was investigated. A 15-item modified UEFI was derived to achieve fit to the Rasch model where the total score was supported as a measure of upper extremity function only. The resultant UEFI-15 interval-level scale (0-100, worst to best state) demonstrated excellent internal consistency (person separation index=0.94) and test-retest reliability (intraclass correlation coefficient [2,1]=.95). The minimal detectable change at the 90% confidence interval was 8.1. Patients who were ambidextrous or bilaterally affected were excluded to allow for the analysis of differential item functioning due to limb involvement and arm dominance. Rasch analysis did not support the validity of the 20-item UEFI. However, the UEFI-15 was a valid and reliable interval-level measure of a single dimension: upper extremity function. Rasch analysis supports using the UEFI-15 in physical therapist practice to quantify upper extremity function in patients with musculoskeletal disorders of the upper extremity.

Improving power and robustness for detecting genetic association with extreme-value sampling design.

PubMed

Chen, Hua Yun; Li, Mingyao

2011-12-01

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs. © 2011 Wiley Periodicals, Inc.

Spatial distribution of precipitation extremes in Norway

NASA Astrophysics Data System (ADS)

Verpe Dyrrdal, Anita; Skaugen, Thomas; Lenkoski, Alex; Thorarinsdottir, Thordis; Stordal, Frode; Førland, Eirik J.

2015-04-01

Estimates of extreme precipitation, in terms of return levels, are crucial in planning and design of important infrastructure. Through two separate studies, we have examined the levels and spatial distribution of daily extreme precipitation over catchments in Norway, and hourly extreme precipitation in a point. The analyses were carried out through the development of two new methods for estimating extreme precipitation in Norway. For daily precipitation we fit the Generalized Extreme Value (GEV) distribution to areal time series from a gridded dataset, consisting of daily precipitation during the period 1957-today with a resolution of 1x1 km². This grid-based method is more objective and less manual and time-consuming compared to the existing method at MET Norway. In addition, estimates in ungauged catchments are easier to obtain, and the GEV approach includes a measure of uncertainty, which is a requirement in climate studies today. Further, we go into depth on the debated GEV shape parameter, which plays an important role for longer return periods. We show that it varies according to dominating precipitation types, having positive values in the southeast and negative values in the southwest. We also find indications that the degree of orographic enhancement might affect the shape parameter. For hourly precipitation, we estimate return levels on a 1x1 km² grid, by linking GEV distributions with latent Gaussian fields in a Bayesian hierarchical model (BHM). Generalized linear models on the GEV parameters, estimated from observations, are able to incorporate location-specific geographic and meteorological information and thereby accommodate these effects on extreme precipitation. Gaussian fields capture additional unexplained spatial heterogeneity and overcome the sparse grid on which observations are collected, while a Bayesian model averaging component directly assesses model uncertainty. We find that mean summer precipitation, mean summer temperature, latitude

Effects of exposure estimation errors on estimated exposure-response relations for PM2.5.

PubMed

Cox, Louis Anthony Tony

2018-07-01

Associations between fine particulate matter (PM2.5) exposure concentrations and a wide variety of undesirable outcomes, from autism and auto theft to elderly mortality, suicide, and violent crime, have been widely reported. Influential articles have argued that reducing National Ambient Air Quality Standards for PM2.5 is desirable to reduce these outcomes. Yet, other studies have found that reducing black smoke and other particulate matter by as much as 70% and dozens of micrograms per cubic meter has not detectably affected all-cause mortality rates even after decades, despite strong, statistically significant positive exposure concentration-response (C-R) associations between them. This paper examines whether this disconnect between association and causation might be explained in part by ignored estimation errors in estimated exposure concentrations. We use EPA air quality monitor data from the Los Angeles area of California to examine the shapes of estimated C-R functions for PM2.5 when the true C-R functions are assumed to be step functions with well-defined response thresholds. The estimated C-R functions mistakenly show risk as smoothly increasing with concentrations even well below the response thresholds, thus incorrectly predicting substantial risk reductions from reductions in concentrations that do not affect health risks. We conclude that ignored estimation errors obscure the shapes of true C-R functions, including possible thresholds, possibly leading to unrealistic predictions of the changes in risk caused by changing exposures. Instead of estimating improvements in public health per unit reduction (e.g., per 10 µg/m 3 decrease) in average PM2.5 concentrations, it may be essential to consider how interventions change the distributions of exposure concentrations. Copyright © 2018 Elsevier Inc. All rights reserved.

Urbanization, Extreme Events, and Health: The Case for Systems Approaches in Mitigation, Management, and Response.

PubMed

Siri, José Gabriel; Newell, Barry; Proust, Katrina; Capon, Anthony

2016-03-01

Extreme events, both natural and anthropogenic, increasingly affect cities in terms of economic losses and impacts on health and well-being. Most people now live in cities, and Asian cities, in particular, are experiencing growth on unprecedented scales. Meanwhile, the economic and health consequences of climate-related events are worsening, a trend projected to continue. Urbanization, climate change and other geophysical and social forces interact with urban systems in ways that give rise to complex and in many cases synergistic relationships. Such effects may be mediated by location, scale, density, or connectivity, and also involve feedbacks and cascading outcomes. In this context, traditional, siloed, reductionist approaches to understanding and dealing with extreme events are unlikely to be adequate. Systems approaches to mitigation, management and response for extreme events offer a more effective way forward. Well-managed urban systems can decrease risk and increase resilience in the face of such events. © 2015 APJPH.

Response of shoal grass, Halodule wrightii, to extreme winter conditions in the Lower Laguna Madre, Texas

USGS Publications Warehouse

Hicks, D.W.; Onuf, C.P.; Tunnell, J.W.

1998-01-01

Effects of a severe freeze on the shoal grass, Halodule wrightii, were documented through analysis of temporal and spatial trends in below-ground biomass. The coincidence of the second lowest temperature (-10.6??C) in 107 years of record, 56 consecutive hours below freezing, high winds and extremely low water levels exposed the Laguna Madre, TX, to the most severe cold stress in over a century. H. wrightii tolerated this extreme freeze event. Annual pre- and post-freeze surveys indicated that below-ground biomass estimated from volume was Unaffected by the freeze event. Nor was there any post-freeze change in biomass among intertidal sites directly exposed to freezing air temperatures relative to subtidal sites which remained submerged during the freezing period.

Legacy effects of land-use modulate tree growth responses to climate extremes.

PubMed

Mausolf, Katharina; Härdtle, Werner; Jansen, Kirstin; Delory, Benjamin M; Hertel, Dietrich; Leuschner, Christoph; Temperton, Vicky M; von Oheimb, Goddert; Fichtner, Andreas

2018-05-10

Climate change can impact forest ecosystem processes via individual tree and community responses. While the importance of land-use legacies in modulating these processes have been increasingly recognised, evidence of former land-use mediated climate-growth relationships remain rare. We analysed how differences in former land-use (i.e. forest continuity) affect the growth response of European beech to climate extremes. Here, using dendrochronological and fine root data, we show that ancient forests (forests with a long forest continuity) and recent forests (forests afforested on former farmland) clearly differ with regard to climate-growth relationships. We found that sensitivity to climatic extremes was lower for trees growing in ancient forests, as reflected by significantly lower growth reductions during adverse climatic conditions. Fine root morphology also differed significantly between the former land-use types: on average, trees with high specific root length (SRL) and specific root area (SRA) and low root tissue density (RTD) were associated with recent forests, whereas the opposite traits were characteristic of ancient forests. Moreover, we found that trees of ancient forests hold a larger fine root system than trees of recent forests. Our results demonstrate that land-use legacy-mediated modifications in the size and morphology of the fine root system act as a mechanism in regulating drought resistance of beech, emphasising the need to consider the 'ecological memory' of forests when assessing or predicting the sensitivity of forest ecosystems to global environmental change.

Estimating disease prevalence from two-phase surveys with non-response at the second phase

PubMed Central

Gao, Sujuan; Hui, Siu L.; Hall, Kathleen S.; Hendrie, Hugh C.

2010-01-01

SUMMARY In this paper we compare several methods for estimating population disease prevalence from data collected by two-phase sampling when there is non-response at the second phase. The traditional weighting type estimator requires the missing completely at random assumption and may yield biased estimates if the assumption does not hold. We review two approaches and propose one new approach to adjust for non-response assuming that the non-response depends on a set of covariates collected at the first phase: an adjusted weighting type estimator using estimated response probability from a response model; a modelling type estimator using predicted disease probability from a disease model; and a regression type estimator combining the adjusted weighting type estimator and the modelling type estimator. These estimators are illustrated using data from an Alzheimer’s disease study in two populations. Simulation results are presented to investigate the performances of the proposed estimators under various situations. PMID:10931514

Age Modulates Physiological Responses during Fan Use under Extreme Heat and Humidity.

PubMed

Gagnon, Daniel; Romero, Steven A; Cramer, Matthew N; Kouda, Ken; Poh, Paula Y S; Ngo, Hai; Jay, Ollie; Crandall, Craig G

2017-11-01

We examined the effect of electric fan use on cardiovascular and thermoregulatory responses of nine young (26 ± 3 yr) and nine aged (68 ± 4 yr) adults exposed to extreme heat and humidity. While resting at a temperature of 42°C, relative humidity increased from 30% to 70% in 2% increments every 5 min. On randomized days, the protocol was repeated without or with fan use. HR, core (Tcore) and mean skin (Tsk) temperatures were measured continuously. Whole-body sweat loss was measured from changes in nude body weight. Other measures of cardiovascular (cardiac output), thermoregulatory (local cutaneous and forearm vascular conductance, local sweat rate), and perceptual (thermal and thirst sensations) responses were also examined. When averaged over the entire protocol, fan use resulted in a small reduction of HR (-2 bpm, 95% confidence interval [CI], -8 to 3), and slightly greater Tcore (+0.05°C; 95% CI, -0.13 to 0.23) and Tsk (+0.03°C; 95% CI, -0.36 to 0.42) in young adults. In contrast, fan use resulted in greater HR (+5 bpm; 95% CI, 0-10), Tcore (+0.20°C; 95% CI, 0.00-0.41), and Tsk (+0.47°C; 95% CI, 0.18-0.76) in aged adults. A greater whole-body sweat loss during fan use was observed in young (+0.2 kg; 95% CI, -0.2 to 0.6) but not aged (0.0 kg; 95% CI, -0.2 to 0.2) adults. Greater local sweat rate and cutaneous vascular conductance were observed with fan use in aged adults. Other measures of cardiovascular, thermoregulatory, and perceptual responses were unaffected by fan use in both groups. During extreme heat and humidity, fan use elevates physiological strain in aged, but not young, adults.

Boron stress response and accumulation potential of the extremely tolerant species Puccinellia frigida.

PubMed

Rámila, Consuelo D P; Contreras, Samuel A; Di Domenico, Camila; Molina-Montenegro, Marco A; Vega, Andrea; Handford, Michael; Bonilla, Carlos A; Pizarro, Gonzalo E

2016-11-05

Phytoremediation is a promising technology to tackle boron toxicity, which restricts agricultural activities in many arid and semi-arid areas. Puccinellia frigida is a perennial grass that was reported to hyperaccumulate boron in extremely boron-contaminated sites. To further investigate its potential for phytoremediation, we determined its response to boron stress under controlled conditions (hydroponic culture). Also, as a first step towards understanding the mechanisms underlying its extreme tolerance, we evaluated the presence and expression of genes related with boron tolerance. We found that P. frigida grew normally even at highly toxic boron concentrations in the medium (500mg/L), and within its tissues (>5000mg/kg DW). We postulate that the strategies conferring this extreme tolerance involve both restricting boron accumulation and an internal tolerance mechanism; this is consistent with the identification of putative genes involved in both mechanisms, including the expression of a possible boron efflux transporter. We also found that P. frigida hyperaccumulated boron over a wide range of boron concentrations. We propose that P. frigida could be used for boron phytoremediation strategies in places with different soil characteristics and boron concentrations. Further studies should pave the way for the development of clean and low-cost solutions to boron toxicity problems. Copyright © 2016 Elsevier B.V. All rights reserved.

Influence of conservative corrections on parameter estimation for extreme-mass-ratio inspirals

NASA Astrophysics Data System (ADS)

Huerta, E. A.; Gair, Jonathan R.

2009-04-01

We present an improved numerical kludge waveform model for circular, equatorial extreme-mass-ratio inspirals (EMRIs). The model is based on true Kerr geodesics, augmented by radiative self-force corrections derived from perturbative calculations, and in this paper for the first time we include conservative self-force corrections that we derive by comparison to post-Newtonian results. We present results of a Monte Carlo simulation of parameter estimation errors computed using the Fisher matrix and also assess the theoretical errors that would arise from omitting the conservative correction terms we include here. We present results for three different types of system, namely, the inspirals of black holes, neutron stars, or white dwarfs into a supermassive black hole (SMBH). The analysis shows that for a typical source (a 10M⊙ compact object captured by a 106M⊙ SMBH at a signal to noise ratio of 30) we expect to determine the two masses to within a fractional error of ˜10-4, measure the spin parameter q to ˜10-4.5, and determine the location of the source on the sky and the spin orientation to within 10-3 steradians. We show that, for this kludge model, omitting the conservative corrections leads to a small error over much of the parameter space, i.e., the ratio R of the theoretical model error to the Fisher matrix error is R<1 for all ten parameters in the model. For the few systems with larger errors typically R<3 and hence the conservative corrections can be marginally ignored. In addition, we use our model and first-order self-force results for Schwarzschild black holes to estimate the error that arises from omitting the second-order radiative piece of the self-force. This indicates that it may not be necessary to go beyond first order to recover accurate parameter estimates.

Estimation of the phase response curve from Parkinsonian tremor.

PubMed

Saifee, Tabish A; Edwards, Mark J; Kassavetis, Panagiotis; Gilbertson, Tom

2016-01-01

Phase response curves (PRCs), characterizing the response of an oscillator to weak external perturbation, have been estimated from a broad range of biological oscillators, including single neurons in vivo. PRC estimates, in turn, provide an intuitive insight into how oscillatory systems become entrained and how they can be desynchronized. Here, we explore the application of PRC theory to the case of Parkinsonian tremor. Initial attempts to establish a causal effect of subthreshold transcranial magnetic stimulation applied to primary motor cortex on the filtered tremor phase were unsuccessful. We explored the possible explanations of this and demonstrate that assumptions made when estimating the PRC in a traditional setting, such as a single neuron, are not arbitrary when applied to the case of tremor PRC estimation. We go on to extract the PRC of Parkinsonian tremor using an iterative method that requires varying the definition of the tremor cycle and estimating the PRC at multiple peristimulus time samples. Justification for this method is supported by estimates of PRC from simulated single neuron data. We provide an approach to estimating confidence limits for tremor PRC and discuss the interpretational caveats introduced by tremor harmonics and the intrinsic variability of the tremor's period. Copyright © 2016 the American Physiological Society.

Estimation of the phase response curve from Parkinsonian tremor

PubMed Central

Saifee, Tabish A.; Edwards, Mark J.; Kassavetis, Panagiotis

2015-01-01

Phase response curves (PRCs), characterizing the response of an oscillator to weak external perturbation, have been estimated from a broad range of biological oscillators, including single neurons in vivo. PRC estimates, in turn, provide an intuitive insight into how oscillatory systems become entrained and how they can be desynchronized. Here, we explore the application of PRC theory to the case of Parkinsonian tremor. Initial attempts to establish a causal effect of subthreshold transcranial magnetic stimulation applied to primary motor cortex on the filtered tremor phase were unsuccessful. We explored the possible explanations of this and demonstrate that assumptions made when estimating the PRC in a traditional setting, such as a single neuron, are not arbitrary when applied to the case of tremor PRC estimation. We go on to extract the PRC of Parkinsonian tremor using an iterative method that requires varying the definition of the tremor cycle and estimating the PRC at multiple peristimulus time samples. Justification for this method is supported by estimates of PRC from simulated single neuron data. We provide an approach to estimating confidence limits for tremor PRC and discuss the interpretational caveats introduced by tremor harmonics and the intrinsic variability of the tremor's period. PMID:26561596

Stationary and non-stationary extreme value modeling of extreme temperature in Malaysia

NASA Astrophysics Data System (ADS)

Hasan, Husna; Salleh, Nur Hanim Mohd; Kassim, Suraiya

2014-09-01

Extreme annual temperature of eighteen stations in Malaysia is fitted to the Generalized Extreme Value distribution. Stationary and non-stationary models with trend are considered for each station and the Likelihood Ratio test is used to determine the best-fitting model. Results show that three out of eighteen stations i.e. Bayan Lepas, Labuan and Subang favor a model which is linear in the location parameter. A hierarchical cluster analysis is employed to investigate the existence of similar behavior among the stations. Three distinct clusters are found in which one of them consists of the stations that favor the non-stationary model. T-year estimated return levels of the extreme temperature are provided based on the chosen models.

Estimating the effects of extreme weather on transportation infrastructure.

DOT National Transportation Integrated Search

2016-12-01

Climate change, already taking place, is expected to become more pronounced in the future. Current damage assessment models for extreme weather events, such as FEMAs Hazus, do not take the full impact to transportation systems into consideration. ...

Equal Area Logistic Estimation for Item Response Theory

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching; Wang, Kuo-Chang; Chang, Hsin-Li

2009-08-01

Item response theory (IRT) models use logistic functions exclusively as item response functions (IRFs). Applications of IRT models require obtaining the set of values for logistic function parameters that best fit an empirical data set. However, success in obtaining such set of values does not guarantee that the constructs they represent actually exist, for the adequacy of a model is not sustained by the possibility of estimating parameters. In this study, an equal area based two-parameter logistic model estimation algorithm is proposed. Two theorems are given to prove that the results of the algorithm are equivalent to the results of fitting data by logistic model. Numerical results are presented to show the stability and accuracy of the algorithm.

Energy estimation of inclined air showers with help of detector responses

NASA Astrophysics Data System (ADS)

Dedenko, L. G.; Fedorova, G. F.; Fedunin, E. Yu.; Glushkov, A. V.; Kolosov, V. A.; Podgrudkov, D. A.; Pravdin, M. I.; Roganova, T. M.; Sleptsov, I. E.

2004-11-01

The method of groups of muons have been suggested to estimate the detector responses for the inclined giant air shower in terms of quark-gluon string model with the geomagnetic field taken into account. Groups are average numbers of muons of positive or negative sign in small intervals of energy, height production and direction of motion in the atmosphere estimated with help of transport equations. For every group a relativistic equation of motion has been solved with geomagnetic field and ionization losses taken into account. The response of a detector and arrival time for every group which strike a detector has been estimated. The energy of the inclined giant air shower estimated with help of calculated responses and the data observed at the Yakutsk array happens to be above 10 20 eV.

Aircraft Fault Detection Using Real-Time Frequency Response Estimation

NASA Technical Reports Server (NTRS)

Grauer, Jared A.

2016-01-01

A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

Extreme geomagnetic storms: Probabilistic forecasts and their uncertainties

USGS Publications Warehouse

Riley, Pete; Love, Jeffrey J.

2017-01-01

Extreme space weather events are low-frequency, high-risk phenomena. Estimating their rates of occurrence, as well as their associated uncertainties, is difficult. In this study, we derive statistical estimates and uncertainties for the occurrence rate of an extreme geomagnetic storm on the scale of the Carrington event (or worse) occurring within the next decade. We model the distribution of events as either a power law or lognormal distribution and use (1) Kolmogorov-Smirnov statistic to estimate goodness of fit, (2) bootstrapping to quantify the uncertainty in the estimates, and (3) likelihood ratio tests to assess whether one distribution is preferred over another. Our best estimate for the probability of another extreme geomagnetic event comparable to the Carrington event occurring within the next 10 years is 10.3% 95%  confidence interval (CI) [0.9,18.7] for a power law distribution but only 3.0% 95% CI [0.6,9.0] for a lognormal distribution. However, our results depend crucially on (1) how we define an extreme event, (2) the statistical model used to describe how the events are distributed in intensity, (3) the techniques used to infer the model parameters, and (4) the data and duration used for the analysis. We test a major assumption that the data represent time stationary processes and discuss the implications. If the current trends persist, suggesting that we are entering a period of lower activity, our forecasts may represent upper limits rather than best estimates.

Apoptosis-Like Death, an Extreme SOS Response in Escherichia coli

PubMed Central

Erental, Ariel; Kalderon, Ziva; Saada, Ann; Smith, Yoav

2014-01-01

ABSTRACT In bacteria, SOS is a global response to DNA damage, mediated by the recA-lexA genes, resulting in cell cycle arrest, DNA repair, and mutagenesis. Previously, we reported that Escherichia coli responds to DNA damage via another recA-lexA-mediated pathway resulting in programmed cell death (PCD). We called it apoptosis-like death (ALD) because it is characterized by membrane depolarization and DNA fragmentation, which are hallmarks of eukaryotic mitochondrial apoptosis. Here, we show that ALD is an extreme SOS response that occurs only under conditions of severe DNA damage. Furthermore, we found that ALD is characterized by additional hallmarks of eukaryotic mitochondrial apoptosis, including (i) rRNA degradation by the endoribonuclease YbeY, (ii) upregulation of a unique set of genes that we called extensive-damage-induced (Edin) genes, (iii) a decrease in the activities of complexes I and II of the electron transport chain, and (iv) the formation of high levels of OH˙ through the Fenton reaction, eventually resulting in cell death. Our genetic and molecular studies on ALD provide additional insight for the evolution of mitochondria and the apoptotic pathway in eukaryotes. PMID:25028428

Landscape composition creates a threshold influencing Lesser Prairie-Chicken population resilience to extreme drought

USGS Publications Warehouse

Ross, Beth E.; Haukos, David A.; Hagen, Christian A.; Pitman, James C.

2016-01-01

Habitat loss and degradation compound the effects of climate change on wildlife, yet responses to climate and land cover change are often quantified independently. The interaction between climate and land cover change could be intensified in the Great Plains region where grasslands are being converted to row-crop agriculture concurrent with increased frequency of extreme drought events. We quantified the combined effects of land cover and climate change on a species of conservation concern in the Great Plains, the Lesser Prairie-Chicken (Tympanuchus pallidicinctus  ). We combined extreme drought events and land cover change with lek count surveys in a Bayesian hierarchical model to quantify changes in abundance of male Lesser Prairie-Chickens from 1978 to 2014 in Kansas, the core of their species range. Our estimates of abundance indicate a gradually decreasing population through 2010 corresponding to drought events and reduced grassland areas. Decreases in Lesser Prairie-Chicken abundance were greatest in areas with increasing row-crop to grassland land cover ratio during extreme drought events, and decreased grassland reduces the resilience of Lesser Prairie-Chicken populations to extreme drought events. A threshold exists for Lesser Prairie-Chickens in response to the gradient of cropland:grassland land cover. When moving across the gradient of grassland to cropland, abundance initially increased in response to more cropland on the landscape, but declined in response to more cropland after the threshold (δ=0.096, or 9.6% cropland). Preservation of intact grasslands and continued implementation of initiatives to revert cropland to grassland should increase Lesser Prairie-Chicken resilience to extreme drought events due to climate change.

Evaluating the extreme precipitation events using a mesoscale atmopshere model

NASA Astrophysics Data System (ADS)

Yucel, I.; Onen, A.

2012-04-01

Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. Mesoscale atmospheric models coupled with land surface models provide efficient forecasts for meteorological events in high lead time and therefore they should be used for flood forecasting and warning issues as they provide more continuous monitoring of precipitation over large areas. This study examines the performance of the Weather Research and Forecasting (WRF) model in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in West Black Sea Region of Turkey. Extreme precipitation events usually resulted in flood conditions as an associated hydrologic response of the basin. The performance of the WRF system is further investigated by using the three dimensional variational (3D-VAR) data assimilation scheme within WRF. WRF performance with and without data assimilation at high spatial resolution (4 km) is evaluated by making comparison with gauge precipitation and satellite-estimated rainfall data from Multi Precipitation Estimates (MPE). WRF-derived precipitation showed capabilities in capturing the timing of the precipitation extremes and in some extent spatial distribution and magnitude of the heavy rainfall events. These precipitation characteristics are enhanced with the use of 3D-VAR scheme in WRF system. Data assimilation improved area-averaged precipitation forecasts by 9 percent and at some points there exists quantitative match in precipitation events, which are critical for hydrologic forecast application.

Nonparametric Item Response Curve Estimation with Correction for Measurement Error

ERIC Educational Resources Information Center

Guo, Hongwen; Sinharay, Sandip

2011-01-01

Nonparametric or kernel regression estimation of item response curves (IRCs) is often used in item analysis in testing programs. These estimates are biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. Accuracy of this estimation is a concern theoretically and operationally.…

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE PAGES

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.; ...

2018-03-01

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous

Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

USGS Publications Warehouse

Friedel, M.J.

2008-01-01

A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

Physiological responses at five estimates of critical velocity.

PubMed

Bull, Anthony J; Housh, Terry J; Johnson, Glen O; Rana, Sharon R

2008-04-01

The purpose of this study was to compare critical velocity (CV) estimates from five mathematical models, and to examine the oxygen uptake (VO(2)) and heart rate (HR) responses during treadmill runs at the five estimates of CV. Ten subjects (six males and four females) performed one incremental test to determine maximal oxygen consumption (VO(2max)) and four or five randomly ordered constant-velocity trials on a treadmill for the estimation of CV. Five mathematical models were used to estimate CV for each subject including two linear, two nonlinear, and an exponential model. Up to five randomly ordered runs to exhaustion were performed by each subject at treadmill velocities that corresponded to the five CV estimates, and VO(2) and HR responses were monitored throughout each trial. The 3-parameter, nonlinear (Non-3) model produced CV estimates that were significantly (P < 0.05) less than the other four models. During runs at CV estimates, five subjects did not complete 60 min at the their estimate from the Non-3 model, nine did not complete 60 min at their estimate from the Non-2 model, and no subjects completed 60 min at any estimate from the other three models. The mean HR value (179 +/- 18 beats min(-1), HR(peak)) at the end of runs at CV using the Non-3 model was significantly less than the maximal HR (195 +/- 7 beats min(-1), HR(max)) achieved during the incremental trial to exhaustion. However, mean HR(peak) values from runs at all other CV estimates were not significantly different from HR(max). Furthermore, data indicated that mean HR(peak) values increased during runs at CV estimates from the third minute to the end of exercise for all models, and that these increases in VO(2) (range = 367-458 ml min(-1)) were significantly greater than that typically associated with O(2) drift ( approximately 200 ml min(-1)) for all but the exponential model, indicating a VO(2) slow component associated with CV estimates from four of the five models. However, the mean VO(2

A New Approach to Extreme Value Estimation Applicable to a Wide Variety of Random Variables

NASA Technical Reports Server (NTRS)

Holland, Frederic A., Jr.

1997-01-01

Designing reliable structures requires an estimate of the maximum and minimum values (i.e., strength and load) that may be encountered in service. Yet designs based on very extreme values (to insure safety) can result in extra material usage and hence, uneconomic systems. In aerospace applications, severe over-design cannot be tolerated making it almost mandatory to design closer to the assumed limits of the design random variables. The issue then is predicting extreme values that are practical, i.e. neither too conservative or non-conservative. Obtaining design values by employing safety factors is well known to often result in overly conservative designs and. Safety factor values have historically been selected rather arbitrarily, often lacking a sound rational basis. To answer the question of how safe a design needs to be has lead design theorists to probabilistic and statistical methods. The so-called three-sigma approach is one such method and has been described as the first step in utilizing information about the data dispersion. However, this method is based on the assumption that the random variable is dispersed symmetrically about the mean and is essentially limited to normally distributed random variables. Use of this method can therefore result in unsafe or overly conservative design allowables if the common assumption of normality is incorrect.

Estimating least-developed countries' vulnerability to climate-related extreme events over the next 50 years.

PubMed

Patt, Anthony G; Tadross, Mark; Nussbaumer, Patrick; Asante, Kwabena; Metzger, Marc; Rafael, Jose; Goujon, Anne; Brundrit, Geoff

2010-01-26

When will least developed countries be most vulnerable to climate change, given the influence of projected socio-economic development? The question is important, not least because current levels of international assistance to support adaptation lag more than an order of magnitude below what analysts estimate to be needed, and scaling up support could take many years. In this paper, we examine this question using an empirically derived model of human losses to climate-related extreme events, as an indicator of vulnerability and the need for adaptation assistance. We develop a set of 50-year scenarios for these losses in one country, Mozambique, using high-resolution climate projections, and then extend the results to a sample of 23 least-developed countries. Our approach takes into account both potential changes in countries' exposure to climatic extreme events, and socio-economic development trends that influence countries' own adaptive capacities. Our results suggest that the effects of socio-economic development trends may begin to offset rising climate exposure in the second quarter of the century, and that it is in the period between now and then that vulnerability will rise most quickly. This implies an urgency to the need for international assistance to finance adaptation.

Estimating least-developed countries’ vulnerability to climate-related extreme events over the next 50 years

PubMed Central

Patt, Anthony G.; Tadross, Mark; Nussbaumer, Patrick; Asante, Kwabena; Metzger, Marc; Rafael, Jose; Goujon, Anne; Brundrit, Geoff

2010-01-01

When will least developed countries be most vulnerable to climate change, given the influence of projected socio-economic development? The question is important, not least because current levels of international assistance to support adaptation lag more than an order of magnitude below what analysts estimate to be needed, and scaling up support could take many years. In this paper, we examine this question using an empirically derived model of human losses to climate-related extreme events, as an indicator of vulnerability and the need for adaptation assistance. We develop a set of 50-year scenarios for these losses in one country, Mozambique, using high-resolution climate projections, and then extend the results to a sample of 23 least-developed countries. Our approach takes into account both potential changes in countries’ exposure to climatic extreme events, and socio-economic development trends that influence countries’ own adaptive capacities. Our results suggest that the effects of socio-economic development trends may begin to offset rising climate exposure in the second quarter of the century, and that it is in the period between now and then that vulnerability will rise most quickly. This implies an urgency to the need for international assistance to finance adaptation. PMID:20080585

Distinguishing Buried Objects in Extremely Shallow Underground by Frequency Response Using Scanning Laser Doppler Vibrometer

NASA Astrophysics Data System (ADS)

Abe, Touma; Sugimoto, Tsuneyoshi

2010-07-01

A sound wave vibration using a scanning laser Doppler vibrometer are used as a method of exploring and imaging an extremely shallow underground. Flat speakers are used as a vibration source. We propose a method of distinguishing a buried object using a response range of a frequencies corresponding to a vibration velocities. Buried objects (plastic containers, a hollow steel can, an unglazed pot, and a stone) are distinguished using a response range of frequencies. Standardization and brightness imaging are used as methods of discrimination. As a result, it was found that the buried objects show different response ranges of frequencies. From the experimental results, we confirmed the effectiveness of our proposed method.

Risk-based damage potential and loss estimation of extreme flooding scenarios in the Austrian Federal Province of Tyrol

NASA Astrophysics Data System (ADS)

Huttenlau, M.; Stötter, J.; Stiefelmeyer, H.

2010-12-01

Within the last decades serious flooding events occurred in many parts of Europe and especially in 2005 the Austrian Federal Province of Tyrol was serious affected. These events in general and particularly the 2005 event have sensitised decision makers and the public. Beside discussions pertaining to protection goals and lessons learnt, the issue concerning potential consequences of extreme and severe flooding events has been raised. Additionally to the general interest of the public, decision makers of the insurance industry, public authorities, and responsible politicians are especially confronted with the question of possible consequences of extreme events. Answers thereof are necessary for the implementation of preventive appropriate risk management strategies. Thereby, property and liability losses reflect a large proportion of the direct tangible losses. These are of great interest for the insurance sector and can be understood as main indicators to interpret the severity of potential events. The natural scientific-technical risk analysis concept provides a predefined and structured framework to analyse the quantities of affected elements at risk, their corresponding damage potentials, and the potential losses. Generally, this risk concept framework follows the process steps hazard analysis, exposition analysis, and consequence analysis. Additionally to the conventional hazard analysis, the potential amount of endangered elements and their corresponding damage potentials were analysed and, thereupon, concrete losses were estimated. These took the specific vulnerability of the various individual elements at risk into consideration. The present flood risk analysis estimates firstly the general exposures of the risk indicators in the study area and secondly analyses the specific exposures and consequences of five extreme event scenarios. In order to precisely identify, localize, and characterize the relevant risk indicators of buildings, dwellings and inventory

Maternal Microbe-Specific Modulation of Inflammatory Response in Extremely Low-Gestational-Age Newborns

PubMed Central

Fichorova, Raina N.; Onderdonk, Andrew B.; Yamamoto, Hidemi; Delaney, Mary L.; DuBois, Andrea M.; Allred, Elizabeth; Leviton, Alan

2011-01-01

The fetal response to intrauterine inflammatory stimuli appears to contribute to the onset of preterm labor as well as fetal injury, especially affecting newborns of extremely low gestational age. To investigate the role of placental colonization by specific groups of microorganisms in the development of inflammatory responses present at birth, we analyzed 25 protein biomarkers in dry blood spots obtained from 527 newborns delivered by Caesarean section in the 23rd to 27th gestation weeks. Bacteria were detected in placentas and characterized by culture techniques. Odds ratios for having protein concentrations in the top quartile for gestation age for individual and groups of microorganisms were calculated. Mixed bacterial vaginosis (BV) organisms were associated with a proinflammatory pattern similar to those of infectious facultative anaerobes. Prevotella and Gardnerella species, anaerobic streptococci, peptostreptococci, and genital mycoplasmas each appeared to be associated with a different pattern of elevated blood levels of inflammation-related proteins. Lactobacillus was associated with low odds of an inflammatory response. This study provides evidence that microorganisms colonizing the placenta provoke distinctive newborn inflammatory responses and that Lactobacillus may suppress these responses. PMID:21264056

A Rasch-Validated Version of the Upper Extremity Functional Index for Interval-Level Measurement of Upper Extremity Function

PubMed Central

Chesworth, Bert M.

2013-01-01

Background The original 20-item Upper Extremity Functional Index (UEFI) has not undergone Rasch validation. Objective The purpose of this study was to determine whether Rasch analysis supports the UEFI as a measure of a single construct (ie, upper extremity function) and whether a Rasch-validated UEFI has adequate reproducibility for individual-level patient evaluation. Design This was a secondary analysis of data from a repeated-measures study designed to evaluate the measurement properties of the UEFI over a 3-week period. Methods Patients (n=239) with musculoskeletal upper extremity disorders were recruited from 17 physical therapy clinics across 4 Canadian provinces. Rasch analysis of the UEFI measurement properties was performed. If the UEFI did not fit the Rasch model, misfitting patients were deleted, items with poor response structure were corrected, and misfitting items and redundant items were deleted. The impact of differential item functioning on the ability estimate of patients was investigated. Results A 15-item modified UEFI was derived to achieve fit to the Rasch model where the total score was supported as a measure of upper extremity function only. The resultant UEFI-15 interval-level scale (0–100, worst to best state) demonstrated excellent internal consistency (person separation index=0.94) and test-retest reliability (intraclass correlation coefficient [2,1]=.95). The minimal detectable change at the 90% confidence interval was 8.1. Limitations Patients who were ambidextrous or bilaterally affected were excluded to allow for the analysis of differential item functioning due to limb involvement and arm dominance. Conclusion Rasch analysis did not support the validity of the 20-item UEFI. However, the UEFI-15 was a valid and reliable interval-level measure of a single dimension: upper extremity function. Rasch analysis supports using the UEFI-15 in physical therapist practice to quantify upper extremity function in patients with musculoskeletal

Characterization of extreme air-sea turbulent fluxes

NASA Astrophysics Data System (ADS)

Gulev, Sergey; Belyaev, Konstantin

2017-04-01

Extreme ocean-atmosphere turbulent fluxes play a critical role in the convective processes in the mid and subpolar latitudes and may also affect a variety of atmospheric processes, such as generation and re-intensification of extreme cyclones in the areas of the mid latitude storm tracks. From the ocean dynamics perspective, specifically for quantifying extreme vertical mixing, characterization of the extreme fluxes requires, besides estimation of the extreme events, also consideration of the relative extremeness of surface fluxes and their timing, e.g. the duration of periods of high surface fluxes. In order to comprehensively characterize extreme turbulent fluxes at sea surface we propose a formalism based upon probability density distributions of surface turbulent fluxes and flux-related variables. Individual absolute flux extremes were derived using Modified Fisher-Tippett (MFT) distribution of turbulent fluxes. Then, we extend this distribution to the fractional distribution, characterizing the fraction of time-integrated turbulent heat flux provided by the fluxes exceeding a given percentile. Finally, we consider the time durations during which fluxes of a given intensity provide extreme accumulations of heat loss from the surface. For estimation of these characteristics of surface fluxes we use fluxes recomputed from the state variables available from modern era reanalyses (ERA-Interim, MERRA and CFSR) for the period from 1979 onwards. Applications of the formalism to the VOS (Voluntary Observing Ship) - based surface fluxes are also considered. We discuss application of the new metrics of mesoscale and synoptic variability of surface fluxes to the dynamics of mixed layer depth in the North Atlantic.

Apoptosis-like death, an extreme SOS response in Escherichia coli.

PubMed

Erental, Ariel; Kalderon, Ziva; Saada, Ann; Smith, Yoav; Engelberg-Kulka, Hanna

2014-07-15

In bacteria, SOS is a global response to DNA damage, mediated by the recA-lexA genes, resulting in cell cycle arrest, DNA repair, and mutagenesis. Previously, we reported that Escherichia coli responds to DNA damage via another recA-lexA-mediated pathway resulting in programmed cell death (PCD). We called it apoptosis-like death (ALD) because it is characterized by membrane depolarization and DNA fragmentation, which are hallmarks of eukaryotic mitochondrial apoptosis. Here, we show that ALD is an extreme SOS response that occurs only under conditions of severe DNA damage. Furthermore, we found that ALD is characterized by additional hallmarks of eukaryotic mitochondrial apoptosis, including (i) rRNA degradation by the endoribonuclease YbeY, (ii) upregulation of a unique set of genes that we called extensive-damage-induced (Edin) genes, (iii) a decrease in the activities of complexes I and II of the electron transport chain, and (iv) the formation of high levels of OH˙ through the Fenton reaction, eventually resulting in cell death. Our genetic and molecular studies on ALD provide additional insight for the evolution of mitochondria and the apoptotic pathway in eukaryotes. Importance: The SOS response is the first described and the most studied bacterial response to DNA damage. It is mediated by a set of two genes, recA-lexA, and it results in DNA repair and thereby in the survival of the bacterial culture. We have shown that Escherichia coli responds to DNA damage by an additional recA-lexA-mediated pathway resulting in an apoptosis-like death (ALD). Apoptosis is a mode of cell death that has previously been reported only in eukaryotes. We found that E. coli ALD is characterized by several hallmarks of eukaryotic mitochondrial apoptosis. Altogether, our results revealed that recA-lexA is a DNA damage response coordinator that permits two opposite responses: life, mediated by the SOS, and death, mediated by the ALD. The choice seems to be a function of the degree

Influence of turbulence, orientation, and site configuration on the response of buildings to extreme wind.

PubMed

Aly, Aly Mousaad

2014-01-01

Atmospheric turbulence results from the vertical movement of air, together with flow disturbances around surface obstacles which make low- and moderate-level winds extremely irregular. Recent advancements in wind engineering have led to the construction of new facilities for testing residential homes at relatively high Reynolds numbers. However, the generation of a fully developed turbulence in these facilities is challenging. The author proposed techniques for the testing of residential buildings and architectural features in flows that lack fully developed turbulence. While these methods are effective for small structures, the extension of the approach for large and flexible structures is not possible yet. The purpose of this study is to investigate the role of turbulence in the response of tall buildings to extreme winds. In addition, the paper presents a detailed analysis to investigate the influence of upstream terrain conditions, wind direction angle (orientation), and the interference effect from the surrounding on the response of high-rise buildings. The methodology presented can be followed to help decision makers to choose among innovative solutions like aerodynamic mitigation, structural member size adjustment, and/or damping enhancement, with an objective to improve the resiliency and the serviceability of buildings.

Influence of Turbulence, Orientation, and Site Configuration on the Response of Buildings to Extreme Wind

PubMed Central

2014-01-01

Atmospheric turbulence results from the vertical movement of air, together with flow disturbances around surface obstacles which make low- and moderate-level winds extremely irregular. Recent advancements in wind engineering have led to the construction of new facilities for testing residential homes at relatively high Reynolds numbers. However, the generation of a fully developed turbulence in these facilities is challenging. The author proposed techniques for the testing of residential buildings and architectural features in flows that lack fully developed turbulence. While these methods are effective for small structures, the extension of the approach for large and flexible structures is not possible yet. The purpose of this study is to investigate the role of turbulence in the response of tall buildings to extreme winds. In addition, the paper presents a detailed analysis to investigate the influence of upstream terrain conditions, wind direction angle (orientation), and the interference effect from the surrounding on the response of high-rise buildings. The methodology presented can be followed to help decision makers to choose among innovative solutions like aerodynamic mitigation, structural member size adjustment, and/or damping enhancement, with an objective to improve the resiliency and the serviceability of buildings. PMID:24701140

Extremes in ecology: Avoiding the misleading effects of sampling variation in summary analyses

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1996-01-01

Surveys such as the North American Breeding Bird Survey (BBS) produce large collections of parameter estimates. One's natural inclination when confronted with lists of parameter estimates is to look for the extreme values: in the BBS, these correspond to the species that appear to have the greatest changes in population size through time. Unfortunately, extreme estimates are liable to correspond to the most poorly estimated parameters. Consequently, the most extreme parameters may not match up with the most extreme parameter estimates. The ranking of parameter values on the basis of their estimates are a difficult statistical problem. We use data from the BBS and simulations to illustrate the potential misleading effects of sampling variation in rankings of parameters. We describe empirical Bayes and constrained empirical Bayes procedures which provide partial solutions to the problem of ranking in the presence of sampling variation.

Response and Recovery of Streams From an Extreme Flood

NASA Astrophysics Data System (ADS)

Kantack, K. M.; Renshaw, C. E.; Magilligan, F. J.; Dethier, E.

2015-12-01

In temperate regions, channels are expected to recover from intense floods in a matter of months to years, but quantitative empirical support for this idea remains limited. Moreover, existing literature fails to address the spatial variability of the recovery process. Using an emerging technology, we investigate the immediate response to and progressive recovery of channels in the Northeastern United States from an extreme flood. We seek to determine what factors, including the nature and extent of the immediate response of the channel to the flood and post-flood availability of sediment, contribute to the spatial variability of the rate of recovery. Taking advantage of the 2011 flooding from Tropical Storm Irene, for which pre- and post-flood aerial lidar exist, along with a third set of terrestrial lidar collected in 2015, we assess channel response and recovery with multi-temporal lidar comparison. This method, with kilometers of continuous data, allows for analysis beyond traditional cross-section and reach-scale studies. Results indicate that landscape-scale factors, such as valley morphology and gradients in unit stream power, are controls on channel response to the flood, producing spatially variable impacts. Along a 16.4-km section (drainage area = 82 km2) of the Deerfield River in Vermont, over 148,000 m3 or erosion occurred during the flood. The spatial variation of impacts was correlated (R2= 0.476) with the ratio of channel width to valley width. We expect the recovery process will similarly exhibit spatial variation in rate and magnitude, possibly being governed by gradients in unit stream power and sediment availability. We test the idea that channel widening during the flood reduces post-flood unit stream power, creating a pathway for deposition and recovery to pre-flood width. Flood-widened reaches downstream of point-sources of sediment, such as landslides, will recover more quickly than those without consistent sediment supply. Results of this

NEUROTOXIC EFFECTS OF ENVIRONMENTAL AGENTS: DATA GAPS THAT CHALLENGE DOSE-RESPONSE ESTIMATION

EPA Science Inventory

Neurotoxic effects of environmental agents: Data gaps that challenge dose-response estimation
S Gutter*, P Mendola+, SG Selevan**, D Rice** (*UNC Chapel Hill; +US EPA, NHEERL; **US EPA, NCEA)

Dose-response estimation is a critical feature of risk assessment. It can be...

Model design for predicting extreme precipitation event impacts on water quality in a water supply reservoir

NASA Astrophysics Data System (ADS)

Hagemann, M.; Jeznach, L. C.; Park, M. H.; Tobiason, J. E.

2016-12-01

Extreme precipitation events such as tropical storms and hurricanes are by their nature rare, yet have disproportionate and adverse effects on surface water quality. In the context of drinking water reservoirs, common concerns of such events include increased erosion and sediment transport and influx of natural organic matter and nutrients. As part of an effort to model the effects of an extreme precipitation event on water quality at the reservoir intake of a major municipal water system, this study sought to estimate extreme-event watershed responses including streamflow and exports of nutrients and organic matter for use as inputs to a 2-D hydrodynamic and water quality reservoir model. Since extreme-event watershed exports are highly uncertain, we characterized and propagated predictive uncertainty using a quasi-Monte Carlo approach to generate reservoir model inputs. Three storm precipitation depths—corresponding to recurrence intervals of 5, 50, and 100 years—were converted to streamflow in each of 9 tributaries by volumetrically scaling 2 storm hydrographs from the historical record. Rating-curve models for concentratoin, calibrated using 10 years of data for each of 5 constituents, were then used to estimate the parameters of a multivariate lognormal probability model of constituent concentrations, conditional on each scenario's storm date and streamflow. A quasi-random Halton sequence (n = 100) was drawn from the conditional distribution for each event scenario, and used to generate input files to a calibrated CE-QUAL-W2 reservoir model. The resulting simulated concentrations at the reservoir's drinking water intake constitute a low-discrepancy sample from the estimated uncertainty space of extreme-event source water-quality. Limiting factors to the suitability of this approach include poorly constrained relationships between hydrology and constituent concentrations, a high-dimensional space from which to generate inputs, and relatively long run

Response of snow-dependent hydrologic extremes to continued global warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diffenbaugh, Noah; Scherer, Martin; Ashfaq, Moetasim

2012-01-01

Snow accumulation is critical for water availability in the Northern Hemisphere1,2, raising concern that global warming could have important impacts on natural and human systems in snow-dependent regions1,3. Although regional hydrologic changes have been observed (for example, refs 1,3 5), the time of emergence of extreme changes in snow accumulation and melt remains a key unknown for assessing climate- change impacts3,6,7. We find that the CMIP5 global climate model ensemble exhibits an imminent shift towards low snow years in the Northern Hemisphere, with areas of western North America, northeastern Europe and the Greater Himalaya showing the strongest emergence during themore » near- termdecadesandat2 Cglobalwarming.Theoccurrenceof extremely low snow years becomes widespread by the late twenty-first century, as do the occurrences of extremely high early-season snowmelt and runoff (implying increasing flood risk), and extremely low late-season snowmelt and runoff (implying increasing water stress). Our results suggest that many snow-dependent regions of the Northern Hemisphere are likely to experience increasing stress from low snow years within the next three decades, and from extreme changes in snow-dominated water resources if global warming exceeds 2 C above the pre-industrial baseline.« less

Remote Sensing of Surficial Process Responses to Extreme Meteorological Events

NASA Technical Reports Server (NTRS)

Brakenridge, G. Robert

1997-01-01

. Karen Prestegaard at the University of Maryland (geomorphological responses to the extreme 1993 flood along the Raccoon drainage in central Iowa), and with Mr Tim Scrom of the Albany National Weather Service River Forecast Center (initial planning for the use of Radarsat and ERS-2 for flood warning). The work thus initiated with this proposal is continuing.

Whole-Exome Sequencing in Two Extreme Phenotypes of Response to VEGF-Targeted Therapies in Patients With Metastatic Clear Cell Renal Cell Carcinoma.

PubMed

Fay, Andre P; de Velasco, Guillermo; Ho, Thai H; Van Allen, Eliezer M; Murray, Bradley; Albiges, Laurence; Signoretti, Sabina; Hakimi, A Ari; Stanton, Melissa L; Bellmunt, Joaquim; McDermott, David F; Atkins, Michael B; Garraway, Levi A; Kwiatkowski, David J; Choueiri, Toni K

2016-07-01

Advances in next-generation sequencing have provided a unique opportunity to understand the biology of disease and mechanisms of sensitivity or resistance to specific agents. Renal cell carcinoma (RCC) is a heterogeneous disease and highly variable clinical responses have been observed with vascular endothelial growth factor (VEGF)-targeted therapy (VEGF-TT). We hypothesized that whole-exome sequencing analysis might identify genotypes associated with extreme response or resistance to VEGF-TT in metastatic (mRCC). Patients with mRCC who had received first-line sunitinib or pazopanib and were in 2 extreme phenotypes of response were identified. Extreme responders (ERs) were defined as those with partial response or complete response for 3 or more years (n=13) and primary refractory patients (PRPs) were defined as those with progressive disease within the first 3 months of therapy (n=14). International Metastatic RCC Database Consortium prognostic scores were not significantly different between the groups (P=.67). Considering the genes known to be mutated in RCC at significant frequency, PBRM1 mutations were identified in 7 ERs (54%) versus 1 PRP (7%) (P=.01). In addition, mutations in TP53 (n=4) were found only in PRPs (P=.09). Our data suggest that mutations in some genes in RCC may impact response to VEGF-TT. Copyright © 2016 by the National Comprehensive Cancer Network.

Human impact parameterization in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study

NASA Astrophysics Data System (ADS)

Veldkamp, Ted; Ward, Philip; de Moel, Hans; Aerts, Jeroen; Muller Schmied, Hannes; Portmann, Felix; Zhao, Fang; Gerten, Dieter; Masaki, Yoshimitsu; Pokhrel, Yadu; Satoh, Yusuke; Gosling, Simon; Zaherpour, Jamal; Wada, Yoshihide

2017-04-01

Human impacts on freshwater resources and hydrological features form the core of present-day water related hazards, like flooding, droughts, water scarcity, and water quality issues. Driven by the societal and scientific needs to correctly model such water related hazards a fair amount of resources has been invested over the past decades to represent human activities and their interactions with the hydrological cycle in global hydrological models (GHMs). Use of these GHMs - including the human dimension - is widespread, especially in water resources research. Evaluation or comparative assessments of the ability of such GHMs to represent real-world hydrological conditions are, unfortunately, however often limited to (near-)natural river basins. Such studies are, therefore, not able to test the model representation of human activities and its associated impact on estimates of freshwater resources or assessments of hydrological extremes. Studies that did perform a validation exercise - including the human dimension and looking into managed catchments - either focused only on one hydrological model, and/or incorporated only a few data points (i.e. river basins) for validation. To date, a comprehensive comparative analysis that evaluates whether and where incorporating the human dimension actually improves the performance of different GHMs with respect to their representation of real-world hydrological conditions and extremes is missing. The absence of such study limits the potential benchmarking of GHMs and their outcomes in hydrological hazard and risk assessments significantly, potentially hampering incorporation of GHMs and their modelling results in actual policy making and decision support with respect to water resources management. To address this issue, we evaluate in this study the performance of five state-of-the-art GHMs that include anthropogenic activities in their modelling scheme, with respect to their representation of monthly discharges and hydrological

Spectrum response estimation for deep-water floating platforms via retardation function representation

NASA Astrophysics Data System (ADS)

Liu, Fushun; Liu, Chengcheng; Chen, Jiefeng; Wang, Bin

2017-08-01

The key concept of spectrum response estimation with commercial software, such as the SESAM software tool, typically includes two main steps: finding a suitable loading spectrum and computing the response amplitude operators (RAOs) subjected to a frequency-specified wave component. In this paper, we propose a nontraditional spectrum response estimation method that uses a numerical representation of the retardation functions. Based on estimated added mass and damping matrices of the structure, we decompose and replace the convolution terms with a series of poles and corresponding residues in the Laplace domain. Then, we estimate the power density corresponding to each frequency component using the improved periodogram method. The advantage of this approach is that the frequency-dependent motion equations in the time domain can be transformed into the Laplace domain without requiring Laplace-domain expressions for the added mass and damping. To validate the proposed method, we use a numerical semi-submerged pontoon from the SESAM. The numerical results show that the responses of the proposed method match well with those obtained from the traditional method. Furthermore, the estimated spectrum also matches well, which indicates its potential application to deep-water floating structures.

Correlation dimension and phase space contraction via extreme value theory

NASA Astrophysics Data System (ADS)

Faranda, Davide; Vaienti, Sandro

2018-04-01

We show how to obtain theoretical and numerical estimates of correlation dimension and phase space contraction by using the extreme value theory. The maxima of suitable observables sampled along the trajectory of a chaotic dynamical system converge asymptotically to classical extreme value laws where: (i) the inverse of the scale parameter gives the correlation dimension and (ii) the extremal index is associated with the rate of phase space contraction for backward iteration, which in dimension 1 and 2, is closely related to the positive Lyapunov exponent and in higher dimensions is related to the metric entropy. We call it the Dynamical Extremal Index. Numerical estimates are straightforward to obtain as they imply just a simple fit to a univariate distribution. Numerical tests range from low dimensional maps, to generalized Henon maps and climate data. The estimates of the indicators are particularly robust even with relatively short time series.

Extreme-event geoelectric hazard maps

NASA Astrophysics Data System (ADS)

Love, J. J.; Bedrosian, P.

2017-12-01

Maps covering about half of the continental United States are presented of geoelectric field amplitude that will be exceeded, on average, once per century in response to extreme-intensity geomagnetic disturbance. These maps are constructed using an empirical parameterization of induction: convolving latitude-dependent statistical maps of extreme-value geomagnetic disturbance, obtained from decades of 1-minute magnetic observatory data, with local estimates of Earth-surface impedance, obtained at discrete geographic sites from magnetotelluric surveys. Geoelectric amplitudes are estimated for geomagnetic waveforms having 240-s (and 1200-s) sinusoidal period and amplitudes over 10 minutes (1-hr) that exceed a once-per-century threshold. As a result of the combination of geographic differences in geomagnetic variation and Earth-surface impedance, once-per-century geoelectric amplitudes span more than two orders of magnitude and are a highly granular function of location. Specifically: for north-south 240-s induction, once-per-century geoelectric amplitudes across large parts of the United States have a median value of 0.34 V/km; for east-west variation, they have a median value of 0.23 V/km. In Northern Minnesota, amplitudes exceed 14.00 V/km for north-south geomagnetic variation (23.34 V/km for east-west variation), while just over 100 km away, amplitudes are only 0.08 V/km (0.02 V/km). At some sites in the Northern Central United States, once-per-century geoelectric amplitudes exceed the 2 V/km realized in Quebec during the March 1989 storm. These hazard maps are incomplete over large parts of the United States, including major population centers in the southern United States, due to a lack of publically available impedance data.

Nonstationary Extreme Value Analysis in a Changing Climate: A Software Package

NASA Astrophysics Data System (ADS)

Cheng, L.; AghaKouchak, A.; Gilleland, E.

2013-12-01

Numerous studies show that climatic extremes have increased substantially in the second half of the 20th century. For this reason, analysis of extremes under a nonstationary assumption has received a great deal of attention. This paper presents a software package developed for estimation of return levels, return periods, and risks of climatic extremes in a changing climate. This MATLAB software package offers tools for analysis of climate extremes under both stationary and non-stationary assumptions. The Nonstationary Extreme Value Analysis (hereafter, NEVA) provides an efficient and generalized framework for analyzing extremes using Bayesian inference. NEVA estimates the extreme value parameters using a Differential Evolution Markov Chain (DE-MC) which utilizes the genetic algorithm Differential Evolution (DE) for global optimization over the real parameter space with the Markov Chain Monte Carlo (MCMC) approach and has the advantage of simplicity, speed of calculation and convergence over conventional MCMC. NEVA also offers the confidence interval and uncertainty bounds of estimated return levels based on the sampled parameters. NEVA integrates extreme value design concepts, data analysis tools, optimization and visualization, explicitly designed to facilitate analysis extremes in geosciences. The generalized input and output files of this software package make it attractive for users from across different fields. Both stationary and nonstationary components of the package are validated for a number of case studies using empirical return levels. The results show that NEVA reliably describes extremes and their return levels.

Dryland ecosystem responses to precipitation extremes and wildfire at a long-term rainfall manipulation experiment

NASA Astrophysics Data System (ADS)

Brown, R. F.; Collins, S. L.

2017-12-01

Climate is becoming increasingly more variable due to global environmental change, which is evidenced by fewer, but more extreme precipitation events, changes in precipitation seasonality, and longer, higher severity droughts. These changes, combined with a rising incidence of wildfire, have the potential to strongly impact net primary production (NPP) and key biogeochemical cycles, particularly in dryland ecosystems where NPP is sequentially limited by water and nutrient availability. Here we utilize a ten-year dataset from an ongoing long-term field experiment established in 2007 in which we experimentally altered monsoon rainfall variability to examine how our manipulations, along with naturally occurring events, affect NPP and associated biogeochemical cycles in a semi-arid grassland in central New Mexico, USA. Using long-term regional averages, we identified extremely wet monsoon years (242.8 mm, 2013), and extremely dry monsoon years (86.0 mm, 2011; 80.0 mm, 2015) and water years (117.0 mm, 2011). We examined how changes in precipitation variability and extreme events affected ecosystem processes and function particularly in the context of ecosystem recovery following a 2009 wildfire. Response variables included above- and below-ground plant biomass (ANPP & BNPP) and abundance, soil nitrogen availability, and soil CO2 efflux. Mean ANPP ranged from 3.6 g m-2 in 2011 to 254.5 g m-2 in 2013, while BNPP ranged from 23.5 g m-2 in 2015 to 194.2 g m-2 in 2013, demonstrating NPP in our semi-arid grassland is directly linked to extremes in both seasonal and annual precipitation. We also show increased nitrogen deposition positively affects NPP in unburned grassland, but has no significant impact on NPP post-fire except during extremely wet monsoon years. While soil respiration rates reflect lower ANPP post-fire, patterns in CO2 efflux have not been shown to change significantly in that efflux is greatest following large precipitation events preceded by longer drying

Streamflow response to increasing precipitation extremes altered by forest management

Treesearch

Charlene N. Kelly; Kevin J. McGuire; Chelcy Ford Miniat; James M. Vose

2016-01-01

Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the...

Simulation of Theoretical Most-Extreme Geomagnetic Sudden Commencements

NASA Astrophysics Data System (ADS)

Welling, D. T.; Love, J. J.; Wiltberger, M. J.; Rigler, E. J.

2016-12-01

We report results from a numerical simulation of geomagnetic sudden commencements driven by solar wind conditions given by theoretical-limit extreme coronal-mass ejections (CMEs) estimated by Tsurutani and Lakhina [2014]. The CME characteristics at Earth are a step function that jumps from typical quiet values to 2700 km/s flow speed and a magnetic field magnitude of 127 nT. These values are used to drive three coupled models: a global magnetohydrodynamic (MHD) magnetospheric model (BATS-R-US), a ring current model (the Rice Convection Model, RCM), and a height-integrated ionospheric electrodynamics model (the Ridley Ionosphere Model, RIM), all coupled together using the Space Weather Modeling Framework (SWMF). Additionally, simulations from the Lyon-Fedder-Mobarry MHD model are performed for comparison. The commencement is simulated with both purely northward and southward IMF orientations. Low-latitude ground-level geomagnetic variations, both B and dB/dt, are estimated in response to the storm sudden commencement. For a northward interplanetary magnetic field (IMF) storm, the combined models predict a maximum sudden commencement response, Dst-equivalent of +200 nT and a maximum local dB/dt of 200nT/s. While this positive Dst response is driven mainly by magnetopause currents, complicated and dynamic Birkeland current patterns also develop, which drive the strong dB/dt responses at high latitude. For southward IMF conditions, erosion of dayside magnetic flux allows magnetopause currents to approach much closer to the Earth, leading to a stronger terrestrial response (Dst-equivalent of +250 nT). Further, high latitude signals from Region 1 Birkeland currents move to lower latitudes during the southward IMF case, increasing the risk to populated areas around the globe. Results inform fundamental understanding of solar-terrestrial interaction and benchmark estimates for induction hazards of interest to the electric-power grid industry.

The effects of non-stationary noise on electromagnetic response estimates

NASA Astrophysics Data System (ADS)

Banks, R. J.

1998-11-01

The noise in natural electromagnetic time series is typically non-stationary. Sections of data with high magnetic noise levels bias impedances and generate unreliable error estimates. Sections containing noise that is coherent between electric and magnetic channels also produce inappropriate impedances and errors. The answer is to compute response values for data sections which are as short as is feasible, i.e. which are compatible both with the chosen bandwidth and with the need to over-determine the least-squares estimation of the impedance and coherence. Only those values that are reliable are selected, and the best single measure of the reliability of Earth impedance estimates is their temporal invariance, which is tested by the coherence between the measured and predicted electric fields. Complex demodulation is the method used here to explore the temporal structure of electromagnetic fields in the period range 20-6000 s. For periods above 300 s, noisy sections are readily identified in time series of impedance values. The corresponding estimates deviate strongly from the normal value, are biased towards low impedance values, and are associated with low coherences. Plots of the impedance against coherence are particularly valuable diagnostic aids. For periods below 300 s, impedance bias increases systematically as the coherence falls, identifying input channel noise as the cause. By selecting sections with high coherence (equivalent to the impedance being invariant over the section) unbiased impedances and realistic errors can be determined. The scatter in impedance values among high-coherence sections is due to noise that is coherent between input and output channels, implying the presence of two or more systems for which a consistent response can be defined. Where the Earth and noise responses are significantly different, it may be possible to improve estimates of the former by rejecting sections that do not generate satisfactory values for all the response

Mapping Dependence Between Extreme Rainfall and Storm Surge

NASA Astrophysics Data System (ADS)

Wu, Wenyan; McInnes, Kathleen; O'Grady, Julian; Hoeke, Ron; Leonard, Michael; Westra, Seth

2018-04-01

Dependence between extreme storm surge and rainfall can have significant implications for flood risk in coastal and estuarine regions. To supplement limited observational records, we use reanalysis surge data from a hydrodynamic model as the basis for dependence mapping, providing information at a resolution of approximately 30 km along the Australian coastline. We evaluated this approach by comparing the dependence estimates from modeled surge to that calculated using historical surge records from 79 tide gauges around Australia. The results show reasonable agreement between the two sets of dependence values, with the exception of lower seasonal variation in the modeled dependence values compared to the observed data, especially at locations where there are multiple processes driving extreme storm surge. This is due to the combined impact of local bathymetry as well as the resolution of the hydrodynamic model and its meteorological inputs. Meteorological drivers were also investigated for different combinations of extreme rainfall and surge—namely rain-only, surge-only, and coincident extremes—finding that different synoptic patterns are responsible for each combination. The ability to supplement observational records with high-resolution modeled surge data enables a much more precise quantification of dependence along the coastline, strengthening the physical basis for assessments of flood risk in coastal regions.

Temporal Treatment of a Thermal Response for Defect Depth Estimation

NASA Technical Reports Server (NTRS)

Plotnikov, Y. A.; Winfree, W. P.

2004-01-01

Transient thermography, which employs pulse surface heating of an inspected component followed by acquisition of the thermal decay stage, is gaining wider acceptance as a result of its remoteness and rapidness. Flaws in the component s material may induce a thermal contrast in surface thermograms. An important issue in transient thermography is estimating the depth of a subsurface flaw from the thermal response. This improves the quantitative ability of the thermal evaluation: from one scan it is possible to locate regions of anomalies in thickness (caused by corrosion) and estimate the implications of the flaw on the integrity of the structure. Our research focuses on thick composite aircraft components. A long square heating pulse and several minutes observation period are required to receive an adequate thermal response from such a component. Application of various time-related informative parameters of the thermal response for depth estimation is discussed. A three-dimensional finite difference model of heat propagation in solids in Cartesian coordinates is used to simulate the thermographic process. Typical physical properties of polymer graphite composites are assumed for the model.

Responses of Mean and Extreme Precipitation to Deforestation in the Maritime Continent

NASA Astrophysics Data System (ADS)

Chen, C. C.; Lo, M. H.; Yu, J. Y.

2017-12-01

Anthropogenic land use and land cover change, including tropical deforestation, could have substantial effects on local surface energy and water budgets, and thus on the atmospheric stability which may result in changes in precipitation. Maritime Continent has undergone severe deforestation in recent decades but has received less attention than Amazon or Congo rainforests. Therefore, this study is to decipher the precipitation response to deforestation in the Maritime Continent. We conduct deforestation experiments using Community Earth System Model (CESM) and through converting the tropical rainforest into grassland. The results show that deforestation in Maritime Continent leads to an increase in both mean temperature and mean precipitation. Moisture budget analysis indicates that the increase in precipitation is associated with the vertically integrated vertical moisture advection, especially the dynamic component (changes in convection). In addition, through moist static energy (MSE) budget analysis, we find the atmosphere among deforested areas become unstable owing to the combined effects of positive specific humidity anomalies at around 850 hPa and anomalous warming extended from the surface to 750 hPa. This instability will induce anomalous ascending motion, which could enhance the low-level moisture convergence, providing water vapor from the surrounding warm ocean. To further evaluate the precipitation response to deforestation, we examine the precipitation changes under La Niña events and global warming scenario using CESM Atmospheric Model Intercomparison Project (AMIP) simulations and Representative Concentration Pathway (RCP) 8.5 simulations. We find that the precipitation increase caused by deforestation in Maritime Continent is comparable in magnitude to that generated by either natural variability or global warming forcing. Besides the changes in mean precipitation, preliminary results show the extreme precipitation also increases. We will further

A Coupled Approach with Stochastic Rainfall-Runoff Simulation and Hydraulic Modeling for Extreme Flood Estimation on Large Watersheds

NASA Astrophysics Data System (ADS)

Paquet, E.

2015-12-01

The SCHADEX method aims at estimating the distribution of peak and daily discharges up to extreme quantiles. It couples a precipitation probabilistic model based on weather patterns, with a stochastic rainfall-runoff simulation process using a conceptual lumped model. It allows exploring an exhaustive set of hydrological conditions and watershed responses to intense rainfall events. Since 2006, it has been widely applied in France to about one hundred watersheds for dam spillway design, and also aboard (Norway, Canada and central Europe among others). However, its application to large watersheds (above 10 000 km²) faces some significant issues: spatial heterogeneity of rainfall and hydrological processes and flood peak damping due to hydraulic effects (flood plains, natural or man-made embankment) being the more important. This led to the development of an extreme flood simulation framework for large and heterogeneous watersheds, based on the SCHADEX method. Its main features are: Division of the large (or main) watershed into several smaller sub-watersheds, where the spatial homogeneity of the hydro-meteorological processes can reasonably be assumed, and where the hydraulic effects can be neglected. Identification of pilot watersheds where discharge data are available, thus where rainfall-runoff models can be calibrated. They will be parameters donors to non-gauged watersheds. Spatially coherent stochastic simulations for all the sub-watersheds at the daily time step. Identification of a selection of simulated events for a given return period (according to the distribution of runoff volumes at the scale of the main watershed). Generation of the complete hourly hydrographs at each of the sub-watersheds outlets. Routing to the main outlet with hydraulic 1D or 2D models. The presentation will be illustrated with the case-study of the Isère watershed (9981 km), a French snow-driven watershed. The main novelties of this method will be underlined, as well as its

Changes in extremes due to half a degree warming in observations and models

NASA Astrophysics Data System (ADS)

Fischer, E. M.; Schleussner, C. F.; Pfleiderer, P.

2017-12-01

Assessing the climate impacts of half-a-degree warming increments is high on the post-Paris science agenda. Discriminating those effects is particularly challenging for climate extremes such as heavy precipitation and heat extremes for which model uncertainties are generally large, and for which internal variability is so important that it can easily offset or strongly amplify the forced local changes induced by half a degree warming. Despite these challenges we provide evidence for large-scale changes in the intensity and frequency of climate extremes due to half a degree warming. We first assess the difference in extreme climate indicators in observational data for the 1960s and 1970s versus the recent past, two periods differ by half a degree. We identify distinct differences for the global and continental-scale occurrence of heat and heavy precipitation extremes. We show that those observed changes in heavy precipitation and heat extremes broadly agree with simulated historical differences and are informative for the projected differences between 1.5 and 2°C warming despite different radiative forcings. We therefore argue that evidence from the observational record can inform the debate about discernible climate impacts in the light of model uncertainty by providing a conservative estimate of the implications of 0.5°C warming. A limitation of using the observational record arises from potential non-linearities in the response of climate extremes to a certain level of warming. We test for potential non-linearities in the response of heat and heavy precipitation extremes in a large ensemble of transient climate simulations. We further quantify differences between a time-window approach in a coupled model large ensemble vs. time-slice experiments using prescribed SST experiments performed in the context of the HAPPI-MIP project. Thereby we provide different lines of evidence that half a degree warming leads to substantial changes in the expected occurrence of

Rapid estimation of frequency response functions by close-range photogrammetry

NASA Technical Reports Server (NTRS)

Tripp, J. S.

1985-01-01

The accuracy of a rapid method which estimates the frequency response function from stereoscopic dynamic data is computed. It is shown that reversal of the order of the operations of coordinate transformation and Fourier transformation, which provides a significant increase in computational speed, introduces error. A portion of the error, proportional to the perturbation components normal to the camera focal planes, cannot be eliminated. The remaining error may be eliminated by proper scaling of frequency data prior to coordinate transformation. Methods are developed for least squares estimation of the full 3x3 frequency response matrix for a three dimensional structure.

Risk assessment of precipitation extremes in northern Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Jun; Pei, Ying; Zhang, Yanwei; Ge, Quansheng

2018-05-01

This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity-humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity-humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites' 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.

Modeling human perception and estimation of kinematic responses during aircraft landing

NASA Technical Reports Server (NTRS)

Schmidt, David K.; Silk, Anthony B.

1988-01-01

The thrust of this research is to determine estimation accuracy of aircraft responses based on observed cues. By developing the geometric relationships between the outside visual scene and the kinematics during landing, visual and kinesthetic cues available to the pilot were modeled. Both fovial and peripheral vision was examined. The objective was to first determine estimation accuracy in a variety of flight conditions, and second to ascertain which parameters are most important and lead to the best achievable accuracy in estimating the actual vehicle response. It was found that altitude estimation was very sensitive to the FOV. For this model the motion cue of perceived vertical acceleration was shown to be less important than the visual cues. The inclusion of runway geometry in the visual scene increased estimation accuracy in most cases. Finally, it was shown that for this model if the pilot has an incorrect internal model of the system kinematics the choice of observations thought to be 'optimal' may in fact be suboptimal.

Edge Response and NIIRS Estimates for Commercial Remote Sensing Satellites

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Ryan, Robert E.; Pagnutti, mary; Stanley, Thomas

2006-01-01

Spatial resolution of panchromatic imagery from commercial remote sensing satellites was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative Edge Response (RER) was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS). By assuming a plausible range of signal-to-noise ratio and assessing the effects of Modulation Transfer Function compensation, the NIIRS estimates were made and then compared with vendor-provided values and evaluations conducted by the National Geospatial-Intelligence Agency.

Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

The effect of asymmetrical body orientation during simulated forward falls on the distal upper extremity impact response of healthy people.

PubMed

Burkhart, Timothy A; Brydges, Evan; Stefanczyk, Jennifer; Andrews, David M

2017-04-01

The occurrence of distal upper extremity injuries resulting from forward falls (approximately 165,000 per year) has remained relatively constant for over 20years. Previous work has provided valuable insight into fall arrest strategies, but only symmetric falls in body postures that do not represent actual fall scenarios closely have been evaluated. This study quantified the effect of asymmetric loading and body postures on distal upper extremity response to simulated forward falls. Twenty participants were suspended from the Propelled Upper Limb fall ARest Impact System (PULARIS) in different torso and leg postures relative to the ground and to the sagittal plane (0°, 30° and 45°). When released from PULARIS (hands 10cm above surface, velocity 1m/s), participants landed on two force platforms, one for each hand. Right forearm impact response was measured with distal (radial styloid) and proximal (olecranon) tri-axial accelerometers and bipolar EMG from seven muscles. Overall, the relative height of the torso and legs had little effect on the forces, or forearm response variables. Muscle activation patterns consistently increased from the start to the peak activation levels after impact for all muscles, followed by a rapid decline after peak. The impact forces and accelerations suggest that the distal upper extremity is loaded more medial-laterally during asymmetric falls than symmetric falls. Altering the direction of the impact force in this way (volar-dorsal to medial-lateral) may help reduce distal extremity injuries caused when landing occurs symmetrically in the sagittal plane as it has been shown that volar-dorsal forces increase the risk of injury. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analyzing phenological extreme events over the past five decades in Germany

NASA Astrophysics Data System (ADS)

Schleip, Christoph; Menzel, Annette; Estrella, Nicole; Graeser, Philipp

2010-05-01

As climate change may alter the frequency and intensity of extreme temperatures, we analysed whether warming of the last 5 decades has already changed the statistics of phenological extreme events. In this context, two extreme value statistical concepts are discussed and applied to existing phenological datasets of German Weather Service (DWD) in order to derive probabilities of occurrence for extreme early or late phenological events. We analyse four phenological groups; "begin of flowering, "leaf foliation", "fruit ripening" and "leaf colouring" as well as DWD indicator phases of the "phenological year". Additionally we put an emphasis on a between-species analysis; a comparison of differences in extreme onsets between three common northern conifers. Furthermore we conducted a within-species analysis with different phases of horse chestnut throughout a year. The first statistical approach fits data to a Gaussian model using traditional statistical techniques, and then analyses the extreme quantile. The key point of this approach is the adoption of an appropriate probability density function (PDF) to the observed data and the assessment of the PDF parameters change in time. The full analytical description in terms of the estimated PDF for defined time steps of the observation period allows probability assessments of extreme values for e.g. annual or decadal time steps. Related with this approach is the possibility of counting out the onsets which fall in our defined extreme percentiles. The estimation of the probability of extreme events on the basis of the whole data set is in contrast to analyses with the generalized extreme value distribution (GEV). The second approach deals with the extreme PDFs itself and fits the GEV distribution to annual minima of phenological series to provide useful estimates about return levels. For flowering and leaf unfolding phases exceptionally early extremes are seen since the mid 1980s and especially for the single years 1961

Impacts of climate extremes on gross primary productivity of terrestrial ecosystems in conterminous USA

NASA Astrophysics Data System (ADS)

Wu, X.; Xiao, X.; Zhang, Y.; Zhang, G.

2016-12-01

By offsetting one-third of anthropogenic carbon emissions, terrestrial carbon uptake mitigates atmospheric CO2 concentration and consequent global warming. However, the current global warming trend is inducing more climate extremes, which in turn cause large changes in terrestrial carbon uptake. Here we report the seasonal and regional anomalies of gross primary productivity (GPP) across the conterminous USA (CONUS) in response to two contrasting climate extremes: the cool and wet 2009 versus the warm and dry 2012. We used the Vegetation Photosynthesis Model (VPM, Xiao et al., 2006), MODIS images and NCEP/NARR climate data to estimate GPP from 2009-2014, and evaluated the VPM-predicted GPP with the estimated GPP from the CO2 eddy flux tower sites (24 sites). We analyze the correlation between the anomalies of the continental GPP and the anomalies of temperature and precipitation. The results show a substantial, negative GPP anomaly in 2009, in addition to the positive GPP anomaly in 2012, which was already reported in a previous study (Wolf et al., 2016). We also found that GPP anomalies of different climate regions in four seasons are controlled by either temperature or precipitation. Our study shows the robustness of the VPM to simulate GPP under the condition of climate extremes, and highlights the need of investigating the impacts of cooling events on the terrestrial carbon cycle. Our finding also suggests that there is no uniform pattern for terrestrial ecosystems responding to climate extremes, and that climate extremes should be studied in a case-by-case, location-based approach.

Extreme value analysis in biometrics.

PubMed

Hüsler, Jürg

2009-04-01

We review some approaches of extreme value analysis in the context of biometrical applications. The classical extreme value analysis is based on iid random variables. Two different general methods are applied, which will be discussed together with biometrical examples. Different estimation, testing, goodness-of-fit procedures for applications are discussed. Furthermore, some non-classical situations are considered where the data are possibly dependent, where a non-stationary behavior is observed in the data or where the observations are not univariate. A few open problems are also stated.

Evaluation of Daily Extreme Precipitation Derived From Long-term Global Satellite Quantitative Precipitation Estimates (QPEs)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Nickl, E.; Ferraro, R. R.

2017-12-01

This study evaluates the ability of different satellite-based precipitation products to capture daily precipitation extremes over the entire globe. The satellite products considered are the datasets belonging to the Reference Environmental Data Records (REDRs) program (PERSIANN-CDR, GPCP, CMORPH, AMSU-A,B, Hydrologic bundle). Those products provide long-term global records of daily adjusted Quantitative Precipitation Estimates (QPEs) that range from 20-year (CMORPH-CDR) to 35-year (PERSIANN-CDR, GPCP) record of daily adjusted global precipitation. The AMSU-A,B, Hydro-bundle is an 11-year record of daily rain rate over land and ocean, snow cover and surface temperature over land, and sea ice concentration, cloud liquid water, and total precipitable water over ocean among others. The aim of this work is to evaluate the ability of the different satellite QPE products to capture daily precipitation extremes. This evaluation will also include comparison with in-situ data sets at the daily scale from the Global Historical Climatology Network (GHCN-Daily), the Global Precipitation Climatology Centre (GPCC) gridded full data daily product, and the US Climate Reference Network (USCRN). In addition, while the products mentioned above only provide QPEs, the AMSU-A,B hydro-bundle provides additional hydrological information (precipitable water, cloud liquid water, snow cover, sea ice concentration). We will also present an analysis of those additional variables available from global satellite measurements and their relevance and complementarity in the context of long-term hydrological and climate studies.

Financial market response to extreme events indicating climatic change

NASA Astrophysics Data System (ADS)

Anttila-Hughes, J. K.

2016-05-01

A variety of recent extreme climatic events are considered to be strong evidence that the climate is warming, but these incremental advances in certainty often seem ignored by non-scientists. I identify two unusual types of events that are considered to be evidence of climate change, announcements by NASA that the global annual average temperature has set a new record, and the sudden collapse of major polar ice shelves, and then conduct an event study to test whether news of these events changes investors' valuation of energy companies, a subset of firms whose future performance is closely tied to climate change. I find evidence that both classes of events have influenced energy stock prices since the 1990s, with record temperature announcements on average associated with negative returns and ice shelf collapses associated with positive returns. I identify a variety of plausible mechanisms that may be driving these differential responses, discuss implications for energy markets' views on long-term regulatory risk, and conclude that investors not only pay attention to scientifically significant climate events, but discriminate between signals carrying different information about the nature of climatic change.

Applications of Extreme Value Theory in Public Health.

PubMed

Thomas, Maud; Lemaitre, Magali; Wilson, Mark L; Viboud, Cécile; Yordanov, Youri; Wackernagel, Hans; Carrat, Fabrice

2016-01-01

We present how Extreme Value Theory (EVT) can be used in public health to predict future extreme events. We applied EVT to weekly rates of Pneumonia and Influenza (P&I) deaths over 1979-2011. We further explored the daily number of emergency department visits in a network of 37 hospitals over 2004-2014. Maxima of grouped consecutive observations were fitted to a generalized extreme value distribution. The distribution was used to estimate the probability of extreme values in specified time periods. An annual P&I death rate of 12 per 100,000 (the highest maximum observed) should be exceeded once over the next 30 years and each year, there should be a 3% risk that the P&I death rate will exceed this value. Over the past 10 years, the observed maximum increase in the daily number of visits from the same weekday between two consecutive weeks was 1133. We estimated at 0.37% the probability of exceeding a daily increase of 1000 on each month. The EVT method can be applied to various topics in epidemiology thus contributing to public health planning for extreme events.

Inaccurate Estimation of Disparities Due to Mischievous Responders: Several Suggestions to Assess Conclusions

ERIC Educational Resources Information Center

Robinson-Cimpian, Joseph P.

2014-01-01

This article introduces novel sensitivity-analysis procedures for investigating and reducing the bias that mischievous responders (i.e., youths who provide extreme, and potentially untruthful, responses to multiple questions) often introduce in adolescent disparity estimates based on data from self-administered questionnaires (SAQs). Mischievous…

PROBABILITIES OF TEMPERATURE EXTREMES IN THE U.S.

EPA Science Inventory

The model Temperature Extremes Version 1.0 provides the capability to estimate the probability, for 332 locations in the 50 U.S. states, that an extreme temperature will occur for one or more consecutive days and/or for any number of days in a given month or season, based on stat...

Extreme Response Style in Recurrent and Chronically Depressed Patients: Change with Antidepressant Administration and Stability during Continuation Treatment

ERIC Educational Resources Information Center

Peterson, Timothy J.; Feldman, Greg; Harley, Rebecca; Fresco, David M.; Graves, Lesley; Holmes, Avram; Bogdan, Ryan; Papakostas, George I.; Bohn, Laurie; Lury, R. Alana; Fava, Maurizio; Segal, Zindel V.

2007-01-01

The authors examined extreme response style in recurrently and chronically depressed patients, assessing its role in therapeutic outcome. During the acute phase, outpatients with major depressive disorder (N = 384) were treated with fluoxetine for 8 weeks. Remitted patients (n = 132) entered a continuation phase during which their fluoxetine dose…

Response of ice caves to weather extremes in the southeastern Alps, Europe

NASA Astrophysics Data System (ADS)

Colucci, R. R.; Fontana, D.; Forte, E.; Potleca, M.; Guglielmin, M.

2016-05-01

High altitude karstic environments often preserve permanent ice deposits within caves, representing the lesser-known portion of the cryosphere. Despite being not so widespread and easily reachable as mountain glaciers and ice caps, ice caves preserve much information about past environmental changes and climatic evolution. We selected 1111 ice caves from the existing cave inventory, predominantly but not exclusively located in the periglacial domain where permafrost is not dominant (i.e., with mean annual air temperature < 3 °C but not in a permafrost environment). The influence of climate and topography on ice cave distribution is also investigated. In order to assess the thickness and the inner structure of the deposits, we selected two exemplary ice caves in the Canin massif (Julian Alps) performing several multifrequency GPR surveys. A strong influence of global and local climate change in the evolution of the ice deposits has been particularly highlighted in the dynamic ice cave type, especially in regard to the role of weather extremes. The natural response of ice caves to a warming climate could lead to a fast reduction of such ice masses. The increased occurrence of weather extremes, especially warmer and more intense precipitation caused by higher mean 0 °C-isotherms, could in fact be crucial in the future mass balance evolution of such permanent ice deposits.

Method for Estimating Patronage of Demand Responsive Transportation Systems

DOT National Transportation Integrated Search

1977-12-01

This study has developed a method for estimating patronage of demand responsive transportation (DRT) systems. This procedure requires as inputs a description of the intended service area, current work trip patterns, characteristics of the served popu...

Variation in vulnerability to extreme-temperature-related mortality in Japan: A 40-year time-series analysis.

PubMed

Onozuka, Daisuke; Hagihara, Akihito

2015-07-01

Although the impact of extreme heat and cold on mortality has been documented in recent years, few studies have investigated whether variation in susceptibility to extreme temperatures has changed in Japan. We used data on daily total mortality and mean temperatures in Fukuoka, Japan, for 1973-2012. We used time-series analysis to assess the effects of extreme hot and low temperatures on all-cause mortality, stratified by decade, gender, and age, adjusting for time trends. We used a multivariate meta-analysis with a distributed lag non-linear model to estimate pooled non-linear lag-response relationships associated with extreme temperatures on mortality. The relative risk of mortality increased during heat extremes in all decades, with a declining trend over time. The mortality risk was higher during cold extremes for the entire study period, with a dispersed pattern across decades. Meta-analysis showed that both heat and cold extremes increased the risk of mortality. Cold effects were delayed and lasted for several days, whereas heat effects appeared quickly and did not last long. Our study provides quantitative evidence that extreme heat and low temperatures were significantly and non-linearly associated with the increased risk of mortality with substantial variation. Our results suggest that timely preventative measures are important for extreme high temperatures, whereas several days' protection should be provided for extreme low temperatures. Copyright © 2015 Elsevier Inc. All rights reserved.

Climate Change Extreme Events: Meeting the Information Needs of Water Resource Managers

NASA Astrophysics Data System (ADS)

Quay, R.; Garfin, G. M.; Dominguez, F.; Hirschboeck, K. K.; Woodhouse, C. A.; Guido, Z.; White, D. D.

2013-12-01

Information about climate has long been used by water managers to develop short term and long term plans and strategies for regional and local water resources. Inherent within longer term forecasts is an element of uncertainty, which is particularly evident in Global Climate model results for precipitation. For example in the southwest estimates in the flow of the Colorado River based on GCM results indicate changes from 120% or current flow to 60%. Many water resource managers are now using global climate model down scaled estimates results as indications of potential climate change as part of that planning. They are addressing the uncertainty within these estimates by using an anticipatory planning approach looking at a range of possible futures. One aspect of climate that is important for such planning are estimates of future extreme storm (short term) and drought (long term) events. However, the climate science of future possible changes in extreme events is less mature than general climate change science. At a recent workshop among climate scientists and water managers in the southwest, it was concluded the science of climate change extreme events is at least a decade away from being robust enough to be useful for water managers in their water resource management activities. However, it was proposed that there are existing estimates and records of past flooding and drought events that could be combined with general climate change science to create possible future events. These derived events could be of sufficient detail to be used by water resource managers until such time that the science of extreme events is able to provide more detailed estimates. Based on the results of this workshop and other work being done by the Decision Center for a Desert City at Arizona State University and the Climate Assessment for the Southwest center at University of Arizona., this article will 1) review what are the extreme event data needs of Water Resource Managers in the

Mathematical modeling improves EC50 estimations from classical dose-response curves.

PubMed

Nyman, Elin; Lindgren, Isa; Lövfors, William; Lundengård, Karin; Cervin, Ida; Sjöström, Theresia Arbring; Altimiras, Jordi; Cedersund, Gunnar

2015-03-01

The β-adrenergic response is impaired in failing hearts. When studying β-adrenergic function in vitro, the half-maximal effective concentration (EC50 ) is an important measure of ligand response. We previously measured the in vitro contraction force response of chicken heart tissue to increasing concentrations of adrenaline, and observed a decreasing response at high concentrations. The classical interpretation of such data is to assume a maximal response before the decrease, and to fit a sigmoid curve to the remaining data to determine EC50 . Instead, we have applied a mathematical modeling approach to interpret the full dose-response curve in a new way. The developed model predicts a non-steady-state caused by a short resting time between increased concentrations of agonist, which affect the dose-response characterization. Therefore, an improved estimate of EC50 may be calculated using steady-state simulations of the model. The model-based estimation of EC50 is further refined using additional time-resolved data to decrease the uncertainty of the prediction. The resulting model-based EC50 (180-525 nm) is higher than the classically interpreted EC50 (46-191 nm). Mathematical modeling thus makes it possible to re-interpret previously obtained datasets, and to make accurate estimates of EC50 even when steady-state measurements are not experimentally feasible. The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database, and may be accessed at http://jjj.bio.vu.nl/database/nyman. © 2015 FEBS.

Active muscle response contributes to increased injury risk of lower extremity in occupant-knee airbag interaction.

PubMed

Nie, Bingbing; Sathyanarayan, Deepak; Ye, Xin; Crandall, Jeff R; Panzer, Matthew B

2018-02-28

Recent field data analysis has demonstrated that knee airbags (KABs) can reduce occupant femur and pelvis injuries but may be insufficient to decrease leg injuries in motor vehicle crashes. An enhanced understanding of the associated injury mechanisms requires accurate assessment of physiological-based occupant parameters, some of which are difficult or impossible to obtain from experiments. This study sought to explore how active muscle response can influence the injury risk of lower extremities during KAB deployment using computational biomechanical analysis. A full-factorial matrix, consisting of 48 finite element simulations of a 50th percentile occupant human model in a simplified vehicle interior, was designed. The matrix included 32 new cases in combination with 16 previously reported cases. The following influencing factors were taken into account: muscle activation, KAB use, KAB design, pre-impact seating position, and crash mode. Responses of 32 lower extremity muscles during emergency braking were replicated using one-dimensional elements of a Hill-type constitutive model, with the activation level determined from inverse dynamics and validated by existing volunteer tests. Dynamics of unfolding and inflating of the KABs were represented using the state-of-the-art corpuscular particle method. Abbreviated Injury Scale (AIS) 2+ injury risks of the knee-thigh-hip (KTH) complex and the tibia were assessed using axial force and resultant bending moments. With all simulation cases being taken together, a general linear model was used to assess factor significance (P <.05). As estimated by the regression model across all simulation cases, use of KABs significantly reduced axial femur forces by 4.74 ± 0.43 kN and AIS 2+ injury risk of KTH by 47 ± 6% (P <.05) but did not provide substantial change to injury risk of leg fractures. Muscle activation significantly increased axial force and bending moment of the femur (3.87 ± 0.38 kN and 64.3 ± 5.9 Nm), the

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

PubMed

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

Response of vegetation NDVI to climatic extremes in the arid region of Central Asia: a case study in Xinjiang, China

NASA Astrophysics Data System (ADS)

Yao, Junqiang; Chen, Yaning; Zhao, Yong; Mao, Weiyi; Xu, Xinbing; Liu, Yang; Yang, Qing

2018-02-01

Observed data showed the climatic transition from warm-dry to warm-wet in Xinjiang during the past 30 years and will probably affect vegetation dynamics. Here, we analyze the interannual change of vegetation index based on the satellite-derived normalized difference vegetation index (NDVI) with temperature and precipitation extreme over the Xinjiang, using the 8-km NDVI third-generation (NDVI3g) from the Global Inventory Modelling and Mapping Studies (GIMMS) from 1982 to 2010. Few previous studies analyzed the link between climate extremes and vegetation response. From the satellite-based results, annual NDVI significantly increased in the first two decades (1981-1998) and then decreased after 1998. We show that the NDVI decrease over the past decade may conjointly be triggered by the increases of temperature and precipitation extremes. The correlation analyses demonstrated that the trends of NDVI was close to the trend of extreme precipitation; that is, consecutive dry days (CDD) and torrential rainfall days (R24) positively correlated with NDVI during 1998-2010. For the temperature extreme, while the decreases of NDVI correlate positively with warmer mean minimum temperature ( Tnav), it correlates negatively with the number of warmest night days ( Rwn). The results suggest that the climatic extremes have possible negative effects on the ecosystem.

A comparison of observed extreme water levels at the German Bight elaborated through an extreme value analysis (EVA) with extremes derived from a regionally coupled ocean-atmospheric climate model (MPI-OM)

NASA Astrophysics Data System (ADS)

Möller, Jens; Heinrich, Hartmut

2017-04-01

As a consequence of climate change atmospheric and oceanographic extremes and their potential impacts on coastal regions are of growing concern for governmental authorities responsible for the transportation infrastructure. Highest risks for shipping as well as for rail and road traffic originate from combined effects of extremes of storm surges and heavy rainfall which sometimes lead to insufficient dewatering of inland waterways. The German Ministry of Transport and digital Infrastructure therefore has tasked its Network of Experts to investigate the possible evolutions of extreme threats for low lands and especially for Kiel Canal, which is an important shortcut for shipping between the North and Baltic Seas. In this study we present results of a comparison of an Extreme Value Analysis (EVA) carried out on gauge observations and values derived from a coupled Regional Ocean-Atmosphere Climate Model (MPI-OM). High water levels at the coasts of the North and Baltic Seas are one of the most important hazards which increase the risk of flooding of the low-lying land and prevents such areas from an adequate dewatering. In this study changes in the intensity (magnitude of the extremes) and duration of extreme water levels (above a selected threshold) are investigated for several gauge stations with data partly reaching back to 1843. Different methods are used for the extreme value statistics, (1) a stationary general Pareto distribution (GPD) model as well as (2) an instationary statistical model for better reproduction of the impact of climate change. Most gauge stations show an increase of the mean water level of about 1-2 mm/year, with a stronger increase of the highest water levels and a decrease (or lower increase) of the lowest water levels. Also, the duration of possible dewatering time intervals for the Kiel-Canal was analysed. The results for the historical gauge station observations are compared to the statistics of modelled water levels from the coupled

Changes in the probability of co-occurring extreme climate events

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2017-12-01

Extreme climate events such as floods, droughts, heatwaves, and severe storms exert acute stresses on natural and human systems. When multiple extreme events co-occur, either in space or time, the impacts can be substantially compounded. A diverse set of human interests - including supply chains, agricultural commodities markets, reinsurance, and deployment of humanitarian aid - have historically relied on the rarity of extreme events to provide a geographic hedge against the compounded impacts of co-occuring extremes. However, changes in the frequency of extreme events in recent decades imply that the probability of co-occuring extremes is also changing, and is likely to continue to change in the future in response to additional global warming. This presentation will review the evidence for historical changes in extreme climate events and the response of extreme events to continued global warming, and will provide some perspective on methods for quantifying changes in the probability of co-occurring extremes in the past and future.

Biological Extreme Events - Past, Present, and Future

NASA Astrophysics Data System (ADS)

Gutschick, V. P.

2010-12-01

Biological extreme events span wide ranges temporally and spatially and in type - population dieoffs, extinctions, ecological reorganizations, changes in biogeochemical fluxes, and more. Driving variables consist in meteorology, tectonics, orbital changes, anthropogenic changes (land-use change, species introductions, reactive N injection into the biosphere), and evolution (esp. of diseases). However, the mapping of extremes in the drivers onto biological extremes as organismal responses is complex, as laid out originally in the theoretical framework of Gutschick and BassiriRad (New Phytologist [2003] 100:21-42). Responses are nonlinear and dependent on (mostly unknown and) complex temporal sequences - often of multiple environmental variables. The responses are species- and genotype specific. I review extreme events over from past to present over wide temporal scales, while noting that they are not wholly informative of responses to the current and near-future drivers for at least two reasons: 1) the current combination of numerous environmental extremes - changes in CO2, temperature, precipitation, reactive N, land fragmentation, O3, etc. -is unprecedented in scope, and 2) adaptive genetic variation for organismal responses is constrained by poorly-characterized genetic structures (in organisms and populations) and by loss of genetic variation by genetic drift over long periods. We may expect radical reorganizations of ecosystem and biogeochemical functions. These changes include many ecosystem services in flood control, crop pollination and insect/disease control, C-water-mineral cycling, and more, as well as direct effects on human health. Predictions of such changes will necessarily be very weak in the critical next few decades, given the great deal of observation, experimentation, and theory construction that will be necessary, on both organisms and drivers. To make the research efforts most effective will require extensive, insightful planning, beginning

A general theoretical framework for interpreting patient-reported outcomes estimated from ordinally scaled item responses.

PubMed

Massof, Robert W

2014-10-01

A simple theoretical framework explains patient responses to items in rating scale questionnaires. Fixed latent variables position each patient and each item on the same linear scale. Item responses are governed by a set of fixed category thresholds, one for each ordinal response category. A patient's item responses are magnitude estimates of the difference between the patient variable and the patient's estimate of the item variable, relative to his/her personally defined response category thresholds. Differences between patients in their personal estimates of the item variable and in their personal choices of category thresholds are represented by random variables added to the corresponding fixed variables. Effects of intervention correspond to changes in the patient variable, the patient's response bias, and/or latent item variables for a subset of items. Intervention effects on patients' item responses were simulated by assuming the random variables are normally distributed with a constant scalar covariance matrix. Rasch analysis was used to estimate latent variables from the simulated responses. The simulations demonstrate that changes in the patient variable and changes in response bias produce indistinguishable effects on item responses and manifest as changes only in the estimated patient variable. Changes in a subset of item variables manifest as intervention-specific differential item functioning and as changes in the estimated person variable that equals the average of changes in the item variables. Simulations demonstrate that intervention-specific differential item functioning produces inefficiencies and inaccuracies in computer adaptive testing. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Soil response to long-term projections of extreme temperature and precipitation in the southern La Plata Basin

NASA Astrophysics Data System (ADS)

Pántano, Vanesa C.; Penalba, Olga C.

2017-12-01

Projected changes were estimated considering the main variables which take part in soil-atmosphere interaction. The analysis was focused on the potential impact of these changes on soil hydric condition under extreme precipitation and evapotranspiration, using the combination of Global Climate Models (GCMs) and observational data. The region of study is the southern La Plata Basin that covers part of Argentine territory, where rainfed agriculture production is one of the most important economic activities. Monthly precipitation and maximum and minimum temperatures were used from high quality-controlled observed data from 46 meteorological stations and the ensemble of seven CMIP5 GCMs in two periods: 1970-2005 and 2065-2100. Projected changes in monthly effective temperature and precipitation were analysed. These changes were combined with observed series for each probabilistic interval. The result was used as input variables for the water balance model in order to obtain consequent soil hydric condition (deficit or excess). Effective temperature and precipitation are expected to increase according to the projections of GCMs, with few exceptions. The analysis revealed increase (decrease) in the prevalence of evapotranspiration over precipitation, during spring (winter). Projections for autumn months show precipitation higher than potential evapotranspiration more frequently. Under dry extremes, the analysis revealed higher projected deficit conditions, impacting on crop development. On the other hand, under wet extremes, excess would reach higher values only in particular months. During December, projected increase in temperatures reduces the impact of extreme high precipitation but favours deficit conditions, affecting flower-fructification stage of summer crops.

Observation-based Estimate of Climate Sensitivity with a Scaling Climate Response Function

NASA Astrophysics Data System (ADS)

Hébert, Raphael; Lovejoy, Shaun

2016-04-01

To properly adress the anthropogenic impacts upon the earth system, an estimate of the climate sensitivity to radiative forcing is essential. Observation-based estimates of climate sensitivity are often limited by their ability to take into account the slower response of the climate system imparted mainly by the large thermal inertia of oceans, they are nevertheless essential to provide an alternative to estimates from global circulation models and increase our confidence in estimates of climate sensitivity by the multiplicity of approaches. It is straightforward to calculate the Effective Climate Sensitivity(EffCS) as the ratio of temperature change to the change in radiative forcing; the result is almost identical to the Transient Climate Response(TCR), but it underestimates the Equilibrium Climate Sensitivity(ECS). A study of global mean temperature is thus presented assuming a Scaling Climate Response Function to deterministic radiative forcing. This general form is justified as there exists a scaling symmetry respected by the dynamics, and boundary conditions, over a wide range of scales and it allows for long-range dependencies while retaining only 3 parameter which are estimated empirically. The range of memory is modulated by the scaling exponent H. We can calculate, analytically, a one-to-one relation between the scaling exponent H and the ratio of EffCS to TCR and EffCS to ECS. The scaling exponent of the power law is estimated by a regression of temperature as a function of forcing. We consider for the analysis 4 different datasets of historical global mean temperature and 100 scenario runs of the Coupled Model Intercomparison Project Phase 5 distributed among the 4 Representative Concentration Pathways(RCP) scenarios. We find that the error function for the estimate on historical temperature is very wide and thus, many scaling exponent can be used without meaningful changes in the fit residuals of historical temperatures; their response in the year 2100

Slice sampling technique in Bayesian extreme of gold price modelling

NASA Astrophysics Data System (ADS)

Rostami, Mohammad; Adam, Mohd Bakri; Ibrahim, Noor Akma; Yahya, Mohamed Hisham

2013-09-01

In this paper, a simulation study of Bayesian extreme values by using Markov Chain Monte Carlo via slice sampling algorithm is implemented. We compared the accuracy of slice sampling with other methods for a Gumbel model. This study revealed that slice sampling algorithm offers more accurate and closer estimates with less RMSE than other methods . Finally we successfully employed this procedure to estimate the parameters of Malaysia extreme gold price from 2000 to 2011.

[An intractable gastric cancer showing an extremely effective response to immunochemotherapy].

PubMed

Takashima, S; Komaki, H; Yokota, H; Kiriyama, M; Kinami, Y

1988-07-01

Reported herein is the case of a terminal patient with advanced gastric cancer who was shown an extremely effective response to immunochemotherapy. The patient, a 62-year-old female, was determined as having a gastric cancer, Borr. type 2, originating in the pyloric antrum. The tumor was found to be H3P3S2N2 (stage IV), and its histology revealed a mucus-producing papillary adeno-carcinoma, ss gamma, n(+), ly2, and V1. Thus the patient underwent a distal gastrectomy, and was given an operative administration of MMC, followed by postoperative immunochemotherapy with FT 207 and OK 432. Consequently, no ascites were noticed throughout the recuperative course, and repeated CT scannings of the hepatic metastatic lesions, revealed a remarkable regression. Two years after this operation, she resumed normal daily life. Further, her preoperatively elevated tumor markers have returned to normal.

Extreme-event geoelectric hazard maps: Chapter 9

USGS Publications Warehouse

Love, Jeffrey J.; Bedrosian, Paul A.

2018-01-01

Maps of geoelectric amplitude covering about half the continental United States are presented that will be exceeded, on average, once per century in response to an extreme-intensity geomagnetic disturbance. These maps are constructed using an empirical parameterization of induction: convolving latitude-dependent statistical maps of extreme-value geomagnetic disturbances, obtained from decades of 1-minute magnetic observatory data, with local estimates of Earth-surface impedance obtained at discrete geographic sites from magnetotelluric surveys. Geoelectric amplitudes are estimated for geomagnetic waveforms having a 240-s (and 1200-s) sinusoidal period and amplitudes over 10 min (1 h) that exceed a once-per-century threshold. As a result of the combination of geographic differences in geomagnetic variation and Earth-surface impedance, once-per-century geoelectric amplitudes span more than two orders of magnitude and are a highly granular function of location. Specifically for north-south 240-s induction, once-per-century geoelectric amplitudes across large parts of the United States have a median value of 0.34 V/km; for east-west variation, they have a median value of 0.23 V/km. In Northern Minnesota, amplitudes exceed 14.00 V/km for north-south geomagnetic variation (23.34 V/km for east-west variation), while just over 100 km away, amplitudes are only 0.08 V/km (0.02 V/km). At some sites in the northern-central United States, once-per-century geoelectric amplitudes exceed the 2 V/km realized in Québec during the March 1989 storm.

Effects of anthropogenic activity emerging as intensified extreme precipitation over China

NASA Astrophysics Data System (ADS)

Li, Huixin; Chen, Huopo; Wang, Huijun

2017-07-01

This study aims to provide an assessment of the effects of anthropogenic (ANT) forcings and other external factors on observed increases in extreme precipitation over China from 1961 to 2005. Extreme precipitation is represented by the annual maximum 1 day precipitation (RX1D) and the annual maximum 5 day consecutive precipitation (RX5D), and these variables are investigated using observations and simulations from the Coupled Model Intercomparison Project phase 5. The analyses mainly focus on the probability-based index (PI), which is derived from RX1D and RX5D by fitting generalized extreme value distributions. The results indicate that the simulations that include the ANT forcings provide the best representation of the spatial and temporal characteristics of extreme precipitation over China. We use the optimal fingerprint method to obtain the univariate and multivariate fingerprints of the responses to external forcings. The results show that only the ANT forcings are detectable at a 90% confidence level, both individually and when natural forcings are considered simultaneously. The impact of the forcing associated with greenhouse gases (GHGs) is also detectable in RX1D, but its effects cannot be separated from those of combinations of forcings that exclude the GHG forcings in the two-signal analyses. Besides, the estimated changes of PI, extreme precipitation, and events with a 20 year return period under nonstationary climate states are potentially attributable to ANT or GHG forcings, and the relationships between extreme precipitation and temperature from ANT forcings show agreement with observations.

Upper-extremity and mobility subdomains from the Patient-Reported Outcomes Measurement Information System (PROMIS) adult physical functioning item bank.

PubMed

Hays, Ron D; Spritzer, Karen L; Amtmann, Dagmar; Lai, Jin-Shei; Dewitt, Esi Morgan; Rothrock, Nan; Dewalt, Darren A; Riley, William T; Fries, James F; Krishnan, Eswar

2013-11-01

To create upper-extremity and mobility subdomain scores from the Patient-Reported Outcomes Measurement Information System (PROMIS) physical functioning adult item bank. Expert reviews were used to identify upper-extremity and mobility items from the PROMIS item bank. Psychometric analyses were conducted to assess empirical support for scoring upper-extremity and mobility subdomains. Data were collected from the U.S. general population and multiple disease groups via self-administered surveys. The sample (N=21,773) included 21,133 English-speaking adults who participated in the PROMIS wave 1 data collection and 640 Spanish-speaking Latino adults recruited separately. Not applicable. We used English- and Spanish-language data and existing PROMIS item parameters for the physical functioning item bank to estimate upper-extremity and mobility scores. In addition, we fit graded response models to calibrate the upper-extremity items and mobility items separately, compare separate to combined calibrations, and produce subdomain scores. After eliminating items because of local dependency, 16 items remained to assess upper extremity and 17 items to assess mobility. The estimated correlation between upper extremity and mobility was .59 using existing PROMIS physical functioning item parameters (r=.60 using parameters calibrated separately for upper-extremity and mobility items). Upper-extremity and mobility subdomains shared about 35% of the variance in common, and produced comparable scores whether calibrated separately or together. The identification of the subset of items tapping these 2 aspects of physical functioning and scored using the existing PROMIS parameters provides the option of scoring these subdomains in addition to the overall physical functioning score. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Transcriptomes of the Extremely Thermoacidophilic Archaeon Metallosphaera sedula Exposed to Metal "Shock" Reveal Generic and Specific Metal Responses.

PubMed

Wheaton, Garrett H; Mukherjee, Arpan; Kelly, Robert M

2016-08-01

The extremely thermoacidophilic archaeon Metallosphaera sedula mobilizes metals by novel membrane-associated oxidase clusters and, consequently, requires metal resistance strategies. This issue was examined by "shocking" M. sedula with representative metals (Co(2+), Cu(2+), Ni(2+), UO2 (2+), Zn(2+)) at inhibitory and subinhibitory levels. Collectively, one-quarter of the genome (554 open reading frames [ORFs]) responded to inhibitory levels, and two-thirds (354) of the ORFs were responsive to a single metal. Cu(2+) (259 ORFs, 106 Cu(2+)-specific ORFs) and Zn(2+) (262 ORFs, 131 Zn(2+)-specific ORFs) triggered the largest responses, followed by UO2 (2+) (187 ORFs, 91 UO2 (2+)-specific ORFs), Ni(2+) (93 ORFs, 25 Ni(2+)-specific ORFs), and Co(2+) (61 ORFs, 1 Co(2+)-specific ORF). While one-third of the metal-responsive ORFs are annotated as encoding hypothetical proteins, metal challenge also impacted ORFs responsible for identifiable processes related to the cell cycle, DNA repair, and oxidative stress. Surprisingly, there were only 30 ORFs that responded to at least four metals, and 10 of these responded to all five metals. This core transcriptome indicated induction of Fe-S cluster assembly (Msed_1656-Msed_1657), tungsten/molybdenum transport (Msed_1780-Msed_1781), and decreased central metabolism. Not surprisingly, a metal-translocating P-type ATPase (Msed_0490) associated with a copper resistance system (Cop) was upregulated in response to Cu(2+) (6-fold) but also in response to UO2 (2+) (4-fold) and Zn(2+) (9-fold). Cu(2+) challenge uniquely induced assimilatory sulfur metabolism for cysteine biosynthesis, suggesting a role for this amino acid in Cu(2+) resistance or issues in sulfur metabolism. The results indicate that M. sedula employs a range of physiological and biochemical responses to metal challenge, many of which are specific to a single metal and involve proteins with yet unassigned or definitive functions. The mechanisms by which extremely

Modeling Hydrological Extremes in the Anthropocene

NASA Astrophysics Data System (ADS)

Di Baldassarre, Giuliano; Martinez, Fabian; Kalantari, Zahra; Viglione, Alberto

2017-04-01

Hydrological studies have investigated human impacts on hydrological extremes, i.e. droughts and floods, while social studies have explored human responses and adaptation to them. Yet, there is still little understanding about the dynamics resulting from two-way feedbacks, i.e. both impacts and responses. Traditional risk assessment methods therefore fail to assess future dynamics, and thus risk reduction strategies built on these methods can lead to unintended consequences in the medium-long term. Here we review the dynamics resulting from the reciprocal links between society and hydrological extremes, and describe initial efforts to model floods and droughts in the Anthropocene. In particular, we first discuss the need for a novel approach to explicitly account for human interactions with both hydrological extremes, and then present a stylized model simulating the reciprocal effects between droughts, foods and reservoir operation rules. Unprecedented opportunities offered by the growing availability of global data and worldwide archives to uncover the mutual shaping of hydrological extremes and society across places and scales are also discussed.

Simulator study of young driver's instinctive response of lower extremity to a collision.

PubMed

Gao, Zhenhai; Li, Chuzhao; Hu, Hongyu; Zhao, Hui; Chen, Chaoyang; Yu, Huili

2016-05-18

A driver's instinctive response of the lower extremity in braking movement consists of two parts, including reaction time and braking reaction behavior. It is critical to consider these two components when conducting studies concerning driver's brake movement intention and injury analysis. The purposes of this study were to investigate the driver reaction time to an oncoming collision and muscle activation of lower extremity muscles at the collision moment. The ultimate goal is to provide data that aid in both the optimization of intervention time of an active safety system and the improvement of precise protection performance of a passive safety system. A simulated collision scene was constructed in a driving simulator, and 40 young volunteers (20 male and 20 female) were recruited for tests. Vehicle control parameters and electromyography characteristics of eight muscles of the lower extremity were recorded. The driver reaction time was divided into pre-motor time (PMT) and muscle activation time (MAT). Muscle activation level (ACOL) at the collision moment was calculated and analysed. PMT was shortest for the tibialis anterior (TA) muscle (243∼317 ms for male and 278∼438 ms for female). Average MAT of the TA ranged from 28-55 ms. ACOL was large (5∼31% for male and 5∼23% for female) at 50 km/h, but small (<12%) at 100 km/h. ACOL of the gluteus maximus was smallest (<3%) in the 25 and 100 km/h tests. ACOL of RF of men was significantly smaller than that of women at different speeds. Ankle dorsiflexion is firstly activated at the beginning of the emergency brake motion. Males showed stronger reaction ability than females, as suggested by male's shorter PMT. The detection of driver's brake intention is upwards of 55ms sooner after introducing the electromyography. Muscle activation of the lower extremity is an important factor for 50 km/h collision injury analysis. For higher speed collisions, this might not be a major factor. The activations of certain

Measurement and control of bias in patient reported outcomes using multidimensional item response theory.

PubMed

Dowling, N Maritza; Bolt, Daniel M; Deng, Sien; Li, Chenxi

2016-05-26

Patient-reported outcome (PRO) measures play a key role in the advancement of patient-centered care research. The accuracy of inferences, relevance of predictions, and the true nature of the associations made with PRO data depend on the validity of these measures. Errors inherent to self-report measures can seriously bias the estimation of constructs assessed by the scale. A well-documented disadvantage of self-report measures is their sensitivity to response style (RS) effects such as the respondent's tendency to select the extremes of a rating scale. Although the biasing effect of extreme responding on constructs measured by self-reported tools has been widely acknowledged and studied across disciplines, little attention has been given to the development and systematic application of methodologies to assess and control for this effect in PRO measures. We review the methodological approaches that have been proposed to study extreme RS effects (ERS). We applied a multidimensional item response theory model to simultaneously estimate and correct for the impact of ERS on trait estimation in a PRO instrument. Model estimates were used to study the biasing effects of ERS on sum scores for individuals with the same amount of the targeted trait but different levels of ERS. We evaluated the effect of joint estimation of multiple scales and ERS on trait estimates and demonstrated the biasing effects of ERS on these trait estimates when used as explanatory variables. A four-dimensional model accounting for ERS bias provided a better fit to the response data. Increasing levels of ERS showed bias in total scores as a function of trait estimates. The effect of ERS was greater when the pattern of extreme responding was the same across multiple scales modeled jointly. The estimated item category intercepts provided evidence of content independent category selection. Uncorrected trait estimates used as explanatory variables in prediction models showed downward bias. A

Phenological response of an Arizona dryland forest to short-term climatic extremes

USGS Publications Warehouse

Walker, Jessica; de Beurs, Kirsten; Wynne, Randolph

2015-01-01

Baseline information about dryland forest phenology is necessary to accurately anticipate future ecosystem shifts. The overarching goal of our study was to investigate the variability of vegetation phenology across a dryland forest landscape in response to climate alterations. We analyzed the influence of site characteristics and climatic conditions on the phenological patterns of an Arizona, USA, ponderosa pine (Pinus ponderosa) forest during a five-year period (2005 to 2009) that encompassed extreme wet and dry precipitation regimes. We assembled 80 synthetic Landsat images by applying the spatial and temporal adaptive reflectance fusion method (STARFM) to 500 m MODIS and 30 m Landsat-5 Thematic Mapper (TM) data. We tested relationships between site characteristics and the timing of peak Normalized Difference Vegetation Index (NDVI) to assess the effect of climatic stress on the green-up of individual pixels during or after the summer monsoon. Our results show that drought-induced stress led to a fragmented phenological response that was highly dependent on microsite parameters, as both the spatial autocorrelation of peak timing and the number of significant site variables increased during the drought year. Pixels at lower elevations and with higher proportions of herbaceous vegetation were more likely to exhibit dynamic responses to changes in precipitation conditions. Our study demonstrates the complexity of responses within dryland forest ecosystems and highlights the need for standardized monitoring of phenology trends in these areas. The spatial and temporal variability of phenological signals may provide a quantitative solution to the problem of how to evaluate dryland land surface trends across time.

Evidence of population resistance to extreme low flows in a fluvial-dependent fish species

USGS Publications Warehouse

Katz, Rachel A.; Freeman, Mary C.

2015-01-01

Extreme low streamflows are natural disturbances to aquatic populations. Species in naturally intermittent streams display adaptations that enhance persistence during extreme events; however, the fate of populations in perennial streams during unprecedented low-flow periods is not well-understood. Biota requiring swift-flowing habitats may be especially vulnerable to flow reductions. We estimated the abundance and local survival of a native fluvial-dependent fish species (Etheostoma inscriptum) across 5 years encompassing historic low flows in a sixth-order southeastern USA perennial river. Based on capturemark-recapture data, the study shoal may have acted as a refuge during severe drought, with increased young-of-the-year (YOY) recruitment and occasionally high adult immigration. Contrary to expectations, summer and autumn survival rates (30 days) were not strongly depressed during low-flow periods, despite 25%-80% reductions in monthly discharge. Instead, YOY survival increased with lower minimum discharge and in response to small rain events that increased low-flow variability. Age-1+ fish showed the opposite pattern, with survival decreasing in response to increasing low-flow variability. Results from this population dynamics study of a small fish in a perennial river suggest that fluvial-dependent species can be resistant to extreme flow reductions through enhanced YOY recruitment and high survival

Real-Time Frequency Response Estimation Using Joined-Wing SensorCraft Aeroelastic Wind-Tunnel Data

NASA Technical Reports Server (NTRS)

Grauer, Jared A; Heeg, Jennifer; Morelli, Eugene A

2012-01-01

A new method is presented for estimating frequency responses and their uncertainties from wind-tunnel data in real time. The method uses orthogonal phase-optimized multi- sine excitation inputs and a recursive Fourier transform with a least-squares estimator. The method was first demonstrated with an F-16 nonlinear flight simulation and results showed that accurate short period frequency responses were obtained within 10 seconds. The method was then applied to wind-tunnel data from a previous aeroelastic test of the Joined- Wing SensorCraft. Frequency responses describing bending strains from simultaneous control surface excitations were estimated in a time-efficient manner.

A comparison of two global datasets of extreme sea levels and resulting flood exposure

NASA Astrophysics Data System (ADS)

Muis, Sanne; Verlaan, Martin; Nicholls, Robert J.; Brown, Sally; Hinkel, Jochen; Lincke, Daniel; Vafeidis, Athanasios T.; Scussolini, Paolo; Winsemius, Hessel C.; Ward, Philip J.

2017-04-01

Estimating the current risk of coastal flooding requires adequate information on extreme sea levels. For over a decade, the only global data available was the DINAS-COAST Extreme Sea Levels (DCESL) dataset, which applies a static approximation to estimate extreme sea levels. Recently, a dynamically derived dataset was developed: the Global Tide and Surge Reanalysis (GTSR) dataset. Here, we compare the two datasets. The differences between DCESL and GTSR are generally larger than the confidence intervals of GTSR. Compared to observed extremes, DCESL generally overestimates extremes with a mean bias of 0.6 m. With a mean bias of -0.2 m GTSR generally underestimates extremes, particularly in the tropics. The Dynamic Interactive Vulnerability Assessment model is applied to calculate the present-day flood exposure in terms of the land area and the population below the 1 in 100-year sea levels. Global exposed population is 28% lower when based on GTSR instead of DCESL. Considering the limited data available at the time, DCESL provides a good estimate of the spatial variation in extremes around the world. However, GTSR allows for an improved assessment of the impacts of coastal floods, including confidence bounds. We further improve the assessment of coastal impacts by correcting for the conflicting vertical datum of sea-level extremes and land elevation, which has not been accounted for in previous global assessments. Converting the extreme sea levels to the same vertical reference used for the elevation data is shown to be a critical step resulting in 39-59% higher estimate of population exposure.

Two Approaches to Estimation of Classification Accuracy Rate under Item Response Theory

ERIC Educational Resources Information Center

Lathrop, Quinn N.; Cheng, Ying

2013-01-01

Within the framework of item response theory (IRT), there are two recent lines of work on the estimation of classification accuracy (CA) rate. One approach estimates CA when decisions are made based on total sum scores, the other based on latent trait estimates. The former is referred to as the Lee approach, and the latter, the Rudner approach,…

Extreme values and fat tails of multifractal fluctuations

NASA Astrophysics Data System (ADS)

Muzy, J. F.; Bacry, E.; Kozhemyak, A.

2006-06-01

In this paper we discuss the problem of the estimation of extreme event occurrence probability for data drawn from some multifractal process. We also study the heavy (power-law) tail behavior of probability density function associated with such data. We show that because of strong correlations, the standard extreme value approach is not valid and classical tail exponent estimators should be interpreted cautiously. Extreme statistics associated with multifractal random processes turn out to be characterized by non-self-averaging properties. Our considerations rely upon some analogy between random multiplicative cascades and the physics of disordered systems and also on recent mathematical results about the so-called multifractal formalism. Applied to financial time series, our findings allow us to propose an unified framework that accounts for the observed multiscaling properties of return fluctuations, the volatility clustering phenomenon and the observed “inverse cubic law” of the return pdf tails.

Evaluating the applicability of four recent satellite–gauge combined precipitation estimates for extreme precipitation and streamflow predictions over the upper Yellow river basin in China

USDA-ARS?s Scientific Manuscript database

This study aimed to statistically and hydrologically assess the performance of four latest and widely used satellite–gauge combined precipitation estimates (SGPEs), namely CRT, BLD, 3B42CDR, and 3B42 for the extreme precipitation and stream'ow scenarios over the upper Yellow river basin (UYRB) in ch...

How extreme are extremes?

NASA Astrophysics Data System (ADS)

Cucchi, Marco; Petitta, Marcello; Calmanti, Sandro

2016-04-01

High temperatures have an impact on the energy balance of any living organism and on the operational capabilities of critical infrastructures. Heat-wave indicators have been mainly developed with the aim of capturing the potential impacts on specific sectors (agriculture, health, wildfires, transport, power generation and distribution). However, the ability to capture the occurrence of extreme temperature events is an essential property of a multi-hazard extreme climate indicator. Aim of this study is to develop a standardized heat-wave indicator, that can be combined with other indices in order to describe multiple hazards in a single indicator. The proposed approach can be used in order to have a quantified indicator of the strenght of a certain extreme. As a matter of fact, extremes are usually distributed in exponential or exponential-exponential functions and it is difficult to quickly asses how strong was an extreme events considering only its magnitude. The proposed approach simplify the quantitative and qualitative communication of extreme magnitude

A general model for estimating lower extremity inertial properties of individuals with transtibial amputation.

PubMed

Ferris, Abbie E; Smith, Jeremy D; Heise, Gary D; Hinrichs, Richard N; Martin, Philip E

2017-03-21

Lower extremity joint moment magnitudes during swing are dependent on the inertial properties of the prosthesis and residual limb of individuals with transtibial amputation (TTA). Often, intact limb inertial properties (INTACT) are used for prosthetic limb values in an inverse dynamics model even though these values overestimate the amputated limb's inertial properties. The purpose of this study was to use subject-specific (SPECIFIC) measures of prosthesis inertial properties to generate a general model (GENERAL) for estimating TTA prosthesis inertial properties. Subject-specific mass, center of mass, and moment of inertia were determined for the shank and foot segments of the prosthesis (n=11) using an oscillation technique and reaction board. The GENERAL model was derived from the means of the SPECIFIC model. Mass and segment lengths are required GENERAL model inputs. Comparisons of segment inertial properties and joint moments during walking were made using three inertial models (unique sample; n=9): (1) SPECIFIC, (2) GENERAL, and (3) INTACT. Prosthetic shank inertial properties were significantly smaller with the SPECIFIC and GENERAL model than the INTACT model, but the SPECIFIC and GENERAL model did not statistically differ. Peak knee and hip joint moments during swing were significantly smaller for the SPECIFIC and GENERAL model compared with the INTACT model and were not significantly different between SPECIFIC and GENERAL models. When subject-specific measures are unavailable, using the GENERAL model produces a better estimate of prosthetic side inertial properties resulting in more accurate joint moment measurements for individuals with TTA than the INTACT model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stationary variational estimates for the effective response and field fluctuations in nonlinear composites

NASA Astrophysics Data System (ADS)

Ponte Castañeda, Pedro

2016-11-01

This paper presents a variational method for estimating the effective constitutive response of composite materials with nonlinear constitutive behavior. The method is based on a stationary variational principle for the macroscopic potential in terms of the corresponding potential of a linear comparison composite (LCC) whose properties are the trial fields in the variational principle. When used in combination with estimates for the LCC that are exact to second order in the heterogeneity contrast, the resulting estimates for the nonlinear composite are also guaranteed to be exact to second-order in the contrast. In addition, the new method allows full optimization with respect to the properties of the LCC, leading to estimates that are fully stationary and exhibit no duality gaps. As a result, the effective response and field statistics of the nonlinear composite can be estimated directly from the appropriately optimized linear comparison composite. By way of illustration, the method is applied to a porous, isotropic, power-law material, and the results are found to compare favorably with earlier bounds and estimates. However, the basic ideas of the method are expected to work for broad classes of composites materials, whose effective response can be given appropriate variational representations, including more general elasto-plastic and soft hyperelastic composites and polycrystals.

The use of historical information for regional frequency analysis of extreme skew surge

NASA Astrophysics Data System (ADS)

Frau, Roberto; Andreewsky, Marc; Bernardara, Pietro

2018-03-01

The design of effective coastal protections requires an adequate estimation of the annual occurrence probability of rare events associated with a return period up to 103 years. Regional frequency analysis (RFA) has been proven to be an applicable way to estimate extreme events by sorting regional data into large and spatially distributed datasets. Nowadays, historical data are available to provide new insight on past event estimation. The utilisation of historical information would increase the precision and the reliability of regional extreme's quantile estimation. However, historical data are from significant extreme events that are not recorded by tide gauge. They usually look like isolated data and they are different from continuous data from systematic measurements of tide gauges. This makes the definition of the duration of our observations period complicated. However, the duration of the observation period is crucial for the frequency estimation of extreme occurrences. For this reason, we introduced here the concept of credible duration. The proposed RFA method (hereinafter referenced as FAB, from the name of the authors) allows the use of historical data together with systematic data, which is a result of the use of the credible duration concept.

Evaluation of the National Weather Service Extreme Cold Warning Experiment in North Dakota

PubMed Central

Chiu, Cindy H.; Vagi, Sara J.; Wolkin, Amy F.; Martin, John Paul; Noe, Rebecca S.

2016-01-01

Dangerously cold weather threatens life and property. During periods of extreme cold due to wind chill, the National Weather Service (NWS) issues wind chill warnings to prompt the public to take action to mitigate risks. Wind chill warnings are based on ambient temperatures and wind speeds. Since 2010, NWS has piloted a new extreme cold warning issued for cold temperatures in wind and nonwind conditions. The North Dakota Department of Health, NWS, and the Centers for Disease Control and Prevention collaborated in conducting household surveys in Burleigh County, North Dakota, to evaluate this new warning. The objectives of the evaluation were to assess whether residents heard the new warning and to determine if protective behaviors were prompted by the warning. This was a cross-sectional survey design using the Community Assessment for Public Health Emergency Response (CASPER) methodology to select a statistically representative sample of households from Burleigh County. From 10 to 11 April 2012, 188 door-to-door household interviews were completed. The CASPER methodology uses probability sampling with weighted analysis to estimate the number and percentage of households with a specific response within Burleigh County. The majority of households reported having heard both the extreme cold and wind chill warnings, and both warnings prompted protective behaviors. These results suggest this community heard the new warning and took protective actions after hearing the warning. PMID:27239260

Outcomes for extremely premature infants.

PubMed

Glass, Hannah C; Costarino, Andrew T; Stayer, Stephen A; Brett, Claire M; Cladis, Franklyn; Davis, Peter J

2015-06-01

Premature birth is a significant cause of infant and child morbidity and mortality. In the United States, the premature birth rate, which had steadily increased during the 1990s and early 2000s, has decreased annually for 7 years and is now approximately 11.39%. Human viability, defined as gestational age at which the chance of survival is 50%, is currently approximately 23 to 24 weeks in developed countries. Infant girls, on average, have better outcomes than infant boys. A relatively uncomplicated course in the intensive care nursery for an extremely premature infant results in a discharge date close to the prenatal estimated date of confinement. Despite technological advances and efforts of child health experts during the last generation, the extremely premature infant (less than 28 weeks gestation) and extremely low birth weight infant (<1000 g) remain at high risk for death and disability with 30% to 50% mortality and, in survivors, at least 20% to 50% risk of morbidity. The introduction of continuous positive airway pressure, mechanical ventilation, and exogenous surfactant increased survival and spurred the development of neonatal intensive care in the 1970s through the early 1990s. Routine administration of antenatal steroids during premature labor improved neonatal mortality and morbidity in the late 1990s. The recognition that chronic postnatal administration of steroids to infants should be avoided may have improved outcomes in the early 2000s. Evidence from recent trials attempting to define the appropriate target for oxygen saturation in preterm infants suggests arterial oxygen saturation between 91% and 95% (compared with 85%-89%) avoids excess mortality; however, final analyses of data from these trials have not been published, so definitive recommendations are still pending. The development of neonatal neurocritical intensive care units may improve neurocognitive outcomes in this high-risk group. Long-term follow-up to detect and address

Long-term records reveal decoupling of nitrogen and phosphorus cycles in a large, urban lake in response to an extreme rainfall event

NASA Astrophysics Data System (ADS)

Corman, J. R.; Loken, L. C.; Oliver, S. K.; Collins, S.; Butitta, V.; Stanley, E. H.

2017-12-01

Extreme events can play powerful roles in shifting ecosystem processes. In lakes, heavy rainfall can transport large amounts of particulates and dissolved nutrients into the water column and, potentially, alter biogeochemical cycling. However, the impacts of extreme rainfall events are often difficult to study due to a lack of long-term records. In this paper, we combine daily discharge records with long-term lake water quality information collected by the North Temperate Lakes Long-Term Ecological Research (NTL LTER) site to investigate the impacts of extreme events on nutrient cycling in lakes. We focus on Lake Mendota, an urban lake within the Yahara River Watershed in Madison, Wisconsin, USA, where nutrient data are available at least seasonally from 1995 - present. In June 2008, precipitation amounts in the Yahara watershed were 400% above normal values, triggering the largest discharge event on record for the 40 years of monitoring at the streamgage station; hence, we are able to compare water quality records before and after this event as a case study of how extreme rain events couple or decouple lake nutrient cycling. Following the extreme event, the lake-wide mass of nitrogen and phosphorus increased in the summer of 2008 by 35% and 21%, respectively, shifting lake stoichiometry by increasing N:P ratios (Figure 1). Nitrogen concentrations remained elevated longer than phosphorus, suggesting (1) that nitrogen inputs into the lake were sustained longer than phosphorus (i.e., a "smear" versus "pulse" loading of nitrogen versus phosphorus, respectively, in response to the extreme event) and/or (2) that in-lake biogeochemical processing was more efficient at removing phosphorus compared to nitrogen. While groundwater loading data are currently unavailable to test the former hypothesis, preliminary data from surficial nitrogen and phosphorus loading to Lake Mendota (available for 2011 - 2013) suggest that nitrogen removal efficiency is less than phosphorus

Measurement Properties of the Lower Extremity Functional Scale: A Systematic Review.

PubMed

Mehta, Saurabh P; Fulton, Allison; Quach, Cedric; Thistle, Megan; Toledo, Cesar; Evans, Neil A

2016-03-01

Systematic review of measurement properties. Many primary studies have examined the measurement properties, such as reliability, validity, and sensitivity to change, of the Lower Extremity Functional Scale (LEFS) in different clinical populations. A systematic review summarizing these properties for the LEFS may provide an important resource. To locate and synthesize evidence on the measurement properties of the LEFS and to discuss the clinical implications of the evidence. A literature search was conducted in 4 databases (PubMed, MEDLINE, Embase, and CINAHL), using predefined search terms. Two reviewers performed a critical appraisal of the included studies using a standardized assessment form. A total of 27 studies were included in the review, of which 18 achieved a very good to excellent methodological quality level. The LEFS scores demonstrated excellent test-retest reliability (intraclass correlation coefficients ranging between 0.85 and 0.99) and demonstrated the expected relationships with measures assessing similar constructs (Pearson correlation coefficient values of greater than 0.7). The responsiveness of the LEFS scores was excellent, as suggested by consistently high effect sizes (greater than 0.8) in patients with different lower extremity conditions. Minimal detectable change at the 90% confidence level (MDC90) for the LEFS scores varied between 8.1 and 15.3 across different reassessment intervals in a wide range of patient populations. The pooled estimate of the MDC90 was 6 points and the minimal clinically important difference was 9 points in patients with lower extremity musculoskeletal conditions, which are indicative of true change and clinically meaningful change, respectively. The results of this review support the reliability, validity, and responsiveness of the LEFS scores for assessing functional impairment in a wide array of patient groups with lower extremity musculoskeletal conditions.

Error analysis and new dual-cosine window for estimating the sensor frequency response function from the step response data

NASA Astrophysics Data System (ADS)

Yang, Shuang-Long; Liang, Li-Ping; Liu, Hou-De; Xu, Ke-Jun

2018-03-01

Aiming at reducing the estimation error of the sensor frequency response function (FRF) estimated by the commonly used window-based spectral estimation method, the error models of interpolation and transient errors are derived in the form of non-parameter models. Accordingly, window effects on the errors are analyzed and reveal that the commonly used hanning window leads to smaller interpolation error which can also be significantly eliminated by the cubic spline interpolation method when estimating the FRF from the step response data, and window with smaller front-end value can restrain more transient error. Thus, a new dual-cosine window with its non-zero discrete Fourier transform bins at -3, -1, 0, 1, and 3 is constructed for FRF estimation. Compared with the hanning window, the new dual-cosine window has the equivalent interpolation error suppression capability and better transient error suppression capability when estimating the FRF from the step response; specifically, it reduces the asymptotic property of the transient error from O(N-2) of the hanning window method to O(N-4) while only increases the uncertainty slightly (about 0.4 dB). Then, one direction of a wind tunnel strain gauge balance which is a high order, small damping, and non-minimum phase system is employed as the example for verifying the new dual-cosine window-based spectral estimation method. The model simulation result shows that the new dual-cosine window method is better than the hanning window method for FRF estimation, and compared with the Gans method and LPM method, it has the advantages of simple computation, less time consumption, and short data requirement; the actual data calculation result of the balance FRF is consistent to the simulation result. Thus, the new dual-cosine window is effective and practical for FRF estimation.

A startling acoustic stimulus facilitates voluntary lower extremity movements and automatic postural responses in people with chronic stroke.

PubMed

Coppens, Milou J M; Roelofs, Jolanda M B; Donkers, Nicole A J; Nonnekes, Jorik; Geurts, Alexander C H; Weerdesteyn, Vivian

2018-05-14

A startling acoustic stimulus (SAS) involuntary releases prepared movements at accelerated latencies, known as the StartReact effect. Previous work has demonstrated intact StartReact in paretic upper extremity movements in people after stroke, suggesting preserved motor preparation. The question remains whether motor preparation of lower extremity movements is also unaffected after stroke. Here, we investigated StartReact effects on ballistic lower extremity movements and on automatic postural responses (APRs) following perturbations to standing balance. These APRs are particularly interesting as they are critical to prevent a fall following balance perturbations, but show substantial delays and poor muscle coordination after stroke. Twelve chronic stroke patients and 12 healthy controls performed voluntary ankle dorsiflexion movements in response to a visual stimulus, and responded to backward balance perturbations evoking APRs. Twenty-five percent of all trials contained a SAS (120 dB) simultaneously with the visual stimulus or balance perturbation. As expected, in the absence of a SAS muscle and movement onset latencies at the paretic side were delayed compared to the non-paretic leg and to controls. The SAS accelerated ankle dorsiflexion onsets in both the legs of the stroke subjects and in controls. Following perturbations, the SAS accelerated bilateral APR onsets not only in controls, but for the first time, we also demonstrated this effect in people after stroke. Moreover, APR inter- and intra-limb muscle coordination was rather weak in our stroke subjects, but substantially improved when the SAS was applied. These findings show preserved movement preparation, suggesting that there is residual (subcortical) capacity for motor recovery.

An Analysis of Variance Approach for the Estimation of Response Time Distributions in Tests

ERIC Educational Resources Information Center

Attali, Yigal

2010-01-01

Generalizability theory and analysis of variance methods are employed, together with the concept of objective time pressure, to estimate response time distributions and the degree of time pressure in timed tests. By estimating response time variance components due to person, item, and their interaction, and fixed effects due to item types and…

Modeling the distribution of extreme share return in Malaysia using Generalized Extreme Value (GEV) distribution

NASA Astrophysics Data System (ADS)

Hasan, Husna; Radi, Noor Fadhilah Ahmad; Kassim, Suraiya

2012-05-01

Extreme share return in Malaysia is studied. The monthly, quarterly, half yearly and yearly maximum returns are fitted to the Generalized Extreme Value (GEV) distribution. The Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests are performed to test for stationarity, while Mann-Kendall (MK) test is for the presence of monotonic trend. Maximum Likelihood Estimation (MLE) is used to estimate the parameter while L-moments estimate (LMOM) is used to initialize the MLE optimization routine for the stationary model. Likelihood ratio test is performed to determine the best model. Sherman's goodness of fit test is used to assess the quality of convergence of the GEV distribution by these monthly, quarterly, half yearly and yearly maximum. Returns levels are then estimated for prediction and planning purposes. The results show all maximum returns for all selection periods are stationary. The Mann-Kendall test indicates the existence of trend. Thus, we ought to model for non-stationary model too. Model 2, where the location parameter is increasing with time is the best for all selection intervals. Sherman's goodness of fit test shows that monthly, quarterly, half yearly and yearly maximum converge to the GEV distribution. From the results, it seems reasonable to conclude that yearly maximum is better for the convergence to the GEV distribution especially if longer records are available. Return level estimates, which is the return level (in this study return amount) that is expected to be exceeded, an average, once every t time periods starts to appear in the confidence interval of T = 50 for quarterly, half yearly and yearly maximum.

Modeling And Economics Of Extreme Subduction Earthquakes: Two Case Studies

NASA Astrophysics Data System (ADS)

Chavez, M.; Cabrera, E.; Emerson, D.; Perea, N.; Moulinec, C.

2008-05-01

The destructive effects of large magnitude, thrust subduction superficial (TSS) earthquakes on Mexico City (MC) and Guadalajara (G) has been shown in the recent centuries. For example, the 7/04/1845 and the 19/09/1985, two TSS earthquakes occurred on the coast of the state of Guerrero and Michoacan, with Ms 7+ and 8.1. The economical losses for the later were of about 7 billion US dollars. Also, the largest Ms 8.2, instrumentally observed TSS earthquake in Mexico, occurred in the Colima-Jalisco region the 3/06/1932, and the 9/10/1995 another similar, Ms 7.4 event occurred in the same region, the later produced economical losses of hundreds of thousands US dollars.The frequency of occurrence of large TSS earthquakes in Mexico is poorly known, but it might vary from decades to centuries [1]. Therefore there is a lack of strong ground motions records for extreme TSS earthquakes in Mexico, which as mentioned above, recently had an important economical impact on MC and potentially could have it in G. In this work we obtained samples of broadband synthetics [2,3] expected in MC and G, associated to extreme (plausible) magnitude Mw 8.5, TSS scenario earthquakes, with epicenters in the so-called Guerrero gap and in the Colima-Jalisco zone, respectively. The economical impacts of the proposed extreme TSS earthquake scenarios for MC and G were considered as follows: For MC by using a risk acceptability criteria, the probabilities of exceedance of the maximum seismic responses of their construction stock under the assumed scenarios, and the estimated economical losses observed for the 19/09/1985 earthquake; and for G, by estimating the expected economical losses, based on the seismic vulnerability assessment of their construction stock under the extreme seismic scenario considered. ----------------------- [1] Nishenko S.P. and Singh SK, BSSA 77, 6, 1987 [2] Cabrera E., Chavez M., Madariaga R., Mai M, Frisenda M., Perea N., AGU, Fall Meeting, 2005 [3] Chavez M., Olsen K

Transcriptomes of the Extremely Thermoacidophilic Archaeon Metallosphaera sedula Exposed to Metal “Shock” Reveal Generic and Specific Metal Responses

PubMed Central

Wheaton, Garrett H.; Mukherjee, Arpan

2016-01-01

ABSTRACT The extremely thermoacidophilic archaeon Metallosphaera sedula mobilizes metals by novel membrane-associated oxidase clusters and, consequently, requires metal resistance strategies. This issue was examined by “shocking” M. sedula with representative metals (Co2+, Cu2+, Ni2+, UO22+, Zn2+) at inhibitory and subinhibitory levels. Collectively, one-quarter of the genome (554 open reading frames [ORFs]) responded to inhibitory levels, and two-thirds (354) of the ORFs were responsive to a single metal. Cu2+ (259 ORFs, 106 Cu2+-specific ORFs) and Zn2+ (262 ORFs, 131 Zn2+-specific ORFs) triggered the largest responses, followed by UO22+ (187 ORFs, 91 UO22+-specific ORFs), Ni2+ (93 ORFs, 25 Ni2+-specific ORFs), and Co2+ (61 ORFs, 1 Co2+-specific ORF). While one-third of the metal-responsive ORFs are annotated as encoding hypothetical proteins, metal challenge also impacted ORFs responsible for identifiable processes related to the cell cycle, DNA repair, and oxidative stress. Surprisingly, there were only 30 ORFs that responded to at least four metals, and 10 of these responded to all five metals. This core transcriptome indicated induction of Fe-S cluster assembly (Msed_1656-Msed_1657), tungsten/molybdenum transport (Msed_1780-Msed_1781), and decreased central metabolism. Not surprisingly, a metal-translocating P-type ATPase (Msed_0490) associated with a copper resistance system (Cop) was upregulated in response to Cu2+ (6-fold) but also in response to UO22+ (4-fold) and Zn2+ (9-fold). Cu2+ challenge uniquely induced assimilatory sulfur metabolism for cysteine biosynthesis, suggesting a role for this amino acid in Cu2+ resistance or issues in sulfur metabolism. The results indicate that M. sedula employs a range of physiological and biochemical responses to metal challenge, many of which are specific to a single metal and involve proteins with yet unassigned or definitive functions. IMPORTANCE The mechanisms by which extremely thermoacidophilic archaea resist

Bayesian Non-Stationary Index Gauge Modeling of Gridded Precipitation Extremes

NASA Astrophysics Data System (ADS)

Verdin, A.; Bracken, C.; Caldwell, J.; Balaji, R.; Funk, C. C.

2017-12-01

We propose a Bayesian non-stationary model to generate watershed scale gridded estimates of extreme precipitation return levels. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset is used to obtain gridded seasonal precipitation extremes over the Taylor Park watershed in Colorado for the period 1981-2016. For each year, grid cells within the Taylor Park watershed are aggregated to a representative "index gauge," which is input to the model. Precipitation-frequency curves for the index gauge are estimated for each year, using climate variables with significant teleconnections as proxies. Such proxies enable short-term forecasting of extremes for the upcoming season. Disaggregation ratios of the index gauge to the grid cells within the watershed are computed for each year and preserved to translate the index gauge precipitation-frequency curve to gridded precipitation-frequency maps for select return periods. Gridded precipitation-frequency maps are of the same spatial resolution as CHIRPS (0.05° x 0.05°). We verify that the disaggregation method preserves spatial coherency of extremes in the Taylor Park watershed. Validation of the index gauge extreme precipitation-frequency method consists of ensuring extreme value statistics are preserved on a grid cell basis. To this end, a non-stationary extreme precipitation-frequency analysis is performed on each grid cell individually, and the resulting frequency curves are compared to those produced by the index gauge disaggregation method.

The critical role of uncertainty in projections of hydrological extremes

NASA Astrophysics Data System (ADS)

Meresa, Hadush K.; Romanowicz, Renata J.

2017-08-01

This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high- and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management.

Spatial extremes modeling applied to extreme precipitation data in the state of Paraná

NASA Astrophysics Data System (ADS)

Olinda, R. A.; Blanchet, J.; dos Santos, C. A. C.; Ozaki, V. A.; Ribeiro, P. J., Jr.

2014-11-01

Most of the mathematical models developed for rare events are based on probabilistic models for extremes. Although the tools for statistical modeling of univariate and multivariate extremes are well developed, the extension of these tools to model spatial extremes includes an area of very active research nowadays. A natural approach to such a modeling is the theory of extreme spatial and the max-stable process, characterized by the extension of infinite dimensions of multivariate extreme value theory, and making it possible then to incorporate the existing correlation functions in geostatistics and therefore verify the extremal dependence by means of the extreme coefficient and the Madogram. This work describes the application of such processes in modeling the spatial maximum dependence of maximum monthly rainfall from the state of Paraná, based on historical series observed in weather stations. The proposed models consider the Euclidean space and a transformation referred to as space weather, which may explain the presence of directional effects resulting from synoptic weather patterns. This method is based on the theorem proposed for de Haan and on the models of Smith and Schlather. The isotropic and anisotropic behavior of these models is also verified via Monte Carlo simulation. Estimates are made through pairwise likelihood maximum and the models are compared using the Takeuchi Information Criterion. By modeling the dependence of spatial maxima, applied to maximum monthly rainfall data from the state of Paraná, it was possible to identify directional effects resulting from meteorological phenomena, which, in turn, are important for proper management of risks and environmental disasters in countries with its economy heavily dependent on agribusiness.

Hot spots of multivariate extreme anomalies in Earth observations

NASA Astrophysics Data System (ADS)

Flach, M.; Sippel, S.; Bodesheim, P.; Brenning, A.; Denzler, J.; Gans, F.; Guanche, Y.; Reichstein, M.; Rodner, E.; Mahecha, M. D.

2016-12-01

Anomalies in Earth observations might indicate data quality issues, extremes or the change of underlying processes within a highly multivariate system. Thus, considering the multivariate constellation of variables for extreme detection yields crucial additional information over conventional univariate approaches. We highlight areas in which multivariate extreme anomalies are more likely to occur, i.e. hot spots of extremes in global atmospheric Earth observations that impact the Biosphere. In addition, we present the year of the most unusual multivariate extreme between 2001 and 2013 and show that these coincide with well known high impact extremes. Technically speaking, we account for multivariate extremes by using three sophisticated algorithms adapted from computer science applications. Namely an ensemble of the k-nearest neighbours mean distance, a kernel density estimation and an approach based on recurrences is used. However, the impact of atmosphere extremes on the Biosphere might largely depend on what is considered to be normal, i.e. the shape of the mean seasonal cycle and its inter-annual variability. We identify regions with similar mean seasonality by means of dimensionality reduction in order to estimate in each region both the `normal' variance and robust thresholds for detecting the extremes. In addition, we account for challenges like heteroscedasticity in Northern latitudes. Apart from hot spot areas, those anomalies in the atmosphere time series are of particular interest, which can only be detected by a multivariate approach but not by a simple univariate approach. Such an anomalous constellation of atmosphere variables is of interest if it impacts the Biosphere. The multivariate constellation of such an anomalous part of a time series is shown in one case study indicating that multivariate anomaly detection can provide novel insights into Earth observations.

Loss Factor Estimation Using the Impulse Response Decay Method on a Stiffened Structure

NASA Technical Reports Server (NTRS)

Cabell, Randolph; Schiller, Noah; Allen, Albert; Moeller, Mark

2009-01-01

High-frequency vibroacoustic modeling is typically performed using energy-based techniques such as Statistical Energy Analysis (SEA). Energy models require an estimate of the internal damping loss factor. Unfortunately, the loss factor is difficult to estimate analytically, and experimental methods such as the power injection method can require extensive measurements over the structure of interest. This paper discusses the implications of estimating damping loss factors using the impulse response decay method (IRDM) from a limited set of response measurements. An automated procedure for implementing IRDM is described and then evaluated using data from a finite element model of a stiffened, curved panel. Estimated loss factors are compared with loss factors computed using a power injection method and a manual curve fit. The paper discusses the sensitivity of the IRDM loss factor estimates to damping of connected subsystems and the number and location of points in the measurement ensemble.

Capturing spatial and temporal patterns of widespread, extreme flooding across Europe

NASA Astrophysics Data System (ADS)

Busby, Kathryn; Raven, Emma; Liu, Ye

2013-04-01

Statistical characterisation of physical hazards is an integral part of probabilistic catastrophe models used by the reinsurance industry to estimate losses from large scale events. Extreme flood events are not restricted by country boundaries which poses an issue for reinsurance companies as their exposures often extend beyond them. We discuss challenges and solutions that allow us to appropriately capture the spatial and temporal dependence of extreme hydrological events on a continental-scale, which in turn enables us to generate an industry-standard stochastic event set for estimating financial losses for widespread flooding. By presenting our event set methodology, we focus on explaining how extreme value theory (EVT) and dependence modelling are used to account for short, inconsistent hydrological data from different countries, and how to make appropriate statistical decisions that best characterise the nature of flooding across Europe. The consistency of input data is of vital importance when identifying historical flood patterns. Collating data from numerous sources inherently causes inconsistencies and we demonstrate our robust approach to assessing the data and refining it to compile a single consistent dataset. This dataset is then extrapolated using a parameterised EVT distribution to estimate extremes. Our method then captures the dependence of flood events across countries using an advanced multivariate extreme value model. Throughout, important statistical decisions are explored including: (1) distribution choice; (2) the threshold to apply for extracting extreme data points; (3) a regional analysis; (4) the definition of a flood event, which is often linked with reinsurance industry's hour's clause; and (5) handling of missing values. Finally, having modelled the historical patterns of flooding across Europe, we sample from this model to generate our stochastic event set comprising of thousands of events over thousands of years. We then briefly

Proof of concept and dose estimation with binary responses under model uncertainty.

PubMed

Klingenberg, B

2009-01-30

This article suggests a unified framework for testing Proof of Concept (PoC) and estimating a target dose for the benefit of a more comprehensive, robust and powerful analysis in phase II or similar clinical trials. From a pre-specified set of candidate models, we choose the ones that best describe the observed dose-response. To decide which models, if any, significantly pick up a dose effect, we construct the permutation distribution of the minimum P-value over the candidate set. This allows us to find critical values and multiplicity adjusted P-values that control the familywise error rate of declaring any spurious effect in the candidate set as significant. Model averaging is then used to estimate a target dose. Popular single or multiple contrast tests for PoC, such as the Cochran-Armitage, Dunnett or Williams tests, are only optimal for specific dose-response shapes and do not provide target dose estimates with confidence limits. A thorough evaluation and comparison of our approach to these tests reveal that its power is as good or better in detecting a dose-response under various shapes with many more additional benefits: It incorporates model uncertainty in PoC decisions and target dose estimation, yields confidence intervals for target dose estimates and extends to more complicated data structures. We illustrate our method with the analysis of a Phase II clinical trial. Copyright (c) 2008 John Wiley & Sons, Ltd.

Calculation of Coupled Vibroacoustics Response Estimates from a Library of Available Uncoupled Transfer Function Sets

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Hunt, Ron; Fulcher, Clay; Towner, Robert; McDonald, Emmett

2012-01-01

The design and theoretical basis of a new database tool that quickly generates vibroacoustic response estimates using a library of transfer functions (TFs) is discussed. During the early stages of a launch vehicle development program, these response estimates can be used to provide vibration environment specification to hardware vendors. The tool accesses TFs from a database, combines the TFs, and multiplies these by input excitations to estimate vibration responses. The database is populated with two sets of uncoupled TFs; the first set representing vibration response of a bare panel, designated as H(sup s), and the second set representing the response of the free-free component equipment by itself, designated as H(sup c). For a particular configuration undergoing analysis, the appropriate H(sup s) and H(sup c) are selected and coupled to generate an integrated TF, designated as H(sup s +c). This integrated TF is then used with the appropriate input excitations to estimate vibration responses. This simple yet powerful tool enables a user to estimate vibration responses without directly using finite element models, so long as suitable H(sup s) and H(sup c) sets are defined in the database libraries. The paper discusses the preparation of the database tool and provides the assumptions and methodologies necessary to combine H(sup s) and H(sup c) sets into an integrated H(sup s + c). An experimental validation of the approach is also presented.

The responsiveness and correlation between Fugl-Meyer Assessment, Motor Status Scale, and the Action Research Arm Test in chronic stroke with upper-extremity rehabilitation robotic training.

PubMed

Wei, Xi-Jun; Tong, Kai-Yu; Hu, Xiao-Ling

2011-12-01

Responsiveness of clinical assessments is an important element in the report of clinical effectiveness after rehabilitation. The correlation could reflect the validity of assessments as an indication of clinical performance before and after interventions. This study investigated the correlation and responsiveness of Fugl-Meyer Assessment (FMA), Motor Status Scale (MSS), Action Research Arm Test (ARAT) and the Modified Ashworth Scale (MAS), which are used frequently in effectiveness studies of robotic upper-extremity training in stroke rehabilitation. Twenty-seven chronic stroke patients were recruited for a 20-session upper-extremity rehabilitation robotic training program. This was a rater-blinded randomized controlled trial. All participants were evaluated with FMA, MSS, ARAT, MAS, and Functional Independent Measure before and after robotic training. Spearman's rank correlation coefficient was applied for the analysis of correlation. The standardized response mean (SRM) and Guyatt's responsiveness index (GRI) were used to analyze responsiveness. Spearman's correlation coefficient showed a significantly high correlation (ρ=0.91-0.96) among FMA, MSS, and ARAT and a fair-to-moderate correlation (ρ=0.40-0.62) between MAS and the other assessments. FMA, MSS, and MAS on the wrist showed higher responsiveness (SRM=0.85-0.98, GRI=1.59-3.62), whereas ARAT showed relatively less responsiveness (SRM=0.22, GRI=0.81). The results showed that FMA or MSS would be the best choice for evaluating the functional improvement in stroke studies on robotic upper-extremity training with high responsiveness and good correlation with ARAT. MAS could be used separately to evaluate the spasticity changes after intervention in terms of high responsiveness.

Deciphering landscape complexity to predict (non)linear responses to extreme climatic events

USDA-ARS?s Scientific Manuscript database

Extreme events are increasing in frequency and magnitude for many landscapes globally. Ecologically, most of the focus on extreme climatic events has been on effects of either short-term pulses (floods, freezes) or long-term drought. Multi-year increases in precipitation are also occurring with litt...

Detecting Changes in Functional Traits of Forest after Extreme Climate Episode using Model Data Fusion

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Kawai, Y.; Toda, M.

2016-12-01

The increase in extreme climate episodes associated with ongoing climate change may induce extensive damage to terrestrial ecosystems, changing plant functional traits that regulate ecosystem carbon budget. Over the last two decades, an advanced observational operation of tower-based eddy covariance has enhanced our ability to understand spatial and temporal features of ecosystem carbon exchange worldwide. In contrast, there remain several unresolved issues regarding plant function responses to extreme climate episodes and the resulting effects on the terrestrial carbon balance. In this work, we examined the effects of an extreme climatic event (typhoon) on plant functional traits of a cool-temperate forest in Japan using a model data fusion technique. We used a semi-process model to describes the time changes in net ecosystem exchange (NEE) of CO2 between atmosphere and ecosystem based on the distributions of foliage and size of an individual in a plant population, assuming the diameter profile and the pipe model theory (Shinozaki et al., 1964). The canopy photosynthesis model (Yokozawa et al., 1996) provides us the vertical distribution of gross photosynthetic rates within stand. It can allow us to examine the differences in photosynthetic rate with plant functional traits changed by climate disturbance. The DREAM(ZS) algorithm (ter Braak & Vrugt, 2008) was used to estimate the model parameters. To reduce the effects of heteroscedastic error, a generalized likelihood function was adopted (Schoup & Vrugt, 2010). The estimated annual parameter which represents the initial slope of light-photosynthetic rate curve, significantly changed after typhoon disturbance in 2004. Time changes in the profile of the maximum photosynthetic rate also shows the intensive response to the disturbance. After the disturbance, the values at upper foliage layer are higher than at lower foliage layer in contrast to that before disturbance. Specifically, just after disturbance in 2004b-5a

Item Response Theory with Estimation of the Latent Density Using Davidian Curves

ERIC Educational Resources Information Center

Woods, Carol M.; Lin, Nan

2009-01-01

Davidian-curve item response theory (DC-IRT) is introduced, evaluated with simulations, and illustrated using data from the Schedule for Nonadaptive and Adaptive Personality Entitlement scale. DC-IRT is a method for fitting unidimensional IRT models with maximum marginal likelihood estimation, in which the latent density is estimated,…

Classes of Split-Plot Response Surface Designs for Equivalent Estimation

NASA Technical Reports Server (NTRS)

Parker, Peter A.; Kowalski, Scott M.; Vining, G. Geoffrey

2006-01-01

When planning an experimental investigation, we are frequently faced with factors that are difficult or time consuming to manipulate, thereby making complete randomization impractical. A split-plot structure differentiates between the experimental units associated with these hard-to-change factors and others that are relatively easy-to-change and provides an efficient strategy that integrates the restrictions imposed by the experimental apparatus. Several industrial and scientific examples are presented to illustrate design considerations encountered in the restricted randomization context. In this paper, we propose classes of split-plot response designs that provide an intuitive and natural extension from the completely randomized context. For these designs, the ordinary least squares estimates of the model are equivalent to the generalized least squares estimates. This property provides best linear unbiased estimators and simplifies model estimation. The design conditions that allow for equivalent estimation are presented enabling design construction strategies to transform completely randomized Box-Behnken, equiradial, and small composite designs into a split-plot structure.

Continental-Scale Estimates of Runoff Using Future Climate ...

EPA Pesticide Factsheets

Recent runoff events have had serious repercussions to both natural ecosystems and human infrastructure. Understanding how shifts in storm event intensities are expected to change runoff responses are valuable for local, regional, and landscape planning. To address this challenge, relative changes in runoff using predicted future climate conditions were estimated over different biophysical areas for the CONterminous U.S. (CONUS). Runoff was estimated using the Curve Number (CN) developed by the USDA Soil Conservation Service (USDA, 1986). A seamless gridded dataset representing a CN for existing land use/land cover (LULC) across the CONUS was used along with two different storm event grids created specifically for this effort. The two storm event grids represent a 2- and a 100-year, 24-hour storm event under current climate conditions. The storm event grids were generated using a compilation of county-scale Texas USGS Intensity-Duration-Frequency (IDF) data (provided by William Asquith, USGS, Lubbock, Texas), and NOAA Atlas-2 and NOAA Atlas-14 gridded data sets. Future CN runoff was predicted using extreme storm events grids created using a method based on Kao and Ganguly (2011) where precipitation extremes reflect changes in saturated water vapor pressure of the atmosphere in response to temperature changes. The Clausius-Clapeyron relationship establishes that the total water vapor mass of fully saturated air increases with increasing temperature, leading to

Estimation of the auto frequency response function at unexcited points using dummy masses

NASA Astrophysics Data System (ADS)

Hosoya, Naoki; Yaginuma, Shinji; Onodera, Hiroshi; Yoshimura, Takuya

2015-02-01

If structures with complex shapes have space limitations, vibration tests using an exciter or impact hammer for the excitation are difficult. Although measuring the auto frequency response function at an unexcited point may not be practical via a vibration test, it can be obtained by assuming that the inertia acting on a dummy mass is an external force on the target structure upon exciting a different excitation point. We propose a method to estimate the auto frequency response functions at unexcited points by attaching a small mass (dummy mass), which is comparable to the accelerometer mass. The validity of the proposed method is demonstrated by comparing the auto frequency response functions estimated at unexcited points in a beam structure to those obtained from numerical simulations. We also consider random measurement errors by finite element analysis and vibration tests, but not bias errors. Additionally, the applicability of the proposed method is demonstrated by applying it to estimate the auto frequency response function of the lower arm in a car suspension.

Characterization, parameter estimation, and aircraft response statistics of atmospheric turbulence

NASA Technical Reports Server (NTRS)

Mark, W. D.

1981-01-01

A nonGaussian three component model of atmospheric turbulence is postulated that accounts for readily observable features of turbulence velocity records, their autocorrelation functions, and their spectra. Methods for computing probability density functions and mean exceedance rates of a generic aircraft response variable are developed using nonGaussian turbulence characterizations readily extracted from velocity recordings. A maximum likelihood method is developed for optimal estimation of the integral scale and intensity of records possessing von Karman transverse of longitudinal spectra. Formulas for the variances of such parameter estimates are developed. The maximum likelihood and least-square approaches are combined to yield a method for estimating the autocorrelation function parameters of a two component model for turbulence.

Acclimatization and tolerance to extreme altitude

NASA Technical Reports Server (NTRS)

West, J. B.

1993-01-01

During the last ten years, two major experiments have elucidated the factors determining acclimatization and tolerance to extreme altitude (over 7000 m). These were the American Medical Research Expedition to Everest, and the low pressure chamber simulation, Operation Everest II. Extreme hyperventilation is one of the most important responses to extreme altitude. Its chief value is that it allows the climber to maintain an alveolar PO2 which keeps the arterial PO2 above dangerously low levels. Even so, there is evidence of residual impairment of central nervous system function after ascents to extreme altitude, and maximal oxygen consumption falls precipitously above 7000 m. The term 'acclimatization' is probably not appropriate for altitudes above 8000 m, because the body steadily deteriorates at these altitudes. Tolerance to extreme altitude is critically dependent on barometric pressure, and even seasonal changes in pressure probably affect climbing performance near the summit of Mt Everest. Supplementary oxygen always improves exercise tolerance at extreme altitudes, and rescue oxygen should be available on climbing expeditions to 8000 m peaks.

Temporal development of extreme precipitation in Germany projected by EURO-CORDEX simulations

NASA Astrophysics Data System (ADS)

Brendel, Christoph; Deutschländer, Thomas

2017-04-01

A sustainable operation of transport infrastructure requires an enhanced resilience to the increasing impacts of climate change and related extreme meteorological events. To meet this challenge, the German Federal Ministry of Transport and Digital Infrastructure (BMVI) commenced a comprehensive national research program on safe and sustainable transport in Germany. A network of departmental research institutes addresses the "Adaptation of the German transport infrastructure towards climate change and extreme events". Various studies already have identified an increase in the average global precipitation for the 20th century. There is some indication that these increases are most visible in a rising frequency of precipitation extremes. However, the changes are highly variable between regions and seasons. With a further increase of atmospheric greenhouse gas concentrations in the 21st century, the likelihood of occurrence of such extreme events will continue to rise. A kernel estimator has been used in order to obtain a robust estimate of the temporal development of extreme precipitation events projected by an ensemble of EURO-CORDEX simulations. The kernel estimator measures the intensity of the poisson point process indicating temporal changes in the frequency of extreme events. Extreme precipitation events were selected using the peaks over threshold (POT) method with the 90th, 95th and 99th quantile of daily precipitation sums as thresholds. Application of this non-parametric approach with relative thresholds renders the use of a bias correction non-mandatory. In addition, in comparison to fitting an extreme value theory (EVT) distribution, the method is completely unsusceptible to outliers. First results show an overall increase of extreme precipitation events for Germany until the end of the 21st century. However, major differences between seasons, quantiles and the three different Representative Concentration Pathways (RCP 2.6, 4.5, and 8.5) have been

Logit-normal mixed model for Indian Monsoon rainfall extremes

NASA Astrophysics Data System (ADS)

Dietz, L. R.; Chatterjee, S.

2014-03-01

Describing the nature and variability of Indian monsoon rainfall extremes is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Several GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data procured from the National Climatic Data Center. The logit-normal model was applied with fixed covariates of latitude, longitude, elevation, daily minimum and maximum temperatures with a random intercept by weather station. In general, the estimation methods concurred in their suggestion of a relationship between the El Niño Southern Oscillation (ENSO) and extreme rainfall variability estimates. This work provides a valuable starting point for extending GLMM to incorporate the intricate dependencies in extreme climate events.

Individual estimation of exposures to extremely low frequency magnetic fields in jobs commonly held by women.

PubMed

Deadman, J E; Infante-Rivard, C

2002-02-15

Exposures to extremely low frequency (ELF) magnetic fields have not been documented extensively in occupations besides the work environments of electric or telephone utilities. A 1980-1993 study of childhood acute lymphoblastic leukemia (ALL) in Québec, Canada, gathered detailed information about the occupations of 491 mothers of ALL cases and mothers of a similar number of healthy controls. This information was combined with published data on the intensities of ELF magnetic fields associated with sources or work environments to estimate ELF magnetic field exposures for a wide range of jobs commonly held by women. Estimated exposures for 61 job categories ranged from 0.03 to 0.68 microT; the 25th, 50th, and 75th percentiles were 0.135, 0.17, and 0.23 microT, respectively. By job category, the most highly exposed jobs (>0.23 microT) included bakery worker, cashier, cook and kitchen worker, electronics worker, residential and industrial sewing machine operator, and textile machine operator. By work environment, the most highly exposed job categories were electronics worker in an assembly plant (0.70 microT) and sewing machine operators in a textile factory (0.68 microT) and shoe factory (0.66 microT). These results provide new information on expected levels of exposure in a wide range of jobs commonly held by women.

Evaluation of satellite-retrieved extreme precipitation using gauge observations

NASA Astrophysics Data System (ADS)

Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

2012-04-01

Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

Do Extremely Violent Juveniles Respond Differently to Treatment?

PubMed Central

Asscher, Jessica J.; Deković, M.; Van den Akker, Alithe L.; Prins, Pier J. M.; Van der Laan, Peter H.

2016-01-01

This study increases knowledge on effectiveness of treatment for extremely violent (EV) youth by investigating their response to multisystemic therapy (MST). Using data of a randomized controlled trial on effectiveness of MST, we investigated differences in treatment response between EV youth and not extremely violent (NEV) youth. Pre- to post-treatment comparison indicated MST was equally effective for EV and NEV youth, whereas treatment as usual was not effective for either group. Growth curves of within-treatment changes indicated EV youth responded differently to MST than NEV youth. The within-treatment change was for EV youth non-linear: Initially, they show a deterioration; however, after one month, EV juveniles respond positively to MST, indicating longer lasting, intensive programs may be effective in treating extreme violence. PMID:27794135

Statistical methods for the analysis of climate extremes

NASA Astrophysics Data System (ADS)

Naveau, Philippe; Nogaj, Marta; Ammann, Caspar; Yiou, Pascal; Cooley, Daniel; Jomelli, Vincent

2005-08-01

Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its 'normal' variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005).

Extreme Weather Events and Climate Change Attribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Katherine

A report from the National Academies of Sciences, Engineering, and Medicine concludes it is now possible to estimate the influence of climate change on some types of extreme events. The science of extreme event attribution has advanced rapidly in recent years, giving new insight to the ways that human-caused climate change can influence the magnitude or frequency of some extreme weather events. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities. Confidence is strongest in attributing types of extreme events that are influenced by climatemore » change through a well-understood physical mechanism, such as, the more frequent heat waves that are closely connected to human-caused global temperature increases, the report finds. Confidence is lower for other types of events, such as hurricanes, whose relationship to climate change is more complex and less understood at present. For any extreme event, the results of attribution studies hinge on how questions about the event's causes are posed, and on the data, modeling approaches, and statistical tools chosen for the analysis.« less

Quantile-based bias correction and uncertainty quantification of extreme event attribution statements

DOE PAGES

Jeon, Soyoung; Paciorek, Christopher J.; Wehner, Michael F.

2016-02-16

Extreme event attribution characterizes how anthropogenic climate change may have influenced the probability and magnitude of selected individual extreme weather and climate events. Attribution statements often involve quantification of the fraction of attributable risk (FAR) or the risk ratio (RR) and associated confidence intervals. Many such analyses use climate model output to characterize extreme event behavior with and without anthropogenic influence. However, such climate models may have biases in their representation of extreme events. To account for discrepancies in the probabilities of extreme events between observational datasets and model datasets, we demonstrate an appropriate rescaling of the model output basedmore » on the quantiles of the datasets to estimate an adjusted risk ratio. Our methodology accounts for various components of uncertainty in estimation of the risk ratio. In particular, we present an approach to construct a one-sided confidence interval on the lower bound of the risk ratio when the estimated risk ratio is infinity. We demonstrate the methodology using the summer 2011 central US heatwave and output from the Community Earth System Model. In this example, we find that the lower bound of the risk ratio is relatively insensitive to the magnitude and probability of the actual event.« less

Intrinsic solubility estimation and pH-solubility behavior of cosalane (NSC 658586), an extremely hydrophobic diprotic acid.

PubMed

Venkatesh, S; Li, J; Xu, Y; Vishnuvajjala, R; Anderson, B D

1996-10-01

The selection of cosalane (NSC 658586) by the National Cancer Institute for further development as a potential drug candidate for the treatment of AIDS led to the exploration of the solubility behavior of this extremely hydrophobic drug, which has an intrinsic solubility (S0 approaching 1 ng/ml. This study describes attempts to reliably measure the intrinsic solubility of cosalane and examine its pH-solubility behavior. S0 was estimated by 5 different strategies: (a) direct determination in an aqueous suspension: (b) facilitated dissolution; (c) estimation from the octanol/water partition coefficient and octanol solubility (d) application of an empirical equation based on melting point and partition coefficient; and (e) estimation from the hydrocarbon solubility and functional group contributions for transfer from hydrocarbon to water. S0 estimates using these five methods varied over a 5 x 107-fold range Method (a) yielded the highest values, two-orders of magnitude greater than those obtained by method (b) (facilitated dissolution. 1.4 +/- 0.5 ng/ml). Method (c) gave a value 20-fold higher while that from method (d) was in fair agreement with that from facilitated dissolution. Method (e) yielded a value several orders-of-magnitude lower than other methods. A molecular dynamics simulation suggests that folded conformations not accounted for by group contributions may reduce cosalane's effective hydrophobicity. Ionic equilibria calculations for this weak diprotic acid suggested a 100-fold increase in solubility per pH unit increase. The pH-solubility profile of cosalane at 25 degrees C agreed closely with theory. These studies highlight the difficulty in determining solubility of very poorly soluble compounds and the possible advantage of the facilitated dissolution method. The diprotic nature of cosalane enabled a solubility enhancement of > 107-fold by simple pH adjustment.

Inconsistent Responses of Hot Extremes to Historical Land Use and Cover Change Among the Selected CMIP5 Models

NASA Astrophysics Data System (ADS)

Li, Xing; Chen, Haishan; Wei, Jiangfeng; Hua, Wenjian; Sun, Shanlei; Ma, Hedi; Li, Xiao; Li, Jingping

2018-04-01

Land use and cover change (LUCC) is an important anthropogenic forcing of the climate system. Previous studies have demonstrated that LUCC significantly impacts both mean and extreme temperatures. In this study, we explored the multimodel performance of simulating LUCC-induced asymmetric effects on the different percentiles of maximum temperatures (Tmax) as well as the possible reasons for these effects using results from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Four state-of-art Earth system models (which provide the necessary data) are selected for investigating this issue. In general, all the cases of the model from the Geophysical Fluid Dynamics Laboratory show robust asymmetric responses between the 90th (TX90P) and 10th percentiles (TX10P) of Tmax, mainly due to cropland expansions, especially over India, the Sahel, and some parts of North America. However, weak and insignificant responses are shown for both the TX90P and TX10P in other models. The different changes in the Tmax variability among the models are primarily responsible for the occurrence of asymmetric features. Furthermore, by decomposing the Tmax changes over three typical regions, we analyze the potential causes for the inconsistencies among these models' results and find two crucial processes, that is, the repartitioning of the turbulent heat fluxes and the changes of the diurnal cycle variability due to LUCC. Whether these processes are pronounced determines the occurrence of the asymmetric Tmax responses. Overall, this study provides a critical clue for reducing the uncertainties of the LUCC effects on temperature extremes, which should be evaluated against observations.

Extreme Precipitation, Public Health Emergencies, and Safe Drinking Water in the USA.

PubMed

Exum, Natalie G; Betanzo, Elin; Schwab, Kellogg J; Chen, Thomas Y J; Guikema, Seth; Harvey, David E

2018-06-01

This review examines the effectiveness of drinking water regulations to inform public health during extreme precipitation events. This paper estimates the vulnerability of specific populations to flooding in their public water system, reviews the literature linking precipitation to waterborne outbreaks, examines the role that Safe Drinking Water Act and Public Notification (PN) Rule have in public health emergencies, and reviews the effectiveness of the PN Rule during the 2017 Hurricane Maria in Puerto Rico. Public water systems in large metropolitan areas have substantial portions of their customer base at risk for a waterborne outbreak during a flooding event. The PN Rule are ambiguous for who is responsible for declaring a "waterborne emergency" following a natural disaster like Hurricane Maria. Revisions to the current PN Rule that mandate public notification and water quality sampling during extreme precipitation events are necessary to ensure the public is aware of their drinking water quality following these events.

Estimation of the full-field dynamic response of a floating bridge using Kalman-type filtering algorithms

NASA Astrophysics Data System (ADS)

Petersen, Ø. W.; Øiseth, O.; Nord, T. S.; Lourens, E.

2018-07-01

Numerical predictions of the dynamic response of complex structures are often uncertain due to uncertainties inherited from the assumed load effects. Inverse methods can estimate the true dynamic response of a structure through system inversion, combining measured acceleration data with a system model. This article presents a case study of full-field dynamic response estimation of a long-span floating bridge: the Bergøysund Bridge in Norway. This bridge is instrumented with a network of 14 triaxial accelerometers. The system model consists of 27 vibration modes with natural frequencies below 2 Hz, obtained from a tuned finite element model that takes the fluid-structure interaction with the surrounding water into account. Two methods, a joint input-state estimation algorithm and a dual Kalman filter, are applied to estimate the full-field response of the bridge. The results demonstrate that the displacements and the accelerations can be estimated at unmeasured locations with reasonable accuracy when the wave loads are the dominant source of excitation.

On the asymptotic standard error of a class of robust estimators of ability in dichotomous item response models.

PubMed

Magis, David

2014-11-01

In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large-sample) standard errors (ASE) for these robust estimators, however, has not yet been fully considered. This paper focuses on a broad class of robust ability estimators, defined by an appropriate selection of the weight function and the residual measure, for which the ASE is derived from the theory of estimating equations. The maximum likelihood (ML) and the robust estimators, together with their estimated ASEs, are then compared in a simulation study by generating random guessing disturbances. It is concluded that both the estimators and their ASE perform similarly in the absence of random guessing, while the robust estimator and its estimated ASE are less biased and outperform their ML counterparts in the presence of random guessing with large impact on the item response process. © 2013 The British Psychological Society.

A Generalized Framework for Non-Stationary Extreme Value Analysis

NASA Astrophysics Data System (ADS)

Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.

2017-12-01

Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA

Relevance of the correlation between precipitation and the 0 °C isothermal altitude for extreme flood estimation

NASA Astrophysics Data System (ADS)

Zeimetz, Fraenz; Schaefli, Bettina; Artigue, Guillaume; García Hernández, Javier; Schleiss, Anton J.

2017-08-01

Extreme floods are commonly estimated with the help of design storms and hydrological models. In this paper, we propose a new method to take into account the relationship between precipitation intensity (P) and air temperature (T) to account for potential snow accumulation and melt processes during the elaboration of design storms. The proposed method is based on a detailed analysis of this P-T relationship in the Swiss Alps. The region, no upper precipitation intensity limit is detectable for increasing temperature. However, a relationship between the highest measured temperature before a precipitation event and the duration of the subsequent event could be identified. An explanation for this relationship is proposed here based on the temperature gradient measured before the precipitation events. The relevance of these results is discussed for an example of Probable Maximum Precipitation-Probable Maximum Flood (PMP-PMF) estimation for the high mountainous Mattmark dam catchment in the Swiss Alps. The proposed method to associate a critical air temperature to a PMP is easily transposable to similar alpine settings where meteorological soundings as well as ground temperature and precipitation measurements are available. In the future, the analyses presented here might be further refined by distinguishing between precipitation event types (frontal versus orographic).

Extreme Events in Urban Streams Leading to Extreme Temperatures in Birmingham, UK

NASA Astrophysics Data System (ADS)

Rangecroft, S.; Croghan, D.; Van Loon, A.; Sadler, J. P.; Hannah, D. M.

2016-12-01

Extreme flows and high water temperature events act as critical stressors on the ecological health of rivers. Urban headwater streams are considered particularly vulnerable to the effects of these extreme events. Despite this, such catchments remain poorly characterised and the effect of differences in land use is rarely quantified, especially in relation to water temperature. Thus a key research gap has emerged in understanding the patterns of water temperature during extreme events within contrasting urban, headwater catchments. We studied the headwaters of two bordering urban catchments of contrasting land use within Birmingham, UK. To characterise response to extreme events, precipitation and flow were analysed for the period of 1970-2016. To analyse the effects of extreme events on water temperature, 10 temperature loggers recording at 15 minute intervals were placed within each catchment covering a range of land use for the period May 2016 - present. During peak over threshold flood events higher average peaks were observed in the less urbanised catchment; however highest maximum flow peaks took place in the more densely urbanised catchment. Very similar average drought durations were observed between the two catchments with average flow drought durations of 27 days in the most urbanised catchment, and 29 in the less urbanised catchment. Flashier water temperature regimes were observed within the more urbanised catchment and increases of up to 5 degrees were apparent within 30 minutes during certain storms at the most upstream sites. Only in the most extreme events did the more densely urban stream appear more susceptible to both extreme high flows and extreme water temperature events, possibly resultant from overland flow emerging as the dominant flow pathway during intense precipitation events. Water temperature surges tended to be highly spatially variable indicating the importance of local land use. During smaller events, water temperature was less

Delayed responses of an Arctic ecosystem to an extremely dry summer: impacts on net ecosystem exchange and vegetation functioning

NASA Astrophysics Data System (ADS)

Zona, D.; Lipson, D. A.; Richards, J. H.; Phoenix, G. K.; Liljedahl, A. K.; Ueyama, M.; Sturtevant, C. S.; Oechel, W. C.

2013-12-01

The importance and mode of action of extreme events on the global carbon budget are inadequately understood. This includes the differential impact of extreme events on various ecosystem components, lag effects, recovery times, and compensatory processes. Summer 2007 in Barrow, Arctic Alaska, experienced unusually high air temperatures (fifth warmest over a 65 yr period) and record low precipitation (lowest over a 65 yr period). These abnormal conditions resulted in strongly reduced net Sphagnum CO2 uptake, but no effect neither on vascular plant development nor on net ecosystem exchange (NEE) from this arctic tundra ecosystem. Gross primary production (GPP) and ecosystem respiration (Reco) were both generally greater during most of this extreme summer. Cumulative ecosystem C uptake in 2007 was similar to the previous summers, showing the capacity of the ecosystem to compensate in its net ecosystem exchange (NEE) despite the impact on other functions and structure such as substantial necrosis of the Sphagnum layer. Surprisingly, the lowest ecosystem C uptake (2005-2009) was observed during the 2008 summer, i.e the year directly following the extremely summer. In 2008, cumulative C uptake was ∼70% lower than prior years. This reduction cannot solely be attributed to mosses, which typically contribute with ∼40% - of the entire ecosystem C uptake. The minimum summer cumulative C uptake in 2008 suggests that the entire ecosystem experienced difficulty readjusting to more typical weather after experiencing exceptionally warm and dry conditions. Importantly, the return to a substantial cumulative C uptake occurred two summers after the extreme event, which suggest a high resilience of this tundra ecosystem. Overall, these results show a highly complex response of the C uptake and its sub-components to atypically dry conditions. The impact of multiple extreme events still awaits further investigation.

Exchangeability, extreme returns and Value-at-Risk forecasts

NASA Astrophysics Data System (ADS)

Huang, Chun-Kai; North, Delia; Zewotir, Temesgen

2017-07-01

In this paper, we propose a new approach to extreme value modelling for the forecasting of Value-at-Risk (VaR). In particular, the block maxima and the peaks-over-threshold methods are generalised to exchangeable random sequences. This caters for the dependencies, such as serial autocorrelation, of financial returns observed empirically. In addition, this approach allows for parameter variations within each VaR estimation window. Empirical prior distributions of the extreme value parameters are attained by using resampling procedures. We compare the results of our VaR forecasts to that of the unconditional extreme value theory (EVT) approach and the conditional GARCH-EVT model for robust conclusions.

A single pH fluorescent probe for biosensing and imaging of extreme acidity and extreme alkalinity.

PubMed

Chao, Jian-Bin; Wang, Hui-Juan; Zhang, Yong-Bin; Li, Zhi-Qing; Liu, Yu-Hong; Huo, Fang-Jun; Yin, Cai-Xia; Shi, Ya-Wei; Wang, Juan-Juan

2017-07-04

A simple tailor-made pH fluorescent probe 2-benzothiazole (N-ethylcarbazole-3-yl) hydrazone (Probe) is facilely synthesized by the condensation reaction of 2-hydrazinobenzothiazole with N-ethylcarbazole-3-formaldehyde, which is a useful fluorescent probe for monitoring extremely acidic and alkaline pH, quantitatively. The pH titrations indicate that Probe displays a remarkable emission enhancement with a pK a of 2.73 and responds linearly to minor pH fluctuations within the extremely acidic range of 2.21-3.30. Interestingly, Probe also exhibits strong pH-dependent characteristics with pK a 11.28 and linear response to extreme-alkalinity range of 10.41-12.43. In addition, Probe shows a large Stokes shift of 84 nm under extremely acidic and alkaline conditions, high selectivity, excellent sensitivity, good water-solubility and fine stability, all of which are favorable for intracellular pH imaging. The probe is further successfully applied to image extremely acidic and alkaline pH values fluctuations in E. coli cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Properties of model-averaged BMDLs: a study of model averaging in dichotomous response risk estimation.

PubMed

Wheeler, Matthew W; Bailer, A John

2007-06-01

Model averaging (MA) has been proposed as a method of accounting for model uncertainty in benchmark dose (BMD) estimation. The technique has been used to average BMD dose estimates derived from dichotomous dose-response experiments, microbial dose-response experiments, as well as observational epidemiological studies. While MA is a promising tool for the risk assessor, a previous study suggested that the simple strategy of averaging individual models' BMD lower limits did not yield interval estimators that met nominal coverage levels in certain situations, and this performance was very sensitive to the underlying model space chosen. We present a different, more computationally intensive, approach in which the BMD is estimated using the average dose-response model and the corresponding benchmark dose lower bound (BMDL) is computed by bootstrapping. This method is illustrated with TiO(2) dose-response rat lung cancer data, and then systematically studied through an extensive Monte Carlo simulation. The results of this study suggest that the MA-BMD, estimated using this technique, performs better, in terms of bias and coverage, than the previous MA methodology. Further, the MA-BMDL achieves nominal coverage in most cases, and is superior to picking the "best fitting model" when estimating the benchmark dose. Although these results show utility of MA for benchmark dose risk estimation, they continue to highlight the importance of choosing an adequate model space as well as proper model fit diagnostics.

Estimating Non-Normal Latent Trait Distributions within Item Response Theory Using True and Estimated Item Parameters

ERIC Educational Resources Information Center

Sass, D. A.; Schmitt, T. A.; Walker, C. M.

2008-01-01

Item response theory (IRT) procedures have been used extensively to study normal latent trait distributions and have been shown to perform well; however, less is known concerning the performance of IRT with non-normal latent trait distributions. This study investigated the degree of latent trait estimation error under normal and non-normal…

Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.

2016-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.

Hierarchy and extremes in selections from pools of randomized proteins

PubMed Central

Boyer, Sébastien; Biswas, Dipanwita; Kumar Soshee, Ananda; Scaramozzino, Natale; Nizak, Clément; Rivoire, Olivier

2016-01-01

Variation and selection are the core principles of Darwinian evolution, but quantitatively relating the diversity of a population to its capacity to respond to selection is challenging. Here, we examine this problem at a molecular level in the context of populations of partially randomized proteins selected for binding to well-defined targets. We built several minimal protein libraries, screened them in vitro by phage display, and analyzed their response to selection by high-throughput sequencing. A statistical analysis of the results reveals two main findings. First, libraries with the same sequence diversity but built around different “frameworks” typically have vastly different responses; second, the distribution of responses of the best binders in a library follows a simple scaling law. We show how an elementary probabilistic model based on extreme value theory rationalizes the latter finding. Our results have implications for designing synthetic protein libraries, estimating the density of functional biomolecules in sequence space, characterizing diversity in natural populations, and experimentally investigating evolvability (i.e., the potential for future evolution). PMID:26969726

Hierarchy and extremes in selections from pools of randomized proteins.

PubMed

Boyer, Sébastien; Biswas, Dipanwita; Kumar Soshee, Ananda; Scaramozzino, Natale; Nizak, Clément; Rivoire, Olivier

2016-03-29

Variation and selection are the core principles of Darwinian evolution, but quantitatively relating the diversity of a population to its capacity to respond to selection is challenging. Here, we examine this problem at a molecular level in the context of populations of partially randomized proteins selected for binding to well-defined targets. We built several minimal protein libraries, screened them in vitro by phage display, and analyzed their response to selection by high-throughput sequencing. A statistical analysis of the results reveals two main findings. First, libraries with the same sequence diversity but built around different "frameworks" typically have vastly different responses; second, the distribution of responses of the best binders in a library follows a simple scaling law. We show how an elementary probabilistic model based on extreme value theory rationalizes the latter finding. Our results have implications for designing synthetic protein libraries, estimating the density of functional biomolecules in sequence space, characterizing diversity in natural populations, and experimentally investigating evolvability (i.e., the potential for future evolution).

Estimating 4D CBCT from prior information and extremely limited angle projections using structural PCA and weighted free-form deformation for lung radiotherapy

PubMed Central

Harris, Wendy; Zhang, You; Yin, Fang-Fang; Ren, Lei

2017-01-01

Purpose To investigate the feasibility of using structural-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. Methods A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion-model extracted by global PCA and free-form deformation (GMM-FD) technique, using a data fidelity constraint and deformation energy minimization. In this study, a new structural-PCA method was developed to build a structural motion-model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D-CT to onboard volume to evaluate the method. The estimation accuracy was evaluated by the Volume-Percent-Difference (VPD)/Center-of-Mass-Shift (COMS) between lesions in the estimated and “ground-truth” on board 4D-CBCT. Different onboard projection acquisition scenarios and projection noise levels were simulated to investigate their effects on the estimation accuracy. The method was also evaluated against 3 lung patients. Results The SMM-WFD method achieved substantially better accuracy than the GMM-FD method for CBCT

Estimating 4D-CBCT from prior information and extremely limited angle projections using structural PCA and weighted free-form deformation for lung radiotherapy.

PubMed

Harris, Wendy; Zhang, You; Yin, Fang-Fang; Ren, Lei

2017-03-01

To investigate the feasibility of using structural-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion model extracted by a global PCA and free-form deformation (GMM-FD) technique, using a data fidelity constraint and deformation energy minimization. In this study, a new structural PCA method was developed to build a structural motion model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respiratory changes from planning 4D-CT to on-board volume to evaluate the method. The estimation accuracy was evaluated by the volume percent difference (VPD)/center-of-mass-shift (COMS) between lesions in the estimated and "ground-truth" on-board 4D-CBCT. Different on-board projection acquisition scenarios and projection noise levels were simulated to investigate their effects on the estimation accuracy. The method was also evaluated against three lung patients. The SMM-WFD method achieved substantially better accuracy than the GMM-FD method for CBCT estimation using extremely

Towards a General Theory of Extremes for Observables of Chaotic Dynamical Systems.

PubMed

Lucarini, Valerio; Faranda, Davide; Wouters, Jeroen; Kuna, Tobias

2014-01-01

In this paper we provide a connection between the geometrical properties of the attractor of a chaotic dynamical system and the distribution of extreme values. We show that the extremes of so-called physical observables are distributed according to the classical generalised Pareto distribution and derive explicit expressions for the scaling and the shape parameter. In particular, we derive that the shape parameter does not depend on the chosen observables, but only on the partial dimensions of the invariant measure on the stable, unstable, and neutral manifolds. The shape parameter is negative and is close to zero when high-dimensional systems are considered. This result agrees with what was derived recently using the generalized extreme value approach. Combining the results obtained using such physical observables and the properties of the extremes of distance observables, it is possible to derive estimates of the partial dimensions of the attractor along the stable and the unstable directions of the flow. Moreover, by writing the shape parameter in terms of moments of the extremes of the considered observable and by using linear response theory, we relate the sensitivity to perturbations of the shape parameter to the sensitivity of the moments, of the partial dimensions, and of the Kaplan-Yorke dimension of the attractor. Preliminary numerical investigations provide encouraging results on the applicability of the theory presented here. The results presented here do not apply for all combinations of Axiom A systems and observables, but the breakdown seems to be related to very special geometrical configurations.

Towards a General Theory of Extremes for Observables of Chaotic Dynamical Systems

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Faranda, Davide; Wouters, Jeroen; Kuna, Tobias

2014-02-01

In this paper we provide a connection between the geometrical properties of the attractor of a chaotic dynamical system and the distribution of extreme values. We show that the extremes of so-called physical observables are distributed according to the classical generalised Pareto distribution and derive explicit expressions for the scaling and the shape parameter. In particular, we derive that the shape parameter does not depend on the chosen observables, but only on the partial dimensions of the invariant measure on the stable, unstable, and neutral manifolds. The shape parameter is negative and is close to zero when high-dimensional systems are considered. This result agrees with what was derived recently using the generalized extreme value approach. Combining the results obtained using such physical observables and the properties of the extremes of distance observables, it is possible to derive estimates of the partial dimensions of the attractor along the stable and the unstable directions of the flow. Moreover, by writing the shape parameter in terms of moments of the extremes of the considered observable and by using linear response theory, we relate the sensitivity to perturbations of the shape parameter to the sensitivity of the moments, of the partial dimensions, and of the Kaplan-Yorke dimension of the attractor. Preliminary numerical investigations provide encouraging results on the applicability of the theory presented here. The results presented here do not apply for all combinations of Axiom A systems and observables, but the breakdown seems to be related to very special geometrical configurations.

ZnO quantum dot-doped graphene/h-BN/GaN-heterostructure ultraviolet photodetector with extremely high responsivity

NASA Astrophysics Data System (ADS)

Lu, Yanghua; Wu, Zhiqian; Xu, Wenli; Lin, Shisheng

2016-12-01

A ZnO quantum dot photo-doped graphene/h-BN/GaN-heterostructure ultraviolet photodetector with extremely high responsivity of more than 1915 A W-1 and detectivity of more than 1.02 × 1013 Jones (Jones = cm Hz1/2 W-1) has been demonstrated. The interfaced h-BN layer increases the barrier height at the graphene/GaN heterojunction, which decreases the dark current and improves the on/off current ratio of the device. The photo-doping effect increases the barrier height and carrier concentration at the graphene/h-BN/GaN heterojunction, thus the responsivity is improved from 1473 A W-1 to 1915 A W-1 and the detectivity is improved from 5.8 × 1012 to 1.0 × 1013 Jones. Moreover, all of the responsivity and detectivity values are the highest values among all the graphene-based ultraviolet photodetectors.

Responses of Soil CO2 Emissions to Extreme Precipitation Regimes: a Simulation on Loess Soil in Semi-arid Regions

NASA Astrophysics Data System (ADS)

Wang, R.; Zhao, M.; Hu, Y.; Guo, S.

2016-12-01

Responses of soil CO2 emission to natural precipitation play an essential role in regulating regional C cycling. With more erratic precipitation regimes, mostly likely of more frequent heavy rainstorms, projected into the future, extreme precipitation would potentially affect local soil moisture, plant growth, microbial communities, and further soil CO2 emissions. However, responses of soil CO2 emissions to extreme precipitation have not yet been systematically investigated. Such performances could be of particular importance for rainfed arable soil in semi-arid regions where soil microbial respiration stress is highly sensitive to temporal distribution of natural precipitation.In this study, a simulated experiment was conducted on bare loess soil from the semi-arid Chinese Loess Plateau. Three precipitation regimes with total precipitation amounts of 150 mm, 300 mm and 600 mm were carried out to simulate the extremely dry, business as usual, and extremely wet summer. The three regimes were individually materialized by wetting soils in a series of sub-events (10 mm or 150 mm). Co2 emissions from surface soil were continuously measured in-situ for one month. The results show that: 1) Evident CO2 emission pulses were observed immediately after applying sub-events, and cumulative CO2 emissions from events of total amount of 600 mm were greater than that from 150 mm. 3) In particular, for the same total amount of 600 mm, wetting regimes by applying four times of 150 mm sub-events resulted in 20% less CO2 emissions than by applying 60 times of 10 mm sub-events. This is mostly because its harsh 150 mm storms introduced more over-wet soil microbial respiration stress days (moisture > 28%). As opposed, for the same total amount of 150 mm, CO2 emissions from wetting regimes by applying 15 times of 10 mm sub-events were 22% lower than by wetting at once with 150 mm water, probably because its deficiency of soil moisture resulted in more over-dry soil microbial respiration

Analysis of Extreme Snow Water Equivalent Data in Central New Hampshire

NASA Astrophysics Data System (ADS)

Vuyovich, C.; Skahill, B. E.; Kanney, J. F.; Carr, M.

2017-12-01

Heavy snowfall and snowmelt-related events have been linked to widespread flooding and damages in many regions of the U.S. Design of critical infrastructure in these regions requires spatial estimates of extreme snow water equivalent (SWE). In this study, we develop station specific and spatially explicit estimates of extreme SWE using data from fifteen snow sampling stations maintained by the New Hampshire Department of Environmental Services. The stations are located in the Mascoma, Pemigewasset, Winnipesaukee, Ossipee, Salmon Falls, Lamprey, Sugar, and Isinglass basins in New Hampshire. The average record length for the fifteen stations is approximately fifty-nine years. The spatial analysis of extreme SWE involves application of two Bayesian Hierarchical Modeling methods, one that assumes conditional independence, and another which uses the Smith max-stable process model to account for spatial dependence. We also apply additional max-stable process models, albeit not in a Bayesian framework, that better model the observed dependence among the extreme SWE data. The spatial process modeling leverages readily available and relevant spatially explicit covariate data. The noted additional max-stable process models also used the nonstationary winter North Atlantic Oscillation index, which has been observed to influence snowy weather along the east coast of the United States. We find that, for this data set, SWE return level estimates are consistently higher when derived using methods which account for the observed spatial dependence among the extreme data. This is particularly significant for design scenarios of relevance for critical infrastructure evaluation.

The Importance of Studying Past Extreme Floods to Prepare for Uncertain Future Extremes

NASA Astrophysics Data System (ADS)

Burges, S. J.

2016-12-01

Hoyt and Langbein, 1955 in their book `Floods' wrote: " ..meteorologic and hydrologic conditions will combine to produce superfloods of unprecedented magnitude. We have every reason to believe that in most rivers past floods may not be an accurate measure of ultimate flood potentialities. It is this superflood with which we are always most concerned". I provide several examples to offer some historical perspective on assessing extreme floods. In one example, flooding in the Miami Valley, OH in 1913 claimed 350 lives. The engineering and socio-economic challenges facing the Morgan Engineering Co in how to mitigate against future flood damage and loss of life when limited information was available provide guidance about ways to face an uncertain hydroclimate future, particularly one of a changed climate. A second example forces us to examine mixed flood populations and illustrates the huge uncertainty in assigning flood magnitude and exceedance probability to extreme floods in such cases. There is large uncertainty in flood frequency estimates; knowledge of the total flood hydrograph, not the peak flood flow rate alone, is what is needed for hazard mitigation assessment or design. Some challenges in estimating the complete flood hydrograph in an uncertain future climate, including demands on hydrologic models and their inputs, are addressed.

Extreme oceanographic forcing and coastal response due to the 2015-2016 El Niño.

PubMed

Barnard, Patrick L; Hoover, Daniel; Hubbard, David M; Snyder, Alex; Ludka, Bonnie C; Allan, Jonathan; Kaminsky, George M; Ruggiero, Peter; Gallien, Timu W; Gabel, Laura; McCandless, Diana; Weiner, Heather M; Cohn, Nicholas; Anderson, Dylan L; Serafin, Katherine A

2017-02-14

The El Niño-Southern Oscillation is the dominant mode of interannual climate variability across the Pacific Ocean basin, with influence on the global climate. The two end members of the cycle, El Niño and La Niña, force anomalous oceanographic conditions and coastal response along the Pacific margin, exposing many heavily populated regions to increased coastal flooding and erosion hazards. However, a quantitative record of coastal impacts is spatially limited and temporally restricted to only the most recent events. Here we report on the oceanographic forcing and coastal response of the 2015-2016 El Niño, one of the strongest of the last 145 years. We show that winter wave energy equalled or exceeded measured historical maxima across the US West Coast, corresponding to anomalously large beach erosion across the region. Shorelines in many areas retreated beyond previously measured landward extremes, particularly along the sediment-starved California coast.

Irrigation mitigates against heat extremes

NASA Astrophysics Data System (ADS)

Thiery, Wim; Fischer, Erich; Visser, Auke; Hirsch, Annette L.; Davin, Edouard L.; Lawrence, Dave; Hauser, Mathias; Seneviratne, Sonia I.

2017-04-01

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use gridded observations and ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on hot extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Finally we find that present-day irrigation is partly masking GHG-induced warming of extreme temperatures, with particularly strong effects in South Asia. Our results overall underline that irrigation substantially reduces our exposure to hot temperature extremes and highlight the need to account for irrigation in future climate projections.

Influence of Forest Disturbance on Hydrologic Extremes in the Colorado River Basin

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Middleton, R. S.; McDowell, N. G.; Xu, C.; Wilson, C. J.

2015-12-01

The Colorado River is one of the most important freshwater rivers in the United States: it provides water supply to more than 30 million people, irrigation to 5.7 million acres of cropland, and produces over 8 billion kilowatt hours of hydroelectric power each year. Our study focuses on changes to hydrological extremes and threshold responses across the Colorado River basin due to forest fires, infestations, and stress-induced tree mortality using a scenario-based approach to estimate forest cover disturbance. Scenarios include static vegetation reductions and dynamic reductions in forest compositions based on three CMIP5 global climate models and one emission scenario (1950-2099). For headwater systems, large intra-year variability exists, indicating the influence of climate on these snowmelt driven basins. Strong seasonality in flow responses are also noted; in the Piedra River higher runoff occurs during freshet under a no-forest condition, with the greatest changes observed for maximum streamflow. Conversely, during the recessional period, flows are lower in scenarios with reduced forest compositions. Low-flows appear to be affected in some basins but not others; for example small headwater systems demonstrate higher low-flows with increased disturbance. Global Climate Model scenarios indicate a range of responses in these basins, characterized by lower peak streamflow but with higher winter flows. This response is influenced by shifts in water, and energy balances associated with a combined response of changing climate and forest cover compositions. Results also clearly show how changes in extreme events are forced by shifts in major water balance parameters (runoff, evapotranspiration, snow water equivalent, and soil moisture) from headwater basins spanning a range of hydrological regimes and ecological environments across the Colorado.

Overview of the biology of extreme events

NASA Astrophysics Data System (ADS)

Gutschick, V. P.; Bassirirad, H.

2008-12-01

Extreme events have, variously, meteorological origins as in heat waves or precipitation extremes, or biological origins as in pest and disease eruptions (or tectonic, earth-orbital, or impact-body origins). Despite growing recognition that these events are changing in frequency and intensity, a universal model of ecological responses to these events is slow to emerge. Extreme events, negative and positive, contrast with normal events in terms of their effects on the physiology, ecology, and evolution of organisms, hence also on water, carbon, and nutrient cycles. They structure biogeographic ranges and biomes, almost surely more than mean values often used to define biogeography. They are challenging to study for obvious reasons of field-readiness but also because they are defined by sequences of driving variables such as temperature, not point events. As sequences, their statistics (return times, for example) are challenging to develop, as also from the involvement of multiple environmental variables. These statistics are not captured well by climate models. They are expected to change with climate and land-use change but our predictive capacity is currently limited. A number of tools for description and analysis of extreme events are available, if not widely applied to date. Extremes for organisms are defined by their fitness effects on those organisms, and are specific to genotypes, making them major agents of natural selection. There is evidence that effects of extreme events may be concentrated in an extended recovery phase. We review selected events covering ranges of time and magnitude, from Snowball Earth to leaf functional loss in weather events. A number of events, such as the 2003 European heat wave, evidence effects on water and carbon cycles over large regions. Rising CO2 is the recent extreme of note, for its climatic effects and consequences for growing seasons, transpiration, etc., but also directly in its action as a substrate of photosynthesis

Comparison of total body water estimates from O-18 and bioelectrical response prediction equations

NASA Technical Reports Server (NTRS)

Barrows, Linda H.; Inners, L. Daniel; Stricklin, Marcella D.; Klein, Peter D.; Wong, William W.; Siconolfi, Steven F.

1993-01-01

Identification of an indirect, rapid means to measure total body water (TBW) during space flight may aid in quantifying hydration status and assist in countermeasure development. Bioelectrical response testing and hydrostatic weighing were performed on 27 subjects who ingested O-18, a naturally occurring isotope of oxygen, to measure true TBW. TBW estimates from three bioelectrical response prediction equations and fat-free mass (FFM) were compared to TBW measured from O-18. A repeated measures MANOVA with post-hoc Dunnett's Test indicated a significant (p less than 0.05) difference between TBW estimates from two of the three bioelectrical response prediction equations and O-18. TBW estimates from FFM and the Kushner & Schoeller (1986) equation yielded results that were similar to those given by O-18. Strong correlations existed between each prediction method and O-18; however, standard errors, identified through regression analyses, were higher for the bioelectrical response prediction equations compared to those derived from FFM. These findings suggest (1) the Kushner & Schoeller (1986) equation may provide a valid measure of TBW, (2) other TBW prediction equations need to be identified that have variability similar to that of FFM, and (3) bioelectrical estimates of TBW may prove valuable in quantifying hydration status during space flight.

XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

NASA Astrophysics Data System (ADS)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-08-01

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

Return levels of temperature extremes in southern Pakistan

NASA Astrophysics Data System (ADS)

Zahid, Maida; Blender, Richard; Lucarini, Valerio; Caterina Bramati, Maria

2017-12-01

Southern Pakistan (Sindh) is one of the hottest regions in the world and is highly vulnerable to temperature extremes. In order to improve rural and urban planning, it is useful to gather information about the recurrence of temperature extremes. In this work, return levels of the daily maximum temperature Tmax are estimated, as well as the daily maximum wet-bulb temperature TWmax extremes. We adopt the peaks over threshold (POT) method, which has not yet been used for similar studies in this region. Two main datasets are analyzed: temperatures observed at nine meteorological stations in southern Pakistan from 1980 to 2013, and the ERA-Interim (ECMWF reanalysis) data for the nearest corresponding locations. The analysis provides the 2-, 5-, 10-, 25-, 50-, and 100-year return levels (RLs) of temperature extremes. The 90 % quantile is found to be a suitable threshold for all stations. We find that the RLs of the observed Tmax are above 50 °C at northern stations and above 45 °C at the southern stations. The RLs of the observed TWmax exceed 35 °C in the region, which is considered as a limit of survivability. The RLs estimated from the ERA-Interim data are lower by 3 to 5 °C than the RLs assessed for the nine meteorological stations. A simple bias correction applied to ERA-Interim data improves the RLs remarkably, yet discrepancies are still present. The results have potential implications for the risk assessment of extreme temperatures in Sindh.

Influence of extreme weather disasters on global crop production.

PubMed

Lesk, Corey; Rowhani, Pedram; Ramankutty, Navin

2016-01-07

In recent years, several extreme weather disasters have partially or completely damaged regional crop production. While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964-2007. We show that droughts and extreme heat significantly reduced national cereal production by 9-10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8-11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.

Implementation and Evaluation of Weather Responsive Traffic Estimation and Prediction System

DOT National Transportation Integrated Search

2012-06-01

The objective of the project is to develop a framework and procedures for implementing and evaluating weather-responsive traffic management (WRTM) strategies using Traffic Estimation and Prediction System (TrEPS) methodologies. In a previous FHWA-fun...

A review of statistical methods to analyze extreme precipitation and temperature events in the Mediterranean region

NASA Astrophysics Data System (ADS)

Lazoglou, Georgia; Anagnostopoulou, Christina; Tolika, Konstantia; Kolyva-Machera, Fotini

2018-04-01

The increasing trend of the intensity and frequency of temperature and precipitation extremes during the past decades has substantial environmental and socioeconomic impacts. Thus, the objective of the present study is the comparison of several statistical methods of the extreme value theory (EVT) in order to identify which is the most appropriate to analyze the behavior of the extreme precipitation, and high and low temperature events, in the Mediterranean region. The extremes choice was made using both the block maxima and the peaks over threshold (POT) technique and as a consequence both the generalized extreme value (GEV) and generalized Pareto distributions (GPDs) were used to fit them. The results were compared, in order to select the most appropriate distribution for extremes characterization. Moreover, this study evaluates the maximum likelihood estimation, the L-moments and the Bayesian method, based on both graphical and statistical goodness-of-fit tests. It was revealed that the GPD can characterize accurately both precipitation and temperature extreme events. Additionally, GEV distribution with the Bayesian method is proven to be appropriate especially for the greatest values of extremes. Another important objective of this investigation was the estimation of the precipitation and temperature return levels for three return periods (50, 100, and 150 years) classifying the data into groups with similar characteristics. Finally, the return level values were estimated with both GEV and GPD and with the three different estimation methods, revealing that the selected method can affect the return level values for both the parameter of precipitation and temperature.

Bi-Factor Multidimensional Item Response Theory Modeling for Subscores Estimation, Reliability, and Classification

ERIC Educational Resources Information Center

Md Desa, Zairul Nor Deana

2012-01-01

In recent years, there has been increasing interest in estimating and improving subscore reliability. In this study, the multidimensional item response theory (MIRT) and the bi-factor model were combined to estimate subscores, to obtain subscores reliability, and subscores classification. Both the compensatory and partially compensatory MIRT…

Estimation of Item Response Theory Parameters in the Presence of Missing Data

ERIC Educational Resources Information Center

Finch, Holmes

2008-01-01

Missing data are a common problem in a variety of measurement settings, including responses to items on both cognitive and affective assessments. Researchers have shown that such missing data may create problems in the estimation of item difficulty parameters in the Item Response Theory (IRT) context, particularly if they are ignored. At the same…

Animal responses to natural disturbance and climate extremes: a review

NASA Astrophysics Data System (ADS)

Sergio, Fabrizio; Blas, Julio; Hiraldo, Fernando

2018-02-01

Natural disturbances, such as droughts, fires or hurricanes, are key drivers of ecological heterogeneity and ecosystem function. The frequency and severity of these episodes is unequivocally expected to increase in the coming decades, through the concerted action of climate change and anthropogenic pressures. This will impose severe challenges for many biota through exposure to rapidly changing conditions never experienced in the preceding millennia. Thus, it is urgently needed to gain a thorough understanding of animal responses and adaptations to disturbances in order to better estimate potential future impacts. Here, we review such adjustments and find that animals may respond to disturbances through changes in: (1) behaviour, such as altered mobility, emigration, resource-switching, refuge use, suspended animation, or biotic interactions; (2) life history traits, such as survival, aging, longevity, recruitment, reproductive restraint, breeding output, phenology and bet-hedging tactics; (3) morphology, such as rapid evolution through size-dependent mortality or facultative metamorphosis; (4) physiology, such as altered body condition, pathogen prevalence and transmission, or adrenocortical modulation of stress responses to emergency conditions; (5) genetic structure, such as changes in frequency of polymorphic variants or diversity-modulation through mortality bottlenecks. Individual-level responses scale up to population and community responses, such as altered density, population dynamics, distribution, local extinction and colonization, or assemblage structure and diversity. Overall, disturbances have pervasive effects on individuals, populations and communities of vertebrates and invertebrates of all realms, biomes, continents and ecosystems. Their rapidly increasing incidence and severity will bring unique study opportunities for researchers and novel, unpredictable challenges for managers, while demanding tougher choices and more proactive crisis

A Novel Methodology to Estimate the Treatment Effect in Presence of Highly Variable Placebo Response

PubMed Central

Gomeni, Roberto; Goyal, Navin; Bressolle, Françoise; Fava, Maurizio

2015-01-01

One of the main reasons for the inefficiency of multicenter randomized clinical trials (RCTs) in depression is the excessively high level of placebo response. The aim of this work was to propose a novel methodology to analyze RCTs based on the assumption that centers with high placebo response are less informative than the other centers for estimating the ‘true' treatment effect (TE). A linear mixed-effect modeling approach for repeated measures (MMRM) was used as a reference approach. The new method for estimating TE was based on a nonlinear longitudinal modeling of clinical scores (NLMMRM). NLMMRM estimates TE by associating a weighting factor to the data collected in each center. The weight was defined by the posterior probability of detecting a clinically relevant difference between active treatment and placebo at that center. Data from five RCTs in depression were used to compare the performance of MMRM with NLMMRM. The results of the analyses showed an average improvement of ~15% in the TE estimated with NLMMRM when the center effect was included in the analyses. Opposite results were observed with MMRM: TE estimate was reduced by ~4% when the center effect was considered as covariate in the analysis. The novel NLMMRM approach provides a tool for controlling the confounding effect of high placebo response, to increase signal detection and to provide a more reliable estimate of the ‘true' TE by controlling false negative results associated with excessively high placebo response. PMID:25895454

ZnO quantum dot-doped graphene/h-BN/GaN-heterostructure ultraviolet photodetector with extremely high responsivity.

PubMed

Lu, Yanghua; Wu, Zhiqian; Xu, Wenli; Lin, Shisheng

2016-12-02

A ZnO quantum dot  photo-doped graphene/h-BN/GaN-heterostructure ultraviolet photodetector with extremely high responsivity of more than 1915 A W -1 and detectivity of more than 1.02 × 10 13 Jones (Jones = cm Hz 1/2 W -1 ) has been demonstrated. The interfaced h-BN layer increases the barrier height at the graphene/GaN heterojunction, which decreases the dark current and improves the on/off current ratio of the device. The photo-doping effect increases the barrier height and carrier concentration at the graphene/h-BN/GaN heterojunction, thus the responsivity is improved from 1473 A W -1 to 1915 A W -1 and the detectivity is improved from 5.8 × 10 12 to 1.0 × 10 13 Jones. Moreover, all of the responsivity and detectivity values are the highest values among all the graphene-based ultraviolet photodetectors.

Estimation of dose-response models for discrete and continuous data in weed science

USDA-ARS?s Scientific Manuscript database

Dose-response analysis is widely used in biological sciences and has application to a variety of risk assessment, bioassay, and calibration problems. In weed science, dose-response methodologies have typically relied on least squares estimation under an assumption of normality. Advances in computati...

Warmest extreme year in U.S. history alters thermal requirements for tree phenology.

PubMed

Carter, Jacob M; Orive, Maria E; Gerhart, Laci M; Stern, Jennifer H; Marchin, Renée M; Nagel, Joane; Ward, Joy K

2017-04-01

The frequency of extreme warm years is increasing across the majority of the planet. Shifts in plant phenology in response to extreme years can influence plant survival, productivity, and synchrony with pollinators/herbivores. Despite extensive work on plant phenological responses to climate change, little is known about responses to extreme warm years, particularly at the intraspecific level. Here we investigate 43 populations of white ash trees (Fraxinus americana) from throughout the species range that were all grown in a common garden. We compared the timing of leaf emergence during the warmest year in U.S. history (2012) with relatively non-extreme years. We show that (a) leaf emergence among white ash populations was accelerated by 21 days on average during the extreme warm year of 2012 relative to non-extreme years; (b) rank order for the timing of leaf emergence was maintained among populations across extreme and non-extreme years, with southern populations emerging earlier than northern populations; (c) greater amounts of warming units accumulated prior to leaf emergence during the extreme warm year relative to non-extreme years, and this constrained the potential for even earlier leaf emergence by an average of 9 days among populations; and (d) the extreme warm year reduced the reliability of a relevant phenological model for white ash by producing a consistent bias toward earlier predicted leaf emergence relative to observations. These results demonstrate a critical need to better understand how extreme warm years will impact tree phenology, particularly at the intraspecific level.

"On-off-on" switchable sensor: a fluorescent spiropyran responds to extreme pH conditions and its bioimaging applications.

PubMed

Wan, Shulin; Zheng, Yang; Shen, Jie; Yang, Wantai; Yin, Meizhen

2014-11-26

A novel spiropyran that responds to both extreme acid and extreme alkali and has an "on-off-on" switch is reported. Benzoic acid at the indole N-position and carboxyl group at the indole 6-position contribute to the extreme acid response. The ionizations of carboxyl and phenolic hydroxyl groups cause the extreme alkali response. Moreover, the fluorescent imaging in bacterial cells under extreme pH conditions supports the mechanism of pH response.

Study on the Strategies for the Soil and Water Resource Con-servation of Slopeland in Taiwan in Response to the Extreme Climate

NASA Astrophysics Data System (ADS)

Huang, Wen-Cheng

2014-05-01

Global climate change results in extreme weather, especially ex-treme precipitation in Taiwan. Though the total amount of precipi-tation remains unchanged, the frequency of rainfall return period increases which affects slopeland and causes sediment disaster. In Taiwan, slopeland occupies about 73% of national territory. Under harsh environmental stress, soil and water conservation of slope-land becomes more important. In response to the trends of global-ization impacts of climate change, long term strategic planning be-comes more necessary. This study reviewed international practices and decision making process about soil and water conservation of slopeland; and conducted the compilation and analysis of water and soil conservation related research projects in Taiwan within the past five years. It is necessary for Taiwan to design timely adaptive strategies about conducting the all-inclusive conservation of na-tional territory, management and business operation of watershed based on the existing regulation with the effects of extreme weather induced by climate change and the changes of social-economic en-vironments. In order to realize the policy vision of "Under the premise of multiple uses, operating the sustainable business and management of the water and soil resources in the watershed through territorial planning in response to the climate and so-cial-economic environment change". This study concluded the future tasks for soil and water con-servation: 1.Design and timely amend strategies for soil and wand water conservation in response to extreme weather. 2. Strengthen the planning and operating of the land management and integrated conservation of the water and soil resources of key watershed. 3. Manage and operate the prevention of debris flow disaster and large-scale landslide. 4. Formulate polices, related regulations and assessment indicators of soil and water conservation. 5. Maintain the biodiversity of the slopeland and reduce the ecological footprint

A comparative assessment of statistical methods for extreme weather analysis

NASA Astrophysics Data System (ADS)

Schlögl, Matthias; Laaha, Gregor

2017-04-01

Extreme weather exposure assessment is of major importance for scientists and practitioners alike. We compare different extreme value approaches and fitting methods with respect to their value for assessing extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series over the standardly used annual maxima series in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing partial duration series, PDS) being superior to the block maxima approach (employing annual maxima series, AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was neither visible from the square-root criterion, nor from standardly used graphical diagnosis (mean residual life plot), but from a direct comparison of AMS and PDS in synoptic quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best suited approach. This will make the analyses more robust, in cases where threshold selection and dependency introduces biases to the PDS approach, but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend conditional performance measures that focus

Can new passenger cars reduce pedestrian lower extremity injury? A review of geometrical changes of front-end design before and after regulatory efforts.

PubMed

Nie, Bingbing; Zhou, Qing

2016-10-02

Pedestrian lower extremity represents the most frequently injured body region in car-to-pedestrian accidents. The European Directive concerning pedestrian safety was established in 2003 for evaluating pedestrian protection performance of car models. However, design changes have not been quantified since then. The goal of this study was to investigate front-end profiles of representative passenger car models and the potential influence on pedestrian lower extremity injury risk. The front-end styling of sedans and sport utility vehicles (SUV) released from 2008 to 2011 was characterized by the geometrical parameters related to pedestrian safety and compared to representative car models before 2003. The influence of geometrical design change on the resultant risk of injury to pedestrian lower extremity-that is, knee ligament rupture and long bone fracture-was estimated by a previously developed assessment tool assuming identical structural stiffness. Based on response surface generated from simulation results of a human body model (HBM), the tool provided kinematic and kinetic responses of pedestrian lower extremity resulted from a given car's front-end design. Newer passenger cars exhibited a "flatter" front-end design. The median value of the sedan models provided 87.5 mm less bottom depth, and the SUV models exhibited 94.7 mm less bottom depth. In the lateral impact configuration similar to that in the regulatory test methods, these geometrical changes tend to reduce the injury risk of human knee ligament rupture by 36.6 and 39.6% based on computational approximation. The geometrical changes did not significantly influence the long bone fracture risk. The present study reviewed the geometrical changes in car front-ends along with regulatory concerns regarding pedestrian safety. A preliminary quantitative benefit of the lower extremity injury reduction was estimated based on these geometrical features. Further investigation is recommended on the structural changes

Seasonal and Non-Seasonal Generalized Pareto Distribution to Estimate Extreme Significant Wave Height in The Banda Sea

NASA Astrophysics Data System (ADS)

Nursamsiah; Nugroho Sugianto, Denny; Suprijanto, Jusup; Munasik; Yulianto, Bambang

2018-02-01

The information of extreme wave height return level was required for maritime planning and management. The recommendation methods in analyzing extreme wave were better distributed by Generalized Pareto Distribution (GPD). Seasonal variation was often considered in the extreme wave model. This research aims to identify the best model of GPD by considering a seasonal variation of the extreme wave. By using percentile 95 % as the threshold of extreme significant wave height, the seasonal GPD and non-seasonal GPD fitted. The Kolmogorov-Smirnov test was applied to identify the goodness of fit of the GPD model. The return value from seasonal and non-seasonal GPD was compared with the definition of return value as criteria. The Kolmogorov-Smirnov test result shows that GPD fits data very well both seasonal and non-seasonal model. The seasonal return value gives better information about the wave height characteristics.

Numerical modeling of space-time wave extremes using WAVEWATCH III

NASA Astrophysics Data System (ADS)

Barbariol, Francesco; Alves, Jose-Henrique G. M.; Benetazzo, Alvise; Bergamasco, Filippo; Bertotti, Luciana; Carniel, Sandro; Cavaleri, Luigi; Y. Chao, Yung; Chawla, Arun; Ricchi, Antonio; Sclavo, Mauro; Tolman, Hendrik

2017-04-01

A novel implementation of parameters estimating the space-time wave extremes within the spectral wave model WAVEWATCH III (WW3) is presented. The new output parameters, available in WW3 version 5.16, rely on the theoretical model of Fedele (J Phys Oceanogr 42(9):1601-1615, 2012) extended by Benetazzo et al. (J Phys Oceanogr 45(9):2261-2275, 2015) to estimate the maximum second-order nonlinear crest height over a given space-time region. In order to assess the wave height associated to the maximum crest height and the maximum wave height (generally different in a broad-band stormy sea state), the linear quasi-determinism theory of Boccotti (2000) is considered. The new WW3 implementation is tested by simulating sea states and space-time extremes over the Mediterranean Sea (forced by the wind fields produced by the COSMO-ME atmospheric model). Model simulations are compared to space-time wave maxima observed on March 10th, 2014, in the northern Adriatic Sea (Italy), by a stereo camera system installed on-board the "Acqua Alta" oceanographic tower. Results show that modeled space-time extremes are in general agreement with observations. Differences are mostly ascribed to the accuracy of the wind forcing and, to a lesser extent, to the approximations introduced in the space-time extremes parameterizations. Model estimates are expected to be even more accurate over areas larger than the mean wavelength (for instance, the model grid size).

Materials and noncoplanar mesh designs for integrated circuits with linear elastic responses to extreme mechanical deformations.

PubMed

Kim, Dae-Hyeong; Song, Jizhou; Choi, Won Mook; Kim, Hoon-Sik; Kim, Rak-Hwan; Liu, Zhuangjian; Huang, Yonggang Y; Hwang, Keh-Chih; Zhang, Yong-wei; Rogers, John A

2008-12-02

Electronic systems that offer elastic mechanical responses to high-strain deformations are of growing interest because of their ability to enable new biomedical devices and other applications whose requirements are impossible to satisfy with conventional wafer-based technologies or even with those that offer simple bendability. This article introduces materials and mechanical design strategies for classes of electronic circuits that offer extremely high stretchability, enabling them to accommodate even demanding configurations such as corkscrew twists with tight pitch (e.g., 90 degrees in approximately 1 cm) and linear stretching to "rubber-band" levels of strain (e.g., up to approximately 140%). The use of single crystalline silicon nanomaterials for the semiconductor provides performance in stretchable complementary metal-oxide-semiconductor (CMOS) integrated circuits approaching that of conventional devices with comparable feature sizes formed on silicon wafers. Comprehensive theoretical studies of the mechanics reveal the way in which the structural designs enable these extreme mechanical properties without fracturing the intrinsically brittle active materials or even inducing significant changes in their electrical properties. The results, as demonstrated through electrical measurements of arrays of transistors, CMOS inverters, ring oscillators, and differential amplifiers, suggest a valuable route to high-performance stretchable electronics.

Hormonal and Neuromuscular Responses to Mechanical Vibration Applied to Upper Extremity Muscles

PubMed Central

Di Giminiani, Riccardo; Fabiani, Leila; Baldini, Giuliano; Cardelli, Giovanni; Giovannelli, Aldo; Tihanyi, Jozsef

2014-01-01

Objective To investigate the acute residual hormonal and neuromuscular responses exhibited following a single session of mechanical vibration applied to the upper extremities among different acceleration loads. Methods Thirty male students were randomly assigned to a high vibration group (HVG), a low vibration group (LVG), or a control group (CG). A randomized double-blind, controlled-parallel study design was employed. The measurements and interventions were performed at the Laboratory of Biomechanics of the University of L'Aquila. The HVG and LVG participants were exposed to a series of 20 trials ×10 s of synchronous whole-body vibration (WBV) with a 10-s pause between each trial and a 4-min pause after the first 10 trials. The CG participants assumed an isometric push-up position without WBV. The outcome measures were growth hormone (GH), testosterone, maximal voluntary isometric contraction during bench-press, maximal voluntary isometric contraction during handgrip, and electromyography root-mean-square (EMGrms) muscle activity (pectoralis major [PM], triceps brachii [TB], anterior deltoid [DE], and flexor carpi radialis [FCR]). Results The GH increased significantly over time only in the HVG (P = 0.003). Additionally, the testosterone levels changed significantly over time in the LVG (P = 0.011) and the HVG (P = 0.001). MVC during bench press decreased significantly in the LVG (P = 0.001) and the HVG (P = 0.002). In the HVG, the EMGrms decreased significantly in the TB (P = 0.006) muscle. In the LVG, the EMGrms decreased significantly in the DE (P = 0.009) and FCR (P = 0.006) muscles. Conclusion Synchronous WBV acutely increased GH and testosterone serum concentrations and decreased the MVC and their respective maximal EMGrms activities, which indicated a possible central fatigue effect. Interestingly, only the GH response was dependent on the acceleration with respect to the subjects' responsiveness. PMID:25368995

Hormonal and neuromuscular responses to mechanical vibration applied to upper extremity muscles.

PubMed

Di Giminiani, Riccardo; Fabiani, Leila; Baldini, Giuliano; Cardelli, Giovanni; Giovannelli, Aldo; Tihanyi, Jozsef

2014-01-01

To investigate the acute residual hormonal and neuromuscular responses exhibited following a single session of mechanical vibration applied to the upper extremities among different acceleration loads. Thirty male students were randomly assigned to a high vibration group (HVG), a low vibration group (LVG), or a control group (CG). A randomized double-blind, controlled-parallel study design was employed. The measurements and interventions were performed at the Laboratory of Biomechanics of the University of L'Aquila. The HVG and LVG participants were exposed to a series of 20 trials ×10 s of synchronous whole-body vibration (WBV) with a 10-s pause between each trial and a 4-min pause after the first 10 trials. The CG participants assumed an isometric push-up position without WBV. The outcome measures were growth hormone (GH), testosterone, maximal voluntary isometric contraction during bench-press, maximal voluntary isometric contraction during handgrip, and electromyography root-mean-square (EMGrms) muscle activity (pectoralis major [PM], triceps brachii [TB], anterior deltoid [DE], and flexor carpi radialis [FCR]). The GH increased significantly over time only in the HVG (P = 0.003). Additionally, the testosterone levels changed significantly over time in the LVG (P = 0.011) and the HVG (P = 0.001). MVC during bench press decreased significantly in the LVG (P = 0.001) and the HVG (P = 0.002). In the HVG, the EMGrms decreased significantly in the TB (P = 0.006) muscle. In the LVG, the EMGrms decreased significantly in the DE (P = 0.009) and FCR (P = 0.006) muscles. Synchronous WBV acutely increased GH and testosterone serum concentrations and decreased the MVC and their respective maximal EMGrms activities, which indicated a possible central fatigue effect. Interestingly, only the GH response was dependent on the acceleration with respect to the subjects' responsiveness.

Cortisol awakening response and emotion at extreme altitudes on Mount Kangchenjunga.

PubMed

Aguilar, Raúl; Martínez, Carlos; Alvero-Cruz, José R

2017-12-24

The cortisol awakening response (CAR) was examined over a 45days stay at extreme altitudes (above of about 5500m) on Mount Kangchenjunga. The CAR refers to a peak cortisol response during the waking period that is superimposed to the diurnal rhythmicity in cortisol secretion, whose function has been proposed to be the anticipation of demands of the upcoming day (the CAR anticipation hypothesis). According to this hypothesis, we distinguished between resting days on which the expedition team engaged in routine activities in the base camp, and ascent days on which it planned to climb up a very demanding track. We were also interested in examining the association of testosterone with emotional anticipation, given the role of this steroid hormone in reward-related processes in challenge situations. Results showed that the climber group had a bigger CAR on ascent days, relative to the Sherpa group at the same altitude and the non-climber group at sea level. Several methodological issues, however, made it difficult to interpret these group differences in terms of the CAR anticipation hypothesis (e.g. a seemingly influential covariate was awakening time). Although based on tentative results, correlational and regression analyses controlling for awakening time coherently showed that the CAR was associated with anticipation of a hard day and feelings of fear, and testosterone was associated with feelings of energy and positive affect. Whether or not the anticipation of a hard day played a key role in regulation of the CAR, the observation of an intact CAR in the climber group under hypobaric hypoxia conditions would require in-depth reflection from the perspective of human adaptive evolution. Copyright © 2017 Elsevier B.V. All rights reserved.

On alternative q-Weibull and q-extreme value distributions: Properties and applications

NASA Astrophysics Data System (ADS)

Zhang, Fode; Ng, Hon Keung Tony; Shi, Yimin

2018-01-01

Tsallis statistics and Tsallis distributions have been attracting a significant amount of research work in recent years. Importantly, the Tsallis statistics, q-distributions have been applied in different disciplines. Yet, a relationship between some existing q-Weibull distributions and q-extreme value distributions that is parallel to the well-established relationship between the conventional Weibull and extreme value distributions through a logarithmic transformation has not be established. In this paper, we proposed an alternative q-Weibull distribution that leads to a q-extreme value distribution via the q-logarithm transformation. Some important properties of the proposed q-Weibull and q-extreme value distributions are studied. Maximum likelihood and least squares estimation methods are used to estimate the parameters of q-Weibull distribution and their performances are investigated through a Monte Carlo simulation study. The methodologies and the usefulness of the proposed distributions are illustrated by fitting the 2014 traffic fatalities data from The National Highway Traffic Safety Administration.

HOW DO HOSPITAL STERILISATION PROCEDURES AFFECT THE RESPONSE OF PERSONAL EXTREMITY RINGS AND OF EYE LENS TL DOSEMETERS?

PubMed

Kopeć, Renata; Bubak, Anna; Budzanowski, Maciej; Sas-Bieniarz, Anna; Szumska, Agnieszka

2016-09-01

Stringent standards of hygiene must be applied in medical institutions, especially at operating blocks or during interventional radiology procedures. Medical equipment, including personal dosemeters that have to be worn by medical staff during such procedures, needs therefore to be sterilised. In this study, the effect of various sterilisation procedures has been tested on the dose response of extremity rings and of eye lens dosemeters in which thermoluminescent (TL) detectors (of types MTS-N and MCP-N, respectively) are used. The effects of medical sterilisation procedures were studied: by chemicals, by steam or by ultraviolet (UV), on the dose assessment by extremity rings and by eye lens dosemeters. Since it often happens that a dosemeter is accidentally machine-washed together with protective clothing, the effect of laundering on dose assessment by these dosemeters was also tested. The sterilisation by chemicals is mostly safe for TL detectors assuming that the dosemeters are waterproofed. Following sterilisation by water vapour, the response of these dosemeters diminished by some 30 %, irrespectively of the period of sterilisation; therefore, this method is not recommended. UV sterilisation can be applied to EYE-D™ eye lens dosemeters if their encapsulation is in black. The accidental dosemeter laundry in a washing machine has no impact on measured dose. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Recovery of Item Parameters in the Nominal Response Model: A Comparison of Marginal Maximum Likelihood Estimation and Markov Chain Monte Carlo Estimation.

ERIC Educational Resources Information Center

Wollack, James A.; Bolt, Daniel M.; Cohen, Allan S.; Lee, Young-Sun

2002-01-01

Compared the quality of item parameter estimates for marginal maximum likelihood (MML) and Markov Chain Monte Carlo (MCMC) with the nominal response model using simulation. The quality of item parameter recovery was nearly identical for MML and MCMC, and both methods tended to produce good estimates. (SLD)

Spatiotemporal variability of extreme temperature frequency and amplitude in China

NASA Astrophysics Data System (ADS)

Zhang, Yuanjie; Gao, Zhiqiu; Pan, Zaitao; Li, Dan; Huang, Xinhui

2017-03-01

Temperature extremes in China are examined based on daily maximum and minimum temperatures from station observations and multiple global climate models. The magnitude and frequency of extremes are expressed in terms of return values and periods, respectively, estimated by the fitted Generalized Extreme Value (GEV) distribution of annual extreme temperatures. The observations suggest that changes in temperature extremes considerably exceed changes in the respective climatological means during the past five decades, with greater amplitude of increases in cold extremes than in warm extremes. The frequency of warm (cold) extremes increases (decreases) over most areas, with an increasingly faster rate as the extremity level rises. Changes in warm extremes are more dependent on the varying shape of GEV distribution than the location shift, whereas changes in cold extremes are more closely associated with the location shift. The models simulate the overall pattern of temperature extremes during 1961-1981 reasonably well in China, but they show a smaller asymmetry between changes in warm and cold extremes primarily due to their underestimation of increases in cold extremes especially over southern China. Projections from a high emission scenario show the multi-model median change in warm and cold extremes by 2040 relative to 1971 will be 2.6 °C and 2.8 °C, respectively, with the strongest changes in cold extremes shifting southward. By 2040, warm extremes at the 1971 20-year return values would occur about every three years, while the 1971 cold extremes would occur once in > 500 years.

XBeach-G: a tool for predicting gravel barrier response to extreme storm conditions

NASA Astrophysics Data System (ADS)

Masselink, Gerd; Poate, Tim; McCall, Robert; Roelvink, Dano; Russell, Paul; Davidson, Mark

2014-05-01

Gravel beaches protect low-lying back-barrier regions from flooding during storm events and their importance to society is widely acknowledged. Unfortunately, breaching and extensive storm damage has occurred at many gravel sites and this is likely to increase as a result of sea-level rise and enhanced storminess due to climate change. Limited scientific guidance is currently available to provide beach managers with operational management tools to predict the response of gravel beaches to storms. The New Understanding and Prediction of Storm Impacts on Gravel beaches (NUPSIG) project aims to improve our understanding of storm impacts on gravel coastal environments and to develop a predictive capability by modelling these impacts. The NUPSIG project uses a 5-pronged approach to address its aim: (1) analyse hydrodynamic data collected during a proto-type laboratory experiment on a gravel beach; (2) collect hydrodynamic field data on a gravel beach under a range of conditions, including storm waves with wave heights up to 3 m; (3) measure swash dynamics and beach response on 10 gravel beaches during extreme wave conditions with wave heights in excess of 3 m; (4) use the data collected under 1-3 to develop and validate a numerical model to model hydrodynamics and morphological response of gravel beaches under storm conditions; and (5) develop a tool for end-users, based on the model formulated under (4), for predicting storm response of gravel beaches and barriers. The aim of this presentation is to present the key results of the NUPSIG project and introduce the end-user tool for predicting storm response on gravel beaches. The model is based on the numerical model XBeach, and different forcing scenarios (wave and tides), barrier configurations (dimensions) and sediment characteristics are easily uploaded for model simulations using a Graphics User Interface (GUI). The model can be used to determine the vulnerability of gravel barriers to storm events, but can also be

Conditional probability of rainfall extremes across multiple durations

NASA Astrophysics Data System (ADS)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2017-04-01

The conditional probability that extreme rainfall will occur at one location given that it is occurring at another location is critical in engineering design and management circumstances including planning of evacuation routes and the sitting of emergency infrastructure. A challenge with this conditional simulation is that in many situations the interest is not so much the conditional distributions of rainfall of the same duration at two locations, but rather the conditional distribution of flooding in two neighbouring catchments, which may be influenced by rainfall of different critical durations. To deal with this challenge, a model that can consider both spatial and duration dependence of extremes is required. The aim of this research is to develop a model that can take account both spatial dependence and duration dependence into the dependence structure of extreme rainfalls. To achieve this aim, this study is a first attempt at combining extreme rainfall for multiple durations within a spatial extreme model framework based on max-stable process theory. Max-stable processes provide a general framework for modelling multivariate extremes with spatial dependence for just a single duration extreme rainfall. To achieve dependence across multiple timescales, this study proposes a new approach that includes addition elements representing duration dependence of extremes to the covariance matrix of max-stable model. To improve the efficiency of calculation, a re-parameterization proposed by Koutsoyiannis et al. (1998) is used to reduce the number of parameters necessary to be estimated. This re-parameterization enables the GEV parameters to be represented as a function of timescale. A stepwise framework has been adopted to achieve the overall aims of this research. Firstly, the re-parameterization is used to define a new set of common parameters for marginal distribution across multiple durations. Secondly, spatial interpolation of the new parameter set is used to

Causing Factors for Extreme Precipitation in the Western Saudi-Arabian Peninsula

NASA Astrophysics Data System (ADS)

Alharbi, M. M.; Leckebusch, G. C.

2015-12-01

In the western coast of Saudi Arabia the climate is in general semi-arid but extreme precipitation events occur on a regular basis: e.g., on 26th November 2009, when 122 people were killed and 350 reported missing in Jeddah following more than 90mm in just four hours. Our investigation will a) analyse major drivers of the generation of extremes and b) investigate major responsible modes of variability for the occurrence of extremes. Firstly, we present a systematic analysis of station based observations of the most relevant extreme events (1985-2013) for 5 stations (Gizan, Makkah, Jeddah, Yenbo and Wejh). Secondly, we investigate the responsible mechanism on the synoptic to large-scale leading to the generation of extremes and will analyse factors for the time variability of extreme event occurrence. Extreme events for each station are identified in the wet season (Nov-Jan): 122 events show intensity above the respective 90th percentile. The most extreme events are systematically investigated with respect to the responsible forcing conditions which we can identify as: The influence of the Soudan Low, active Red-Sea-Trough situations established via interactions with mid-latitude tropospheric wave activity, low pressure systems over the Mediterranean, the influence of the North Africa High, the Arabian Anticyclone and the influence of the Indian monsoon trough. We investigate the role of dynamical forcing factors like the STJ and the upper-troposphere geopotential conditions and the relation to smaller local low-pressure systems. By means of an empirical orthogonal function (EOF) analysis based on MSLP we investigate the possibility to objectively quantify the influence of existing major variability modes and their role for the generation of extreme precipitation events.

Extreme Weather and Climate: Workshop Report

NASA Technical Reports Server (NTRS)

Sobel, Adam; Camargo, Suzana; Debucquoy, Wim; Deodatis, George; Gerrard, Michael; Hall, Timothy; Hallman, Robert; Keenan, Jesse; Lall, Upmanu; Levy, Marc;

A Note on the Reliability Coefficients for Item Response Model-Based Ability Estimates

ERIC Educational Resources Information Center

Kim, Seonghoon

2012-01-01

Assuming item parameters on a test are known constants, the reliability coefficient for item response theory (IRT) ability estimates is defined for a population of examinees in two different ways: as (a) the product-moment correlation between ability estimates on two parallel forms of a test and (b) the squared correlation between the true…

Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Bruce T.

2015-12-11

Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantiallymore » from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have

Forecasting extreme temperature health hazards in Europe

NASA Astrophysics Data System (ADS)

Di Napoli, Claudia; Pappenberger, Florian; Cloke, Hannah L.

2017-04-01

Extreme hot temperatures, such as those experienced during a heat wave, represent a dangerous meteorological hazard to human health. Heat disorders such as sunstroke are harmful to people of all ages and responsible for excess mortality in the affected areas. In 2003 more than 50,000 people died in western and southern Europe because of a severe and sustained episode of summer heat [1]. Furthermore, according to the Intergovernmental Panel on Climate Change heat waves are expected to get more frequent in the future thus posing an increasing threat to human lives. Developing appropriate tools for extreme hot temperatures prediction is therefore mandatory to increase public preparedness and mitigate heat-induced impacts. A recent study has shown that forecasts of the Universal Thermal Climate Index (UTCI) provide a valid overview of extreme temperature health hazards on a global scale [2]. UTCI is a parameter related to the temperature of the human body and its regulatory responses to the surrounding atmospheric environment. UTCI is calculated using an advanced thermo-physiological model that includes the human heat budget, physiology and clothing. To forecast UTCI the model uses meteorological inputs, such as 2m air temperature, 2m water vapour pressure and wind velocity at body height derived from 10m wind speed, from NWP models. Here we examine the potential of UTCI as an extreme hot temperature prediction tool for the European area. UTCI forecasts calculated using above-mentioned parameters from ECMWF models are presented. The skill in predicting UTCI for medium lead times is also analysed and discussed for implementation to international health-hazard warning systems. This research is supported by the ANYWHERE project (EnhANcing emergencY management and response to extreme WeatHER and climate Events) which is funded by the European Commission's HORIZON2020 programme. [1] Koppe C. et al., Heat waves: risks and responses. World Health Organization. Health and

Method of estimating pulse response using an impedance spectrum

DOEpatents

Morrison, John L; Morrison, William H; Christophersen, Jon P; Motloch, Chester G

2014-10-21

Electrochemical Impedance Spectrum data are used to predict pulse performance of an energy storage device. The impedance spectrum may be obtained in-situ. A simulation waveform includes a pulse wave with a period greater than or equal to the lowest frequency used in the impedance measurement. Fourier series coefficients of the pulse train can be obtained. The number of harmonic constituents in the Fourier series are selected so as to appropriately resolve the response, but the maximum frequency should be less than or equal to the highest frequency used in the impedance measurement. Using a current pulse as an example, the Fourier coefficients of the pulse are multiplied by the impedance spectrum at corresponding frequencies to obtain Fourier coefficients of the voltage response to the desired pulse. The Fourier coefficients of the response are then summed and reassembled to obtain the overall time domain estimate of the voltage using the Fourier series analysis.

Extreme Magnitude Earthquakes and their Economical Consequences

NASA Astrophysics Data System (ADS)

Chavez, M.; Cabrera, E.; Ashworth, M.; Perea, N.; Emerson, D.; Salazar, A.; Moulinec, C.

2011-12-01

The frequency of occurrence of extreme magnitude earthquakes varies from tens to thousands of years, depending on the considered seismotectonic region of the world. However, the human and economic losses when their hypocenters are located in the neighborhood of heavily populated and/or industrialized regions, can be very large, as recently observed for the 1985 Mw 8.01 Michoacan, Mexico and the 2011 Mw 9 Tohoku, Japan, earthquakes. Herewith, a methodology is proposed in order to estimate the probability of exceedance of: the intensities of extreme magnitude earthquakes, PEI and of their direct economical consequences PEDEC. The PEI are obtained by using supercomputing facilities to generate samples of the 3D propagation of extreme earthquake plausible scenarios, and enlarge those samples by Monte Carlo simulation. The PEDEC are computed by using appropriate vulnerability functions combined with the scenario intensity samples, and Monte Carlo simulation. An example of the application of the methodology due to the potential occurrence of extreme Mw 8.5 subduction earthquakes on Mexico City is presented.

Extreme Sea Conditions in Shallow Water: Estimation based on in-situ measurements

NASA Astrophysics Data System (ADS)

Le Crom, Izan; Saulnier, Jean-Baptiste

2013-04-01

The design of marine renewable energy devices and components is based, among others, on the assessment of the environmental extreme conditions (winds, currents, waves, and water level) that must be combined together in order to evaluate the maximal loads on a floating/fixed structure, and on the anchoring system over a determined return period. Measuring devices are generally deployed at sea over relatively short durations (a few months to a few years), typically when describing water free surface elevation, and extrapolation methods based on hindcast data (and therefore on wave simulation models) have to be used. How to combine, in a realistic way, the action of the different loads (winds and waves for instance) and which correlation of return periods should be used are highly topical issues. However, the assessment of the extreme condition itself remains a not-fully-solved, crucial, and sensitive task. Above all in shallow water, extreme wave height, Hmax, is the most significant contribution in the dimensioning process of EMR devices. As a case study, existing methodologies for deep water have been applied to SEMREV, the French marine energy test site. The interest of this study, especially at this location, goes beyond the simple application to SEMREV's WEC and floating wind turbines deployment as it could also be extended to the Banc de Guérande offshore wind farm that are planned close by. More generally to pipes and communication cables as it is a redundant problematic. The paper will first present the existing measurements (wave and wind on site), the prediction chain that has been developed via wave models, the extrapolation methods applied to hindcast data, and will try to formulate recommendations for improving this assessment in shallow water.

Extreme weather events and infectious disease outbreaks.

PubMed

McMichael, Anthony J

2015-01-01

Human-driven climatic changes will fundamentally influence patterns of human health, including infectious disease clusters and epidemics following extreme weather events. Extreme weather events are projected to increase further with the advance of human-driven climate change. Both recent and historical experiences indicate that infectious disease outbreaks very often follow extreme weather events, as microbes, vectors and reservoir animal hosts exploit the disrupted social and environmental conditions of extreme weather events. This review article examines infectious disease risks associated with extreme weather events; it draws on recent experiences including Hurricane Katrina in 2005 and the 2010 Pakistan mega-floods, and historical examples from previous centuries of epidemics and 'pestilence' associated with extreme weather disasters and climatic changes. A fuller understanding of climatic change, the precursors and triggers of extreme weather events and health consequences is needed in order to anticipate and respond to the infectious disease risks associated with human-driven climate change. Post-event risks to human health can be constrained, nonetheless, by reducing background rates of persistent infection, preparatory action such as coordinated disease surveillance and vaccination coverage, and strengthened disaster response. In the face of changing climate and weather conditions, it is critically important to think in ecological terms about the determinants of health, disease and death in human populations.

Accurate and efficient calculation of response times for groundwater flow

NASA Astrophysics Data System (ADS)

Carr, Elliot J.; Simpson, Matthew J.

2018-03-01

We study measures of the amount of time required for transient flow in heterogeneous porous media to effectively reach steady state, also known as the response time. Here, we develop a new approach that extends the concept of mean action time. Previous applications of the theory of mean action time to estimate the response time use the first two central moments of the probability density function associated with the transition from the initial condition, at t = 0, to the steady state condition that arises in the long time limit, as t → ∞ . This previous approach leads to a computationally convenient estimation of the response time, but the accuracy can be poor. Here, we outline a powerful extension using the first k raw moments, showing how to produce an extremely accurate estimate by making use of asymptotic properties of the cumulative distribution function. Results are validated using an existing laboratory-scale data set describing flow in a homogeneous porous medium. In addition, we demonstrate how the results also apply to flow in heterogeneous porous media. Overall, the new method is: (i) extremely accurate; and (ii) computationally inexpensive. In fact, the computational cost of the new method is orders of magnitude less than the computational effort required to study the response time by solving the transient flow equation. Furthermore, the approach provides a rigorous mathematical connection with the heuristic argument that the response time for flow in a homogeneous porous medium is proportional to L2 / D , where L is a relevant length scale, and D is the aquifer diffusivity. Here, we extend such heuristic arguments by providing a clear mathematical definition of the proportionality constant.

The Response of Different Audiences to Place-based Communication about the Role of Climate Change in Extreme Weather Events

NASA Astrophysics Data System (ADS)

Halperin, A.; Walton, P.

2015-12-01

As the science of extreme event attribution grows, there is an increasing need to understand how the public responds to this type of climate change communication. Extreme event attribution has the unprecedented potential to locate the effects of climate change in the here and now, but there is little information about how different facets of the public might respond to these local framings of climate change. Drawing on theories of place attachment and psychological distance, this paper explores how people with different beliefs and values shift their willingness to mitigate and adapt to climate change in response to local or global communication of climate change impacts. Results will be presented from a recent survey of over 600 Californians who were each presented with one of three experimental conditions: 1) a local framing of the role of climate change in the California drought 2) a global framing of climate change and droughts worldwide, or 3) a control condition of no text. Participants were categorized into groups based on their prior beliefs about climate change according to the Six Americas classification scheme (Leiserowitz et al., 2011). The results from the survey in conjunction with qualitative results from follow-up interviews shed insight into the importance of place in communicating climate change for people in each of the Six Americas. Additional results examine the role of gender and political affiliation in mediating responses to climate change communication. Despite research that advocates unequivocally for local framing of climate change, this study offers a more nuanced perspective of under which circumstances extreme event attribution might be an effective tool for changing behaviors. These results could be useful for scientists who wish to gain a better understanding of how their event attribution research is perceived or for educators who want to target their message to audiences where it could have the most impact.

Extreme river flow dependence in Northern Scotland

NASA Astrophysics Data System (ADS)

Villoria, M. Franco; Scott, M.; Hoey, T.; Fischbacher-Smith, D.

2012-04-01

Various methods for the spatial analysis of hydrologic data have been developed recently. Here we present results using the conditional probability approach proposed by Keef et al. [Appl. Stat. (2009): 58,601-18] to investigate spatial interdependence in extreme river flows in Scotland. This approach does not require the specification of a correlation function, being mostly suitable for relatively small geographical areas. The work is motivated by the Flood Risk Management Act (Scotland (2009)) which requires maps of flood risk that take account of spatial dependence in extreme river flow. The method is based on two conditional measures of spatial flood risk: firstly the conditional probability PC(p) that a set of sites Y = (Y 1,...,Y d) within a region C of interest exceed a flow threshold Qp at time t (or any lag of t), given that in the specified conditioning site X > Qp; and, secondly the expected number of sites within C that will exceed a flow Qp on average (given that X > Qp). The conditional probabilities are estimated using the conditional distribution of Y |X = x (for large x), which can be modeled using a semi-parametric approach (Heffernan and Tawn [Roy. Statist. Soc. Ser. B (2004): 66,497-546]). Once the model is fitted, pseudo-samples can be generated to estimate functionals of the joint tails of the distribution of (Y,X). Conditional return level plots were directly compared to traditional return level plots thus improving our understanding of the dependence structure of extreme river flow events. Confidence intervals were calculated using block bootstrapping methods (100 replicates). We report results from applying this approach to a set of four rivers (Dulnain, Lossie, Ewe and Ness) in Northern Scotland. These sites were chosen based on data quality, spatial location and catchment characteristics. The river Ness, being the largest (catchment size 1839.1km2) was chosen as the conditioning river. Both the Ewe (441.1km2) and Ness catchments have

Defining Extreme Events: A Cross-Disciplinary Review

NASA Astrophysics Data System (ADS)

McPhillips, Lauren E.; Chang, Heejun; Chester, Mikhail V.; Depietri, Yaella; Friedman, Erin; Grimm, Nancy B.; Kominoski, John S.; McPhearson, Timon; Méndez-Lázaro, Pablo; Rosi, Emma J.; Shafiei Shiva, Javad

2018-03-01

Extreme events are of interest worldwide given their potential for substantial impacts on social, ecological, and technical systems. Many climate-related extreme events are increasing in frequency and/or magnitude due to anthropogenic climate change, and there is increased potential for impacts due to the location of urbanization and the expansion of urban centers and infrastructures. Many disciplines are engaged in research and management of these events. However, a lack of coherence exists in what constitutes and defines an extreme event across these fields, which impedes our ability to holistically understand and manage these events. Here, we review 10 years of academic literature and use text analysis to elucidate how six major disciplines—climatology, earth sciences, ecology, engineering, hydrology, and social sciences—define and communicate extreme events. Our results highlight critical disciplinary differences in the language used to communicate extreme events. Additionally, we found a wide range in definitions and thresholds, with more than half of examined papers not providing an explicit definition, and disagreement over whether impacts are included in the definition. We urge distinction between extreme events and their impacts, so that we can better assess when responses to extreme events have actually enhanced resilience. Additionally, we suggest that all researchers and managers of extreme events be more explicit in their definition of such events as well as be more cognizant of how they are communicating extreme events. We believe clearer and more consistent definitions and communication can support transdisciplinary understanding and management of extreme events.

Extreme Response in Tension and Compression of Tantalum

NASA Astrophysics Data System (ADS)

Remington, Tane Perry

This research on a model bcc metal, tantalum, has three components: the study of tensile failure; defects generated under a nanoindenter; and dislocation velocities in an extreme regime generated by pulsed lasers. The processes of dynamic failure by spalling were established in nano, poly, and mono crystalline tantalum in recovery experiments following laser compression and release. The process of spall was characterized by different techniques: optical microscopy, scanning electron microscopy, microcomputerized tomography and electron backscatter diffraction. Additionally, the pull back signal was measured by VISAR and the pressure decay was compared with HYADES simulations. There are clear differences in the microscopic fracture mechanisms, dictated by the grain sizes. In the nano and poly crystals, spalling occurred by ductile fracture favoring grain boundaries. In the monocrystals, grain boundaries are absent, and the process was of ductile failure by void initiation, growth and coalescence. The spall strength of single crystalline tantalum was higher than the poly and nano crystals. It was experimentally confirmed that spall strength in tantalum increases with strain rate. In order to generate dislocations close to the surface, single crystalline tantalum with orientations (100), (110) and (111) was nanoindented with a Berkovich tip. Atomic force microscopy showed pile-ups of dislocations around the perimeter of the nanoindentations. Sections of nanoindentations were focused ion beam cut into transmission electron microscope foils. The mechanisms of deformation under a nanoindentation in tantalum were identified and quantified. Molecular dynamics simulations were conducted and the simulated plastic deformation proceeds by the formation of nanotwins, which rapidly evolve into shear dislocation loops. Dislocation densities under the indenter were estimated experimentally (~1.2 x 1015 m-2), by MD (~7 x1015 m-2) and through an analytical calculation (2.6--19 x10

Extreme oceanographic forcing and coastal response due to the 2015–2016 El Niño

PubMed Central

Barnard, Patrick L.; Hoover, Daniel; Hubbard, David M.; Snyder, Alex; Ludka, Bonnie C.; Allan, Jonathan; Kaminsky, George M.; Ruggiero, Peter; Gallien, Timu W.; Gabel, Laura; McCandless, Diana; Weiner, Heather M.; Cohn, Nicholas; Anderson, Dylan L.; Serafin, Katherine A.

2017-01-01

The El Niño-Southern Oscillation is the dominant mode of interannual climate variability across the Pacific Ocean basin, with influence on the global climate. The two end members of the cycle, El Niño and La Niña, force anomalous oceanographic conditions and coastal response along the Pacific margin, exposing many heavily populated regions to increased coastal flooding and erosion hazards. However, a quantitative record of coastal impacts is spatially limited and temporally restricted to only the most recent events. Here we report on the oceanographic forcing and coastal response of the 2015–2016 El Niño, one of the strongest of the last 145 years. We show that winter wave energy equalled or exceeded measured historical maxima across the US West Coast, corresponding to anomalously large beach erosion across the region. Shorelines in many areas retreated beyond previously measured landward extremes, particularly along the sediment-starved California coast. PMID:28195580

Extreme oceanographic forcing and coastal response due to the 2015–2016 El Niño

USGS Publications Warehouse

Barnard, Patrick; Hoover, Daniel J.; Hubbard, David M.; Snyder, Alexander; Ludka, Bonnie C.; Allan, Jonathan; Kaminsky, George M.; Ruggiero,; Gallien, Timu W.; Gabel, Laura; McCandless, Diana; Weiner, Heather M.; Cohn, Nicholas; Anderson, Dylan L.; Serafin, Katherine A.

2017-01-01

The El Niño-Southern Oscillation is the dominant mode of interannual climate variability across the Pacific Ocean basin, with influence on the global climate. The two end members of the cycle, El Niño and La Niña, force anomalous oceanographic conditions and coastal response along the Pacific margin, exposing many heavily populated regions to increased coastal flooding and erosion hazards. However, a quantitative record of coastal impacts is spatially limited and temporally restricted to only the most recent events. Here we report on the oceanographic forcing and coastal response of the 2015–2016 El Niño, one of the strongest of the last 145 years. We show that winter wave energy equalled or exceeded measured historical maxima across the US West Coast, corresponding to anomalously large beach erosion across the region. Shorelines in many areas retreated beyond previously measured landward extremes, particularly along the sediment-starved California coast.

Controls on coastal dune morphology, shoreline erosion and barrier island response to extreme storms

USGS Publications Warehouse

Houser, C.; Hapke, C.; Hamilton, S.

2008-01-01

The response of a barrier island to an extreme storm depends in part on the surge elevation relative to the height and extent of the foredunes which can exhibit considerable variability alongshore. While it is recognized that alongshore variations in dune height and width direct barrier island response to storm surge, the underlying causes of the alongshore variation remain poorly understood. This study examines the alongshore variation in dune morphology along a 11 km stretch of Santa Rosa Island in northwest Florida and relates the variation in morphology to the response of the island during Hurricane Ivan and historic and storm-related rates of shoreline erosion. The morphology of the foredune and backbarrier dunes was characterized before and after Hurricane Ivan using Empirical Orthogonal Function (EOF) analysis and related through Canonical Correlation Analysis (CCA). The height and extent of the foredune, and the presence and relative location of the backbarrier dunes, varied alongshore at discrete length scales (of ~ 750, 1450 and 4550 m) that are statistically significant at the 95% confidence level. Cospectral analysis suggests that the variation in dune morphology is correlated with transverse ridges on the inner-shelf, the backbarrier cuspate headlands, and the historical and storm-related trends in shoreline change. Sections of the coast with little to no dune development before Hurricane Ivan were observed in the narrowest portions of the island (between headlands), west of the transverse ridges. Overwash penetration tended to be larger in these areas and island breaching was common, leaving the surface close to the watertable and covered by a lag of shell and gravel. In contrast, large foredunes and the backbarrier dunes were observed at the widest sections of the island (the cuspate headlands) and at crest of the transverse ridges. Due to the large dunes and the presence of the backbarrier dunes, these areas experienced less overwash penetration

Estimation of toxicity using the Toxicity Estimation Software Tool (TEST)

EPA Science Inventory

Tens of thousands of chemicals are currently in commerce, and hundreds more are introduced every year. Since experimental measurements of toxicity are extremely time consuming and expensive, it is imperative that alternative methods to estimate toxicity are developed.

Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

PubMed Central

Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

2013-01-01

Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

41 CFR 102-80.50 - Are Federal agencies responsible for identifying/estimating risks and for appropriate risk...

Code of Federal Regulations, 2010 CFR

2010-07-01

... identify and estimate safety and environmental management risks and appropriate risk reduction strategies... responsible for identifying/estimating risks and for appropriate risk reduction strategies? 102-80.50 Section... Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for...

Estimating synaptic parameters from mean, variance, and covariance in trains of synaptic responses.

PubMed

Scheuss, V; Neher, E

2001-10-01

Fluctuation analysis of synaptic transmission using the variance-mean approach has been restricted in the past to steady-state responses. Here we extend this method to short repetitive trains of synaptic responses, during which the response amplitudes are not stationary. We consider intervals between trains, long enough so that the system is in the same average state at the beginning of each train. This allows analysis of ensemble means and variances for each response in a train separately. Thus, modifications in synaptic efficacy during short-term plasticity can be attributed to changes in synaptic parameters. In addition, we provide practical guidelines for the analysis of the covariance between successive responses in trains. Explicit algorithms to estimate synaptic parameters are derived and tested by Monte Carlo simulations on the basis of a binomial model of synaptic transmission, allowing for quantal variability, heterogeneity in the release probability, and postsynaptic receptor saturation and desensitization. We find that the combined analysis of variance and covariance is advantageous in yielding an estimate for the number of release sites, which is independent of heterogeneity in the release probability under certain conditions. Furthermore, it allows one to calculate the apparent quantal size for each response in a sequence of stimuli.

Short-term cropland responses to temperature extreme events during late winter

NASA Astrophysics Data System (ADS)

De Simon, G.; Alberti, G.; Delle Vedove, G.; Peressotti, A.; Zaldei, A.; Miglietta, F.

2013-04-01

In recent years, several studies have focused on terrestrial ecosystem response to extreme events. Most of this research has been conducted in natural ecosystems, but few have considered agro-ecosystems. In this study, we investigated the impact of a manipulated warmer or cooler late winter-early spring on the carbon budget and final harvest of a soybean crop (Glycine max (L.) Merr.). Soil temperature was altered by manipulating soil albedo by covering the soil surface with a layer of inert silica gravel. We tested three treatments: cooling (Co), warming (W), mix (M) and control (C). An automated system continuously measured soil heterotrophic respiration (Rh), soil temperature profiles, and soil water content across the entire year in each plot. Phenological phases were periodically assessed and final harvest was measured in each plot. Results showed that treatments had only a transient effect on daily Rh rates which did not result in a total annual carbon budget significantly different from control, even though cooling showed a significant reduction in final harvest. We also observed anticipation in seed germination in both W and M treatments and a delay in germination for Co. Moreover, plant density and growth increased in W and M and decreased in Co.

Seasonal extreme value statistics for precipitation in Germany

NASA Astrophysics Data System (ADS)

Fischer, Madlen; Rust, Henning W.; Ulbrich, Uwe

2013-04-01

Extreme precipitation has a strong influence on environment, society and economy. It leads to large damage due to floods, mudslides, increased erosion or hail. While standard annual return levels are important for hydrological structures, seasonaly resolved return levels provide additional information for risk managment, e.g., for the agricultural sector. For 1208 stations in Germany, we calculate monthly resolved return levels. Instead of estimating parameters separately for every month in the year, we use a non-stationary approach and benefit from smoothly varying return levels throughout the year. This natural approach is more suitable to characterise seasonal variability of extreme precipitation and leads to more accurate return level estimates. Harmonic functions of different orders are used to describe the seasonal variation of GEV parameters and crossvalidation is used to determine a suitable model forall stations. Finally particularly vulnerable regions and associated month are investigated in more detail.

The application of the statistical theory of extreme values to gust-load problems

NASA Technical Reports Server (NTRS)

Press, Harry

1950-01-01

An analysis is presented which indicates that the statistical theory of extreme values is applicable to the problems of predicting the frequency of encountering the larger gust loads and gust velocities for both specific test conditions as well as commercial transport operations. The extreme-value theory provides an analytic form for the distributions of maximum values of gust load and velocity. Methods of fitting the distribution are given along with a method of estimating the reliability of the predictions. The theory of extreme values is applied to available load data from commercial transport operations. The results indicate that the estimates of the frequency of encountering the larger loads are more consistent with the data and more reliable than those obtained in previous analyses. (author)

Extreme Rainfall Analysis using Bayesian Hierarchical Modeling in the Willamette River Basin, Oregon

NASA Astrophysics Data System (ADS)

Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

2016-12-01

We present preliminary results of ongoing research directed at evaluating the worth of including various covariate data to support extreme rainfall analysis in the Willamette River basin using Bayesian hierarchical modeling (BHM). We also compare the BHM derived extreme rainfall estimates with their respective counterparts obtained from a traditional regional frequency analysis (RFA) using the same set of rain gage extreme rainfall data. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams in the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two-thirds of Oregon's population and 20 of the 25 most populous cities in the state. Extreme rainfall estimates are required to support risk-informed hydrologic analyses for these projects as part of the USACE Dam Safety Program. We analyze daily annual rainfall maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme rainfall by return level. Our intent is to profile for the USACE an alternate methodology to a RFA which was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. Unlike RFA, the advantage of a BHM-based analysis of hydrometeorological extremes is its ability to account for non-stationarity while providing robust estimates of uncertainty. BHM also allows for the inclusion of geographical and climatological factors which we show for the WRB influence regional rainfall extremes. Moreover, the Bayesian framework permits one to combine additional data types into the analysis; for example, information derived via elicitation and causal information expansion data, both being additional opportunities for future related research.

Subadditive responses to extremely short blue and green pulsed light on visual evoked potentials, pupillary constriction and electroretinograms.

PubMed

Lee, Soomin; Uchiyama, Yuria; Shimomura, Yoshihiro; Katsuura, Tetsuo

2017-11-17

The simultaneous exposure to blue and green light was reported to result in less melatonin suppression than monochromatic exposure to blue or green light. Here, we conducted an experiment using extremely short blue- and green-pulsed light to examine their visual and nonvisual effects on visual evoked potentials (VEPs), pupillary constriction, electroretinograms (ERGs), and subjective evaluations. Twelve adult male subjects were exposed to three light conditions: blue-pulsed light (2.5-ms pulse width), green-pulsed light (2.5-ms pulse width), and simultaneous blue- and green-pulsed light with white background light. We measured the subject's pupil diameter three times in each condition. Then, after 10 min of rest, the subject was exposed to the same three light conditions. We measured the averaged ERG and VEP during 210 pulsed-light exposures in each condition. We also determined subjective evaluations using a visual analog scale (VAS) method. The pupillary constriction during the simultaneous exposure to blue- and green-pulsed light was significantly lower than that during the blue-pulsed light exposure despite the double irradiance intensity of the combination. We also found that the b/|a| wave of the ERGs during the simultaneous exposure to blue- and green-pulsed light was lower than that during the blue-pulsed light exposure. We confirmed the subadditive response to pulsed light on pupillary constriction and ERG. However, the P100 of the VEPs during the blue-pulsed light were smaller than those during the simultaneous blue- and green-pulsed light and green-pulsed light, indicating that the P100 amplitude might depend on the luminance of light. Our findings demonstrated the effect of the subadditive response to extremely short pulsed light on pupillary constriction and ERG responses. The effects on ipRGCs by the blue-pulsed light exposure are apparently reduced by the simultaneous irradiation of green light. The blue versus yellow (b/y) bipolar cells in the

Water Cycle Extremes: from Observations to Decisions

NASA Astrophysics Data System (ADS)

Lawford, R. G.; Unninayar, S.; Berod, D.

2015-12-01

Extremes in the water cycle (droughts and floods) pose major challenges for water resource managers and emergency services. These challenges arise from observational and prediction systems, advisory services, impact reduction strategies, and cleanup and recovery operations. The Group on Earth Observations (GEO) through its Water Strategy ("GEOSS Water Strategy: from observations to decisions") is seeking to provide systems that will enable its members to more effectively meet their information needs prior to and during an extreme event. This presentation reviews the wide range of impacts that arise from extremes in the water cycle and the types of data and information needed to plan for and respond to these extreme events. It identifies the capabilities and limitations of current observational and analysis systems in defining the scale, timing, intensity and impacts of water cycle extremes and in directing society's response to them. This summary represents an early preliminary assessment of the global and regional information needs of water resource managers and begins to outline a strategy within GEO for using Earth Observations and ancillary information to address these needs.

Using prior information to separate the temperature response to greenhouse gas forcing from that of aerosols - Estimating the transient climate response

NASA Astrophysics Data System (ADS)

Schurer, Andrew; Hegerl, Gabriele

2016-04-01

The evaluation of the transient climate response (TCR) is of critical importance to policy makers as it can be used to calculate a simple estimate of the expected warming given predicted greenhouse gas emissions. Previous studies using optimal detection techniques have been able to estimate a TCR value from the historic record using simulations from some of the models which took part in the Coupled Model Intercomparison Project Phase 5 (CMIP5) but have found that others give unconstrained results. At least partly this is due to degeneracy between the greenhouse gas and aerosol signals which makes separation of the temperature response to these forcings problematic. Here we re-visit this important topic by using an adapted optimal detection analysis within a Bayesian framework. We account for observational uncertainty by the use of an ensemble of instrumental observations, and model uncertainty by combining the results from several different models. This framework allows the use of prior information which is found to help separate the response to the different forcings leading to a more constrained estimate of TCR.

Materials and noncoplanar mesh designs for integrated circuits with linear elastic responses to extreme mechanical deformations

PubMed Central

Kim, Dae-Hyeong; Song, Jizhou; Choi, Won Mook; Kim, Hoon-Sik; Kim, Rak-Hwan; Liu, Zhuangjian; Huang, Yonggang Y.; Hwang, Keh-Chih; Zhang, Yong-wei; Rogers, John A.

2008-01-01

Electronic systems that offer elastic mechanical responses to high-strain deformations are of growing interest because of their ability to enable new biomedical devices and other applications whose requirements are impossible to satisfy with conventional wafer-based technologies or even with those that offer simple bendability. This article introduces materials and mechanical design strategies for classes of electronic circuits that offer extremely high stretchability, enabling them to accommodate even demanding configurations such as corkscrew twists with tight pitch (e.g., 90° in ≈1 cm) and linear stretching to “rubber-band” levels of strain (e.g., up to ≈140%). The use of single crystalline silicon nanomaterials for the semiconductor provides performance in stretchable complementary metal-oxide-semiconductor (CMOS) integrated circuits approaching that of conventional devices with comparable feature sizes formed on silicon wafers. Comprehensive theoretical studies of the mechanics reveal the way in which the structural designs enable these extreme mechanical properties without fracturing the intrinsically brittle active materials or even inducing significant changes in their electrical properties. The results, as demonstrated through electrical measurements of arrays of transistors, CMOS inverters, ring oscillators, and differential amplifiers, suggest a valuable route to high-performance stretchable electronics. PMID:19015528

Extreme precipitation response to climate perturbations in an atmospheric mesoscale model

NASA Astrophysics Data System (ADS)

Attema, Jisk J.; Loriaux, Jessica M.; Lenderink, Geert

2014-01-01

Observations of extreme (sub-)hourly precipitation at mid-latitudes show a large dependency on the dew point temperature often close to 14% per degree—2 times the dependency of the specific humidity on dew point temperature which is given by the Clausius-Clapeyron (CC) relation. By simulating a selection of 11 cases over the Netherlands characterized by intense showers, we investigate this behavior in the non-hydrostatic weather prediction model Harmonie at a resolution of 2.5 km. These experiments are repeated using perturbations of the atmospheric profiles of temperature and humidity: (i) using an idealized approach with a 2° warmer (colder) atmosphere assuming constant relative humidity, and (ii) using changes in temperature and humidity derived from a long climate change simulation at 2° global warming. All perturbations have a difference in the local dew point temperature compared to the reference of approximately 2°. Differences are considerable between the cases, with dependencies ranging from almost zero to an increase of 18% per degree rise of the dew point temperature. On average however, we find an increase of extreme precipitation intensity of 11% per degree for the idealized perturbation, and 9% per degree for the climate change perturbation. For the most extreme events these dependencies appear to approach a rate of 11-14% per degree, in closer agreement with the observed relation.

Consequences of Ignoring Guessing when Estimating the Latent Density in Item Response Theory

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters. In extant Monte Carlo evaluations of RC-IRT, the item response function (IRF) used to fit the data is the same one used to generate the data. The present simulation study examines RC-IRT when the IRF is imperfectly…

How can streamflow and climate-landscape data be used to estimate baseflow mean response time?

NASA Astrophysics Data System (ADS)

Zhang, Runrun; Chen, Xi; Zhang, Zhicai; Soulsby, Chris; Gao, Man

2018-02-01

Mean response time (MRT) is a metric describing the propagation of catchment hydraulic behavior that reflects both hydro-climatic conditions and catchment characteristics. To provide a comprehensive understanding of catchment response over a longer-time scale for hydraulic processes, the MRT function for baseflow generation was derived using an instantaneous unit hydrograph (IUH) model that describes the subsurface response to effective rainfall inputs. IUH parameters were estimated based on the "match test" between the autocorrelation function (ACFs) derived from the filtered base flow time series and from the IUH parameters, under the GLUE framework. Regionalization of MRT was conducted using estimates and hydroclimate-landscape indices in 22 sub-basins of the Jinghe River Basin (JRB) in the Loess Plateau of northwest China. Results indicate there is strong equifinality in determination of the best parameter sets but the median values of the MRT estimates are relatively stable in the acceptable range of the parameters. MRTs vary markedly over the studied sub-basins, ranging from tens of days to more than a year. Climate, topography and geomorphology were identified as three first-order controls on recharge-baseflow response processes. Human activities involving the cultivation of permanent crops may elongate the baseflow MRT and hence increase the dynamic storage. Cross validation suggests the model can be used to estimate MRTs in ungauged catchments in similar regions of throughout the Loess Plateau. The proposed method provides a systematic approach for MRT estimation and regionalization in terms of hydroclimate and catchment characteristics, which is helpful in the sustainable water resources utilization and ecological protection in the Loess Plateau.

Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graf, Peter; Damiani, Rick R.; Dykes, Katherine

2017-01-09

A new adaptive stratified importance sampling (ASIS) method is proposed as an alternative approach for the calculation of the 50 year extreme load under operational conditions, as in design load case 1.1 of the the International Electrotechnical Commission design standard. ASIS combines elements of the binning and extrapolation technique, currently described by the standard, and of the importance sampling (IS) method to estimate load probability of exceedances (POEs). Whereas a Monte Carlo (MC) approach would lead to the sought level of POE with a daunting number of simulations, IS-based techniques are promising as they target the sampling of the inputmore » parameters on the parts of the distributions that are most responsible for the extreme loads, thus reducing the number of runs required. We compared the various methods on select load channels as output from FAST, an aero-hydro-servo-elastic tool for the design and analysis of wind turbines developed by the National Renewable Energy Laboratory (NREL). Our newly devised method, although still in its infancy in terms of tuning of the subparameters, is comparable to the others in terms of load estimation and its variance versus computational cost, and offers great promise going forward due to the incorporation of adaptivity into the already powerful importance sampling concept.« less

Lower extremity finite element model for crash simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schauer, D.A.; Perfect, S.A.

1996-03-01

A lower extremity model has been developed to study occupant injury mechanisms of the major bones and ligamentous soft tissues resulting from vehicle collisions. The model is based on anatomically correct digitized bone surfaces of the pelvis, femur, patella and the tibia. Many muscles, tendons and ligaments were incrementally added to the basic bone model. We have simulated two types of occupant loading that occur in a crash environment using a non-linear large deformation finite element code. The modeling approach assumed that the leg was passive during its response to the excitation, that is, no active muscular contraction and thereforemore » no active change in limb stiffness. The approach recognized that the most important contributions of the muscles to the lower extremity response are their ability to define and modify the impedance of the limb. When nonlinear material behavior in a component of the leg model was deemed important to response, a nonlinear constitutive model was incorporated. The accuracy of these assumptions can be verified only through a review of analysis results and careful comparison with test data. As currently defined, the model meets the objective for which it was created. Much work remains to be done, both from modeling and analysis perspectives, before the model can be considered complete. The model implements a modeling philosophy that can accurately capture both kinematic and kinetic response of the lower limb. We have demonstrated that the lower extremity model is a valuable tool for understanding the injury processes and mechanisms. We are now in a position to extend the computer simulation to investigate the clinical fracture patterns observed in actual crashes. Additional experience with this model will enable us to make a statement on what measures are needed to significantly reduce lower extremity injuries in vehicle crashes. 6 refs.« less

Modelling hydrological extremes under non-stationary conditions using climate covariates

NASA Astrophysics Data System (ADS)

Vasiliades, Lampros; Galiatsatou, Panagiota; Loukas, Athanasios

2013-04-01

Extreme value theory is a probabilistic theory that can interpret the future probabilities of occurrence of extreme events (e.g. extreme precipitation and streamflow) using past observed records. Traditionally, extreme value theory requires the assumption of temporal stationarity. This assumption implies that the historical patterns of recurrence of extreme events are static over time. However, the hydroclimatic system is nonstationary on time scales that are relevant to extreme value analysis, due to human-mediated and natural environmental change. In this study the generalized extreme value (GEV) distribution is used to assess nonstationarity in annual maximum daily rainfall and streamflow timeseries at selected meteorological and hydrometric stations in Greece and Cyprus. The GEV distribution parameters (location, scale, and shape) are specified as functions of time-varying covariates and estimated using the conditional density network (CDN) as proposed by Cannon (2010). The CDN is a probabilistic extension of the multilayer perceptron neural network. Model parameters are estimated via the generalized maximum likelihood (GML) approach using the quasi-Newton BFGS optimization algorithm, and the appropriate GEV-CDN model architecture for the selected meteorological and hydrometric stations is selected by fitting increasingly complicated models and choosing the one that minimizes the Akaike information criterion with small sample size correction. For all case studies in Greece and Cyprus different formulations are tested with combinational cases of stationary and nonstationary parameters of the GEV distribution, linear and non-linear architecture of the CDN and combinations of the input climatic covariates. Climatic indices such as the Southern Oscillation Index (SOI), which describes atmospheric circulation in the eastern tropical pacific related to El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) index that varies on an interdecadal

A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence

PubMed Central

Spain, S L; Pedroso, I; Kadeva, N; Miller, M B; Iacono, W G; McGue, M; Stergiakouli, E; Smith, G D; Putallaz, M; Lubinski, D; Meaburn, E L; Plomin, R; Simpson, M A

2016-01-01

Although individual differences in intelligence (general cognitive ability) are highly heritable, molecular genetic analyses to date have had limited success in identifying specific loci responsible for its heritability. This study is the first to investigate exome variation in individuals of extremely high intelligence. Under the quantitative genetic model, sampling from the high extreme of the distribution should provide increased power to detect associations. We therefore performed a case–control association analysis with 1409 individuals drawn from the top 0.0003 (IQ >170) of the population distribution of intelligence and 3253 unselected population-based controls. Our analysis focused on putative functional exonic variants assayed on the Illumina HumanExome BeadChip. We did not observe any individual protein-altering variants that are reproducibly associated with extremely high intelligence and within the entire distribution of intelligence. Moreover, no significant associations were found for multiple rare alleles within individual genes. However, analyses using genome-wide similarity between unrelated individuals (genome-wide complex trait analysis) indicate that the genotyped functional protein-altering variation yields a heritability estimate of 17.4% (s.e. 1.7%) based on a liability model. In addition, investigation of nominally significant associations revealed fewer rare alleles associated with extremely high intelligence than would be expected under the null hypothesis. This observation is consistent with the hypothesis that rare functional alleles are more frequently detrimental than beneficial to intelligence. PMID:26239293

A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence.

PubMed

Spain, S L; Pedroso, I; Kadeva, N; Miller, M B; Iacono, W G; McGue, M; Stergiakouli, E; Davey Smith, G; Putallaz, M; Lubinski, D; Meaburn, E L; Plomin, R; Simpson, M A

2016-08-01

Although individual differences in intelligence (general cognitive ability) are highly heritable, molecular genetic analyses to date have had limited success in identifying specific loci responsible for its heritability. This study is the first to investigate exome variation in individuals of extremely high intelligence. Under the quantitative genetic model, sampling from the high extreme of the distribution should provide increased power to detect associations. We therefore performed a case-control association analysis with 1409 individuals drawn from the top 0.0003 (IQ >170) of the population distribution of intelligence and 3253 unselected population-based controls. Our analysis focused on putative functional exonic variants assayed on the Illumina HumanExome BeadChip. We did not observe any individual protein-altering variants that are reproducibly associated with extremely high intelligence and within the entire distribution of intelligence. Moreover, no significant associations were found for multiple rare alleles within individual genes. However, analyses using genome-wide similarity between unrelated individuals (genome-wide complex trait analysis) indicate that the genotyped functional protein-altering variation yields a heritability estimate of 17.4% (s.e. 1.7%) based on a liability model. In addition, investigation of nominally significant associations revealed fewer rare alleles associated with extremely high intelligence than would be expected under the null hypothesis. This observation is consistent with the hypothesis that rare functional alleles are more frequently detrimental than beneficial to intelligence.

Upper extremity golf injuries.

PubMed

Cohn, Michael A; Lee, Steven K; Strauss, Eric J

2013-01-01

Golf is a global sport enjoyed by an estimated 60 million people around the world. Despite the common misconception that the risk of injury during the play of golf is minimal, golfers are subject to a myriad of potential pathologies. While the majority of injuries in golf are attributable to overuse, acute traumatic injuries can also occur. As the body's direct link to the golf club, the upper extremities are especially prone to injury. A thorough appreciation of the risk factors and patterns of injury will afford accurate diagnosis, treatment, and prevention of further injury.

Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

NASA Astrophysics Data System (ADS)

Islamiyati, A.; Fatmawati; Chamidah, N.

2018-03-01

The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.

More tornadoes in the most extreme U.S. tornado outbreaks

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Lepore, Chiara; Cohen, Joel E.

2016-12-01

Tornadoes and severe thunderstorms kill people and damage property every year. Estimated U.S. insured losses due to severe thunderstorms in the first half of 2016 were $8.5 billion (US). The largest U.S. effects of tornadoes result from tornado outbreaks, which are sequences of tornadoes that occur in close succession. Here, using extreme value analysis, we find that the frequency of U.S. outbreaks with many tornadoes is increasing and that it is increasing faster for more extreme outbreaks. We model this behavior by extreme value distributions with parameters that are linear functions of time or of some indicators of multidecadal climatic variability. Extreme meteorological environments associated with severe thunderstorms show consistent upward trends, but the trends do not resemble those currently expected to result from global warming.

Introduction of a Novel Loss Data Normalization Method for Improved Estimation of Extreme Losses from Natural Catastrophes

NASA Astrophysics Data System (ADS)

Eichner, J. F.; Steuer, M.; Loew, P.

2016-12-01

Past natural catastrophes offer valuable information for present-day risk assessment. To make use of historic loss data one has to find a setting that enables comparison (over place and time) of historic events happening under today's conditions. By means of loss data normalization the influence of socio-economic development, as the fundamental driver in this context, can be eliminated and the data gives way to the deduction of risk-relevant information and allows the study of other driving factors such as influences from climate variability and climate change or changes of vulnerability. Munich Re's NatCatSERVICE database includes for each historic loss event the geographic coordinates of all locations and regions that were affected in a relevant way. These locations form the basis for what is known as the loss footprint of an event. Here we introduce a state of the art and robust method for global loss data normalization. The presented peril-specific loss footprint normalization method adjusts direct economic loss data to the influence of economic growth within each loss footprint (by using gross cell product data as proxy for local economic growth) and makes loss data comparable over time. To achieve a comparative setting for supra-regional economic differences, we categorize the normalized loss values (together with information on fatalities) based on the World Bank income groups into five catastrophe classes, from minor to catastrophic. The data treated in such way allows (a) for studying the influence of improved reporting of small scale loss events over time and (b) for application of standard (stationary) extreme value statistics (here: peaks over threshold method) to compile estimates for extreme and extrapolated loss magnitudes such as a "100 year event" on global scale. Examples of such results will be shown.

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

Estimating adolescent sleep need using dose-response modeling.

PubMed

Short, Michelle A; Weber, Nathan; Reynolds, Chelsea; Coussens, Scott; Carskadon, Mary A

2018-04-01

This study will (1) estimate the nightly sleep need of human adolescents, (2) determine the time course and severity of sleep-related deficits when sleep is reduced below this optimal quantity, and (3) determine whether sleep restriction perturbs the circadian system as well as the sleep homeostat. Thirty-four adolescents aged 15 to 17 years spent 10 days and nine nights in the sleep laboratory. Between two baseline nights and two recovery nights with 10 hours' time in bed (TIB) per night, participants experienced either severe sleep restriction (5-hour TIB), moderate sleep restriction (7.5-hour TIB), or no sleep restriction (10-hour TIB) for five nights. A 10-minute psychomotor vigilance task (PVT; lapse = response after 500 ms) and the Karolinska Sleepiness Scale were administered every 3 hours during wake. Salivary dim-light melatonin onset was calculated at baseline and after four nights of each sleep dose to estimate circadian phase. Dose-dependent deficits to sleep duration, circadian phase timing, lapses of attention, and subjective sleepiness occurred. Less TIB resulted in less sleep, more lapses of attention, greater subjective sleepiness, and larger circadian phase delays. Sleep need estimated from 10-hour TIB sleep opportunities was approximately 9 hours, while modeling PVT lapse data suggested that 9.35 hours of sleep is needed to maintain optimal sustained attention performance. Sleep restriction perturbs homeostatic and circadian systems, leading to dose-dependent deficits to sustained attention and sleepiness. Adolescents require more sleep for optimal functioning than typically obtained.

Item Response Theory with Estimation of the Latent Population Distribution Using Spline-Based Densities

ERIC Educational Resources Information Center

Woods, Carol M.; Thissen, David

2006-01-01

The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the…

Measurement Error in Nonparametric Item Response Curve Estimation. Research Report. ETS RR-11-28

ERIC Educational Resources Information Center

Guo, Hongwen; Sinharay, Sandip

2011-01-01

Nonparametric, or kernel, estimation of item response curve (IRC) is a concern theoretically and operationally. Accuracy of this estimation, often used in item analysis in testing programs, is biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. In this study, we investigate…

A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Cai, Jianhua

2017-05-01

The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

Differential response of vegetation in Hulun Lake region at the northern margin of Asian summer monsoon to extreme cold events of the last deglaciation

NASA Astrophysics Data System (ADS)

Zhang, Shengrui; Xiao, Jule; Xu, Qinghai; Wen, Ruilin; Fan, Jiawei; Huang, Yun; Yamagata, Hideki

2018-06-01

The response of vegetation to extreme cold events during the last deglaciation is important for assessing the impact of possible extreme climatic events on terrestrial ecosystems under future global warming scenarios. Here, we present a detailed record of the development of regional vegetation in the northern margin of Asian summer monsoon during the last deglaciation (16,500-11,000 cal yr BP) based on a radiocarbon-dated high-resolution pollen record from Hulun Lake, northeast China. The results show that the regional vegetation changed from subalpine meadow-desert steppe to mixed coniferous and deciduous forest-typical steppe during the last deglaciation. However, its responses to the Heinrich event 1 (H1) and the Younger Dryas event (YD) were significantly different: during the H1 event, scattered sparse forest was present in the surrounding mountains, while within the lake catchment the vegetation cover was poor and was dominated by desert steppe. In contrast, during the YD event, deciduous forest developed and the proportion of coniferous forest increased in the mountains, the lake catchment was occupied by typical steppe. We suggest that changes in Northern Hemisphere summer insolation and land surface conditions (ice sheets and sea level) caused temperature and monsoonal precipitation variations that contributed to the contrasting vegetation response during the two cold events. We conclude that under future global warming scenarios, extreme climatic events may cause a deterioration of the ecological environment of the Hulun Lake region, resulting in increased coniferous forest and decreased total forest cover in the surrounding mountains, and a reduction in typical steppe in the lake catchment.

Ensemble-based evaluation of extreme water levels for the eastern Baltic Sea

NASA Astrophysics Data System (ADS)

Eelsalu, Maris; Soomere, Tarmo

2016-04-01

The risks and damages associated with coastal flooding that are naturally associated with an increase in the magnitude of extreme storm surges are one of the largest concerns of countries with extensive low-lying nearshore areas. The relevant risks are even more contrast for semi-enclosed water bodies such as the Baltic Sea where subtidal (weekly-scale) variations in the water volume of the sea substantially contribute to the water level and lead to large spreading of projections of future extreme water levels. We explore the options for using large ensembles of projections to more reliably evaluate return periods of extreme water levels. Single projections of the ensemble are constructed by means of fitting several sets of block maxima with various extreme value distributions. The ensemble is based on two simulated data sets produced in the Swedish Meteorological and Hydrological Institute. A hindcast by the Rossby Centre Ocean model is sampled with a resolution of 6 h and a similar hindcast by the circulation model NEMO with a resolution of 1 h. As the annual maxima of water levels in the Baltic Sea are not always uncorrelated, we employ maxima for calendar years and for stormy seasons. As the shape parameter of the Generalised Extreme Value distribution changes its sign and substantially varies in magnitude along the eastern coast of the Baltic Sea, the use of a single distribution for the entire coast is inappropriate. The ensemble involves projections based on the Generalised Extreme Value, Gumbel and Weibull distributions. The parameters of these distributions are evaluated using three different ways: maximum likelihood method and method of moments based on both biased and unbiased estimates. The total number of projections in the ensemble is 40. As some of the resulting estimates contain limited additional information, the members of pairs of projections that are highly correlated are assigned weights 0.6. A comparison of the ensemble-based projection of

Estimation of Supersonic Stage Separation Aerodynamics of Winged-Body Launch Vehicles Using Response Surface Methods

NASA Technical Reports Server (NTRS)

Erickson, Gary E.

2010-01-01

Response surface methodology was used to estimate the longitudinal stage separation aerodynamic characteristics of a generic, bimese, winged multi-stage launch vehicle configuration at supersonic speeds in the NASA LaRC Unitary Plan Wind Tunnel. The Mach 3 staging was dominated by shock wave interactions between the orbiter and booster vehicles throughout the relative spatial locations of interest. The inference space was partitioned into several contiguous regions within which the separation aerodynamics were presumed to be well-behaved and estimable using central composite designs capable of fitting full second-order response functions. The underlying aerodynamic response surfaces of the booster vehicle in belly-to-belly proximity to the orbiter vehicle were estimated using piecewise-continuous lower-order polynomial functions. The quality of fit and prediction capabilities of the empirical models were assessed in detail, and the issue of subspace boundary discontinuities was addressed. Augmenting the central composite designs to full third-order using computer-generated D-optimality criteria was evaluated. The usefulness of central composite designs, the subspace sizing, and the practicality of fitting lower-order response functions over a partitioned inference space dominated by highly nonlinear and possibly discontinuous shock-induced aerodynamics are discussed.

The National Integrated Heat Health Information System (NIHHIS) as a Learning System for Extreme Heat: Evolving Future Resilience from Present Climate Extremes

NASA Astrophysics Data System (ADS)

Jones, H.; Trtanj, J.; Pulwarty, R. S.; Higgins, W.

2016-12-01

There is presently no consensus indicator for the effect of extreme heat on human health. At the early warning timescale, a variety of approaches to setting temperature thresholds (minimum, maximum, time-lagged) or more complex approaches (Heat Index, Thermal Comfort, etc...) for issuing alerts and warnings have been recommended by literature and implemented, leading to much heterogeneity. At longer timescales, efforts have been made to quantify potential future health outcomes using climate projections, but nonstationarity of the climate system, economy, and demography may invalidate many of the assumptions which were necessarily made in these studies. Furthermore, in our pursuit of developing the best models and indicators to represent the impacts of climate extremes, perhaps we have not paid enough attention to what makes them policy-relevant, responsive to changing assumptions, and targeted at elements that can actually be predicted. In response to this concern, a comprehensive approach to improving the impactfulness of these indicators is underway as part of the National Integrated Heat Health Information System (NIHHIS), which was initiated by NOAA and CDC, but has grown to include many other federal agency and non-governmental partners. NIHHIS is a framework that integrates what we know about extreme heat and health outcomes within a learning system - simultaneously informing early warning and long-term risk reduction prior to, during, and while recovering from extreme heat events. NIHHIS develops impactful evolutionary responses to climate extremes. Through ongoing regional engagements, we are applying the lessons of impact modeling studies to create learning systems in the Southwest, Northeast, Midwest, and soon other regions of the U.S. This session will provide a view of this process as it has been carried out in the Southwest region - focused on the transboundary (US-Mexico) region around El Paso, Texas, and the NIHHIS approach to indicators overall.

Direct volume estimation without segmentation

NASA Astrophysics Data System (ADS)

Zhen, X.; Wang, Z.; Islam, A.; Bhaduri, M.; Chan, I.; Li, S.

2015-03-01

Volume estimation plays an important role in clinical diagnosis. For example, cardiac ventricular volumes including left ventricle (LV) and right ventricle (RV) are important clinical indicators of cardiac functions. Accurate and automatic estimation of the ventricular volumes is essential to the assessment of cardiac functions and diagnosis of heart diseases. Conventional methods are dependent on an intermediate segmentation step which is obtained either manually or automatically. However, manual segmentation is extremely time-consuming, subjective and highly non-reproducible; automatic segmentation is still challenging, computationally expensive, and completely unsolved for the RV. Towards accurate and efficient direct volume estimation, our group has been researching on learning based methods without segmentation by leveraging state-of-the-art machine learning techniques. Our direct estimation methods remove the accessional step of segmentation and can naturally deal with various volume estimation tasks. Moreover, they are extremely flexible to be used for volume estimation of either joint bi-ventricles (LV and RV) or individual LV/RV. We comparatively study the performance of direct methods on cardiac ventricular volume estimation by comparing with segmentation based methods. Experimental results show that direct estimation methods provide more accurate estimation of cardiac ventricular volumes than segmentation based methods. This indicates that direct estimation methods not only provide a convenient and mature clinical tool for cardiac volume estimation but also enables diagnosis of cardiac diseases to be conducted in a more efficient and reliable way.

The Science of Climate Responsibility

NASA Astrophysics Data System (ADS)

Mitchell, D.; Frumhoff, P. C.; Sparrow, S.; Allen, M. R.

2015-12-01

Extreme events linked with human induced climate change have now been reported around the globe. Among the most troublesome impacts are increased wild fires, failed crop yields, extreme flooding and increase human mortality (Hansen and Cramer, 2015). Many of these impacts are predicted to increase into the future. Non-industrialised communities around the world will be the least capable of adapting, while the industrial communities, who are often responsible for historical carbon emissions, will find adaptation easier. Such a situation lends itself to the issue of responsibility. In order to assess responsibility, it must first be established where the major carbon and methane emissions are originating. It must then be estimated how these emissions project onto localised climate, which is often the primary indicator behind impacts on society. In this study, we address this question using a 25 km regional climate model capable of simulating climate thousands of times under the Weather@home citizen science project. The use of this framework allows us to generate huge data sample sizes, which can be put in the context of very low sample sizes of observational data. We concentrate on the 2003 heat wave over Europe, but show how this method could be applied to less data rich regions, including the Middle East and the Horn of Africa.

Modeling extreme drought impacts on terrestrial ecosystems when thresholds are exceeded

NASA Astrophysics Data System (ADS)

Holm, J. A.; Rammig, A.; Smith, B.; Medvigy, D.; Lichstein, J. W.; Dukes, J. S.; Allen, C. D.; Beier, C.; Larsen, K. S.; Ficken, C. D.; Pockman, W.; Anderegg, W.; Luo, Y.

2016-12-01

Recent IPCC Assessment Reports suggest that with predicted climate changes future precipitation- and heat-related extreme events are becoming stronger and more frequent with potential for prolonged droughts. To prepare for these changes and their impacts, we need to develop a better understanding of terrestrial ecosystem responses to extreme drought events. In particular, we focus here on large-extent and long-lasting extreme drought events with noticeable impacts on the functioning of forested ecosystems. While most of ecosystem manipulative experiments have been motivated by ongoing and predicted climate change, the majority only applied relatively moderate droughts, not addressing the "very" extreme tail of these scenarios, i.e. "extreme extremes (EEs)". We explore the response of forest ecosystems to EEs using two demographic-based dynamic global vegetation models (DGVMs) (i.e. ED2, LPJ-GUESS) in which the abundances of different plant functional types, as well as tree size- and age-class structure, are emergent properties of resource competition. We evaluate the model's capabilities to represent extreme drought scenarios (i.e., 50% and 90% reduction in precipitation for 1-year, 2-year, and 4-year drought scenarios) at two dry forested sites: Palo Verde, Costa Rica (i.e. tropical) and EucFACE, Australia (i.e. temperate). Through the DGVM modeling outcomes we determine the following five testable hypotheses for future experiments: 1) EEs cannot be extrapolated from mild extremes due to plant plasticity and functional composition. 2) Response to EEs depends on functional diversity, trait combinations, and phenology, such that both models predicted even after 100 years plant biomass did not recover. 3) Mortality from drought reduces the pressure on resources and prevents further damage by subsequent years of drought. 4) Early successional stands are more vulnerable to extreme droughts while older stand are more resilient. 5) Elevated atmospheric CO2 alleviates

A new framework for estimating return levels using regional frequency analysis

NASA Astrophysics Data System (ADS)

Winter, Hugo; Bernardara, Pietro; Clegg, Georgina

2017-04-01

We propose a new framework for incorporating more spatial and temporal information into the estimation of extreme return levels. Currently, most studies use extreme value models applied to data from a single site; an approach which is inefficient statistically and leads to return level estimates that are less physically realistic. We aim to highlight the benefits that could be obtained by using methodology based upon regional frequency analysis as opposed to classic single site extreme value analysis. This motivates a shift in thinking, which permits the evaluation of local and regional effects and makes use of the wide variety of data that are now available on high temporal and spatial resolutions. The recent winter storms over the UK during the winters of 2013-14 and 2015-16, which have caused wide-ranging disruption and damaged important infrastructure, provide the main motivation for the current work. One of the most impactful natural hazards is flooding, which is often initiated by extreme precipitation. In this presentation, we focus on extreme rainfall, but shall discuss other meteorological variables alongside potentially damaging hazard combinations. To understand the risks posed by extreme precipitation, we need reliable statistical models which can be used to estimate quantities such as the T-year return level, i.e. the level which is expected to be exceeded once every T-years. Extreme value theory provides the main collection of statistical models that can be used to estimate the risks posed by extreme precipitation events. Broadly, at a single site, a statistical model is fitted to exceedances of a high threshold and the model is used to extrapolate to levels beyond the range of the observed data. However, when we have data at many sites over a spatial domain, fitting a separate model for each separate site makes little sense and it would be better if we could incorporate all this information to improve the reliability of return level estimates. Here

Modelling of extreme rainfall events in Peninsular Malaysia based on annual maximum and partial duration series

NASA Astrophysics Data System (ADS)

Zin, Wan Zawiah Wan; Shinyie, Wendy Ling; Jemain, Abdul Aziz

2015-02-01

In this study, two series of data for extreme rainfall events are generated based on Annual Maximum and Partial Duration Methods, derived from 102 rain-gauge stations in Peninsular from 1982-2012. To determine the optimal threshold for each station, several requirements must be satisfied and Adapted Hill estimator is employed for this purpose. A semi-parametric bootstrap is then used to estimate the mean square error (MSE) of the estimator at each threshold and the optimal threshold is selected based on the smallest MSE. The mean annual frequency is also checked to ensure that it lies in the range of one to five and the resulting data is also de-clustered to ensure independence. The two data series are then fitted to Generalized Extreme Value and Generalized Pareto distributions for annual maximum and partial duration series, respectively. The parameter estimation methods used are the Maximum Likelihood and the L-moment methods. Two goodness of fit tests are then used to evaluate the best-fitted distribution. The results showed that the Partial Duration series with Generalized Pareto distribution and Maximum Likelihood parameter estimation provides the best representation for extreme rainfall events in Peninsular Malaysia for majority of the stations studied. Based on these findings, several return values are also derived and spatial mapping are constructed to identify the distribution characteristic of extreme rainfall in Peninsular Malaysia.

Characterization of the Martian magnetic topology response to extreme solar transient events with MGS data

NASA Astrophysics Data System (ADS)

Xu, S.; Curry, S.; Mitchell, D. L.; Luhmann, J. G.; Lillis, R. J.; Dong, C.

2017-12-01

Characterizing how the solar cycle affects the physics of the Mars-solar wind interaction can improve our understanding of Mars' atmospheric evolution and the plasma environment at Mars. In particular, solar transient events such as Interplanetary Coronal Mass Ejections (ICMEs) and Stream Interaction Regions (SIRs) significantly change the solar-wind interaction, including the magnetic topology and ion acceleration. However, both the Mars Express and Mars Atmosphere Volatile EvolutioN (MAVEN) missions have encountered relatively few extreme solar transient events due to the recent low solar activity (2004-2017). In contrast, Mars Global Surveyor (MGS) was operating during a relatively active solar maximum (1999-2003). Based on new results from MAVEN, this study reanalyzes MGS data to better understand how the Martian plasma environment responds to extreme solar events. In particular, we aim to investigate how the magnetic topology during these extreme events differs from the topology during quiet times. We conduct orbit comparisons of the magnetic topology inferred from MGS electron pitch angle distributions during quiet periods and extreme events to determine how the open and closed field patterns respond to extreme events.

The Engineering for Climate Extremes Partnership

NASA Astrophysics Data System (ADS)

Holland, G. J.; Tye, M. R.

2014-12-01

Hurricane Sandy and the recent floods in Thailand have demonstrated not only how sensitive the urban environment is to the impact of severe weather, but also the associated global reach of the ramifications. These, together with other growing extreme weather impacts and the increasing interdependence of global commercial activities point towards a growing vulnerability to weather and climate extremes. The Engineering for Climate Extremes Partnership brings academia, industry and government together with the goals encouraging joint activities aimed at developing new, robust, and well-communicated responses to this increasing vulnerability. Integral to the approach is the concept of 'graceful failure' in which flexible designs are adopted that protect against failure by combining engineering or network strengths with a plan for efficient and rapid recovery if and when they fail. Such an approach enables optimal planning for both known future scenarios and their assessed uncertainty.

Efficient Algorithms for Estimating the Absorption Spectrum within Linear Response TDDFT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brabec, Jiri; Lin, Lin; Shao, Meiyue

We present two iterative algorithms for approximating the absorption spectrum of molecules within linear response of time-dependent density functional theory (TDDFT) framework. These methods do not attempt to compute eigenvalues or eigenvectors of the linear response matrix. They are designed to approximate the absorption spectrum as a function directly. They take advantage of the special structure of the linear response matrix. Neither method requires the linear response matrix to be constructed explicitly. They only require a procedure that performs the multiplication of the linear response matrix with a vector. These methods can also be easily modified to efficiently estimate themore » density of states (DOS) of the linear response matrix without computing the eigenvalues of this matrix. We show by computational experiments that the methods proposed in this paper can be much more efficient than methods that are based on the exact diagonalization of the linear response matrix. We show that they can also be more efficient than real-time TDDFT simulations. We compare the pros and cons of these methods in terms of their accuracy as well as their computational and storage cost.« less