A dynamical systems approach to studying midlatitude weather extremes
NASA Astrophysics Data System (ADS)
Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide
2017-04-01
Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.
NASA Astrophysics Data System (ADS)
Keilis-Borok, V. I.; Soloviev, A. A.
2010-09-01
Socioeconomic and natural complex systems persistently generate extreme events also known as disasters, crises, or critical transitions. Here we analyze patterns of background activity preceding extreme events in four complex systems: economic recessions, surges in homicides in a megacity, magnetic storms, and strong earthquakes. We use as a starting point the indicators describing the system's behavior and identify changes in an indicator's trend. Those changes constitute our background events (BEs). We demonstrate a premonitory pattern common to all four systems considered: relatively large magnitude BEs become more frequent before extreme event. A premonitory change of scaling has been found in various models and observations. Here we demonstrate this change in scaling of uniformly defined BEs in four real complex systems, their enormous differences notwithstanding.
Facilitating Co-Design for Extreme-Scale Systems Through Lightweight Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Engelmann, Christian; Lauer, Frank
This work focuses on tools for investigating algorithm performance at extreme scale with millions of concurrent threads and for evaluating the impact of future architecture choices to facilitate the co-design of high-performance computing (HPC) architectures and applications. The approach focuses on lightweight simulation of extreme-scale HPC systems with the needed amount of accuracy. The prototype presented in this paper is able to provide this capability using a parallel discrete event simulation (PDES), such that a Message Passing Interface (MPI) application can be executed at extreme scale, and its performance properties can be evaluated. The results of an initial prototype aremore » encouraging as a simple 'hello world' MPI program could be scaled up to 1,048,576 virtual MPI processes on a four-node cluster, and the performance properties of two MPI programs could be evaluated at up to 16,384 virtual MPI processes on the same system.« less
Dynamical systems proxies of atmospheric predictability and mid-latitude extremes
NASA Astrophysics Data System (ADS)
Messori, Gabriele; Faranda, Davide; Caballero, Rodrigo; Yiou, Pascal
2017-04-01
Extreme weather ocurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. Many extremes (for e.g. storms, heatwaves, cold spells, heavy precipitation) are tied to specific patterns of midlatitude atmospheric circulation. The ability to identify these patterns and use them to enhance the predictability of the extremes is therefore a topic of crucial societal and economic value. We propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We use two simple dynamical systems metrics - local dimension and persistence - to identify sets of similar large-scale atmospheric flow patterns which present a coherent temporal evolution. When these patterns correspond to weather extremes, they therefore afford a particularly good forward predictability. We specifically test this technique on European winter temperatures, whose variability largely depends on the atmospheric circulation in the North Atlantic region. We find that our dynamical systems approach provides predictability of large-scale temperature extremes up to one week in advance.
A characterization of workflow management systems for extreme-scale applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia
We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less
A characterization of workflow management systems for extreme-scale applications
Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia; ...
2017-02-16
We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less
NASA Astrophysics Data System (ADS)
Walz, M. A.; Donat, M.; Leckebusch, G. C.
2017-12-01
As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.
Opportunities for nonvolatile memory systems in extreme-scale high-performance computing
Vetter, Jeffrey S.; Mittal, Sparsh
2015-01-12
For extreme-scale high-performance computing systems, system-wide power consumption has been identified as one of the key constraints moving forward, where DRAM main memory systems account for about 30 to 50 percent of a node's overall power consumption. As the benefits of device scaling for DRAM memory slow, it will become increasingly difficult to keep memory capacities balanced with increasing computational rates offered by next-generation processors. However, several emerging memory technologies related to nonvolatile memory (NVM) devices are being investigated as an alternative for DRAM. Moving forward, NVM devices could offer solutions for HPC architectures. Researchers are investigating how to integratemore » these emerging technologies into future extreme-scale HPC systems and how to expose these capabilities in the software stack and applications. In addition, current results show several of these strategies could offer high-bandwidth I/O, larger main memory capacities, persistent data structures, and new approaches for application resilience and output postprocessing, such as transaction-based incremental checkpointing and in situ visualization, respectively.« less
Epidemic failure detection and consensus for extreme parallelism
Katti, Amogh; Di Fatta, Giuseppe; Naughton, Thomas; ...
2017-02-01
Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that inmore » all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.« less
Extreme-scale Algorithms and Solver Resilience
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dongarra, Jack
A widening gap exists between the peak performance of high-performance computers and the performance achieved by complex applications running on these platforms. Over the next decade, extreme-scale systems will present major new challenges to algorithm development that could amplify this mismatch in such a way that it prevents the productive use of future DOE Leadership computers due to the following; Extreme levels of parallelism due to multicore processors; An increase in system fault rates requiring algorithms to be resilient beyond just checkpoint/restart; Complex memory hierarchies and costly data movement in both energy and performance; Heterogeneous system architectures (mixing CPUs, GPUs,more » etc.); and Conflicting goals of performance, resilience, and power requirements.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katti, Amogh; Di Fatta, Giuseppe; Naughton, Thomas
Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that inmore » all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.« less
Extreme Events in China under Climate Change: Uncertainty and related impacts (CSSP-FOREX)
NASA Astrophysics Data System (ADS)
Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.
2016-04-01
Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.
Forest-fire model as a supercritical dynamic model in financial systems
NASA Astrophysics Data System (ADS)
Lee, Deokjae; Kim, Jae-Young; Lee, Jeho; Kahng, B.
2015-02-01
Recently large-scale cascading failures in complex systems have garnered substantial attention. Such extreme events have been treated as an integral part of self-organized criticality (SOC). Recent empirical work has suggested that some extreme events systematically deviate from the SOC paradigm, requiring a different theoretical framework. We shed additional theoretical light on this possibility by studying financial crisis. We build our model of financial crisis on the well-known forest fire model in scale-free networks. Our analysis shows a nontrivial scaling feature indicating supercritical behavior, which is independent of system size. Extreme events in the supercritical state result from bursting of a fat bubble, seeds of which are sown by a protracted period of a benign financial environment with few shocks. Our findings suggest that policymakers can control the magnitude of financial meltdowns by keeping the economy operating within reasonable duration of a benign environment.
PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deelman, Ewa; Carothers, Christopher; Mandal, Anirban
Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less
PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows
Deelman, Ewa; Carothers, Christopher; Mandal, Anirban; ...
2015-07-14
Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less
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.
A variational approach to probing extreme events in turbulent dynamical systems
Farazmand, Mohammad; Sapsis, Themistoklis P.
2017-01-01
Extreme events are ubiquitous in a wide range of dynamical systems, including turbulent fluid flows, nonlinear waves, large-scale networks, and biological systems. We propose a variational framework for probing conditions that trigger intermittent extreme events in high-dimensional nonlinear dynamical systems. We seek the triggers as the probabilistically feasible solutions of an appropriately constrained optimization problem, where the function to be maximized is a system observable exhibiting intermittent extreme bursts. The constraints are imposed to ensure the physical admissibility of the optimal solutions, that is, significant probability for their occurrence under the natural flow of the dynamical system. We apply the method to a body-forced incompressible Navier-Stokes equation, known as the Kolmogorov flow. We find that the intermittent bursts of the energy dissipation are independent of the external forcing and are instead caused by the spontaneous transfer of energy from large scales to the mean flow via nonlinear triad interactions. The global maximizer of the corresponding variational problem identifies the responsible triad, hence providing a precursor for the occurrence of extreme dissipation events. Specifically, monitoring the energy transfers within this triad allows us to develop a data-driven short-term predictor for the intermittent bursts of energy dissipation. We assess the performance of this predictor through direct numerical simulations. PMID:28948226
Projected changes to precipitation extremes over the Canadian Prairies using multi-RCM ensemble
NASA Astrophysics Data System (ADS)
Masud, M. B.; Khaliq, M. N.; Wheater, H. S.
2016-12-01
Information on projected changes to precipitation extremes is needed for future planning of urban drainage infrastructure and storm water management systems and to sustain socio-economic activities and ecosystems at local, regional and other scales of interest. This study explores the projected changes to seasonal (April-October) precipitation extremes at daily, hourly and sub-hourly scales over the Canadian Prairie Provinces of Alberta, Saskatchewan, and Manitoba, based on the North American Regional Climate Change Assessment Program multi-Regional Climate Model (RCM) ensemble and regional frequency analysis. The performance of each RCM is evaluated regarding boundary and performance errors to study various sources of uncertainties and the impact of large-scale driving fields. In the absence of RCM-simulated short-duration extremes, a framework is developed to derive changes to extremes of these durations. Results from this research reveal that the relative changes in sub-hourly extremes are higher than those in the hourly and daily extremes. Overall, projected changes in precipitation extremes are larger for southeastern parts of this region than southern and northern areas, and smaller for southwestern and western parts of the study area. Keywords: climate change, precipitation extremes, regional frequency analysis, NARCCAP, Canadian Prairie provinces
NASA Astrophysics Data System (ADS)
Nunes, Ana
2015-04-01
Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme events also helps the development of a system for decision-making, regarding natural and social disasters, and reducing impacts. Numerical experiments using this regional modeling system successfully modeled severe weather events in Brazil. Comparisons with the NCEP Climate Forecast System Reanalysis outputs were made at resolutions of about 40- and 25-km of the regional climate model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilke, Jeremiah J; Kenny, Joseph P.
2015-02-01
Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading frameworkmore » allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.« less
NASA Astrophysics Data System (ADS)
Faranda, D.; Yiou, P.; Alvarez-Castro, M. C. M.
2015-12-01
A combination of dynamical systems and statistical techniques allows for a robust assessment of the dynamical properties of the mid-latitude atmospheric circulation. Extremes at different spatial and time scales are not only associated to exceptionally intense weather structures (e.g. extra-tropical cyclones) but also to rapid changes of circulation regimes (thunderstorms, supercells) or the extreme persistence of weather structure (heat waves, cold spells). We will show how the dynamical systems theory of recurrence combined to the extreme value theory can take into account the spatial and temporal dependence structure of the mid-latitude circulation structures and provide information on the statistics of extreme events.
Power-law scaling of extreme dynamics near higher-order exceptional points
NASA Astrophysics Data System (ADS)
Zhong, Q.; Christodoulides, D. N.; Khajavikhan, M.; Makris, K. G.; El-Ganainy, R.
2018-02-01
We investigate the extreme dynamics of non-Hermitian systems near higher-order exceptional points in photonic networks constructed using the bosonic algebra method. We show that strong power oscillations for certain initial conditions can occur as a result of the peculiar eigenspace geometry and its dimensionality collapse near these singularities. By using complementary numerical and analytical approaches, we show that, in the parity-time (PT ) phase near exceptional points, the logarithm of the maximum optical power amplification scales linearly with the order of the exceptional point. We focus in our discussion on photonic systems, but we note that our results apply to other physical systems as well.
NASA Astrophysics Data System (ADS)
Agel, Laurie; Barlow, Mathew; Feldstein, Steven B.; Gutowski, William J.
2018-03-01
Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.
Impact of climate change on European weather extremes
NASA Astrophysics Data System (ADS)
Duchez, Aurelie; Forryan, Alex; Hirschi, Joel; Sinha, Bablu; New, Adrian; Freychet, Nicolas; Scaife, Adam; Graham, Tim
2015-04-01
An emerging science consensus is that global climate change will result in more extreme weather events with concomitant increasing financial losses. Key questions that arise are: Can an upward trend in natural extreme events be recognised and predicted at the European scale? What are the key drivers within the climate system that are changing and making extreme weather events more frequent, more intense, or both? Using state-of-the-art coupled climate simulations from the UK Met Office (HadGEM3-GC2, historical and future scenario runs) as well as reanalysis data, we highlight the potential of the currently most advanced forecasting systems to progress understanding of the causative drivers of European weather extremes, and assess future frequency and intensity of extreme weather under various climate change scenarios. We characterize European extremes in these simulations using a subset of the 27 core indices for temperature and precipitation from The Expert Team on Climate Change Detection and Indices (Tank et al., 2009). We focus on temperature and precipitation extremes (e.g. extremes in daily and monthly precipitation and temperatures) and relate them to the atmospheric modes of variability over Europe in order to establish the large-scale atmospheric circulation patterns that are conducive to the occurrence of extreme precipitation and temperature events. Klein Tank, Albert M.G., and Francis W. Zwiers. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation. WMO-TD No. 1500. Climate Data and Monitoring. World Meteorological Organization, 2009.
Censored rainfall modelling for estimation of fine-scale extremes
NASA Astrophysics Data System (ADS)
Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro
2018-01-01
Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.
NASA Astrophysics Data System (ADS)
Takayabu, Yukari; Hamada, Atsushi; Mori, Yuki; Murayama, Yuki; Liu, Chuntao; Zipser, Edward
2015-04-01
While extreme rainfall has a huge impact upon human society, the characteristics of the extreme precipitation vary from region to region. Seventeen years of three dimensional precipitation measurements from the space-borne precipitation radar equipped with the Tropical Precipitation Measurement Mission satellite enabled us to describe the characteristics of regional extreme precipitation globally. Extreme rainfall statistics are based on rainfall events defined as a set of contiguous PR rainy pixels. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile in each 2.5degree x2.5degree horizontal resolution grid. First, regional extreme rainfall is characterized in terms of its intensity and event size. Regions of ''intense and extensive'' extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of ''intense but less extensive'' extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of ''extensive but less intense'' extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones. Secondly, regional extremes in terms of surface rainfall intensity and those in terms of convection height are compared. Conventionally, extremely tall convection is considered to contribute the largest to the intense rainfall. Comparing probability density functions (PDFs) of 99th percentiles in terms of the near surface rainfall intensity in each regional grid and those in terms of the 40dBZ echo top heights, it is found that heaviest precipitation in the region is not associated with tallest systems, but rather with systems with moderate heights. Interestingly, this separation of extremely heavy precipitation from extremely tall convection is found to be quite universal, irrespective of regions. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Thus it is demonstrated that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. Third, the size effect of rainfall events on the precipitation intensity is investigated. Comparisons of normalized PDFs of foot-print size rainfall intensity for different sizes of rainfall events show that footprint-scale extreme rainfall becomes stronger as the rainfall events get larger. At the same time, stratiform ratio in area as well as in rainfall amount increases with the size, confirming larger sized features are more organized systems. After all, it is statistically shown that organization of precipitation not only brings about an increase in extreme volumetric rainfall but also an increase in probability of the satellite footprint scale extreme rainfall.
Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.
Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne
2018-01-01
State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.
Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne
2018-01-01
State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems. PMID:29503613
Towards a Unified Framework in Hydroclimate Extremes Prediction in Changing Climate
NASA Astrophysics Data System (ADS)
Moradkhani, H.; Yan, H.; Zarekarizi, M.; Bracken, C.
2016-12-01
Spatio-temporal analysis and prediction of hydroclimate extremes are of paramount importance in disaster mitigation and emergency management. The IPCC special report on managing the risks of extreme events and disasters emphasizes that the global warming would change the frequency, severity, and spatial pattern of extremes. In addition to climate change, land use and land cover changes also influence the extreme characteristics at regional scale. Therefore, natural variability and anthropogenic changes to the hydroclimate system result in nonstationarity in hydroclimate variables. In this presentation recent advancements in developing and using Bayesian approaches to account for non-stationarity in hydroclimate extremes are discussed. Also, implications of these approaches in flood frequency analysis, treatment of spatial dependence, the impact of large-scale climate variability, the selection of cause-effect covariates, with quantification of model errors in extreme prediction is explained. Within this framework, the applicability and usefulness of the ensemble data assimilation for extreme flood predictions is also introduced. Finally, a practical and easy to use approach for better communication with decision-makers and emergency managers is presented.
Inter-model variability in hydrological extremes projections for Amazonian sub-basins
NASA Astrophysics Data System (ADS)
Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier
2014-05-01
Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.
NASA Technical Reports Server (NTRS)
Zhou, Yaping; Lau, William K M.; Liu, Chuntao
2013-01-01
This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.
ScaleNet: A literature-based model of scale insect biology and systematics
USDA-ARS?s Scientific Manuscript database
Scale insects (Hemiptera: Coccoidea) are small herbivorous insects found in all continents except Antarctica. They are extremely invasive, and many species are serious agricultural pests. They are also emerging models for studies of the evolution of genetic systems, endosymbiosis, and plant-insect i...
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.
Army Maneuver Center of Excellence
2012-10-18
agreements throughout DoD DARPA, JIEDDO, DHS, FAA, DoE, NSA , NASA, SMDC, etc. Strategic Partnerships Benefit the Army Materiel Enterprise External... Neuroscience Network Sciences Hierarchical Computing Extreme Energy Science Autonomous Systems Technology Emerging Sciences Meso-scale (grain...scales • Improvements in Soldier-system overall performance → operational neuroscience and advanced simulation and training technologies
The science of visual analysis at extreme scale
NASA Astrophysics Data System (ADS)
Nowell, Lucy T.
2011-01-01
Driven by market forces and spanning the full spectrum of computational devices, computer architectures are changing in ways that present tremendous opportunities and challenges for data analysis and visual analytic technologies. Leadership-class high performance computing system will have as many as a million cores by 2020 and support 10 billion-way concurrency, while laptop computers are expected to have as many as 1,000 cores by 2015. At the same time, data of all types are increasing exponentially and automated analytic methods are essential for all disciplines. Many existing analytic technologies do not scale to make full use of current platforms and fewer still are likely to scale to the systems that will be operational by the end of this decade. Furthermore, on the new architectures and for data at extreme scales, validating the accuracy and effectiveness of analytic methods, including visual analysis, will be increasingly important.
NASA Astrophysics Data System (ADS)
Parisi, Alessandro; Fidelibus, Maria Dolores
2017-04-01
Physical extremes can be distinguished in "sudden physical extremes" (e.g. earthquakes, tsunami) and "progressive physical extremes" (e.g. drought, desertification, landslides). They differ for frequency, intensity, spatial extent, duration and timing of occurrence. If a physical extreme, by interacting with human systems, induces negative consequences, its outcome can be a "disaster". The disasters are, in both above cases, characterized by a few phases: physical extreme occurrence, emergency, response, and recovery. However, in the case of a progressive physical extreme, the disaster develops with an overlap in the time of the above-mentioned phases. When the events are repetitive, the emergency planning (which follows a cycle) succeeds with preparedness and mitigation with the intent of reducing the risk. Both the sudden and progressive physical extremes produce cascading effects of consequences on social, environmental and economic systems. Disasters consequent to sudden and progressive extremes show, however, some differences, mainly attributable to the "visibility" of the effects and to their time scale of evolution. As matter of fact, a disaster consequent to a progressive physical extreme produces "emerging signals" that are often invisible. Moreover, the emergency phase can arise with a time delay compared to the occurrence of the physical extreme, depending on the spatial scale of impacted system. The above differences allow defining "creeping disasters" the potential disasters related to progressive physical extremes. This study deals with some peculiar "cascading disasters" consequent to drought, which is the main "creeping disaster", namely the groundwater drought and the consequent salinization of coastal aquifers. In regional flow systems, their effects are invisible in the immediate to common people (and often even to managers) because of the concealed nature of groundwater; moreover, they are difficult to assess because of the shift over time of their evolution compared to the promptness of surface effects. The study area is the Salento coastal karstic aquifer (Apulia region, Southern Italy), where the groundwater flows according to a regional flow system. It has been subject to successive meteorological droughts between 1960 and 2010. The groundwater monitoring performed during this period, even with some gaps, allows identifying time lags between superficial effects and underground system response, potential tipping points, and emerging signals of the cascading disasters.
Modelling Precipitation and Temperature Extremes: The Importance of Horizontal Resolution
NASA Astrophysics Data System (ADS)
Shields, C. A.; Kiehl, J. T.; Meehl, G. A.
2013-12-01
Understanding Earth's water cycle on a warming planet is of critical importance in society's ability to adapt to climate change. Extreme weather events, such as floods, heat waves, and drought will likely change with the water cycle as greenhouse gases continue to rise. Location, duration, and intensity of extreme events can be studied using complex earth system models. Here, we employ the fully coupled Community Earth System Model (CESM1.0) to evaluate extreme event impacts for different possible future forcing scenarios. Simulations applying the Representative Concentration Pathway (RCP) scenarios 2.6 and 8.5 were chosen to bracket the range of model responses. Because extreme weather events happen on a regional scale, there is a tendency to favor using higher resolution models, i.e. models that can represent regional features with greater accuracy. Within the CESM1.0 framework, we evaluate both the standard 1 degree resolution (1 degree atmosphere/land coupled to 1 degree ocean/sea ice), and the higher 0.5 degree resolution version (0.5 degree atmosphere/land coupled to 1 degree ocean/sea ice), focusing on extreme precipitation events, heat waves, and droughts. We analyze a variety of geographical regions, but generally find that benefits from increased horizontal resolution are most significant on the regional scale.
Millimeter-scale MEMS enabled autonomous systems: system feasibility and mobility
NASA Astrophysics Data System (ADS)
Pulskamp, Jeffrey S.
2012-06-01
Millimeter-scale robotic systems based on highly integrated microelectronics and micro-electromechanical systems (MEMS) could offer unique benefits and attributes for small-scale autonomous systems. This extreme scale for robotics will naturally constrain the realizable system capabilities significantly. This paper assesses the feasibility of developing such systems by defining the fundamental design trade spaces between component design variables and system level performance parameters. This permits the development of mobility enabling component technologies within a system relevant context. Feasible ranges of system mass, required aerodynamic power, available battery power, load supported power, flight endurance, and required leg load bearing capability are presented for millimeter-scale platforms. The analysis illustrates the feasibility of developing both flight capable and ground mobile millimeter-scale autonomous systems while highlighting the significant challenges that must be overcome to realize their potential.
Response of the Vegetation-Climate System to High Temperature (Invited)
NASA Astrophysics Data System (ADS)
Berry, J. A.
2009-12-01
High temperature extremes may lead to inhibition of photosynthesis and stomatal closure at the leaf scale. When these responses occur over regional scales, they can initiate a positive feedback loop in the coupled vegetation-climate system. The fraction of net radiation that is used by the land surface to evaporate water decreases leading to deeper, drier boundary layers, fewer clouds, increased solar radiation reaching the surface, and possibility reduced precipitation. These interactions within the vegetation-climate system may amplify natural (or greenhouse gas forced) variations in temperature and further stress the vegetation. Properly modeling of this system depends, among other things, on getting the plant responses to high temperature correct. I will review the current state of this problem and present some studies of rain forest trees to high temperature and drought conducted in the Biosphere 2 enclosure that illustrate how experiments in controlled systems can contribute to our understanding of complex systems to extreme events.
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.
NASA Astrophysics Data System (ADS)
Collow, A.; Bosilovich, M. G.; Koster, R. D.
2016-12-01
Over the past two decades a statistically significant increase in the frequency of summertime extreme precipitation events has been observed over the northeastern United States - the largest such increase in the US in terms of area and magnitude. In an effort to characterize synoptic scale patterns and changes to the atmospheric circulation associated with extreme precipitation events in this region, atmospheric fields from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) are composited on days that exceed the 90th percentile of precipitation from the CPC-Unified daily gauge-based precipitation observations. Changes over time in composites of sea level pressure, 500 hPa height, and the vertical profile of equivalent potential temperature indicate that the observed increase in extreme precipitation events is associated with extratropical cyclones, including cut off low pressure and frontal systems. Analysis of the Eady maximum growth rate, an indicator for storm tracks, shows that storms tracks in recent years have shifted southward. In addition, mean summertime transient meridional winds have decreased over time, slowing baroclinic systems and causing stationary systems to become more frequent, in agreement with previous studies examining blocking due to high pressure systems. The Atlantic Ocean provides a significant supply of moisture that converges over the region when a cyclonic circulation is situated to the south, and the statistically significant increase in Eady maximum growth rate over time there provides an increasingly improved thermodynamic environment for extreme precipitation events.
Changes and Attribution of Extreme Precipitation in Climate Models: Subdaily and Daily Scales
NASA Astrophysics Data System (ADS)
Zhang, W.; Villarini, G.; Scoccimarro, E.; Vecchi, G. A.
2017-12-01
Extreme precipitation events are responsible for numerous hazards, including flooding, soil erosion, and landslides. Because of their significant socio-economic impacts, the attribution and projection of these events is of crucial importance to improve our response, mitigation and adaptation strategies. Here we present results from our ongoing work.In terms of attribution, we use idealized experiments [pre-industrial control experiment (PI) and 1% per year increase (1%CO2) in atmospheric CO2] from ten general circulation models produced under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the fraction of attributable risk to examine the CO2 effects on extreme precipitation at the sub-daily and daily scales. We find that the increased CO2 concentration substantially increases the odds of the occurrence of sub-daily precipitation extremes compared to the daily scale in most areas of the world, with the exception of some regions in the sub-tropics, likely in relation to the subsidence of the Hadley Cell. These results point to the large role that atmospheric CO2 plays in extreme precipitation under an idealized framework. Furthermore, we investigate the changes in extreme precipitation events with the Community Earth System Model (CESM) climate experiments using the scenarios consistent with the 1.5°C and 2°C temperature targets. We find that the frequency of annual extreme precipitation at a global scale increases in both 1.5°C and 2°C scenarios until around 2070, after which the magnitudes of the trend become much weaker or even negative. Overall, the frequency of global annual extreme precipitation is similar between 1.5°C and 2°C for the period 2006-2035, and the changes in extreme precipitation in individual seasons are consistent with those for the entire year. The frequency of extreme precipitation in the 2°C experiments is higher than for the 1.5°C experiment after the late 2030s, particularly for the period 2071-2100.
Robust increase in extreme summer rainfall intensity during the past four decades observed in China
NASA Astrophysics Data System (ADS)
Xiao, Chan; Wu, Peili; Zhang, Lixia; Song, Lianchun
2016-12-01
Global warming increases the moisture holding capacity of the atmosphere and consequently the potential risks of extreme rainfall. Here we show that maximum hourly summer rainfall intensity has increased by about 11.2% on average, using continuous hourly gauge records for 1971-2013 from 721 weather stations in China. The corresponding event accumulated precipitation has on average increased by more than 10% aided by a small positive trend in events duration. Linear regression of the 95th percentile daily precipitation intensity with daily mean surface air temperature shows a negative scaling of -9.6%/K, in contrast to a positive scaling of 10.6%/K for hourly data. This is made up of a positive scaling below the summer mean temperature and a negative scaling above. Using seasonal means instead of daily means, we find a consistent scaling rate for the region of 6.7-7%/K for both daily and hourly precipitation extremes, about 10% higher than the regional Clausius-Clapeyron scaling of 6.1%/K based on a mean temperature of 24.6 °C. With up to 18% further increase in extreme precipitation under continuing global warming towards the IPCC’s 1.5 °C target, risks of flash floods will exacerbate on top of the current incapability of urban drainage systems in a rapidly urbanizing China.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chiang, Patrick
2014-01-31
The research goal of this CAREER proposal is to develop energy-efficient, VLSI interconnect circuits and systems that will facilitate future massively-parallel, high-performance computing. Extreme-scale computing will exhibit massive parallelism on multiple vertical levels, from thou sands of computational units on a single processor to thousands of processors in a single data center. Unfortunately, the energy required to communicate between these units at every level (on chip, off-chip, off-rack) will be the critical limitation to energy efficiency. Therefore, the PI's career goal is to become a leading researcher in the design of energy-efficient VLSI interconnect for future computing systems.
Evaluation of Military Trauma System Practices Related to Complications After Injury
2012-01-01
and ventilator- associated pneumonia (VAP).3Y5 This current analysis illustrates three key examples of trauma system PI initiatives related to...the Abbreviated Injury Scale (AIS) body re- gion of 7 (upper extremity) or 8 (lower extremity). Compartment syndrome patients were identified in the...queried met the inclusion criteria for the VAP evaluation study. Of the total study popu- lation, 1.7% of patients (n = 107) acquired VAP, whereas
(U) Status of Trinity and Crossroads Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Archer, Billy Joe; Lujan, James Westley; Hemmert, K. S.
2017-01-10
(U) This paper provides a general overview of current and future plans for the Advanced Simulation and Computing (ASC) Advanced Technology (AT) systems fielded by the New Mexico Alliance for Computing at Extreme Scale (ACES), a collaboration between Los Alamos Laboratory and Sandia National Laboratories. Additionally, this paper touches on research of technology beyond traditional CMOS. The status of Trinity, ASCs first AT system, and Crossroads, anticipated to succeed Trinity as the third AT system in 2020 will be presented, along with initial performance studies of the Intel Knights Landing Xeon Phi processors, introduced on Trinity. The challenges and opportunitiesmore » for our production simulation codes on AT systems will also be discussed. Trinity and Crossroads are a joint procurement by ACES and Lawrence Berkeley Laboratory as part of the Alliance for application Performance at EXtreme scale (APEX) http://apex.lanl.gov.« less
Historical trends and extremes in boreal Alaska river basins
Bennett, Katrina E.; Cannon, Alex J.; Hinzman, Larry
2015-05-12
Climate change will shift the frequency, intensity, duration and persistence of extreme hydroclimate events and have particularly disastrous consequences in vulnerable systems such as the warm permafrost-dominated Interior region of boreal Alaska. This work focuses on recent research results from nonparametric trends and nonstationary generalized extreme value (GEV) analyses at eight Interior Alaskan river basins for the past 50/60 years (1954/64–2013). Trends analysis of maximum and minimum streamflow indicates a strong (>+50%) and statistically significant increase in 11-day flow events during the late fall/winter and during the snowmelt period (late April/mid-May), followed by a significant decrease in the 11-day flowmore » events during the post-snowmelt period (late May and into the summer). The April–May–June seasonal trends show significant decreases in maximum streamflow for snowmelt dominated systems (<–50%) and glacially influenced basins (–24% to –33%). Annual maximum streamflow trends indicate that most systems are experiencing declines, while minimum flow trends are largely increasing. Nonstationary GEV analysis identifies time-dependent changes in the distribution of spring extremes for snowmelt dominated and glacially dominated systems. Temperature in spring influences the glacial and high elevation snowmelt systems and winter precipitation drives changes in the snowmelt dominated basins. The Pacific Decadal Oscillation was associated with changes occurring in snowmelt dominated systems, and the Arctic Oscillation was linked to one lake dominated basin, with half of the basins exhibiting no change in response to climate variability. The paper indicates that broad scale studies examining trend and direction of change should employ multiple methods across various scales and consider regime dependent shifts to identify and understand changes in extreme streamflow within boreal forested watersheds of Alaska.« less
Extreme weather and climate events with ecological relevance: a review
Meehl, Gerald A.
2017-01-01
Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866
Extreme weather and climate events with ecological relevance: a review.
Ummenhofer, Caroline C; Meehl, Gerald A
2017-06-19
Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).
Kinetic turbulence simulations at extreme scale on leadership-class systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Bei; Ethier, Stephane; Tang, William
2013-01-01
Reliable predictive simulation capability addressing confinement properties in magnetically confined fusion plasmas is critically-important for ITER, a 20 billion dollar international burning plasma device under construction in France. The complex study of kinetic turbulence, which can severely limit the energy confinement and impact the economic viability of fusion systems, requires simulations at extreme scale for such an unprecedented device size. Our newly optimized, global, ab initio particle-in-cell code solving the nonlinear equations underlying gyrokinetic theory achieves excellent performance with respect to "time to solution" at the full capacity of the IBM Blue Gene/Q on 786,432 cores of Mira at ALCFmore » and recently of the 1,572,864 cores of Sequoia at LLNL. Recent multithreading and domain decomposition optimizations in the new GTC-P code represent critically important software advances for modern, low memory per core systems by enabling routine simulations at unprecedented size (130 million grid points ITER-scale) and resolution (65 billion particles).« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Melin, Alexander M.; Kisner, Roger A.; Drira, Anis
Embedded instrumentation and control systems that can operate in extreme environments are challenging due to restrictions on sensors and materials. As a part of the Department of Energy's Nuclear Energy Enabling Technology cross-cutting technology development programs Advanced Sensors and Instrumentation topic, this report details the design of a bench-scale embedded instrumentation and control testbed. The design goal of the bench-scale testbed is to build a re-configurable system that can rapidly deploy and test advanced control algorithms in a hardware in the loop setup. The bench-scale testbed will be designed as a fluid pump analog that uses active magnetic bearings tomore » support the shaft. The testbed represents an application that would improve the efficiency and performance of high temperature (700 C) pumps for liquid salt reactors that operate in an extreme environment and provide many engineering challenges that can be overcome with embedded instrumentation and control. This report will give details of the mechanical design, electromagnetic design, geometry optimization, power electronics design, and initial control system design.« less
Public Health System Response to Extreme Weather Events.
Hunter, Mark D; Hunter, Jennifer C; Yang, Jane E; Crawley, Adam W; Aragón, Tomás J
2016-01-01
Extreme weather events, unpredictable and often far-reaching, constitute a persistent challenge for public health preparedness. The goal of this research is to inform public health systems improvement through examination of extreme weather events, comparing across cases to identify recurring patterns in event and response characteristics. Structured telephone-based interviews were conducted with representatives from health departments to assess characteristics of recent extreme weather events and agencies' responses. Response activities were assessed using the Centers for Disease Control and Prevention Public Health Emergency Preparedness Capabilities framework. Challenges that are typical of this response environment are reported. Forty-five local health departments in 20 US states. Respondents described public health system responses to 45 events involving tornadoes, flooding, wildfires, winter weather, hurricanes, and other storms. Events of similar scale were infrequent for a majority (62%) of the communities involved; disruption to critical infrastructure was universal. Public Health Emergency Preparedness Capabilities considered most essential involved environmental health investigations, mass care and sheltering, surveillance and epidemiology, information sharing, and public information and warning. Unanticipated response activities or operational constraints were common. We characterize extreme weather events as a "quadruple threat" because (1) direct threats to population health are accompanied by damage to public health protective and community infrastructure, (2) event characteristics often impose novel and pervasive burdens on communities, (3) responses rely on critical infrastructures whose failure both creates new burdens and diminishes response capacity, and (4) their infrequency and scale further compromise response capacity. Given the challenges associated with extreme weather events, we suggest opportunities for organizational learning and preparedness improvements.
Long-term trend analysis on total and extreme precipitation over Shasta Dam watershed.
Toride, Kinya; Cawthorne, Dylan L; Ishida, Kei; Kavvas, M Levent; Anderson, Michael L
2018-06-01
California's interconnected water system is one of the most advanced water management systems in the world, and understanding of long-term trends in atmospheric and hydrologic behavior has increasingly being seen as vital to its future well-being. Knowledge of such trends is hampered by the lack of long-period observation data and the uncertainty surrounding future projections of atmospheric models. This study examines historical precipitation trends over the Shasta Dam watershed (SDW), which lies upstream of one of the most important components of California's water system, Shasta Dam, using a dynamical downscaling methodology that can produce atmospheric data at fine time-space scales. The Weather Research and Forecasting (WRF) model is employed to reconstruct 159years of long-term hourly precipitation data at 3km spatial resolution over SDW using the 20th Century Reanalysis Version 2c dataset. Trend analysis on this data indicates a significant increase in total precipitation as well as a growing intensity of extreme events such as 1, 6, 12, 24, 48, and 72-hour storms over the period of 1851 to 2010. The turning point of the increasing trend and no significant trend periods is found to be 1940 for annual precipitation and the period of 1950 to 1960 for extreme precipitation using the sequential Mann-Kendall test. Based on these analysis, we find the trends at the regional scale do not necessarily apply to the watershed-scale. The sharp increase in the variability of annual precipitation since 1970s is also detected, which implies an increase in the occurrence of extreme wet and dry conditions. These results inform long-term planning decisions regarding the future of Shasta Dam and California's water system. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Wang, J.
2013-12-01
Extreme weather events have already significantly influenced North America. During 2005-2011, the extreme events have increased by 250 %, from four or fewer events occurring in 2005, while 14 events occurring in 2011 (www.ncdc.noaa.gov/billions/). In addition, extreme rainfall amounts, frequency, and intensity were all expected to increase under greenhouse warming scenarios (Wehner 2005; Kharin et al. 2007; Tebaldi et al. 2006). Global models are powerful tools to investigate the climate and climate change on large scales. However, such models do not represent local terrain and mesoscale weather systems well owing to their coarse horizontal resolution (150-300 km). To capture the fine-scale features of extreme weather events, regional climate models (RCMs) with a more realistic representation of the complex terrain and heterogeneous land surfaces are needed (Mass et al. 2002). This study uses the Nested Regional Climate model (NRCM) to perform regional scale climate simulations on a 12-km × 12-km high resolution scale over North America (including Alaska; with 600 × 515 grid cells at longitude and latitude), known as CORDEX_North America, instead of small regions as studied previously (eg., Dominguez et al. 2012; Gao et al. 2012). The performance and the biases of the NRCM extreme precipitation calculations (2000-2010) have been evaluated with PRISM precipitation (Daly et al. 1997) by Wang and Kotamarthi (2013): the NRCM replicated very well the monthly amount of extreme precipitation with less than 3% overestimation over East CONUS, and the frequency of extremes over West CONUS and upper Mississippi River Basin. The Representative Concentration Pathway (RCP) 8.5 and RCP 4.5 from the new Community Earth System Model version 1.0 (CESM v1.0) are dynamically downscaled to predict the extreme rainfall events at the end-of-century (2085-2095) and to explore the uncertainties of future extreme precipitation induced by different scenarios over distinct regions. We have corrected the CO2 atmospheric concentration in the longwave/shortwave radiation schemes of the NRCM according to the recommended datasets by CMIP5 (Clarke et al. 2007; Riahi et al. 2007). We have also corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask of CLM 4.0 as mentioned by Gao et al. (2012). Acknowledgements: This work was supported under a military interdepartmental purchase request from the SERDP, RC-2242, through U.S. Department of Energy contract DE-AC02-06CH11357.
Statistical Extremes of Turbulence and a Cascade Generalisation of Euler's Gyroscope Equation
NASA Astrophysics Data System (ADS)
Tchiguirinskaia, Ioulia; Scherzer, Daniel
2016-04-01
Turbulence refers to a rather well defined hydrodynamical phenomenon uncovered by Reynolds. Nowadays, the word turbulence is used to designate the loss of order in many different geophysical fields and the related fundamental extreme variability of environmental data over a wide range of scales. Classical statistical techniques for estimating the extremes, being largely limited to statistical distributions, do not take into account the mechanisms generating such extreme variability. An alternative approaches to nonlinear variability are based on a fundamental property of the non-linear equations: scale invariance, which means that these equations are formally invariant under given scale transforms. Its specific framework is that of multifractals. In this framework extreme variability builds up scale by scale leading to non-classical statistics. Although multifractals are increasingly understood as a basic framework for handling such variability, there is still a gap between their potential and their actual use. In this presentation we discuss how to dealt with highly theoretical problems of mathematical physics together with a wide range of geophysical applications. We use Euler's gyroscope equation as a basic element in constructing a complex deterministic system that preserves not only the scale symmetry of the Navier-Stokes equations, but some more of their symmetries. Euler's equation has been not only the object of many theoretical investigations of the gyroscope device, but also generalised enough to become the basic equation of fluid mechanics. Therefore, there is no surprise that a cascade generalisation of this equation can be used to characterise the intermittency of turbulence, to better understand the links between the multifractal exponents and the structure of a simplified, but not simplistic, version of the Navier-Stokes equations. In a given way, this approach is similar to that of Lorenz, who studied how the flap of a butterfly wing could generate a cyclone with the help of a 3D ordinary differential system. Being well supported by the extensive numerical results, the cascade generalisation of Euler's gyroscope equation opens new horizons for predictability and predictions of processes having long-range dependences.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katti, Amogh; Di Fatta, Giuseppe; Naughton III, Thomas J
Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implementedmore » and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.« less
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.
Gravo-Aeroelastic Scaling for Extreme-Scale Wind Turbines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fingersh, Lee J; Loth, Eric; Kaminski, Meghan
2017-06-09
A scaling methodology is described in the present paper for extreme-scale wind turbines (rated at 10 MW or more) that allow their sub-scale turbines to capture their key blade dynamics and aeroelastic deflections. For extreme-scale turbines, such deflections and dynamics can be substantial and are primarily driven by centrifugal, thrust and gravity forces as well as the net torque. Each of these are in turn a function of various wind conditions, including turbulence levels that cause shear, veer, and gust loads. The 13.2 MW rated SNL100-03 rotor design, having a blade length of 100-meters, is herein scaled to the CART3more » wind turbine at NREL using 25% geometric scaling and blade mass and wind speed scaled by gravo-aeroelastic constraints. In order to mimic the ultralight structure on the advanced concept extreme-scale design the scaling results indicate that the gravo-aeroelastically scaled blades for the CART3 are be three times lighter and 25% longer than the current CART3 blades. A benefit of this scaling approach is that the scaled wind speeds needed for testing are reduced (in this case by a factor of two), allowing testing under extreme gust conditions to be much more easily achieved. Most importantly, this scaling approach can investigate extreme-scale concepts including dynamic behaviors and aeroelastic deflections (including flutter) at an extremely small fraction of the full-scale cost.« less
NASA Astrophysics Data System (ADS)
Klein, Cornelia; Belušić, Danijel; Taylor, Christopher M.
2018-03-01
Mesoscale convective systems (MCSs) are frequently associated with rainfall extremes and are expected to further intensify under global warming. However, despite the significant impact of such extreme events, the dominant processes favoring their occurrence are still under debate. Meteosat geostationary satellites provide unique long-term subhourly records of cloud top temperatures, allowing to track changes in MCS structures that could be linked to rainfall intensification. Focusing on West Africa, we show that Meteosat cloud top temperatures are a useful proxy for rainfall intensities, as derived from snapshots from the Tropical Rainfall Measuring Mission 2A25 product: MCSs larger than 15,000 km2 at a temperature threshold of -40°C are found to produce 91% of all extreme rainfall occurrences in the study region, with 80% of the storms producing extreme rain when their minimum temperature drops below -80°C. Furthermore, we present a new method based on 2-D continuous wavelet transform to explore the relationship between cloud top temperature and rainfall intensity for subcloud features at different length scales. The method shows great potential for separating convective and stratiform cloud parts when combining information on temperature and scale, improving the common approach of using a temperature threshold only. We find that below -80°C, every fifth pixel is associated with deep convection. This frequency is doubled when looking at subcloud features smaller than 35 km. Scale analysis of subcloud features can thus help to better exploit cloud top temperature data sets, which provide much more spatiotemporal detail of MCS characteristics than available rainfall data sets alone.
GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation.
Hess, Berk; Kutzner, Carsten; van der Spoel, David; Lindahl, Erik
2008-03-01
Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest numbers of standard cluster nodes.
Extreme Cost Reductions with Multi-Megawatt Centralized Inverter Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schwabe, Ulrich; Fishman, Oleg
2015-03-20
The objective of this project was to fully develop, demonstrate, and commercialize a new type of utility scale PV system. Based on patented technology, this includes the development of a truly centralized inverter system with capacities up to 100MW, and a high voltage, distributed harvesting approach. This system promises to greatly impact both the energy yield from large scale PV systems by reducing losses and increasing yield from mismatched arrays, as well as reduce overall system costs through very cost effective conversion and BOS cost reductions enabled by higher voltage operation.
Resilience Design Patterns - A Structured Approach to Resilience at Extreme Scale (version 1.0)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hukerikar, Saurabh; Engelmann, Christian
Reliability is a serious concern for future extreme-scale high-performance computing (HPC) systems. Projections based on the current generation of HPC systems and technology roadmaps suggest that very high fault rates in future systems. The errors resulting from these faults will propagate and generate various kinds of failures, which may result in outcomes ranging from result corruptions to catastrophic application crashes. Practical limits on power consumption in HPC systems will require future systems to embrace innovative architectures, increasing the levels of hardware and software complexities. The resilience challenge for extreme-scale HPC systems requires management of various hardware and software technologies thatmore » are capable of handling a broad set of fault models at accelerated fault rates. These techniques must seek to improve resilience at reasonable overheads to power consumption and performance. While the HPC community has developed various solutions, application-level as well as system-based solutions, the solution space of HPC resilience techniques remains fragmented. There are no formal methods and metrics to investigate and evaluate resilience holistically in HPC systems that consider impact scope, handling coverage, and performance & power eciency across the system stack. Additionally, few of the current approaches are portable to newer architectures and software ecosystems, which are expected to be deployed on future systems. In this document, we develop a structured approach to the management of HPC resilience based on the concept of resilience-based design patterns. A design pattern is a general repeatable solution to a commonly occurring problem. We identify the commonly occurring problems and solutions used to deal with faults, errors and failures in HPC systems. The catalog of resilience design patterns provides designers with reusable design elements. We define a design framework that enhances our understanding of the important constraints and opportunities for solutions deployed at various layers of the system stack. The framework may be used to establish mechanisms and interfaces to coordinate flexible fault management across hardware and software components. The framework also enables optimization of the cost-benefit trade-os among performance, resilience, and power consumption. The overall goal of this work is to enable a systematic methodology for the design and evaluation of resilience technologies in extreme-scale HPC systems that keep scientific applications running to a correct solution in a timely and cost-ecient manner in spite of frequent faults, errors, and failures of various types.« less
NASA Astrophysics Data System (ADS)
Subramanian, A. C.; Lavers, D.; Matsueda, M.; Shukla, S.; Cayan, D. R.; Ralph, M.
2017-12-01
Atmospheric rivers (ARs) - elongated plumes of intense moisture transport - are a primary source of hydrological extremes, water resources and impactful weather along the West Coast of North America and Europe. There is strong demand in the water management, societal infrastructure and humanitarian sectors for reliable sub-seasonal forecasts, particularly of extreme events, such as floods and droughts so that actions to mitigate disastrous impacts can be taken with sufficient lead-time. Many recent studies have shown that ARs in the Pacific and the Atlantic are modulated by large-scale modes of climate variability. Leveraging the improved understanding of how these large-scale climate modes modulate the ARs in these two basins, we use the state-of-the-art multi-model forecast systems such as the North American Multi-Model Ensemble (NMME) and the Subseasonal-to-Seasonal (S2S) database to help inform and assess the probabilistic prediction of ARs and related extreme weather events over the North American and European West Coasts. We will present results from evaluating probabilistic forecasts of extreme precipitation and AR activity at the sub-seasonal scale. In particular, results from the comparison of two winters (2015-16 and 2016-17) will be shown, winters which defied canonical El Niño teleconnection patterns over North America and Europe. We further extend this study to analyze probabilistic forecast skill of AR events in these two basins and the variability in forecast skill during certain regimes of large-scale climate modes.
Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR
NASA Astrophysics Data System (ADS)
Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.
2017-12-01
Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.
NASA Astrophysics Data System (ADS)
Wohlmuth, Johannes; Andersen, Jørgen Vitting
2006-05-01
We use agent-based models to study the competition among investors who use trading strategies with different amount of information and with different time scales. We find that mixing agents that trade on the same time scale but with different amount of information has a stabilizing impact on the large and extreme fluctuations of the market. Traders with the most information are found to be more likely to arbitrage traders who use less information in the decision making. On the other hand, introducing investors who act on two different time scales has a destabilizing effect on the large and extreme price movements, increasing the volatility of the market. Closeness in time scale used in the decision making is found to facilitate the creation of local trends. The larger the overlap in commonly shared information the more the traders in a mixed system with different time scales are found to profit from the presence of traders acting at another time scale than themselves.
Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Biros, George
Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore » include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a central challenge in UQ, especially for large-scale models. We propose to develop the mathematical tools to address these challenges in the context of extreme-scale problems. 4. Parallel scalable algorithms for Bayesian optimal experimental design (OED). Bayesian inversion yields quantified uncertainties in the model parameters, which can be propagated forward through the model to yield uncertainty in outputs of interest. This opens the way for designing new experiments to reduce the uncertainties in the model parameters and model predictions. Such experimental design problems have been intractable for large-scale problems using conventional methods; we will create OED algorithms that exploit the structure of the PDE model and the parameter-to-output map to overcome these challenges. Parallel algorithms for these four problems were created, analyzed, prototyped, implemented, tuned, and scaled up for leading-edge supercomputers, including UT-Austin’s own 10 petaflops Stampede system, ANL’s Mira system, and ORNL’s Titan system. While our focus is on fundamental mathematical/computational methods and algorithms, we will assess our methods on model problems derived from several DOE mission applications, including multiscale mechanics and ice sheet dynamics.« less
The trend of the multi-scale temporal variability of precipitation in Colorado River Basin
NASA Astrophysics Data System (ADS)
Jiang, P.; Yu, Z.
2011-12-01
Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.
Using Rollback Avoidance to Mitigate Failures in Next-Generation Extreme-Scale Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Levy, Scott N.
2016-05-01
High-performance computing (HPC) systems enable scientists to numerically model complex phenomena in many important physical systems. The next major milestone in the development of HPC systems is the construction of the rst supercomputer capable executing more than an exa op, 10 18 oating point operations per second. On systems of this scale, failures will occur much more frequently than on current systems. As a result, resilience is a key obstacle to building next-generation extremescale systems. Coordinated checkpointing is currently the most widely-used mechanism for handling failures on HPC systems. Although coordinated checkpointing remains e ective on current systems, increasing themore » scale of today's systems to build next-generation systems will increase the cost of fault tolerance as more and more time is taken away from the application to protect against or recover from failure. Rollback avoidance techniques seek to mitigate the cost of checkpoint/restart by allowing an application to continue its execution rather than rolling back to an earlier checkpoint when failures occur. These techniqes include failure prediction and preventive migration, replicated computation, fault-tolerant algorithms, and softwarebased memory fault correction. In this thesis, we examine how rollback avoidance techniques can be used to address failures on extreme-scale systems. Using a combination of analytic modeling and simulation, we evaluate the potential impact of rollback avoidance on these systems. We then present a novel rollback avoidance technique that exploits similarities in application memory. Finally, we examine the feasibility of using this technique to protect against memory faults in kernel memory.« less
NASA Astrophysics Data System (ADS)
Jajcay, N.; Kravtsov, S.; Tsonis, A.; Palus, M.
2017-12-01
A better understanding of dynamics in complex systems, such as the Earth's climate is one of the key challenges for contemporary science and society. A large amount of experimental data requires new mathematical and computational approaches. Natural complex systems vary on many temporal and spatial scales, often exhibiting recurring patterns and quasi-oscillatory phenomena. The statistical inference of causal interactions and synchronization between dynamical phenomena evolving on different temporal scales is of vital importance for better understanding of underlying mechanisms and a key for modeling and prediction of such systems. This study introduces and applies information theory diagnostics to phase and amplitude time series of different wavelet components of the observed data that characterizes El Niño. A suite of significant interactions between processes operating on different time scales was detected, and intermittent synchronization among different time scales has been associated with the extreme El Niño events. The mechanisms of these nonlinear interactions were further studied in conceptual low-order and state-of-the-art dynamical, as well as statistical climate models. Observed and simulated interactions exhibit substantial discrepancies, whose understanding may be the key to an improved prediction. Moreover, the statistical framework which we apply here is suitable for direct usage of inferring cross-scale interactions in nonlinear time series from complex systems such as the terrestrial magnetosphere, solar-terrestrial interactions, seismic activity or even human brain dynamics.
NASA Technical Reports Server (NTRS)
Collow, Allison; Bosilovich, Mike; Koster, Randal
2017-01-01
Over the past 15 years, the northeastern United States has seen a statistically significant increase in the frequency of extreme precipitation events that is larger and more widespread than anywhere else in the country. This increase in events is more likely to be associated with frontal and low-pressure systems, rather than being caused by more tropical cyclones impacting the region.
Impacts of Irrigation on Daily Extremes in the Coupled Climate System
NASA Technical Reports Server (NTRS)
Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide
2014-01-01
Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.
Relating rainfall characteristics to cloud top temperatures at different scales
NASA Astrophysics Data System (ADS)
Klein, Cornelia; Belušić, Danijel; Taylor, Christopher
2017-04-01
Extreme rainfall from mesoscale convective systems (MCS) poses a threat to lives and livelihoods of the West African population through increasingly frequent devastating flooding and loss of crops. However, despite the significant impact of such extreme events, the dominant processes favouring their occurrence are still under debate. In the data-sparse West African region, rainfall radar data from the Tropical Rainfall Measuring Mission (TRMM) gives invaluable information on the distribution and frequency of extreme rainfall. The TRMM 2A25 product provides a 15-year dataset of snapshots of surface rainfall from 2-4 overpasses per day. Whilst this sampling captures the overall rainfall characteristics, it is neither long nor frequent enough to diagnose changes in MCS properties, which may be linked to the trend towards rainfall intensification in the region. On the other hand, Meteosat geostationary satellites provide long-term sub-hourly records of cloud top temperatures, raising the possibility of combining these with the high-quality rainfall data from TRMM. In this study, we relate TRMM 2A25 rainfall to Meteosat Second Generation (MSG) cloud top temperatures, which are available from 2004 at 15 minutes intervals, to get a more detailed picture of the structure of intense rainfall within the life cycle of MCS. We find TRMM rainfall intensities within an MCS to be strongly coupled with MSG cloud top temperatures: the probability for extreme rainfall increases from <10% for minimum temperatures warmer than -40°C to over 70% when temperatures drop below -70°C, confirming the potential in analysing cloud-top temperatures as a proxy for extreme rain. The sheer size of MCS raises the question which scales of sub-cloud structures are more likely to be associated with extreme rain than others. In the end, this information could help to associate scale changes in cloud top temperatures with processes that affect the probability of extreme rain. We use 2D continuous wavelets to decompose cloud top temperatures into power spectra at scales between 15 and 200km. From these, cloud sub-structures are identified as circular areas of respective scale with local power maxima in their centre. These areas are then mapped onto coinciding TRMM rainfall, allowing us to assign rainfall fields to sub-cloud features of different scales. We find a higher probability for extreme rainfall for cloud features above a scale of 30km, with features 100km contributing most to the number of extreme rainfall pixels. Over the average diurnal cycle, the number of smaller cloud features between 15-60km shows an increase between 15 - 1700UTC, gradually developing into larger ones. The maximum of extreme rainfall pixels around 1900UTC coincides with a peak for scales 100km, suggesting a dominant role of these scales for intense rain for the analysed cloud type. Our results demonstrate the suitability of 2D wavelet decomposition for the analysis of sub-cloud structures and their relation to rainfall characteristics, and help us to understand long-term changes in the properties of MCS.
The future of scientific workflows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deelman, Ewa; Peterka, Tom; Altintas, Ilkay
Today’s computational, experimental, and observational sciences rely on computations that involve many related tasks. The success of a scientific mission often hinges on the computer automation of these workflows. In April 2015, the US Department of Energy (DOE) invited a diverse group of domain and computer scientists from national laboratories supported by the Office of Science, the National Nuclear Security Administration, from industry, and from academia to review the workflow requirements of DOE’s science and national security missions, to assess the current state of the art in science workflows, to understand the impact of emerging extreme-scale computing systems on thosemore » workflows, and to develop requirements for automated workflow management in future and existing environments. This article is a summary of the opinions of over 50 leading researchers attending this workshop. We highlight use cases, computing systems, workflow needs and conclude by summarizing the remaining challenges this community sees that inhibit large-scale scientific workflows from becoming a mainstream tool for extreme-scale science.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bennett, Katrina E.; Cannon, Alex J.; Hinzman, Larry
Climate change will shift the frequency, intensity, duration and persistence of extreme hydroclimate events and have particularly disastrous consequences in vulnerable systems such as the warm permafrost-dominated Interior region of boreal Alaska. This work focuses on recent research results from nonparametric trends and nonstationary generalized extreme value (GEV) analyses at eight Interior Alaskan river basins for the past 50/60 years (1954/64–2013). Trends analysis of maximum and minimum streamflow indicates a strong (>+50%) and statistically significant increase in 11-day flow events during the late fall/winter and during the snowmelt period (late April/mid-May), followed by a significant decrease in the 11-day flowmore » events during the post-snowmelt period (late May and into the summer). The April–May–June seasonal trends show significant decreases in maximum streamflow for snowmelt dominated systems (<–50%) and glacially influenced basins (–24% to –33%). Annual maximum streamflow trends indicate that most systems are experiencing declines, while minimum flow trends are largely increasing. Nonstationary GEV analysis identifies time-dependent changes in the distribution of spring extremes for snowmelt dominated and glacially dominated systems. Temperature in spring influences the glacial and high elevation snowmelt systems and winter precipitation drives changes in the snowmelt dominated basins. The Pacific Decadal Oscillation was associated with changes occurring in snowmelt dominated systems, and the Arctic Oscillation was linked to one lake dominated basin, with half of the basins exhibiting no change in response to climate variability. The paper indicates that broad scale studies examining trend and direction of change should employ multiple methods across various scales and consider regime dependent shifts to identify and understand changes in extreme streamflow within boreal forested watersheds of Alaska.« less
Resilience Design Patterns - A Structured Approach to Resilience at Extreme Scale (version 1.1)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hukerikar, Saurabh; Engelmann, Christian
Reliability is a serious concern for future extreme-scale high-performance computing (HPC) systems. Projections based on the current generation of HPC systems and technology roadmaps suggest the prevalence of very high fault rates in future systems. The errors resulting from these faults will propagate and generate various kinds of failures, which may result in outcomes ranging from result corruptions to catastrophic application crashes. Therefore the resilience challenge for extreme-scale HPC systems requires management of various hardware and software technologies that are capable of handling a broad set of fault models at accelerated fault rates. Also, due to practical limits on powermore » consumption in HPC systems future systems are likely to embrace innovative architectures, increasing the levels of hardware and software complexities. As a result the techniques that seek to improve resilience must navigate the complex trade-off space between resilience and the overheads to power consumption and performance. While the HPC community has developed various resilience solutions, application-level techniques as well as system-based solutions, the solution space of HPC resilience techniques remains fragmented. There are no formal methods and metrics to investigate and evaluate resilience holistically in HPC systems that consider impact scope, handling coverage, and performance & power efficiency across the system stack. Additionally, few of the current approaches are portable to newer architectures and software environments that will be deployed on future systems. In this document, we develop a structured approach to the management of HPC resilience using the concept of resilience-based design patterns. A design pattern is a general repeatable solution to a commonly occurring problem. We identify the commonly occurring problems and solutions used to deal with faults, errors and failures in HPC systems. Each established solution is described in the form of a pattern that addresses concrete problems in the design of resilient systems. The complete catalog of resilience design patterns provides designers with reusable design elements. We also define a framework that enhances a designer's understanding of the important constraints and opportunities for the design patterns to be implemented and deployed at various layers of the system stack. This design framework may be used to establish mechanisms and interfaces to coordinate flexible fault management across hardware and software components. The framework also supports optimization of the cost-benefit trade-offs among performance, resilience, and power consumption. The overall goal of this work is to enable a systematic methodology for the design and evaluation of resilience technologies in extreme-scale HPC systems that keep scientific applications running to a correct solution in a timely and cost-efficient manner in spite of frequent faults, errors, and failures of various types.« less
Unveiling non-stationary coupling between Amazon and ocean during recent extreme events
NASA Astrophysics Data System (ADS)
Ramos, Antônio M. de T.; Zou, Yong; de Oliveira, Gilvan Sampaio; Kurths, Jürgen; Macau, Elbert E. N.
2018-02-01
The interplay between extreme events in the Amazon's precipitation and the anomaly in the temperature of the surrounding oceans is not fully understood, especially its causal relations. In this paper, we investigate the climatic interaction between these regions from 1999 until 2012 using modern tools of complex system science. We identify the time scale of the coupling quantitatively and unveil the non-stationary influence of the ocean's temperature. The findings show consistently the distinctions between the coupling in the recent major extreme events in Amazonia, such as the two droughts that happened in 2005 and 2010 and the three floods during 1999, 2009 and 2012. Interestingly, the results also reveal the influence over the anomalous precipitation of Southwest Amazon has become increasingly lagged. The analysis can shed light on the underlying dynamics of the climate network system and consequently can improve predictions of extreme rainfall events.
Settlement-Size Scaling among Prehistoric Hunter-Gatherer Settlement Systems in the New World
Haas, W. Randall; Klink, Cynthia J.; Maggard, Greg J.; Aldenderfer, Mark S.
2015-01-01
Settlement size predicts extreme variation in the rates and magnitudes of many social and ecological processes in human societies. Yet, the factors that drive human settlement-size variation remain poorly understood. Size variation among economically integrated settlements tends to be heavy tailed such that the smallest settlements are extremely common and the largest settlements extremely large and rare. The upper tail of this size distribution is often formalized mathematically as a power-law function. Explanations for this scaling structure in human settlement systems tend to emphasize complex socioeconomic processes including agriculture, manufacturing, and warfare—behaviors that tend to differentially nucleate and disperse populations hierarchically among settlements. But, the degree to which heavy-tailed settlement-size variation requires such complex behaviors remains unclear. By examining the settlement patterns of eight prehistoric New World hunter-gatherer settlement systems spanning three distinct environmental contexts, this analysis explores the degree to which heavy-tailed settlement-size scaling depends on the aforementioned socioeconomic complexities. Surprisingly, the analysis finds that power-law models offer plausible and parsimonious statistical descriptions of prehistoric hunter-gatherer settlement-size variation. This finding reveals that incipient forms of hierarchical settlement structure may have preceded socioeconomic complexity in human societies and points to a need for additional research to explicate how mobile foragers came to exhibit settlement patterns that are more commonly associated with hierarchical organization. We propose that hunter-gatherer mobility with preferential attachment to previously occupied locations may account for the observed structure in site-size variation. PMID:26536241
NASA Astrophysics Data System (ADS)
Wehner, Michael; Pall, Pardeep; Zarzycki, Colin; Stone, Daithi
2016-04-01
Probabilistic extreme event attribution is especially difficult for weather events that are caused by extremely rare large-scale meteorological patterns. Traditional modeling techniques have involved using ensembles of climate models, either fully coupled or with prescribed ocean and sea ice. Ensemble sizes for the latter case ranges from several 100 to tens of thousand. However, even if the simulations are constrained by the observed ocean state, the requisite large-scale meteorological pattern may not occur frequently enough or even at all in free running climate model simulations. We present a method to ensure that simulated events similar to the observed event are modeled with enough fidelity that robust statistics can be determined given the large scale meteorological conditions. By initializing suitably constrained short term ensemble hindcasts of both the actual weather system and a counterfactual weather system where the human interference in the climate system is removed, the human contribution to the magnitude of the event can be determined. However, the change (if any) in the probability of an event of the observed magnitude is conditional not only on the state of the ocean/sea ice system but also on the prescribed initial conditions determined by the causal large scale meteorological pattern. We will discuss the implications of this technique through two examples; the 2013 Colorado flood and the 2014 Typhoon Haiyan.
NASA Astrophysics Data System (ADS)
Loikith, P. C.; Broccoli, A. J.; Waliser, D. E.; Lintner, B. R.; Neelin, J. D.
2015-12-01
Anomalous large-scale circulation patterns often play a key role in the occurrence of temperature extremes. For example, large-scale circulation can drive horizontal temperature advection or influence local processes that lead to extreme temperatures, such as by inhibiting moderating sea breezes, promoting downslope adiabatic warming, and affecting the development of cloud cover. Additionally, large-scale circulation can influence the shape of temperature distribution tails, with important implications for the magnitude of future changes in extremes. As a result of the prominent role these patterns play in the occurrence and character of extremes, the way in which temperature extremes change in the future will be highly influenced by if and how these patterns change. It is therefore critical to identify and understand the key patterns associated with extremes at local to regional scales in the current climate and to use this foundation as a target for climate model validation. This presentation provides an overview of recent and ongoing work aimed at developing and applying novel approaches to identifying and describing the large-scale circulation patterns associated with temperature extremes in observations and using this foundation to evaluate state-of-the-art global and regional climate models. Emphasis is given to anomalies in sea level pressure and 500 hPa geopotential height over North America using several methods to identify circulation patterns, including self-organizing maps and composite analysis. Overall, evaluation results suggest that models are able to reproduce observed patterns associated with temperature extremes with reasonable fidelity in many cases. Model skill is often highest when and where synoptic-scale processes are the dominant mechanisms for extremes, and lower where sub-grid scale processes (such as those related to topography) are important. Where model skill in reproducing these patterns is high, it can be inferred that extremes are being simulated for plausible physical reasons, boosting confidence in future projections of temperature extremes. Conversely, where model skill is identified to be lower, caution should be exercised in interpreting future projections.
On the nonlinearity of spatial scales in extreme weather attribution statements
NASA Astrophysics Data System (ADS)
Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; Alexander, Lisa V.; Wehner, Michael; Shiogama, Hideo; Wolski, Piotr; Ciavarella, Andrew; Christidis, Nikolaos
2018-04-01
In the context of ongoing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporal scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.
On the nonlinearity of spatial scales in extreme weather attribution statements
DOE Office of Scientific and Technical Information (OSTI.GOV)
Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah
In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less
On the nonlinearity of spatial scales in extreme weather attribution statements
Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; ...
2017-06-17
In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less
Scaling of Precipitation Extremes Modelled by Generalized Pareto Distribution
NASA Astrophysics Data System (ADS)
Rajulapati, C. R.; Mujumdar, P. P.
2017-12-01
Precipitation extremes are often modelled with data from annual maximum series or peaks over threshold series. The Generalized Pareto Distribution (GPD) is commonly used to fit the peaks over threshold series. Scaling of precipitation extremes from larger time scales to smaller time scales when the extremes are modelled with the GPD is burdened with difficulties arising from varying thresholds for different durations. In this study, the scale invariance theory is used to develop a disaggregation model for precipitation extremes exceeding specified thresholds. A scaling relationship is developed for a range of thresholds obtained from a set of quantiles of non-zero precipitation of different durations. The GPD parameters and exceedance rate parameters are modelled by the Bayesian approach and the uncertainty in scaling exponent is quantified. A quantile based modification in the scaling relationship is proposed for obtaining the varying thresholds and exceedance rate parameters for shorter durations. The disaggregation model is applied to precipitation datasets of Berlin City, Germany and Bangalore City, India. From both the applications, it is observed that the uncertainty in the scaling exponent has a considerable effect on uncertainty in scaled parameters and return levels of shorter durations.
NASA Astrophysics Data System (ADS)
Black, R. X.
2017-12-01
We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.
NASA Astrophysics Data System (ADS)
Martel, J. L.; Brissette, F.; Mailhot, A.; Wood, R. R.; Ludwig, R.; Frigon, A.; Leduc, M.; Turcotte, R.
2017-12-01
Recent studies indicate that the frequency and intensity of extreme precipitation will increase in future climate due to global warming. In this study, we compare annual maxima precipitation series from three large ensembles of climate simulations at various spatial and temporal resolutions. The first two are at the global scale: the Canadian Earth System Model (CanESM2) 50-member large ensemble (CanESM2-LE) at a 2.8° resolution and the Community Earth System Model (CESM1) 40-member large ensemble (CESM1-LE) at a 1° resolution. The third ensemble is at the regional scale over both Eastern North America and Europe: the Canadian Regional Climate Model (CRCM5) 50-member large ensemble (CRCM5-LE) at a 0.11° resolution, driven at its boundaries by the CanESM-LE. The CRCM5-LE is a new ensemble issued from the ClimEx project (http://www.climex-project.org), a Québec-Bavaria collaboration. Using these three large ensembles, change in extreme precipitations over the historical (1980-2010) and future (2070-2100) periods are investigated. This results in 1 500 (30 years x 50 members for CanESM2-LE and CRCM5-LE) and 1200 (30 years x 40 members for CESM1-LE) simulated years over both the historical and future periods. Using these large datasets, the empirical daily (and sub-daily for CRCM5-LE) extreme precipitation quantiles for large return periods ranging from 2 to 100 years are computed. Results indicate that daily extreme precipitations generally will increase over most land grid points of both domains according to the three large ensembles. Regarding the CRCM5-LE, the increase in sub-daily extreme precipitations will be even more important than the one observed for daily extreme precipitations. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety.
NASA Astrophysics Data System (ADS)
Lui, Yuk Sing; Tam, Chi-Yung; Lau, Ngar-Cheung
2018-04-01
This study examines the impacts of climate change on precipitation extremes in the Asian monsoon region during boreal summer, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model. The model can capture the summertime monsoon rainfall, with characteristics similar to those from Tropical Rainfall Measuring Mission and Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation. By comparing the 2075-2099 with the present-day climate simulations, there is a robust increase of the mean rainfall in many locations due to a warmer climate. Over southeastern China, the Baiu rainband, Bay of Bengal and central India, extreme precipitation rates are also enhanced in the future, which can be inferred from increases of the 95th percentile of daily precipitation, the maximum accumulated precipitation in 5 consecutive days, the simple daily precipitation intensity index, and the scale parameter of the fitted gamma distribution. In these regions, with the exception of the Baiu rainband, most of these metrics give a fractional change of extreme rainfall per degree increase of the lower-tropospheric temperature of 5 to 8.5% K-1, roughly consistent with the Clausius-Clapeyron relation. However, over the Baiu area extreme precipitation change scales as 3.5% K-1 only. We have also stratified the rainfall data into those associated with tropical cyclones (TC) and those with other weather systems. The AGCM gives an increase of the accumulated TC rainfall over southeastern China, and a decrease in southern Japan in the future climate. The latter can be attributed to suppressed TC occurrence in southern Japan, whereas increased accumulated rainfall over southeastern China is due to more intense TC rain rate under global warming. Overall, non-TC weather systems are the main contributor to enhanced precipitation extremes in various locations. In the future, TC activities over southeastern China tend to further exacerbate the precipitation extremes, whereas those in the Baiu region lead to weaker changes of these extremes.
The Seasonal Predictability of Extreme Wind Events in the Southwest United States
NASA Astrophysics Data System (ADS)
Seastrand, Simona Renee
Extreme wind events are a common phenomenon in the Southwest United States. Entities such as the United States Air Force (USAF) find the Southwest appealing for many reasons, primarily for the an expansive, unpopulated, and electronically unpolluted space for large-scale training and testing. However, wind events can cause hazards for the USAF including: surface wind gusts can impact the take-off and landing of all aircraft, can tip the airframes of large wing-surface aircraft during the performance of maneuvers close to the ground, and can even impact weapons systems. This dissertation is comprised of three sections intended to further our knowledge and understanding of wind events in the Southwest. The first section builds a climatology of wind events for seven locations in the Southwest during the twelve 3-month seasons of the year. The first section further examines the wind events in relation to terrain and the large-scale flow of the atmosphere. The second section builds upon the first by taking the wind events and generating mid-level composites for each of the twelve 3-month seasons. In the third section, teleconnections identified as consistent with the large-scale circulation in the second paper were used as predictor variables to build a Poisson regression model for each of the twelve 3-month seasons. The purpose of this research is to increase our understanding of the climatology of extreme wind events, increase our understanding of how the large-scale circulation influences extreme wind events, and create a model to enhance predictability of extreme wind events in the Southwest. Knowledge from this paper will help protect personnel and property associated with not only the USAF, but all those in the Southwest.
Chip Scale Ultra-Stable Clocks: Miniaturized Phonon Trap Timing Units for PNT of CubeSats
NASA Technical Reports Server (NTRS)
Rais-Zadeh, Mina; Altunc, Serhat; Hunter, Roger C.; Petro, Andrew
2016-01-01
The Chip Scale Ultra-Stable Clocks (CSUSC) project aims to provide a superior alternative to current solutions for low size, weight, and power timing devices. Currently available quartz-based clocks have problems adjusting to the high temperature and extreme acceleration found in space applications, especially when scaled down to match small spacecraft size, weight, and power requirements. The CSUSC project aims to utilize dual-mode resonators on an ovenized platform to achieve the exceptional temperature stability required for these systems. The dual-mode architecture utilizes a temperature sensitive and temperature stable mode simultaneously driven on the same device volume to eliminate ovenization error while maintaining extremely high performance. Using this technology it is possible to achieve parts-per-billion (ppb) levels of temperature stability with multiple orders of magnitude smaller size, weight, and power.
Toward High-Energy-Density, High-Efficiency, and Moderate-Temperature Chip-Scale Thermophotovoltaics
2013-04-02
this architecture include concentrated solar photovoltaics , thermoelectrics , and fuel cells. System Testing. Themicroreactorwas ignitedbyhydrogen...2, 3), thermoelectrics (4, 5), and thermophotovoltaics (TPVs) (6, 7). TPVs present an extremely appealing approach for small-scale power sources due...into spectrally confined thermal radiation, optically coupled to low-bandgap photovoltaic (PV) diodes that are electrically interfaced with a unique
Extreme fluctuations in stochastic network coordination with time delays
NASA Astrophysics Data System (ADS)
Hunt, D.; Molnár, F.; Szymanski, B. K.; Korniss, G.
2015-12-01
We study the effects of uniform time delays on the extreme fluctuations in stochastic synchronization and coordination problems with linear couplings in complex networks. We obtain the average size of the fluctuations at the nodes from the behavior of the underlying modes of the network. We then obtain the scaling behavior of the extreme fluctuations with system size, as well as the distribution of the extremes on complex networks, and compare them to those on regular one-dimensional lattices. For large complex networks, when the delay is not too close to the critical one, fluctuations at the nodes effectively decouple, and the limit distributions converge to the Fisher-Tippett-Gumbel density. In contrast, fluctuations in low-dimensional spatial graphs are strongly correlated, and the limit distribution of the extremes is the Airy density. Finally, we also explore the effects of nonlinear couplings on the stability and on the extremes of the synchronization landscapes.
Levy, Scott; Ferreira, Kurt B.; Bridges, Patrick G.; ...
2014-12-09
Building the next-generation of extreme-scale distributed systems will require overcoming several challenges related to system resilience. As the number of processors in these systems grow, the failure rate increases proportionally. One of the most common sources of failure in large-scale systems is memory. In this paper, we propose a novel runtime for transparently exploiting memory content similarity to improve system resilience by reducing the rate at which memory errors lead to node failure. We evaluate the viability of this approach by examining memory snapshots collected from eight high-performance computing (HPC) applications and two important HPC operating systems. Based on themore » characteristics of the similarity uncovered, we conclude that our proposed approach shows promise for addressing system resilience in large-scale systems.« less
Coupling lattice Boltzmann and continuum equations for flow and reactive transport in porous media.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Coon, Ethan; Porter, Mark L.; Kang, Qinjun
2012-06-18
In spatially and temporally localized instances, capturing sub-reservoir scale information is necessary. Capturing sub-reservoir scale information everywhere is neither necessary, nor computationally possible. The lattice Boltzmann Method for solving pore-scale systems. At the pore-scale, LBM provides an extremely scalable, efficient way of solving Navier-Stokes equations on complex geometries. Coupling pore-scale and continuum scale systems via domain decomposition. By leveraging the interpolations implied by pore-scale and continuum scale discretizations, overlapping Schwartz domain decomposition is used to ensure continuity of pressure and flux. This approach is demonstrated on a fractured medium, in which Navier-Stokes equations are solved within the fracture while Darcy'smore » equation is solved away from the fracture Coupling reactive transport to pore-scale flow simulators allows hybrid approaches to be extended to solve multi-scale reactive transport.« less
Extreme precipitation in WRF during the Newcastle East Coast Low of 2007
NASA Astrophysics Data System (ADS)
Gilmore, James B.; Evans, Jason P.; Sherwood, Steven C.; Ekström, Marie; Ji, Fei
2016-08-01
In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8th of June 2007 along the coast of eastern Australia (abbreviated "Newy"). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ˜10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme dependent.
Comparison of the hedonic general Labeled Magnitude Scale with the hedonic 9-point scale.
Kalva, Jaclyn J; Sims, Charles A; Puentes, Lorenzo A; Snyder, Derek J; Bartoshuk, Linda M
2014-02-01
The hedonic 9-point scale was designed to compare palatability among different food items; however, it has also been used occasionally to compare individuals and groups. Such comparisons can be invalid because scale labels (for example, "like extremely") can denote systematically different hedonic intensities across some groups. Addressing this problem, the hedonic general Labeled Magnitude Scale (gLMS) frames affective experience in terms of the strongest imaginable liking/disliking of any kind, which can yield valid group comparisons of food palatability provided extreme hedonic experiences are unrelated to food. For each scale, 200 panelists rated affect for remembered food products (including favorite and least favorite foods) and sampled foods; they also sampled taste stimuli (quinine, sucrose, NaCl, citric acid) and rated their intensity. Finally, subjects identified experiences representing the endpoints of the hedonic gLMS. Both scales were similar in their ability to detect within-subject hedonic differences across a range of food experiences, but group comparisons favored the hedonic gLMS. With the 9-point scale, extreme labels were strongly associated with extremes in food affect. In contrast, gLMS data showed that scale extremes referenced nonfood experiences. Perceived taste intensity significantly influenced differences in food liking/disliking (for example, those experiencing the most intense tastes, called supertasters, showed more extreme liking and disliking for their favorite and least favorite foods). Scales like the hedonic gLMS are suitable for across-group comparisons of food palatability. © 2014 Institute of Food Technologists®
Plasma physics of extreme astrophysical environments.
Uzdensky, Dmitri A; Rightley, Shane
2014-03-01
Among the incredibly diverse variety of astrophysical objects, there are some that are characterized by very extreme physical conditions not encountered anywhere else in the Universe. Of special interest are ultra-magnetized systems that possess magnetic fields exceeding the critical quantum field of about 44 TG. There are basically only two classes of such objects: magnetars, whose magnetic activity is manifested, e.g., via their very short but intense gamma-ray flares, and central engines of supernovae (SNe) and gamma-ray bursts (GRBs)--the most powerful explosions in the modern Universe. Figuring out how these complex systems work necessarily requires understanding various plasma processes, both small-scale kinetic and large-scale magnetohydrodynamic (MHD), that govern their behavior. However, the presence of an ultra-strong magnetic field modifies the underlying basic physics to such a great extent that relying on conventional, classical plasma physics is often not justified. Instead, plasma-physical problems relevant to these extreme astrophysical environments call for constructing relativistic quantum plasma (RQP) physics based on quantum electrodynamics (QED). In this review, after briefly describing the astrophysical systems of interest and identifying some of the key plasma-physical problems important to them, we survey the recent progress in the development of such a theory. We first discuss the ways in which the presence of a super-critical field modifies the properties of vacuum and matter and then outline the basic theoretical framework for describing both non-relativistic and RQPs. We then turn to some specific astrophysical applications of relativistic QED plasma physics relevant to magnetar magnetospheres and to central engines of core-collapse SNe and long GRBs. Specifically, we discuss the propagation of light through a magnetar magnetosphere; large-scale MHD processes driving magnetar activity and responsible for jet launching and propagation in GRBs; energy-transport processes governing the thermodynamics of extreme plasma environments; micro-scale kinetic plasma processes important in the interaction of intense electric currents flowing through a magnetar magnetosphere with the neutron star surface; and magnetic reconnection of ultra-strong magnetic fields. Finally, we point out that future progress in applying RQP physics to real astrophysical problems will require the development of suitable numerical modeling capabilities.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Melin, Alexander M.; Kisner, Roger A.
2016-09-01
Embedded instrumentation and control systems that can operate in extreme environments are challenging to design and operate. Extreme environments limit the options for sensors and actuators and degrade their performance. Because sensors and actuators are necessary for feedback control, these limitations mean that designing embedded instrumentation and control systems for the challenging environments of nuclear reactors requires advanced technical solutions that are not available commercially. This report details the development of testbed that will be used for cross-cutting embedded instrumentation and control research for nuclear power applications. This research is funded by the Department of Energy's Nuclear Energy Enabling Technologymore » program's Advanced Sensors and Instrumentation topic. The design goal of the loop-scale testbed is to build a low temperature pump that utilizes magnetic bearing that will be incorporated into a water loop to test control system performance and self-sensing techniques. Specifically, this testbed will be used to analyze control system performance in response to nonlinear and cross-coupling fluid effects between the shaft axes of motion, rotordynamics and gyroscopic effects, and impeller disturbances. This testbed will also be used to characterize the performance losses when using self-sensing position measurement techniques. Active magnetic bearings are a technology that can reduce failures and maintenance costs in nuclear power plants. They are particularly relevant to liquid salt reactors that operate at high temperatures (700 C). Pumps used in the extreme environment of liquid salt reactors provide many engineering challenges that can be overcome with magnetic bearings and their associated embedded instrumentation and control. This report will give details of the mechanical design and electromagnetic design of the loop-scale embedded instrumentation and control testbed.« less
6th Annual Earth System Grid Federation Face to Face Conference Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Williams, D. N.
The Sixth Annual Face-to-Face (F2F) Conference of the Earth System Grid Federation (ESGF), a global consortium of international government agencies, institutions, and companies dedicated to the creation, management, analysis, and distribution of extreme-scale scientific data, was held December 5–9, 2016, in Washington, D.C.
weather@home 2: validation of an improved global-regional climate modelling system
NASA Astrophysics Data System (ADS)
Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.
2017-05-01
Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.
Haptic biofeedback for improving compliance with lower-extremity partial weight bearing.
Fu, Michael C; DeLuke, Levi; Buerba, Rafael A; Fan, Richard E; Zheng, Ying Jean; Leslie, Michael P; Baumgaertner, Michael R; Grauer, Jonathan N
2014-11-01
After lower-extremity orthopedic trauma and surgery, patients are often advised to restrict weight bearing on the affected limb. Conventional training methods are not effective at enabling patients to comply with recommendations for partial weight bearing. The current study assessed a novel method of using real-time haptic (vibratory/vibrotactile) biofeedback to improve compliance with instructions for partial weight bearing. Thirty healthy, asymptomatic participants were randomized into 1 of 3 groups: verbal instruction, bathroom scale training, and haptic biofeedback. Participants were instructed to restrict lower-extremity weight bearing in a walking boot with crutches to 25 lb, with an acceptable range of 15 to 35 lb. A custom weight bearing sensor and biofeedback system was attached to all participants, but only those in the haptic biofeedback group were given a vibrotactile signal if they exceeded the acceptable range. Weight bearing in all groups was measured with a separate validated commercial system. The verbal instruction group bore an average of 60.3±30.5 lb (mean±standard deviation). The bathroom scale group averaged 43.8±17.2 lb, whereas the haptic biofeedback group averaged 22.4±9.1 lb (P<.05). As a percentage of body weight, the verbal instruction group averaged 40.2±19.3%, the bathroom scale group averaged 32.5±16.9%, and the haptic biofeedback group averaged 14.5±6.3% (P<.05). In this initial evaluation of the use of haptic biofeedback to improve compliance with lower-extremity partial weight bearing, haptic biofeedback was superior to conventional physical therapy methods. Further studies in patients with clinical orthopedic trauma are warranted. Copyright 2014, SLACK Incorporated.
Heating-insensitive scale increase caused by convective precipitation
NASA Astrophysics Data System (ADS)
Haerter, Jan; Moseley, Christopher; Berg, Peter
2017-04-01
The origin of intense convective extremes and their unusual temperature dependence has recently challenged traditional thermodynamic arguments, based on the Clausius-Clapeyron relation. In a sequence of studies (Lenderink and v. Mejgaard, Nat Geosc, 2008; Berg, Haerter, Moseley, Nat Geosc, 2013; and Moseley, Hohenegger, Berg, Haerter, Nat Geosc, 2016) the argument of convective-type precipitation overcoming the 7%/K increase in extremes by dynamical, rather than thermodynamic, processes has been promoted. How can the role of dynamical processes be approached for precipitating convective cloud? One-phase, non-precipitating Rayleigh-Bénard convection is a classical problem in complex systems science. When a fluid between two horizontal plates is sufficiently heated from below, convective rolls spontaneously form. In shallow, non-precipitating atmospheric convection, rolls are also known to form under specific conditions, with horizontal scales roughly proportional to the boundary layer height. Here we explore within idealized large-eddy simulations, how the scale of convection is modified, when precipitation sets in and intensifies in the course of diurnal solar heating. Before onset of precipitation, Bénard cells with relatively constant diameter form, roughly on the scale of the atmospheric boundary layer. We find that the onset of precipitation then signals an approximately linear (in time) increase in horizontal scale. This scale increase progresses at a speed which is rather insensitive to changes in surface temperature or changes in the rate at which boundary conditions change, hinting at spatial characteristics, rather than temperature, as a possible control on spatial scales of convection. When exploring the depth of spatial correlations, we find that precipitation onset causes a sudden disruption of order and a subsequent complete disintegration of organization —until precipitation eventually ceases. Returning to the initial question of convective extremes, we conclude that the formation of extreme events is a highly nonlinear process. However, our results suggest that crucial features of convective organization throughout the day may be independent of temperature - with possible implications for large-scale model parameterizations. Yet, the timing of the onset of initial precipitation depends strongly on the temperature boundary conditions, where higher temperatures, or earlier, moderate heating, lead to earlier initiation of convection and hence allow for more time for development and the production of extremes.
Towards a General Theory of Extremes for Observables of Chaotic Dynamical Systems.
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.
Large-Scale Meteorological Patterns Associated with Extreme Precipitation in the US Northeast
NASA Astrophysics Data System (ADS)
Agel, L. A.; Barlow, M. A.
2016-12-01
Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. Tropopause height provides a compact representation of large-scale circulation patterns, as it is linked to mid-level circulation, low-level thermal contrasts and low-level diabatic heating. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into a larger context. Six tropopause patterns are identified on extreme days: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong upward motion during, and moisture transport preceding, extreme precipitation events.
Extreme Scale Plasma Turbulence Simulations on Top Supercomputers Worldwide
Tang, William; Wang, Bei; Ethier, Stephane; ...
2016-11-01
The goal of the extreme scale plasma turbulence studies described in this paper is to expedite the delivery of reliable predictions on confinement physics in large magnetic fusion systems by using world-class supercomputers to carry out simulations with unprecedented resolution and temporal duration. This has involved architecture-dependent optimizations of performance scaling and addressing code portability and energy issues, with the metrics for multi-platform comparisons being 'time-to-solution' and 'energy-to-solution'. Realistic results addressing how confinement losses caused by plasma turbulence scale from present-day devices to the much larger $25 billion international ITER fusion facility have been enabled by innovative advances in themore » GTC-P code including (i) implementation of one-sided communication from MPI 3.0 standard; (ii) creative optimization techniques on Xeon Phi processors; and (iii) development of a novel performance model for the key kernels of the PIC code. Our results show that modeling data movement is sufficient to predict performance on modern supercomputer platforms.« less
The Microphysical Structure of Extreme Precipitation as Inferred from Ground-Based Raindrop Spectra.
NASA Astrophysics Data System (ADS)
Uijlenhoet, Remko; Smith, James A.; Steiner, Matthias
2003-05-01
The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity-rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distributions corresponding to rain rates exceeding 100 mm h1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes in properties of raindrop size distributions in extreme rainfall are largely produced by varying raindrop concentrations. As a result, rainfall integral variables (such as radar reflectivity and rain rate) are roughly proportional to each other, which is consistent with the concept of the so-called equilibrium raindrop size distribution and has profound implications for radar measurement of extreme rainfall. A time series analysis for two contrasting extreme rainfall events supports the hypothesis that the variability of raindrop size distributions for extreme rain rates is strongly number controlled. However, this analysis also reveals that the actual shapes of the (measured and scaled) spectra may differ significantly from storm to storm. This implies that the exponents of power-law radar reflectivity-rain rate relationships may be similar, and close to unity, for different extreme rainfall events, but their prefactors may differ substantially. Consequently, there is no unique radar reflectivity-rain rate relationship for extreme rain rates, but the variability is essentially reduced to one free parameter (i.e., the prefactor). It is suggested that this free parameter may be estimated on the basis of differential reflectivity measurements in extreme rainfall.
A nested observation and model approach to non linear groundwater surface water interactions.
NASA Astrophysics Data System (ADS)
van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.
2009-04-01
Surface water quality measurements in The Netherlands are scattered in time and space. Therefore, water quality status and its variations and trends are difficult to determine. In order to reach the water quality goals according to the European Water Framework Directive, we need to improve our understanding of the dynamics of surface water quality and the processes that affect it. In heavily drained lowland catchment groundwater influences the discharge towards the surface water network in many complex ways. Especially a strong seasonal contracting and expanding system of discharging ditches and streams affects discharge and solute transport. At a tube drained field site the tube drain flux and the combined flux of all other flow routes toward a stretch of 45 m of surface water have been measured for a year. Also the groundwater levels at various locations in the field and the discharge at two nested catchment scales have been monitored. The unique reaction of individual flow routes on rainfall events at the field site allowed us to separate the discharge at a 4 ha catchment and at a 6 km2 into flow route contributions. The results of this nested experimental setup combined with the results of a distributed hydrological model has lead to the formulation of a process model approach that focuses on the spatial variability of discharge generation driven by temporal and spatial variations in groundwater levels. The main idea of this approach is that discharge is not generated by catchment average storages or groundwater heads, but is mainly generated by points scale extremes i.e. extreme low permeability, extreme high groundwater heads or extreme low surface elevations, all leading to catchment discharge. We focused on describing the spatial extremes in point scale storages and this led to a simple and measurable expression that governs the non-linear groundwater surface water interaction. We will present the analysis of the field site data to demonstrate the potential of nested-scale, high frequency observations. The distributed hydrological model results will be used to show transient catchment scale relations between groundwater levels and discharges. These analyses lead to a simple expression that can describe catchment scale groundwater surface water interactions.
NASA Astrophysics Data System (ADS)
Yu, Lejiang; Zhong, Shiyuan; Pei, Lisi; Bian, Xindi; Heilman, Warren E.
2016-04-01
The mean global climate has warmed as a result of the increasing emission of greenhouse gases induced by human activities. This warming is considered the main reason for the increasing number of extreme precipitation events in the US. While much attention has been given to extreme precipitation events occurring over several days, which are usually responsible for severe flooding over a large region, little is known about how extreme precipitation events that cause flash flooding and occur at sub-daily time scales have changed over time. Here we use the observed hourly precipitation from the North American Land Data Assimilation System Phase 2 forcing datasets to determine trends in the frequency of extreme precipitation events of short (1 h, 3 h, 6 h, 12 h and 24 h) duration for the period 1979-2013. The results indicate an increasing trend in the central and eastern US. Over most of the western US, especially the Southwest and the Intermountain West, the trends are generally negative. These trends can be largely explained by the interdecadal variability of the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation (AMO), with the AMO making a greater contribution to the trends in both warm and cold seasons.
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 rather than interannual time scale and the atmospheric circulation patterns as expressed by the North Atlantic Oscillation (NAO) index are used to express the GEV parameters as functions of the covariates. Results show that the nonstationary GEV model can be an efficient tool to take into account the dependencies between extreme value random variables and the temporal evolution of the climate.
Mesosiderite clasts with the most extreme positive europium anomalies among solar system rocks
NASA Technical Reports Server (NTRS)
Mittlefehldt, David W.; Rubin, Alan E.; Davis, Andrew M.
1992-01-01
Pigeonite-plagioclase gabbros that occur as clasts in mesosiderites (brecciated stony-iron meteorites) show extreme fractionations of the rare-earth elements (REEs) with larger positive europium anomalies than any previously known for igneous rocks from the earth, moon, or meteorite parent bodies and greater depletions of light REEs relative to heavy REEs than known for comparable cumulate gabbros. The REE pattern for merrillite in one of these clasts is depleted in light REEs and has a large positive europium anomaly as a result of metamorphic equilibration with the silicates. The extreme REE ratios exhibited by the mesosiderite clasts demonstrate that multistage igneous processes must have occurred on some asteroids in the early solar system. Melting of the crust by large-scale impacts or electrical induction from an early T-Tauri-phase sun may be responsible for these processes.
Extreme-Scale De Novo Genome Assembly
DOE Office of Scientific and Technical Information (OSTI.GOV)
Georganas, Evangelos; Hofmeyr, Steven; Egan, Rob
De novo whole genome assembly reconstructs genomic sequence from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern genomics. This work presents HipMER, a high-quality end-to-end de novo assembler designed for extreme scale analysis, via efficient parallelization of the Meraculous code. Genome assembly software has many components, each of which stresses different components of a computer system. This chapter explains the computational challenges involved in each step of the HipMer pipeline, the key distributed data structures, and communication costs in detail. We present performance results of assembling the human genome and themore » large hexaploid wheat genome on large supercomputers up to tens of thousands of cores.« less
Scaled Jump in Gravity-Reduced Virtual Environments.
Kim, MyoungGon; Cho, Sunglk; Tran, Tanh Quang; Kim, Seong-Pil; Kwon, Ohung; Han, JungHyun
2017-04-01
The reduced gravity experienced in lunar or Martian surfaces can be simulated on the earth using a cable-driven system, where the cable lifts a person to reduce his or her weight. This paper presents a novel cable-driven system designed for the purpose. It is integrated with a head-mounted display and a motion capture system. Focusing on jump motion within the system, this paper proposes to scale the jump and reports the experiments made for quantifying the extent to which a jump can be scaled without the discrepancy between physical and virtual jumps being noticed by the user. With the tolerable range of scaling computed from these experiments, an application named retargeted jump is developed, where a user can jump up onto virtual objects while physically jumping in the real-world flat floor. The core techniques presented in this paper can be extended to develop extreme-sport simulators such as parasailing and skydiving.
NASA Technical Reports Server (NTRS)
Simpson, M. L.; Sayler, G. S.; Fleming, J. T.; Applegate, B.
2001-01-01
The ability to manipulate systems on the molecular scale naturally leads to speculation about the rational design of molecular-scale machines. Cells might be the ultimate molecular-scale machines and our ability to engineer them is relatively advanced when compared with our ability to control the synthesis and direct the assembly of man-made materials. Indeed, engineered whole cells deployed in biosensors can be considered one of the practical successes of molecular-scale devices. However, these devices explore only a small portion of cellular functionality. Individual cells or self-organized groups of cells perform extremely complex functions that include sensing, communication, navigation, cooperation and even fabrication of synthetic nanoscopic materials. In natural systems, these capabilities are controlled by complex genetic regulatory circuits, which are only partially understood and not readily accessible for use in engineered systems. Here, we focus on efforts to mimic the functionality of man-made information-processing systems within whole cells.
Volatile element chemistry in the solar nebula - Na, K, F, Cl, Br, and P
NASA Technical Reports Server (NTRS)
Fegley, B., Jr.; Lewis, J. S.
1980-01-01
The results of the most extensive set to date of thermodynamic calculations on the equilibrium chemistry of several hundred compounds of the elements Na, K, F, Cl, Br, and P in a solar composition system are reported. Two extreme models of accretion are investigated. In one extreme complete chemical equilibrium between condensates and gases is maintained because the time scale for accretion is long compared to the time scale for cooling or dissipation of the nebula. Condensates formed in this homogeneous accretion model include several phases such as whitlockite, alkali feldspars, and apatite minerals which are found in chondrites. In the other extreme complete isolation of newly formed condensates from prior condensates and gases occurs due to a time scale for accretion that is short relative to the time required for nebular cooling or dissipation. The condensates produced in this heterogeneous accretion model include alkali sulfides, ammonium halides, and ammonium phosphates. None of these phases are found in chondrites. Available observations of the Na, K, F, Cl, Br, and P elemental abundances in the terrestrial planets are found to be compatible with the predictions of the homogeneous accretion model.
Virtual Reality to Assess and Treat Lower Extremity Disorders in Post-stroke Patients.
Luque-Moreno, C; Oliva-Pascual-Vaca, A; Kiper, P; Rodríguez-Blanco, C; Agostini, M; Turolla, A
2016-01-01
This article is part of the Focus Theme of Methods of Information in Medicine on "Methodologies, Models and Algorithms for Patients Rehabilitation". To identify support of a virtual reality system in the kinematic assessment and physiotherapy approach to gait disorders in individuals with stroke. We adapt Virtual Reality Rehabilitation System (VRRS), software widely used in the functional recovery of the upper limb, for its use on the lower limb of hemiplegic patients. Clinical scales have been used to relate them with the kinematic assessment provided by the system. A description of the use of reinforced feedback provided by the system on the recovery of deficits in several real cases in the field of physiotherapy is performed. Specific examples of functional tasks have been detailed, to be considered in creating intelligent health technologies to improve post-stroke gait. Both participants improved scores on the clinical scales, the kinematic parameters in leg stance on plegic lower extremity and walking speed > Minimally Clinically Important Difference (MCID). The use of the VRRS software attached to a motion tracking capture system showed their practical utility and safety in enriching physiotherapeutic assessment and treatment in post-stroke gait disorders.
Flood protection diversification to reduce probabilities of extreme losses.
Zhou, Qian; Lambert, James H; Karvetski, Christopher W; Keisler, Jeffrey M; Linkov, Igor
2012-11-01
Recent catastrophic losses because of floods require developing resilient approaches to flood risk protection. This article assesses how diversification of a system of coastal protections might decrease the probabilities of extreme flood losses. The study compares the performance of portfolios each consisting of four types of flood protection assets in a large region of dike rings. A parametric analysis suggests conditions in which diversifications of the types of included flood protection assets decrease extreme flood losses. Increased return periods of extreme losses are associated with portfolios where the asset types have low correlations of economic risk. The effort highlights the importance of understanding correlations across asset types in planning for large-scale flood protection. It allows explicit integration of climate change scenarios in developing flood mitigation strategy. © 2012 Society for Risk Analysis.
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.
The paper describes a full-scale demonstration program in which several paint booths were modified for recirculation ventilation; the booth exhaust streams are vented to an innovative volatile organic compound (VOC) emission control system having extremely low operating costs. ...
Wii™-habilitation of upper extremity function in children with cerebral palsy. An explorative study.
Winkels, Diny G M; Kottink, Anke I R; Temmink, Rutger A J; Nijlant, Juliëtte M M; Buurke, Jaap H
2013-01-01
Commercially available virtual reality systems can possibly support rehabilitation objectives in training upper arm function in children with Cerebral Palsy (CP). The present study explored the effect of the Nintendo Wii™ training on upper extremity function in children with CP. During six weeks, all children received twice a week training with the Wii™, with their most affected arm. The Melbourne Assessment of Upper Limb Function and ABILHAND-Kids were assessed pre- and post- training. In addition, user satisfaction of both children and health professionals was assessed after training. Enjoyment in gaming was scored on a visual analogue scale scale after each session by the children. Fifteen children with CP participated in the study. The quality of upper extremity movements did not change (-2.1, p > 0.05), while a significant increase of convenience in using hands/arms during performance of daily activities was found (0.6, p < 0.05). Daily activities seem to be easier performed after Wii™ training for most of the included children with CP.
Zhang, Mi; Wen, Xue Fa; Zhang, Lei Ming; Wang, Hui Min; Guo, Yi Wen; Yu, Gui Rui
2018-02-01
Extreme high temperature is one of important extreme weathers that impact forest ecosystem carbon cycle. In this study, applying CO 2 flux and routine meteorological data measured during 2003-2012, we examined the impacts of extreme high temperature and extreme high temperature event on net carbon uptake of subtropical coniferous plantation in Qianyanzhou. Combining with wavelet analysis, we analyzed environmental controls on net carbon uptake at different temporal scales, when the extreme high temperature and extreme high temperature event happened. The results showed that mean daily cumulative NEE decreased by 51% in the days with daily maximum air temperature range between 35 ℃ and 40 ℃, compared with that in the days with the range between 30 ℃ and 34 ℃. The effects of the extreme high temperature and extreme high temperature event on monthly NEE and annual NEE related to the strength and duration of extreme high tempe-rature event. In 2003, when strong extreme high temperature event happened, the sum of monthly cumulative NEE in July and August was only -11.64 g C·m -2 ·(2 month) -1 . The value decreased by 90%, compared with multi-year average value. At the same time, the relative variation of annual NEE reached -6.7%. In July and August, when the extreme high temperature and extreme high temperature event occurred, air temperature (T a ) and vapor press deficit (VPD) were the dominant controller for the daily variation of NEE. The coherency between NEE T a and NEE VPD was 0.97 and 0.95, respectively. At 8-, 16-, and 32-day periods, T a , VPD, soil water content at 5 cm depth (SWC), and precipitation (P) controlled NEE. The coherency between NEE SWC and NEE P was higher than 0.8 at monthly scale. The results indicated that atmospheric water deficit impacted NEE at short temporal scale, when the extreme high temperature and extreme high temperature event occurred, both of atmospheric water deficit and soil drought stress impacted NEE at long temporal scales in this ecosystem.
NASA Technical Reports Server (NTRS)
Crosson, William L; Al-Hamdan, Mohammad Z.; Economou, Sigrid, A.; Estes, Maurice G.; Estes, Sue M.; Puckett, Mark; Quattrochi, Dale A
2013-01-01
In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.
The origins of multifractality in financial time series and the effect of extreme events
NASA Astrophysics Data System (ADS)
Green, Elena; Hanan, William; Heffernan, Daniel
2014-06-01
This paper presents the results of multifractal testing of two sets of financial data: daily data of the Dow Jones Industrial Average (DJIA) index and minutely data of the Euro Stoxx 50 index. Where multifractal scaling is found, the spectrum of scaling exponents is calculated via Multifractal Detrended Fluctuation Analysis. In both cases, further investigations reveal that the temporal correlations in the data are a more significant source of the multifractal scaling than are the distributions of the returns. It is also shown that the extreme events which make up the heavy tails of the distribution of the Euro Stoxx 50 log returns distort the scaling in the data set. The most extreme events are inimical to the scaling regime. This result is in contrast to previous findings that extreme events contribute to multifractality.
Production of extreme-purity aluminum and silicon by fractional crystallization processing
NASA Astrophysics Data System (ADS)
Dawless, R. K.; Troup, R. L.; Meier, D. L.; Rohatgi, A.
1988-06-01
Large scale fractional crystallization is used commercially at Alcoa to produce extreme purity aluminum (99.999+% Al). The primary market is sputtering targets used to make interconnects for integrated circuits. For some applications the impurities uranium and thorium are reduced to less than 1 ppbw to avoid "soft errors" associated with α particle emission. The crystallization process achieves segregation coefficients which are close to theoretical at normal yields, and this, coupled with the scale of the units, allows practical production of this material. The silicon purification process involves crystallization of Si from molten aluminum alloys containing about 30% silicon. The crystallites from this process are further treated to remove residual Al and an extreme purity ingot is obtained. This material is considered suitable for single crystal or ribbon type photovoltaic cells and for certain IC applications, including highly doped substrates used for epitaxial growth. In production of both extreme purity Al and Si, impurities are rejected to the remaining melt as the crystals form and some separation is achieved by draining this downgraded melt from the unit. Purification of this downgrade by crystallization has also been demonstrated for both systems and is important for achieving high recoveries.
NASA Astrophysics Data System (ADS)
Akanda, A. S.; Jutla, A. S.; Islam, S.
2009-12-01
Despite ravaging the continents through seven global pandemics in past centuries, the seasonal and interannual variability of cholera outbreaks remain a mystery. Previous studies have focused on the role of various environmental and climatic factors, but provided little or no predictive capability. Recent findings suggest a more prominent role of large scale hydroclimatic extremes - droughts and floods - and attempt to explain the seasonality and the unique dual cholera peaks in the Bengal Delta region of South Asia. We investigate the seasonal and interannual nature of cholera epidemiology in three geographically distinct locations within the region to identify the larger scale hydroclimatic controls that can set the ecological and environmental ‘stage’ for outbreaks and have significant memory on a seasonal scale. Here we show that two distinctly different, pre and post monsoon, cholera transmission mechanisms related to large scale climatic controls prevail in the region. An implication of our findings is that extreme climatic events such as prolonged droughts, record floods, and major cyclones may cause major disruption in the ecosystem and trigger large epidemics. We postulate that a quantitative understanding of the large-scale hydroclimatic controls and dominant processes with significant system memory will form the basis for forecasting such epidemic outbreaks. A multivariate regression method using these predictor variables to develop probabilistic forecasts of cholera outbreaks will be explored. Forecasts from such a system with a seasonal lead-time are likely to have measurable impact on early cholera detection and prevention efforts in endemic regions.
NASA Technical Reports Server (NTRS)
Wang, Guiling; Wang, Dagang; Trenberth, Kevin E.; Erfanian, Amir; Yu, Miao; Bosilovich, Michael G.; Parr, Dana T.
2017-01-01
Theoretical models predict that, in the absence of moisture limitation, extreme precipitation intensity could exponentially increase with temperatures at a rate determined by the Clausius-Clapeyron (C-C) relationship. Climate models project a continuous increase of precipitation extremes for the twenty-first century over most of the globe. However, some station observations suggest a negative scaling of extreme precipitation with very high temperatures, raising doubts about future increase of precipitation extremes. Here we show for the present-day climate over most of the globe,the curve relating daily precipitation extremes with local temperatures has a peak structure, increasing as expected at the low medium range of temperature variations but decreasing at high temperatures. However, this peak-shaped relationship does not imply a potential upper limit for future precipitation extremes. Climate models project both the peak of extreme precipitation and the temperature at which it peaks (T(sub peak)) will increase with warming; the two increases generally conform to the C-C scaling rate in mid- and high-latitudes,and to a super C-C scaling in most of the tropics. Because projected increases of local mean temperature (T(sub mean)) far exceed projected increases of T(sub peak) over land, the conventional approach of relating extreme precipitation to T(sub mean) produces a misleading sub-C-C scaling rate.
Origin and dynamics of depositionary subduction margins
Vannucchi, Paola; Morgan, Jason P.; Silver, Eli; Kluesner, Jared W.
2016-01-01
Here we propose a new framework for forearc evolution that focuses on the potential feedbacks between subduction tectonics, sedimentation, and geomorphology that take place during an extreme event of subduction erosion. These feedbacks can lead to the creation of a “depositionary forearc,” a forearc structure that extends the traditional division of forearcs into accretionary or erosive subduction margins by demonstrating a mode of rapid basin accretion during an erosive event at a subduction margin. A depositionary mode of forearc evolution occurs when terrigenous sediments are deposited directly on the forearc while it is being removed from below by subduction erosion. In the most extreme case, an entire forearc can be removed by a single subduction erosion event followed by depositionary replacement without involving transfer of sediments from the incoming plate. We need to further recognize that subduction forearcs are often shaped by interactions between slow, long-term processes, and sudden extreme events reflecting the sudden influences of large-scale morphological variations in the incoming plate. Both types of processes contribute to the large-scale architecture of the forearc, with extreme events associated with a replacive depositionary mode that rapidly creates sections of a typical forearc margin. The persistent upward diversion of the megathrust is likely to affect its geometry, frictional nature, and hydrogeology. Therefore, the stresses along the fault and individual earthquake rupture characteristics are also expected to be more variable in these erosive systems than in systems with long-lived megathrust surfaces.
NASA Astrophysics Data System (ADS)
Field, C. B.; Stocker, T. F.; Barros, V. R.; Qin, D.; Ebi, K. L.; Midgley, P. M.
2011-12-01
The Summary for Policy Makers of the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation will be approved by the world governments in November 2011. The focus of the Special Report is on climate change and its role in altering the frequency, severity, and impact of extreme events or disasters, and on the costs of both impacts and the actions taken to prepare for, respond to, and recover from extreme events and disasters. The emphasis is on understanding the factors that make people and infrastructure vulnerable to extreme events, on recent and future changes in the relationship between climate change and extremes, and on managing the risks of disasters over a wide range of spatial and temporal scales. The assessment considers a broad suite of adaptations and explores the limits to adaptation. The assessment was designed to build durable links and foundations for partnerships between the stakeholder communities focused on climate change and those focused on disaster risk reduction. The Special Report begins with material that frames the issues, followed by an assessment of the reasons that communities are vulnerable. Two chapters assess the role of past and future climate change in altering extremes and the impact of these on the physical environment and human systems. Three chapters assess available knowledge on impacts and adaptation, with separate chapters considering the literature, stakeholder relationships, and potential policy tools relevant to the local, national, and international scales. Longer-term components of adaptation to weather and climate extremes and disasters are assessed in the context of moving toward sustainability. The final chapter provides case studies that integrate themes across several chapters or are so unique that they need to be considered separately.
The home stroke rehabilitation and monitoring system trial: a randomized controlled trial.
Linder, Susan M; Rosenfeldt, Anson B; Reiss, Aimee; Buchanan, Sharon; Sahu, Komal; Bay, Curtis R; Wolf, Steven L; Alberts, Jay L
2013-01-01
Because many individuals poststroke lack access to the quality and intensity of rehabilitation to improve upper extremity motor function, a home-based robotic-assisted upper extremity rehabilitation device is being paired with an individualized home exercise program. The primary aim of this project is to determine the effectiveness of robotic-assisted home therapy compared with a home exercise program on upper extremity motor recovery and health-related quality of life for stroke survivors in rural and underserved locations. The secondary aim is to explore whether initial degree of motor function of the upper limb may be a factor in predicting the extent to which patients with stroke may be responsive to a home therapy approach. We hypothesize that the home exercise program intervention, when enhanced with robotic-assisted therapy, will result in significantly better outcomes in motor function and quality of life. A total of 96 participants within six-months of a single, unilateral ischemic, or hemorrhagic stroke will be recruited in this prospective, single-blind, multisite randomized clinical trial. The primary outcome is the change in upper extremity function using the Action Research Arm Test. Secondary outcomes include changes in: upper extremity function (Wolf Motor Function Test), upper extremity impairment (upper extremity portion of the Fugl-Meyer Test), self-reported quality of life (Stroke Impact Scale), and affect (Centers for Epidemiologic Studies Depression Scale). Similar or greater improvements in upper extremity function using the combined robotic home exercise program intervention compared with home exercise program alone will be interpreted as evidence that supports the introduction of in-home technology to augment the recovery of function poststroke. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.
NASA Astrophysics Data System (ADS)
Ganguly, A. R.; Steinbach, M.; Kumar, V.
2009-12-01
The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative predictive insights based on a combination of hypothesis-guided data analysis and relatively hypothesis-free but data-guided discovery processes. The analysis and discovery approaches need to be cognizant of climate data characteristics like nonlinear processes, low-frequency variability, long-range spatial dependence and long-memory temporal processes; the value of physically-motivated conceptual understanding and functional associations; as well as possible thresholds and tipping points in the impacted natural, engineered or human systems. Case studies focusing on new methodologies as well as novel climate insights are discussed with a focus on stakeholder requirements.
Crossing disciplines and scales to understand the critical zone
Brantley, S.L.; Goldhaber, M.B.; Vala, Ragnarsdottir K.
2007-01-01
The Critical Zone (CZ) is the system of coupled chemical, biological, physical, and geological processes operating together to support life at the Earth's surface. While our understanding of this zone has increased over the last hundred years, further advance requires scientists to cross disciplines and scales to integrate understanding of processes in the CZ, ranging in scale from the mineral-water interface to the globe. Despite the extreme heterogeneities manifest in the CZ, patterns are observed at all scales. Explanations require the use of new computational and analytical tools, inventive interdisciplinary approaches, and growing networks of sites and people.
Structural Similitude and Scaling Laws
NASA Technical Reports Server (NTRS)
Simitses, George J.
1998-01-01
Aircraft and spacecraft comprise the class of aerospace structures that require efficiency and wisdom in design, sophistication and accuracy in analysis and numerous and careful experimental evaluations of components and prototype, in order to achieve the necessary system reliability, performance and safety. Preliminary and/or concept design entails the assemblage of system mission requirements, system expected performance and identification of components and their connections as well as of manufacturing and system assembly techniques. This is accomplished through experience based on previous similar designs, and through the possible use of models to simulate the entire system characteristics. Detail design is heavily dependent on information and concepts derived from the previous steps. This information identifies critical design areas which need sophisticated analyses, and design and redesign procedures to achieve the expected component performance. This step may require several independent analysis models, which, in many instances, require component testing. The last step in the design process, before going to production, is the verification of the design. This step necessitates the production of large components and prototypes in order to test component and system analytical predictions and verify strength and performance requirements under the worst loading conditions that the system is expected to encounter in service. Clearly then, full-scale testing is in many cases necessary and always very expensive. In the aircraft industry, in addition to full-scale tests, certification and safety necessitate large component static and dynamic testing. Such tests are extremely difficult, time consuming and definitely absolutely necessary. Clearly, one should not expect that prototype testing will be totally eliminated in the aircraft industry. It is hoped, though, that we can reduce full-scale testing to a minimum. Full-scale large component testing is necessary in other industries as well, Ship building, automobile and railway car construction all rely heavily on testing. Regardless of the application, a scaled-down (by a large factor) model (scale model) which closely represents the structural behavior of the full-scale system (prototype) can prove to be an extremely beneficial tool. This possible development must be based on the existence of certain structural parameters that control the behavior of a structural system when acted upon by static and/or dynamic loads. If such structural parameters exist, a scaled-down replica can be built, which will duplicate the response of the full-scale system. The two systems are then said to be structurally similar. The term, then, that best describes this similarity is structural similitude. Similarity of systems requires that the relevant system parameters be identical and these systems be governed by a unique set of characteristic equations. Thus, if a relation or equation of variables is written for a system, it is valid for all systems which are similar to it. Each variable in a model is proportional to the corresponding variable of the prototype. This ratio, which plays an essential role in predicting the relationship between the model and its prototype, is called the scale factor.
NASA Astrophysics Data System (ADS)
Balasis, George; Donner, Reik V.; Donges, Jonathan F.; Radebach, Alexander; Eftaxias, Konstantinos; Kurths, Jürgen
2013-04-01
The dynamics of many complex systems is characterized by the same universal principles. In particular, systems which are otherwise quite different in nature show striking similarities in their behavior near tipping points (bifurcations, phase transitions, sudden regime shifts) and associated extreme events. Such critical phenomena are frequently found in diverse fields such as climate, seismology, or financial markets. Notably, the observed similarities include a high degree of organization, persistent behavior, and accelerated energy release, which are common to (among others) phenomena related to geomagnetic variability of the terrestrial magnetosphere (intense magnetic storms), seismic activity (electromagnetic emissions prior to earthquakes), solar-terrestrial physics (solar flares), neurophysiology (epileptic seizures), and socioeconomic systems (stock market crashes). It is an open question whether the spatial and temporal complexity associated with extreme events arises from the system's structural organization (geometry) or from the chaotic behavior inherent to the nonlinear equations governing the dynamics of these phenomena. On the one hand, the presence of scaling laws associated with earthquakes and geomagnetic disturbances suggests understanding these events as generalized phase transitions similar to nucleation and critical phenomena in thermal and magnetic systems. On the other hand, because of the structural organization of the systems (e.g., as complex networks) the associated spatial geometry and/or topology of interactions plays a fundamental role in the emergence of extreme events. Here, a few aspects of the interplay between geometry and dynamics (critical phase transitions) that could result in the emergence of extreme events, which is an open problem, will be discussed.
Bravini, Elisabetta; Giordano, Andrea; Sartorio, Francesco; Ferriero, Giorgio; Vercelli, Stefano
2017-04-01
To investigate dimensionality and the measurement properties of the Italian Lower Extremity Functional Scale using both classical test theory and Rasch analysis methods, and to provide insights for an improved version of the questionnaire. Rasch analysis of individual patient data. Rehabilitation centre. A total of 135 patients with musculoskeletal diseases of the lower limb. Patients were assessed with the Lower Extremity Functional Scale before and after the rehabilitation. Rasch analysis showed some problems related to rating scale category functioning, items fit, and items redundancy. After an iterative process, which resulted in the reduction of rating scale categories from 5 to 4, and in the deletion of 5 items, the psychometric properties of the Italian Lower Extremity Functional Scale improved. The retained 15 items with a 4-level response format fitted the Rasch model (internal construct validity), and demonstrated unidimensionality and good reliability indices (person-separation reliability 0.92; Cronbach's alpha 0.94). Then, the analysis showed differential item functioning for six of the retained items. The sensitivity to change of the Italian 15-item Lower Extremity Functional Scale was nearly equal to the one of the original version (effect size: 0.93 and 0.98; standardized response mean: 1.20 and 1.28, respectively for the 15-item and 20-item versions). The Italian Lower Extremity Functional Scale had unsatisfactory measurement properties. However, removing five items and simplifying the scoring from 5 to 4 levels resulted in a more valid measure with good reliability and sensitivity to change.
Scale problems in assessment of hydrogeological parameters of groundwater flow models
NASA Astrophysics Data System (ADS)
Nawalany, Marek; Sinicyn, Grzegorz
2015-09-01
An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i) spatial extent and geometry of hydrogeological system, (ii) spatial continuity and granularity of both natural and man-made objects within the system, (iii) duration of the system and (iv) continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale - scale of pores, meso-scale - scale of laboratory sample, macro-scale - scale of typical blocks in numerical models of groundwater flow, local-scale - scale of an aquifer/aquitard and regional-scale - scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical) block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here). Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.
NASA Astrophysics Data System (ADS)
Sulca, Juan C.
In this Master's dissertation, atmospheric circulation patterns associated with extreme hydrometeorological events in the Mantaro Basin, Peruvian Central Andes, and their teleconnections during the austral summer (December-January-February-March) are addressed. Extreme rainfall events in the Mantaro basin are related to variations of the large-scale circulation as indicated by the changing strength of the Bolivian High-Nordeste Low (BH-NL) system. Dry (wet) spells are associated with a weakening (strengthening) of the BH-NL system and reduced (enhanced) influx of moist air from the lowlands to the east due to strengthened westerly (easterly) wind anomalies at mid- and upper-tropospheric levels. At the same time extreme rainfall events of the opposite sign occur over northeastern Brazil (NEB) due to enhanced (inhibited) convective activity in conjunction with a strengthened (weakened) Nordeste Low. Cold episodes in the Mantaro Basin are grouped in three types: weak, strong and extraordinary cold episodes. Weak and strong cold episodes in the MB are mainly associated with a weakening of the BH-NL system due to tropical-extratropical interactions. Both types of cold episodes are associated with westerly wind anomalies at mid- and upper-tropospheric levels aloft the Peruvian Central Andes, which inhibit the influx of humid air masses from the lowlands to the east and hence limit the potential for development of convective cloud cover. The resulting clear sky conditions cause nighttime temperatures to drop, leading to cold extremes below the 10-percentile. Extraordinary cold episodes in the MB are associated with cold and dry polar air advection at all tropospheric levels toward the central Peruvian Andes. Therefore, weak and strong cold episodes in the MB appear to be caused by radiative cooling associated with reduced cloudiness, rather than cold air advection, while the latter plays an important role for extraordinary cold episodes only.
NASA Astrophysics Data System (ADS)
Drobinski, P.; Alonzo, B.; Bastin, S.; Silva, N. Da; Muller, C.
2016-04-01
Expected changes to future extreme precipitation remain a key uncertainty associated with anthropogenic climate change. Extreme precipitation has been proposed to scale with the precipitable water content in the atmosphere. Assuming constant relative humidity, this implies an increase of precipitation extremes at a rate of about 7% °C-1 globally as indicated by the Clausius-Clapeyron relationship. Increases faster and slower than Clausius-Clapeyron have also been reported. In this work, we examine the scaling between precipitation extremes and temperature in the present climate using simulations and measurements from surface weather stations collected in the frame of the HyMeX and MED-CORDEX programs in Southern France. Of particular interest are departures from the Clausius-Clapeyron thermodynamic expectation, their spatial and temporal distribution, and their origin. Looking at the scaling of precipitation extreme with temperature, two regimes emerge which form a hook shape: one at low temperatures (cooler than around 15°C) with rates of increase close to the Clausius-Clapeyron rate and one at high temperatures (warmer than about 15°C) with sub-Clausius-Clapeyron rates and most often negative rates. On average, the region of focus does not seem to exhibit super Clausius-Clapeyron behavior except at some stations, in contrast to earlier studies. Many factors can contribute to departure from Clausius-Clapeyron scaling: time and spatial averaging, choice of scaling temperature (surface versus condensation level), and precipitation efficiency and vertical velocity in updrafts that are not necessarily constant with temperature. But most importantly, the dynamical contribution of orography to precipitation in the fall over this area during the so-called "Cevenoles" events, explains the hook shape of the scaling of precipitation extremes.
The Top 10 Challenges in Extreme-Scale Visual Analytics
Wong, Pak Chung; Shen, Han-Wei; Johnson, Christopher R.; Chen, Chaomei; Ross, Robert B.
2013-01-01
In this issue of CG&A, researchers share their R&D findings and results on applying visual analytics (VA) to extreme-scale data. Having surveyed these articles and other R&D in this field, we’ve identified what we consider the top challenges of extreme-scale VA. To cater to the magazine’s diverse readership, our discussion evaluates challenges in all areas of the field, including algorithms, hardware, software, engineering, and social issues. PMID:24489426
Field Scale Monitoring and Modeling of Water and Chemical Transfer in the Vadose Zone
USDA-ARS?s Scientific Manuscript database
Natural resource systems involve highly complex interactions of soil-plant-atmosphere-management components that are extremely difficult to quantitatively describe. Computer simulations for prediction and management of watersheds, water supply areas, and agricultural fields and farms have become inc...
R&D100: Lightweight Distributed Metric Service
Gentile, Ann; Brandt, Jim; Tucker, Tom; Showerman, Mike
2018-06-12
On today's High Performance Computing platforms, the complexity of applications and configurations makes efficient use of resources difficult. The Lightweight Distributed Metric Service (LDMS) is monitoring software developed by Sandia National Laboratories to provide detailed metrics of system performance. LDMS provides collection, transport, and storage of data from extreme-scale systems at fidelities and timescales to provide understanding of application and system performance with no statistically significant impact on application performance.
R&D100: Lightweight Distributed Metric Service
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gentile, Ann; Brandt, Jim; Tucker, Tom
2015-11-19
On today's High Performance Computing platforms, the complexity of applications and configurations makes efficient use of resources difficult. The Lightweight Distributed Metric Service (LDMS) is monitoring software developed by Sandia National Laboratories to provide detailed metrics of system performance. LDMS provides collection, transport, and storage of data from extreme-scale systems at fidelities and timescales to provide understanding of application and system performance with no statistically significant impact on application performance.
Toward Zero Micro/Macro-Scale Wear Using Periodic Nano-Layered Coatings.
Penkov, Oleksiy V; Devizenko, Alexander Yu; Khadem, Mahdi; Zubarev, Evgeniy N; Kondratenko, Valeriy V; Kim, Dae-Eun
2015-08-19
Wear is an important phenomenon that affects the efficiency and life of all moving machines. In this regard, extensive efforts have been devoted to achieve the lowest possible wear in sliding systems. With the advent of novel materials in recent years, technology is moving toward realization of zero wear. Here, we report on the development of new functional coatings comprising periodically stacked nanolayers of amorphous carbon and cobalt that are extremely wear resistant at the micro and macro scale. Because of their unique structure, these coatings simultaneously provide high elasticity and ultrahigh shear strength. As a result, almost zero wear was observed even after one million sliding cycles without any lubrication. The wear rate was reduced by 8-10-fold compared with the best previously reported data on extremely low wear materials.
ERIC Educational Resources Information Center
Greene, Jay; Loveless, Tom; MacLeod, W. Bentley; Nechyba, Thomas; Peterson, Paul; Rosenthal, Meredith; Whitehurst, Grover
2010-01-01
Choice is most frequently realized within the public sector using the mechanisms of residence, magnet schools, and open enrollment systems, whereas the voucher-like systems applauded by choice advocates and feared by opponents are extremely rare. Further, the charter sector is neither large enough nor sufficiently prepared to go to scale to…
NASA Astrophysics Data System (ADS)
Aemisegger, Franziska; Piaget, Nicolas
2017-04-01
A new weather-system oriented classification framework of extreme precipitation events leading to large-scale floods in Switzerland is presented on this poster. Thirty-six high impact floods in the last 130 years are assigned to three representative categories of atmospheric moisture origin and transport patterns. The methodology underlying this moisture source classification combines information of the airmass history in the twenty days preceding the precipitation event with humidity variations along the large-scale atmospheric transport systems in a Lagrangian approach. The classification scheme is defined using the 33-year ERA-Interim reanalysis dataset (1979-2011) and is then applied to the Twentieth Century Reanalysis (1871-2011) extreme precipitation events as well as the 36 selected floods. The three defined categories are characterised by different dominant moisture uptake regions including the North Atlantic, the Mediterranean and continental Europe. Furthermore, distinct anomalies in the large-scale atmospheric flow are associated with the different categories. The temporal variations in the relative importance of the three categories over the last 130 years provides new insights into the impact of changing climate conditions on the dynamical mechanisms leading to heavy precipitation in Switzerland.
NASA Astrophysics Data System (ADS)
Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo
2016-04-01
Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.
NASA Astrophysics Data System (ADS)
Sun, N.; Yearsley, J. R.; Nijssen, B.; Lettenmaier, D. P.
2014-12-01
Urban stream quality is particularly susceptible to extreme precipitation events and land use change. Although the projected effects of extreme events and land use change on hydrology have been resonably well studied, the impacts on urban water quality have not been widely examined due in part to the scale mismatch between global climate models and the spatial scales required to represent urban hydrology and water quality signals. Here we describe a grid-based modeling system that integrates the Distributed Hydrology Soil Vegetation Model (DHSVM) and urban water quality module adpated from EPA's Storm Water Management Model (SWMM) and Soil and water assessment tool (SWAT). Using the model system, we evaluate, for four partially urbanized catchments within the Puget Sound basin, urban water quality under current climate conditions, and projected potential changes in urban water quality associated with future changes in climate and land use. We examine in particular total suspended solids, toal nitrogen, total phosphorous, and coliform bacteria, with catchment representations at the 150-meter spatial resolution and the sub-daily timestep. We report long-term streamflow and water quality predictions in response to extreme precipitation events of varying magnitudes in the four partially urbanized catchments. Our simulations show that urban water quality is highly sensitive to both climatic and land use change.
NASA Astrophysics Data System (ADS)
Loikith, Paul C.
Motivated by a desire to understand the physical mechanisms involved in future anthropogenic changes in extreme temperature events, the key atmospheric circulation patterns associated with extreme daily temperatures over North America in the current climate are identified. Several novel metrics are used to systematically identify and describe these patterns for the entire continent. The orientation, physical characteristics, and spatial scale of these circulation patterns vary based on latitude, season, and proximity to important geographic features (i.e., mountains, coastlines). The anomaly patterns associated with extreme cold events tend to be similar to, but opposite in sign of, those associated with extreme warm events, especially within the westerlies, and tend to scale with temperature in the same locations. The influence of the Pacific North American (PNA) pattern, the Northern Annular Mode (NAM), and the El Niño-Southern Oscillation (ENSO) on extreme temperature days and months shows that associations between extreme temperatures and the PNA and NAM are stronger than associations with ENSO. In general, the association with extremes tends to be stronger on monthly than daily time scales. Extreme temperatures are associated with the PNA and NAM in locations typically influenced by these circulation patterns; however many extremes still occur on days when the amplitude and polarity of these patterns do not favor their occurrence. In winter, synoptic-scale, transient weather disturbances are important drivers of extreme temperature days; however these smaller-scale events are often concurrent with amplified PNA or NAM patterns. Associations are weaker in summer when other physical mechanisms affecting the surface energy balance, such as anomalous soil moisture content, are associated with extreme temperatures. Analysis of historical runs from seventeen climate models from the CMIP5 database suggests that most models simulate realistic circulation patterns associated with extreme temperature days in most places. Model-simulated patterns tend to resemble observed patterns better in the winter than the summer and at 500 hPa than at the surface. There is substantial variability among the suite of models analyzed and most models simulate circulation patterns more realistically away from influential features such as large bodies of water and complex topography.
The origin of polygonal troughs on the northern plains of Mars
NASA Astrophysics Data System (ADS)
Pechmann, J. C.
1980-05-01
The morphology, distribution, geologic environment and relative age of large-scale polygonal trough systems on Mars are examined. The troughs are steep-walled, flat-floored, sinuous depressions typically 200-800 m wide, 20-120 m deep and spaced 5-10 km apart. The mechanics of formation of tension cracks is reviewed to identify the factors controlling the scale of tension crack systems; special emphasis is placed on thermal cracking in permafrost. It is shown that because of the extremely large scale of the Martian fracture systems, they could not have formed by thermal cracking in permafrost, dessication cracking in sediments or contraction cracking in cooling lava. On the basis of photogeologic evidence and analog studies, it is proposed that polygonal troughs on the northern plains of Mars are grabens.
Evaluating the Large-Scale Environment of Extreme Events Using Reanalyses
NASA Astrophysics Data System (ADS)
Bosilovich, M. G.; Schubert, S. D.; Koster, R. D.; da Silva, A. M., Jr.; Eichmann, A.
2014-12-01
Extreme conditions and events have always been a long standing concern in weather forecasting and national security. While some evidence indicates extreme weather will increase in global change scenarios, extremes are often related to the large scale atmospheric circulation, but also occurring infrequently. Reanalyses assimilate substantial amounts of weather data and a primary strength of reanalysis data is the representation of the large-scale atmospheric environment. In this effort, we link the occurrences of extreme events or climate indicators to the underlying regional and global weather patterns. Now, with greater than 3o years of data, reanalyses can include multiple cases of extreme events, and thereby identify commonality among the weather to better characterize the large-scale to global environment linked to the indicator or extreme event. Since these features are certainly regionally dependent, and also, the indicators of climate are continually being developed, we outline various methods to analyze the reanalysis data and the development of tools to support regional evaluation of the data. Here, we provide some examples of both individual case studies and composite studies of similar events. For example, we will compare the large scale environment for Northeastern US extreme precipitation with that of highest mean precipitation seasons. Likewise, southerly winds can shown to be a major contributor to very warm days in the Northeast winter. While most of our development has involved NASA's MERRA reanalysis, we are also looking forward to MERRA-2 which includes several new features that greatly improve the representation of weather and climate, especially for the regions and sectors involved in the National Climate Assessment.
Local instability driving extreme events in a pair of coupled chaotic electronic circuits
NASA Astrophysics Data System (ADS)
de Oliveira, Gilson F.; Di Lorenzo, Orlando; de Silans, Thierry Passerat; Chevrollier, Martine; Oriá, Marcos; Cavalcante, Hugo L. D. de Souza
2016-06-01
For a long time, extreme events happening in complex systems, such as financial markets, earthquakes, and neurological networks, were thought to follow power-law size distributions. More recently, evidence suggests that in many systems the largest and rarest events differ from the other ones. They are dragon kings, outliers that make the distribution deviate from a power law in the tail. Understanding the processes of formation of extreme events and what circumstances lead to dragon kings or to a power-law distribution is an open question and it is a very important one to assess whether extreme events will occur too often in a specific system. In the particular system studied in this paper, we show that the rate of occurrence of dragon kings is controlled by the value of a parameter. The system under study here is composed of two nearly identical chaotic oscillators which fail to remain in a permanently synchronized state when coupled. We analyze the statistics of the desynchronization events in this specific example of two coupled chaotic electronic circuits and find that modifying a parameter associated to the local instability responsible for the loss of synchronization reduces the occurrence of dragon kings, while preserving the power-law distribution of small- to intermediate-size events with the same scaling exponent. Our results support the hypothesis that the dragon kings are caused by local instabilities in the phase space.
NASA Technical Reports Server (NTRS)
Grotjahn, Richard; Black, Robert; Leung, Ruby; Wehner, Michael F.; Barlow, Mathew; Bosilovich, Michael G.; Gershunov, Alexander; Gutowski, William J., Jr.; Gyakum, John R.; Katz, Richard W.;
2015-01-01
The objective of this paper is to review statistical methods, dynamics, modeling efforts, and trends related to temperature extremes, with a focus upon extreme events of short duration that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). The statistics, dynamics, and modeling sections of this paper are written to be autonomous and so can be read separately. Methods to define extreme events statistics and to identify and connect LSMPs to extreme temperature events are presented. Recent advances in statistical techniques connect LSMPs to extreme temperatures through appropriately defined covariates that supplement more straightforward analyses. Various LSMPs, ranging from synoptic to planetary scale structures, are associated with extreme temperature events. Current knowledge about the synoptics and the dynamical mechanisms leading to the associated LSMPs is incomplete. Systematic studies of: the physics of LSMP life cycles, comprehensive model assessment of LSMP-extreme temperature event linkages, and LSMP properties are needed. Generally, climate models capture observed properties of heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreak frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Modeling studies have identified the impact of large-scale circulation anomalies and landatmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs to more specifically understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated. The paper concludes with unresolved issues and research questions.
Abbott, J Haxby; Schmitt, John
2014-08-01
Multicenter, prospective, longitudinal cohort study. To investigate the minimum important difference (MID) of the Patient-Specific Functional Scale (PSFS), 4 region-specific outcome measures, and the numeric pain rating scale (NPRS) across 3 levels of patient-perceived global rating of change in a clinical setting. The MID varies depending on the external anchor defining patient-perceived "importance." The MID for the PSFS has not been established across all body regions. One thousand seven hundred eight consecutive patients with musculoskeletal disorders were recruited from 5 physical therapy clinics. The PSFS, NPRS, and 4 region-specific outcome measures-the Oswestry Disability Index, Neck Disability Index, Upper Extremity Functional Index, and Lower Extremity Functional Scale-were assessed at the initial and final physical therapy visits. Global rating of change was assessed at the final visit. MID was calculated for the PSFS and NPRS (overall and for each body region), and for each region-specific outcome measure, across 3 levels of change defined by the global rating of change (small, medium, large change) using receiver operating characteristic curve methodology. The MID for the PSFS (on a scale from 0 to 10) ranged from 1.3 (small change) to 2.3 (medium change) to 2.7 (large change), and was relatively stable across body regions. MIDs for the NPRS (-1.5 to -3.5), Oswestry Disability Index (-12), Neck Disability Index (-14), Upper Extremity Functional Index (6 to 11), and Lower Extremity Functional Scale (9 to 16) are also reported. We reported the MID for small, medium, and large patient-perceived change on the PSFS, NPRS, Oswestry Disability Index, Neck Disability Index, Upper Extremity Functional Index, and Lower Extremity Functional Scale for use in clinical practice and research.
Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.
Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L
2002-09-01
We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.
NASA Astrophysics Data System (ADS)
Matthies, A.; Leckebusch, G. C.; Rohlfing, G.; Ulbrich, U.
2009-04-01
Extreme weather events such as thunderstorms, hail and heavy rain or snowfall can pose a threat to human life and to considerable tangible assets. Yet there is a lack of knowledge about present day climatological risk and its economic effects, and its changes due to rising greenhouse gas concentrations. Therefore, parts of economy particularly sensitve to extreme weather events such as insurance companies and airports require regional risk-analyses, early warning and prediction systems to cope with such events. Such an attempt is made for southern Germany, in close cooperation with stakeholders. Comparing ERA40 and station data with impact records of Munich Re and Munich Airport, the 90th percentile was found to be a suitable threshold for extreme impact relevant precipitation events. Different methods for the classification of causing synoptic situations have been tested on ERA40 reanalyses. An objective scheme for the classification of Lamb's circulation weather types (CWT's) has proved to be most suitable for correct classification of the large-scale flow conditions. Certain CWT's have been turned out to be prone to heavy precipitation or on the other side to have a very low risk of such events. Other large-scale parameters are tested in connection with CWT's to find out a combination that has the highest skill to identify extreme precipitation events in climate model data (ECHAM5 and CLM). For example vorticity advection in 700 hPa shows good results, but assumes knowledge of regional orographic particularities. Therefore ongoing work is focused on additional testing of parameters that indicate deviations of a basic state of the atmosphere like the Eady Growth Rate or the newly developed Dynamic State Index. Evaluation results will be used to estimate the skill of the regional climate model CLM concerning the simulation of frequency and intensity of the extreme weather events. Data of the A1B scenario (2000-2050) will be examined for a possible climate change signal.
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.
Rasch validation of the Arabic version of the lower extremity functional scale.
Alnahdi, Ali H
2018-02-01
The purpose of this study was to examine the internal construct validity of the Arabic version of the Lower Extremity Functional Scale (20-item Arabic LEFS) using Rasch analysis. Patients (n = 170) with lower extremity musculoskeletal dysfunction were recruited. Rasch analysis of 20-item Arabic LEFS was performed. Once the initial Rasch analysis indicated that the 20-item Arabic LEFS did not fit the Rasch model, follow-up analyses were conducted to improve the fit of the scale to the Rasch measurement model. These modifications included removing misfitting individuals, changing item scoring structure, removing misfitting items, addressing bias caused by response dependency between items and differential item functioning (DIF). Initial analysis indicated deviation of the 20-item Arabic LEFS from the Rasch model. Disordered thresholds in eight items and response dependency between six items were detected with the scale as a whole did not meet the requirement of unidimensionality. Refinements led to a 15-item Arabic LEFS that demonstrated excellent internal consistency (person separation index [PSI] = 0.92) and satisfied all the requirement of the Rasch model. Rasch analysis did not support the 20-item Arabic LEFS as a unidimensional measure of lower extremity function. The refined 15-item Arabic LEFS met all the requirement of the Rasch model and hence is a valid objective measure of lower extremity function. The Rasch-validated 15-item Arabic LEFS needs to be further tested in an independent sample to confirm its fit to the Rasch measurement model. Implications for Rehabilitation The validity of the 20-item Arabic Lower Extremity Functional Scale to measure lower extremity function is not supported. The 15-item Arabic version of the LEFS is a valid measure of lower extremity function and can be used to quantify lower extremity function in patients with lower extremity musculoskeletal disorders.
Grotjahn, Richard; Black, Robert; Leung, Ruby; ...
2015-05-22
This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic tomore » planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so more research is needed to understand the limitations of climate models and improve model skill in simulating extreme temperatures and their associated LSMPs. Furthermore, the paper concludes with unresolved issues and research questions.« less
NASA Astrophysics Data System (ADS)
Saito, S.; Yoshihara, T.
2017-08-01
Associated with plasma bubbles, extreme spatial gradients in ionospheric total electron content (TEC) were observed on 8 April 2008 at Ishigaki (24.3°N, 124.2°E, +19.6° magnetic latitude), Japan. The largest gradient was 3.38 TECU km-1 (total electron content unit, 1 TECU = 1016 el m-2), which is equivalent to an ionospheric delay gradient of 540 mm km-1 at the GPS L1 frequency (1.57542 GHz). This value is confirmed by using multiple estimating methods. The observed value exceeds the maximum ionospheric gradient that has ever been observed (412 mm km-1 or 2.59 TECU km-1) to be associated with a severe magnetic storm. It also exceeds the assumed maximum value (500 mm km-1 or 3.08 TECU km-1) which was used to validate the draft international standard for Global Navigation Satellite System (GNSS) Ground-Based Augmentation Systems (GBAS) to support Category II/III approaches and landings. The steepest part of this extreme gradient had a scale size of 5.3 km, and the front-normal velocities were estimated to be 71 m s-1 with a wavefront-normal direction of east-northeastward. The total width of the transition region from outside to inside the plasma bubble was estimated to be 35.3 km. The gradient of relatively small spatial scale size may fall between an aircraft and a GBAS ground subsystem and may be undetectable by both aircraft and ground.
[Principles of management of All-Russia Disaster Medicine Services].
Sakhno, I I
2000-11-01
Experience of liquidation of earthquake consequences in Armenia (1988) has shown that it is extremely necessary to create the system of management in regions of natural disaster, large accident or catastrophe before arrival of main forces in order to provide reconnaissance, to receive the arriving units. It will help to make well-grounded decisions, to set tasks in time, to organize and conduct emergency-and-rescue works. The article contains general material concerning the structure of All-Russia service of disaster medicine (ARSDM), organization of management at all levels and interaction between the components of ARSDM and other subsystems of Russian Service of Extreme Situations. It is recommended how to organize management of ARSDM during liquidation of medical-and-sanitary consequences of large-scale extreme situations.
Attribution of extreme rainfall from Hurricane Harvey, August 2017
NASA Astrophysics Data System (ADS)
van Oldenborgh, Geert Jan; van der Wiel, Karin; Sebastian, Antonia; Singh, Roop; Arrighi, Julie; Otto, Friederike; Haustein, Karsten; Li, Sihan; Vecchi, Gabriel; Cullen, Heidi
2017-12-01
During August 25-30, 2017, Hurricane Harvey stalled over Texas and caused extreme precipitation, particularly over Houston and the surrounding area on August 26-28. This resulted in extensive flooding with over 80 fatalities and large economic costs. It was an extremely rare event: the return period of the highest observed three-day precipitation amount, 1043.4 mm 3dy-1 at Baytown, is more than 9000 years (97.5% one-sided confidence interval) and return periods exceeded 1000 yr (750 mm 3dy-1) over a large area in the current climate. Observations since 1880 over the region show a clear positive trend in the intensity of extreme precipitation of between 12% and 22%, roughly two times the increase of the moisture holding capacity of the atmosphere expected for 1 °C warming according to the Clausius-Clapeyron (CC) relation. This would indicate that the moisture flux was increased by both the moisture content and stronger winds or updrafts driven by the heat of condensation of the moisture. We also analysed extreme rainfall in the Houston area in three ensembles of 25 km resolution models. The first also shows 2 × CC scaling, the second 1 × CC scaling and the third did not have a realistic representation of extreme rainfall on the Gulf Coast. Extrapolating these results to the 2017 event, we conclude that global warming made the precipitation about 15% (8%-19%) more intense, or equivalently made such an event three (1.5-5) times more likely. This analysis makes clear that extreme rainfall events along the Gulf Coast are on the rise. And while fortifying Houston to fully withstand the impact of an event as extreme as Hurricane Harvey may not be economically feasible, it is critical that information regarding the increasing risk of extreme rainfall events in general should be part of the discussion about future improvements to Houston’s flood protection system.
Resilience Design Patterns: A Structured Approach to Resilience at Extreme Scale
Engelmann, Christian; Hukerikar, Saurabh
2017-09-01
Reliability is a serious concern for future extreme-scale high-performance computing (HPC) systems. Projections based on the current generation of HPC systems and technology roadmaps suggest the prevalence of very high fault rates in future systems. While the HPC community has developed various resilience solutions, application-level techniques as well as system-based solutions, the solution space remains fragmented. There are no formal methods and metrics to integrate the various HPC resilience techniques into composite solutions, nor are there methods to holistically evaluate the adequacy and efficacy of such solutions in terms of their protection coverage, and their performance \\& power efficiency characteristics.more » Additionally, few of the current approaches are portable to newer architectures and software environments that will be deployed on future systems. In this paper, we develop a structured approach to the design, evaluation and optimization of HPC resilience using the concept of design patterns. A design pattern is a general repeatable solution to a commonly occurring problem. We identify the problems caused by various types of faults, errors and failures in HPC systems and the techniques used to deal with these events. Each well-known solution that addresses a specific HPC resilience challenge is described in the form of a pattern. We develop a complete catalog of such resilience design patterns, which may be used by system architects, system software and tools developers, application programmers, as well as users and operators as essential building blocks when designing and deploying resilience solutions. We also develop a design framework that enhances a designer's understanding the opportunities for integrating multiple patterns across layers of the system stack and the important constraints during implementation of the individual patterns. It is also useful for defining mechanisms and interfaces to coordinate flexible fault management across hardware and software components. The resilience patterns and the design framework also enable exploration and evaluation of design alternatives and support optimization of the cost-benefit trade-offs among performance, protection coverage, and power consumption of resilience solutions. Here, the overall goal of this work is to establish a systematic methodology for the design and evaluation of resilience technologies in extreme-scale HPC systems that keep scientific applications running to a correct solution in a timely and cost-efficient manner despite frequent faults, errors, and failures of various types.« less
Resilience Design Patterns: A Structured Approach to Resilience at Extreme Scale
DOE Office of Scientific and Technical Information (OSTI.GOV)
Engelmann, Christian; Hukerikar, Saurabh
Reliability is a serious concern for future extreme-scale high-performance computing (HPC) systems. Projections based on the current generation of HPC systems and technology roadmaps suggest the prevalence of very high fault rates in future systems. While the HPC community has developed various resilience solutions, application-level techniques as well as system-based solutions, the solution space remains fragmented. There are no formal methods and metrics to integrate the various HPC resilience techniques into composite solutions, nor are there methods to holistically evaluate the adequacy and efficacy of such solutions in terms of their protection coverage, and their performance \\& power efficiency characteristics.more » Additionally, few of the current approaches are portable to newer architectures and software environments that will be deployed on future systems. In this paper, we develop a structured approach to the design, evaluation and optimization of HPC resilience using the concept of design patterns. A design pattern is a general repeatable solution to a commonly occurring problem. We identify the problems caused by various types of faults, errors and failures in HPC systems and the techniques used to deal with these events. Each well-known solution that addresses a specific HPC resilience challenge is described in the form of a pattern. We develop a complete catalog of such resilience design patterns, which may be used by system architects, system software and tools developers, application programmers, as well as users and operators as essential building blocks when designing and deploying resilience solutions. We also develop a design framework that enhances a designer's understanding the opportunities for integrating multiple patterns across layers of the system stack and the important constraints during implementation of the individual patterns. It is also useful for defining mechanisms and interfaces to coordinate flexible fault management across hardware and software components. The resilience patterns and the design framework also enable exploration and evaluation of design alternatives and support optimization of the cost-benefit trade-offs among performance, protection coverage, and power consumption of resilience solutions. Here, the overall goal of this work is to establish a systematic methodology for the design and evaluation of resilience technologies in extreme-scale HPC systems that keep scientific applications running to a correct solution in a timely and cost-efficient manner despite frequent faults, errors, and failures of various types.« less
Deviations from uniform power law scaling in nonstationary time series
NASA Technical Reports Server (NTRS)
Viswanathan, G. M.; Peng, C. K.; Stanley, H. E.; Goldberger, A. L.
1997-01-01
A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.
Integrating legacy data to understand agroecosystem regional dynamics to catastrophic events
USDA-ARS?s Scientific Manuscript database
Multi-year extreme drought events are part of the history of the Earth system. Legacy data on the climate drivers, geomorphic features, and agroecosystem responses across a dynamically changing landscape throughout a region can provide important insights to a future where large-scale catastrophic ev...
Shea, Sarah; Moriello, Gabriele
2014-07-01
Pilates is a method that can potentially be used for stroke rehabilitation to address impairments in gait, balance, strength, and posture. The purpose of this case report was to document the feasibility of using Pilates and to describe outcomes of a 9-month program on lower extremity strength, balance, posture, gait, and quality of life in an individual with stroke. The participant was taught Pilates exercises up to two times per week for nine months in addition to traditional rehabilitation in the United States. Outcomes were assessed using the Berg Balance Scale (BBS), Stroke Impact Scale (SIS), GAITRite System(®), 5 repetition sit-to-stand test (STST), and flexicurve. Improvements were found in balance, lower extremity strength, and quality of life. Posture and gait speed remained the same. While these changes cannot be specifically attributed to the intervention, Pilates may have added to his overall rehabilitation program and with some modifications was feasible to use in someone with a stroke. Copyright © 2013 Elsevier Ltd. All rights reserved.
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.
Advancing the adaptive capacity of social-ecological systems to absorb climate extremes
NASA Astrophysics Data System (ADS)
Thonicke, Kirsten; Bahn, Michael; Bardgett, Richard; Bloemen, Jasper; Chabay, Ilan; Erb, Karlheinz; Giamberini, Mariasilvia; Gingrich, Simone; Lavorel, Sandra; Liehr, Stefan; Rammig, Anja
2017-04-01
The recent and projected increases in climate variability and the frequency of climate extremes are posing a profound challenge to society and the biosphere (IPCC 2012, IPCC 2013). Climate extremes can affect natural and managed ecosystems more severely than gradual warming. The ability of ecosystems to resist and recover from climate extremes is therefore of fundamental importance for society, which strongly relies on their ability to supply provisioning, regulating, supporting and cultural services. Society in turn triggers land-use and management decisions that affect ecosystem properties. Thus, ecological and socio-economic conditions are tightly coupled in what has been referred to as the social-ecological system. For ensuring human well-being in the light of climate extremes it is crucial to enhance the resilience of the social-ecological system (SES) across spatial, temporal and institutional scales. Stakeholders, such as resource managers, urban, landscape and conservation planners, decision-makers in agriculture and forestry, as well as natural hazards managers, require an improved knowledge base for better-informed decision making. To date the vulnerability and adaptive capacity of SESs to climate extremes is not well understood and large uncertainties exist as to the legacies of climate extremes on ecosystems and on related societal structures and processes. Moreover, we lack empirical evidence and incorporation of simulated future ecosystem and societal responses to support pro-active management and enhance social-ecological resilience. In our presentation, we outline the major research gaps and challenges to be addressed for understanding and enhancing the adaptive capacity of SES to absorb and adapt to climate extremes, including acquisition and elaboration of long-term monitoring data and improvement of ecological models to better project climate extreme effects and provide model uncertainties. We highlight scientific challenges and discuss conceptual and observational gaps that need to be overcome to advance this inter- and transdisciplinary topic.
NASA Astrophysics Data System (ADS)
Huang, Ling; Luo, Yali; Zhang, Da-Lin
2018-04-01
A spectral analysis of daily rainfall data has been performed to investigate extreme rainfall events in south China during the presummer rainy seasons between 1998 and 2015 (excluding 1999, 2006, 2011, and 2014). The results reveal a dominant frequency mode at the synoptic scale with pronounced positive rainfall anomalies. By analyzing the synoptic-scale bandpass-filtered anomalous circulations, 24 extreme rainfall episodes (defined as those with a daily rainfall amount in the top 5%) are categorized into "cyclone" (15) and "trough" (8) types, with the remaining events as an "anticyclone" type, according to the primary anomalous weather system contributing to each extreme rainfall episode. The 15 cyclone-type episodes are further separated into (11) lower- and (4) upper-tropospheric migratory anomalies. An analysis of their anomalous fields shows that both types could be traced back to the generation of cyclonic anomalies downstream of the Tibetan Plateau, except for two episodes of lower-tropospheric migratory anomalies originating over the South China Sea. However, a lower-tropospheric cyclonic anomaly appears during all phases in the former type, but only in the wettest phase in the latter type, with its peak disturbance occurring immediately beneath an upper-level warm anomaly. The production of extreme rainfall in the trough-type episodes is closely related to a deep trough anomaly extending from an intense cyclonic anomaly over north China, which in turn could be traced back to a midlatitude Rossby wave train passing by the Tibetan Plateau. The results have important implications for understanding the origin, structure, and evolution of synoptic disturbances associated with the presummer extreme rainfall in south China.
Baby, André Rolim; Santoro, Diego Monegatto; Velasco, Maria Valéria Robles; Dos Reis Serra, Cristina Helena
2008-09-01
Introducing a pharmaceutical product on the market involves several stages of research. The scale-up stage comprises the integration of previous phases of development and their integration. This phase is extremely important since many process limitations which do not appear on the small scale become significant on the transposition to a large one. Since scientific literature presents only a few reports about the characterization of emulsified systems involving their scaling-up, this research work aimed at evaluating physical properties of non-ionic and anionic emulsions during their manufacturing phases: laboratory stage and scale-up. Prototype non-ionic (glyceryl monostearate) and anionic (potassium cetyl phosphate) emulsified systems had the physical properties by the determination of the droplet size (D[4,3], mum) and rheology profile. Transposition occurred from a batch of 500-50,000g. Semi-industrial manufacturing involved distinct conditions: intensity of agitation and homogenization. Comparing the non-ionic and anionic systems, it was observed that anionic emulsifiers generated systems with smaller droplet size and higher viscosity in laboratory scale. Besides that, for the concentrations tested, augmentation of the glyceryl monostearate emulsifier content provided formulations with better physical characteristics. For systems with potassium cetyl phosphate, droplet size increased with the elevation of the emulsifier concentration, suggesting inadequate stability. The scale-up provoked more significant alterations on the rheological profile and droplet size on the anionic systems than the non-ionic.
Influence of spatial and temporal scales in identifying temperature extremes
NASA Astrophysics Data System (ADS)
van Eck, Christel M.; Friedlingstein, Pierre; Mulder, Vera L.; Regnier, Pierre A. G.
2016-04-01
Extreme heat events are becoming more frequent. Notable are severe heatwaves such as the European heatwave of 2003, the Russian heat wave of 2010 and the Australian heatwave of 2013. Surface temperature is attaining new maxima not only during the summer but also during the winter. The year of 2015 is reported to be a temperature record breaking year for both summer and winter. These extreme temperatures are taking their human and environmental toll, emphasizing the need for an accurate method to define a heat extreme in order to fully understand the spatial and temporal spread of an extreme and its impact. This research aims to explore how the use of different spatial and temporal scales influences the identification of a heat extreme. For this purpose, two near-surface temperature datasets of different temporal scale and spatial scale are being used. First, the daily ERA-Interim dataset of 0.25 degree and a time span of 32 years (1979-2010). Second, the daily Princeton Meteorological Forcing Dataset of 0.5 degree and a time span of 63 years (1948-2010). A temperature is considered extreme anomalous when it is surpassing the 90th, 95th, or the 99th percentile threshold based on the aforementioned pre-processed datasets. The analysis is conducted on a global scale, dividing the world in IPCC's so-called SREX regions developed for the analysis of extreme climate events. Pre-processing is done by detrending and/or subtracting the monthly climatology based on 32 years of data for both datasets and on 63 years of data for only the Princeton Meteorological Forcing Dataset. This results in 6 datasets of temperature anomalies from which the location in time and space of the anomalous warm days are identified. Comparison of the differences between these 6 datasets in terms of absolute threshold temperatures for extremes and the temporal and spatial spread of the extreme anomalous warm days show a dependence of the results on the datasets and methodology used. This stresses the need for a careful selection of data and methodology when identifying heat extremes.
Technology Innovations from NASA's Next Generation Launch Technology Program
NASA Technical Reports Server (NTRS)
Cook, Stephen A.; Morris, Charles E. K., Jr.; Tyson, Richard W.
2004-01-01
NASA's Next Generation Launch Technology Program has been on the cutting edge of technology, improving the safety, affordability, and reliability of future space-launch-transportation systems. The array of projects focused on propulsion, airframe, and other vehicle systems. Achievements range from building miniature fuel/oxygen sensors to hot-firings of major rocket-engine systems as well as extreme thermo-mechanical testing of large-scale structures. Results to date have significantly advanced technology readiness for future space-launch systems using either airbreathing or rocket propulsion.
Navarro-Pujalte, Esther; Gacto-Sánchez, Mariano; Montilla-Herrador, Joaquina; Escolar-Reina, Pilar; Ángeles Franco-Sierra, María; Medina-Mirapeix, Francesc
2018-01-12
Prospective longitudinal study. To examine the sensitivity of the Mobility Activities Measure for lower extremities and to compare it to the sensitivity of the Physical Functioning Scale (PF-10) and the Patient-Specific Functional Scale (PSFS) at week 4 and week 8 post-hospitalization in outpatient rehabilitation settings. Mobility Activities Measure is a set of short mobility measures to track outpatient rehabilitation progress: its scales have shown good properties but its sensitivity to change has not been reported. Patients with musculoskeletal conditions were recruited at admission in three outpatient rehabilitation settings in Spain. Data were collected at admission, week 4 and week 8 from an initial sample of 236 patients (mean age ± SD = 36.7 ± 11.1). Mobility Activities Measure scales for lower extremity; PF-10; and PSFS. All the Mobility Activities Measure scales were sensitive to both positive and negative changes (the Standardized Response Means (SRMs) ranged between 1.05 and 1.53 at week 4, and between 0.63 and 1.47 at week 8). The summary measure encompassing the three Mobility Activities Measure scales detected a higher proportion of participants who had improved beyond the minimal detectable change (MDC) than detected by the PSFS and the PF-10 both at week 4 (86.64% vs. 69.81% and 42.23%, respectively) and week 8 (71.14% vs. 55.65% and 60.81%, respectively). The three Mobility Activities Measure scales assessing the lower extremity can be used across outpatient rehabilitation settings to provide consistent and sensitive measures of changes in patients' mobility. Implications for rehabilitation All the scales of the Mobility Activities Measure for the lower extremity were sensitive to both positive and negative change across the follow-up periods. Overall, the summary measure encompassing the three Mobility Activities Measure scales for the lower extremity appeared more sensitive to positive changes than the Physical Functioning Scale, especially during the first four weeks of treatment. The summary measure also detected a higher percentage of participants with positive change that exceeded the minimal detectable change than the Patient-Specific Functional Scale and the Physical Functioning Scale at the first follow-up period. By demonstrating their consistency and sensitivity to change, the three Mobility Activities Measures scales can now be considered in order to track patients' functional progress. Mobility Activities Measure can be therefore used in patients with musculoskeletal conditions across outpatient rehabilitation settings to provide estimates of change in mobility activities focusing on the lower extremity.
Temporal Clustering of Regional-Scale Extreme Precipitation Events in Southern Switzerland
NASA Astrophysics Data System (ADS)
Barton, Yannick; Giannakaki, Paraskevi; Von Waldow, Harald; Chevalier, Clément; Pfhal, Stephan; Martius, Olivia
2017-04-01
Temporal clustering of extreme precipitation events on subseasonal time scales is a form of compound extremes and is of crucial importance for the formation of large-scale flood events. Here, the temporal clustering of regional-scale extreme precipitation events in southern Switzerland is studied. These precipitation events are relevant for the flooding of lakes in southern Switzerland and northern Italy. This research determines whether temporal clustering is present and then identifies the dynamics that are responsible for the clustering. An observation-based gridded precipitation dataset of Swiss daily rainfall sums and ECMWF reanalysis datasets are used. To analyze the clustering in the precipitation time series a modified version of Ripley's K function is used. It determines the average number of extreme events in a time period, to characterize temporal clustering on subseasonal time scales and to determine the statistical significance of the clustering. Significant clustering of regional-scale precipitation extremes is found on subseasonal time scales during the fall season. Four high-impact clustering episodes are then selected and the dynamics responsible for the clustering are examined. During the four clustering episodes, all heavy precipitation events were associated with an upperlevel breaking Rossby wave over western Europe and in most cases strong diabatic processes upstream over the Atlantic played a role in the amplification of these breaking waves. Atmospheric blocking downstream over eastern Europe supported this wave breaking during two of the clustering episodes. During one of the clustering periods, several extratropical transitions of tropical cyclones in the Atlantic contributed to the formation of high-amplitude ridges over the Atlantic basin and downstream wave breaking. During another event, blocking over Alaska assisted the phase locking of the Rossby waves downstream over the Atlantic.
NASA Astrophysics Data System (ADS)
Lenderink, Geert; Attema, Jisk
2015-08-01
Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change.
Invited Article: Visualisation of extreme value events in optical communications
NASA Astrophysics Data System (ADS)
Derevyanko, Stanislav; Redyuk, Alexey; Vergeles, Sergey; Turitsyn, Sergei
2018-06-01
Fluctuations of a temporal signal propagating along long-haul transoceanic scale fiber links can be visualised in the spatio-temporal domain drawing visual analogy with ocean waves. Substantial overlapping of information symbols or use of multi-frequency signals leads to strong statistical deviations of local peak power from an average signal power level. We consider long-haul optical communication systems from this unusual angle, treating them as physical systems with a huge number of random statistical events, including extreme value fluctuations that potentially might affect the quality of data transmission. We apply the well-established concepts of adaptive wavefront shaping used in imaging through turbid medium to detect the detrimental phase modulated sequences in optical communications that can cause extreme power outages (rare optical waves of ultra-high amplitude) during propagation down the ultra-long fiber line. We illustrate the concept by a theoretical analysis of rare events of high-intensity fluctuations—optical freak waves, taking as an example an increasingly popular optical frequency division multiplexing data format where the problem of high peak to average power ratio is the most acute. We also show how such short living extreme value spikes in the optical data streams are affected by nonlinearity and demonstrate the negative impact of such events on the system performance.
Linking disaster resilience and urban sustainability: a glocal approach for future cities.
Asprone, Domenico; Manfredi, Gaetano
2015-01-01
Resilience and sustainability will be two primary objectives of future cities. The violent consequences of extreme natural events and the environmental, social and economic burden of contemporary cities make the concepts of resilience and sustainability extremely relevant. In this paper we analyse the various definitions of resilience and sustainability applied to urban systems and propose a synthesis, based on similarities between the two concepts. According to the proposed approach, catastrophic events and the subsequent transformations occurring in urban systems represent a moment in the city life cycle to be seen in terms of the complex sustainability framework. Hence, resilience is seen as a requirement for urban system sustainability. In addition, resilience should be evaluated not only for single cities, with their physical and social systems, but also on a global scale, taking into account the complex and dynamic relationships connecting contemporary cities. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.
Effects of BMI on the risk and frequency of AIS 3+ injuries in motor-vehicle crashes.
Rupp, Jonathan D; Flannagan, Carol A C; Leslie, Andrew J; Hoff, Carrie N; Reed, Matthew P; Cunningham, Rebecca M
2013-01-01
Determine the effects of BMI on the risk of serious-to-fatal injury (Abbreviated Injury Scale ≥ 3 or AIS 3+) to different body regions for adults in frontal, nearside, farside, and rollover crashes. Multivariate logistic regression analysis was applied to a probability sample of adult occupants involved in crashes generated by combining the National Automotive Sampling System (NASS-CDS) with a pseudoweighted version of the Crash Injury Research and Engineering Network database. Logistic regression models were applied to weighted data to estimate the change in the number of occupants with AIS 3+ injuries if no occupants were obese. Increasing BMI increased risk of lower-extremity injury in frontal crashes, decreased risk of lower-extremity injury in nearside impacts, increased risk of upper-extremity injury in frontal and nearside crashes, and increased risk of spine injury in frontal crashes. Several of these findings were affected by interactions with gender and vehicle type. If no occupants in frontal crashes were obese, 7% fewer occupants would sustain AIS 3+ upper-extremity injuries, 8% fewer occupants would sustain AIS 3+ lower-extremity injuries, and 28% fewer occupants would sustain AIS 3+ spine injuries. Results of this study have implications on the design and evaluation of vehicle safety systems. Copyright © 2013 The Obesity Society.
NASA Astrophysics Data System (ADS)
Shastri, Hiteshri; Ghosh, Subimal; Karmakar, Subhankar
2017-02-01
Forecasting of extreme precipitation events at a regional scale is of high importance due to their severe impacts on society. The impacts are stronger in urban regions due to high flood potential as well high population density leading to high vulnerability. Although significant scientific improvements took place in the global models for weather forecasting, they are still not adequate at a regional scale (e.g., for an urban region) with high false alarms and low detection. There has been a need to improve the weather forecast skill at a local scale with probabilistic outcome. Here we develop a methodology with quantile regression, where the reliably simulated variables from Global Forecast System are used as predictors and different quantiles of rainfall are generated corresponding to that set of predictors. We apply this method to a flood-prone coastal city of India, Mumbai, which has experienced severe floods in recent years. We find significant improvements in the forecast with high detection and skill scores. We apply the methodology to 10 ensemble members of Global Ensemble Forecast System and find a reduction in ensemble uncertainty of precipitation across realizations with respect to that of original precipitation forecasts. We validate our model for the monsoon season of 2006 and 2007, which are independent of the training/calibration data set used in the study. We find promising results and emphasize to implement such data-driven methods for a better probabilistic forecast at an urban scale primarily for an early flood warning.
NASA Astrophysics Data System (ADS)
Slawinska, J. M.; Bartoszek, K.; Gabriel, C. J.
2016-12-01
Long-term predictions of changes in extreme event frequency are of utmost importance due to their high societal and economic impact. Yet, current projections are of limited skills as they rely on satellite records that are relatively short compared to the timescale of interest, and also due to the presence of a significant anthropogenic trend superimposed onto other low-frequency variabilities. Novel simulations of past climates provide unique opportunity to separate external perturbations from internal climate anomalies and to attribute the latter to systematic changes in different types of synoptic scale circulation and distributions of high-frequency events. Here we study such changes by employing the Last Millennium Ensemble of climate simulations carried out with the Community Earth System Model (CESM) at the U.S. National Center for Atmospheric Research, focusing in particular on decadal changes in frequency of extreme precipitation events over south-east Poland. We analyze low-frequency modulations of dominant patterns of synoptic scale circulations over Europe and their dependence on the Atlantic Meridional Overturning Circulation, along with their coupling with the North Atlantic Oscillation. Moreover, we examine whether some decades of persistently anomalous statistics of extreme events can be attributed to externally forced (e.g., via volcanic eruptions) perturbations of the North Atlantic climate. In the end, we discuss the possible linkages and physical mechanisms connecting volcanic eruptions, low-frequency variabilities of North Atlantic climate and changes in statistics of high impact weather, and compare briefly our results with some historical and paleontological records.
Large Scale Influences on Summertime Extreme Precipitation in the Northeastern United States.
Marquardt Collow, Allison B; Bosilovich, Michael G; Koster, Randal D
2016-12-01
Observations indicate that over the last few decades there has been a statistically significant increase in precipitation in the Northeastern United States and that this can be attributed to an increase in precipitation associated with extreme precipitation events. Here we use a state-of-the-art atmospheric reanalysis to examine such events in detail. Daily extreme precipitation events defined at the 75 th and 95 th percentile from gridded gauge observations are identified for a selected region within the Northeast. Atmospheric variables from the Modern Era Retrospective Analysis for Research and Applications - Version 2 (MERRA-2) are then composited during these events to illustrate the time evolution of associated synoptic structures, with a focus on vertically integrated water vapor fluxes, sea level pressure, and 500 hPa heights. Anomalies of these fields move into the region from the northwest, with stronger anomalies present in the 95 th percentile case. Although previous studies show tropical cyclones are responsible for the most intense extreme precipitation events, only 10% of the events in this study are caused by tropical cyclones. On the other hand, extreme events resulting from cut off low pressure systems have increased. The time period of the study was divided in half to determine how the mean composite has changed over time. An arc of lower sea level pressure along the east coast and a change in the vertical profile of equivalent potential temperature suggest a possible increase in the frequency or intensity of synoptic scale baroclinic disturbances.
Large Scale Influences on Summertime Extreme Precipitation in the Northeastern United States
NASA Technical Reports Server (NTRS)
Collow, Allison B. Marquardt; Bosilovich, Michael G.; Koster, Randal Dean
2016-01-01
Observations indicate that over the last few decades there has been a statistically significant increase in precipitation in the northeastern United States and that this can be attributed to an increase in precipitation associated with extreme precipitation events. Here a state-of-the-art atmospheric reanalysis is used to examine such events in detail. Daily extreme precipitation events defined at the 75th and 95th percentile from gridded gauge observations are identified for a selected region within the Northeast. Atmospheric variables from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), are then composited during these events to illustrate the time evolution of associated synoptic structures, with a focus on vertically integrated water vapor fluxes, sea level pressure, and 500-hectopascal heights. Anomalies of these fields move into the region from the northwest, with stronger anomalies present in the 95th percentile case. Although previous studies show tropical cyclones are responsible for the most intense extreme precipitation events, only 10 percent of the events in this study are caused by tropical cyclones. On the other hand, extreme events resulting from cutoff low pressure systems have increased. The time period of the study was divided in half to determine how the mean composite has changed over time. An arc of lower sea level pressure along the East Coast and a change in the vertical profile of equivalent potential temperature suggest a possible increase in the frequency or intensity of synoptic-scale baroclinic disturbances.
NASA Astrophysics Data System (ADS)
Ruane, A. C.
2016-12-01
The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to build a modeling framework capable of representing the complexities of agriculture, its dependence on climate, and the many elements of society that depend on food systems. AgMIP's 30+ activities explore the interconnected nature of climate, crop, livestock, economics, food security, and nutrition, using common protocols to systematically evaluate the components of agricultural assessment and allow multi-model, multi-scale, and multi-method analysis of intertwining changes in socioeconomic development, environmental change, and technological adaptation. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) with a particular focus on unforeseen consequences of development strategies, interactions between global and local systems, and the resilience of agricultural systems to extreme climate events. Climate extremes shock the agricultural system through local, direct impacts (e.g., droughts, heat waves, floods, severe storms) and also through teleconnections propagated through international trade. As the climate changes, the nature of climate extremes affecting agriculture is also likely to change, leading to shifting intensity, duration, frequency, and geographic extents of extremes. AgMIP researchers are developing new scenario methodologies to represent near-term extreme droughts in a probabilistic manner, field experiments that impose heat wave conditions on crops, increased resolution to differentiate sub-national drought impacts, new behavioral functions that mimic the response of market actors faced with production shortfalls, analysis of impacts from simultaneous failures of multiple breadbasket regions, and more detailed mapping of food and socioeconomic indicators into food security and nutrition metrics that describe the human impact in diverse populations. Agricultural models illustrate the challenges facing agriculture, allowing resilience planning even as precise prediction of extremes remains difficult. Increased research is necessary to understand hazards, vulnerability, and exposure of populations to characterize the risk of shocks and mechanisms by which unexpected losses drive land-use transitions.
NASA Astrophysics Data System (ADS)
Quattrochi, D. A.; Crosson, W. L.; Al-Hamdan, M. Z.; Estes, M. G., Jr.
2013-12-01
In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981-2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a ';heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.
NASA Technical Reports Server (NTRS)
Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.
2013-01-01
In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S
Sahinoğlu, Dilek; Coskun, Gürsoy; Bek, Nilgün
2017-02-01
Adaptive seating supports for cerebral palsy are recommended to develop and maintain optimum posture, and functional use of upper extremities. To compare the effectiveness of different seating adaptations regarding postural alignment and related functions and to investigate the effects of these seating adaptations on different motor levels. Prospective study. A total of 20 children with spastic cerebral palsy (Gross Motor Function Classification System 3-5) were included. Postural control and function (Seated Postural Control Measure, Sitting Assessment Scale) were measured in three different systems: standard chair, adjustable seating system and custom-made orthosis. In results of all participants ungrouped, there was a significant difference in most parameters of both measurement tools in favor of custom-made orthosis and adjustable seating system when compared to standard chair ( p < 0.0017). There was a difference among interventions in most of the Seated Postural Control Measure results in Level 4 when subjects were grouped according to Gross Motor Function Classification System levels. A difference was observed between standard chair and adjustable seating system in foot control, arm control, and total Sitting Assessment Scale scores; and between standard chair and custom-made orthosis in trunk control, arm control, and total Sitting Assessment Scale score in Level 4. There was no difference in adjustable seating system and custom-made orthosis in Sitting Assessment Scale in this group of children ( p < 0.017). Although custom-made orthosis fabrication is time consuming, it is still recommended since it is custom made, easy to use, and low-cost. On the other hand, the adjustable seating system can be modified according to a patient's height and weight. Clinical relevance It was found that Gross Motor Function Classification System Level 4 children benefitted most from the seating support systems. It was presented that standard chair is sufficient in providing postural alignment. Both custom-made orthosis and adjustable seating system have pros and cons and the best solution for each will be dependent on a number of factors.
TECA: Petascale pattern recognition for climate science
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prabhat, .; Byna, Surendra; Vishwanath, Venkatram
Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 5PB in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA (Toolkit for Extreme Climate Analysis) framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBMmore » BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.« less
2010-02-01
condition, etc.) [ Fenske , 2006]. The failures due to friction and wear range across scale boundaries from nanoscale tribology at asperities to...Coatings for Machines and Mechanisnms Operating Under Extreme Conditions (A. review), Journal of Friction and Wear, 25 (3), 78. 2. Fenske G., Robert E
ERIC Educational Resources Information Center
Davies, Malonne; Landis, Linda; Landis, Arthur
2009-01-01
After studying phenomena related to the positions and motions of the Earth, Sun, and Moon, many students are familiar with the positional ordering of the planets, but their knowledge of the distances involved is vague. Scale models are one means of bringing extreme sizes into better focus, cutting them down to relative values that they can better…
Tyler Jon Smith; Lucy Amanda Marshall
2010-01-01
Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are...
Basin scale permeability and thermal evolution of a magmatic hydrothermal system
NASA Astrophysics Data System (ADS)
Taron, J.; Hickman, S. H.; Ingebritsen, S.; Williams, C.
2013-12-01
Large-scale hydrothermal systems are potentially valuable energy resources and are of general scientific interest due to extreme conditions of stress, temperature, and reactive chemistry that can act to modify crustal rheology and composition. With many proposed sites for Enhanced Geothermal Systems (EGS) located on the margins of large-scale hydrothermal systems, understanding the temporal evolution of these systems contributes to site selection, characterization and design of EGS. This understanding is also needed to address the long-term sustainability of EGS once they are created. Many important insights into heat and mass transfer within natural hydrothermal systems can be obtained through hydrothermal modeling assuming that stress and permeability structure do not evolve over time. However, this is not fully representative of natural systems, where the effects of thermo-elastic stress changes, chemical fluid-rock interactions, and rock failure on fluid flow and thermal evolution can be significant. The quantitative importance of an evolving permeability field within the overall behavior of a large-scale hydrothermal system is somewhat untested, and providing such a parametric understanding is one of the goals of this study. We explore the thermal evolution of a sedimentary basin hydrothermal system following the emplacement of a magma body. The Salton Sea geothermal field and its associated magmatic system in southern California is utilized as a general backdrop to define the initial state. Working within the general framework of the open-source scientific computing initiative OpenGeoSys (www.opengeosys.org), we introduce full treatment of thermodynamic properties at the extreme conditions following magma emplacement. This treatment utilizes a combination of standard Galerkin and control-volume finite elements to balance fluid mass, mechanical deformation, and thermal energy with consideration of local thermal non-equilibrium (LTNE) between fluids and solids. Permeability is allowed to evolve under several constitutive models tailored to both porous media and fractures, considering the influence of both mechanical stress and diagenesis. In this first analysis, a relatively simple mechanical model is used; complexity will be added incrementally to represent specific characteristics of the Salton Sea hydrothermal field.
NASA Technical Reports Server (NTRS)
Kremic, Tibor; Vento, Dan; Lalli, Nick; Palinski, Timothy
2014-01-01
Science, technology, and planetary mission communities have a growing interest in components and systems that are capable of working in extreme (high) temperature and pressure conditions. Terrestrial applications range from scientific research, aerospace, defense, automotive systems, energy storage and power distribution, deep mining and others. As the target environments get increasingly extreme, capabilities to develop and test the sensors and systems designed to operate in such environments will be required. An application of particular importance to the planetary science community is the ability for a robotic lander to survive on the Venus surface where pressures are nearly 100 times that of Earth and temperatures approach 500C. The scientific importance and relevance of Venus missions are stated in the current Planetary Decadal Survey. Further, several missions to Venus were proposed in the most recent Discovery call. Despite this interest, the ability to accurately simulate Venus conditions at a scale that can test and validate instruments and spacecraft systems and accurately simulate the Venus atmosphere has been lacking. This paper discusses and compares the capabilities that are known to exist within and outside the United States to simulate the extreme environmental conditions found in terrestrial or planetary surfaces including the Venus atmosphere and surface. The paper then focuses on discussing the recent additional capability found in the NASA Glenn Extreme Environment Rig (GEER). The GEER, located at the NASA Glenn Research Center in Cleveland, Ohio, is designed to simulate not only the temperature and pressure extremes described, but can also accurately reproduce the atmospheric compositions of bodies in the solar system including those with acidic and hazardous elements. GEER capabilities and characteristics are described along with operational considerations relevant to potential users. The paper presents initial operating results and concludes with a sampling of investigations or tests that have been requested or expected.
Processing and Synthesis of Pre-Biotic Chemicals in Hypervelocity Impacts
NASA Technical Reports Server (NTRS)
Brickerhoff, W. B.; Managadze, G. G.; Chumikov, A. E.; Managadze, N. G.
2005-01-01
Hypervelocity impacts (HVIs) may have played a significant role in establishing the initial organic inventory for pre-biotic chemistry on the Earth and other planetary bodies. In addition to the delivery of organic compounds intact to planetary surfaces, generally at velocities below approx.20 km/s, HVIs also enable synthesis of new molecules. The cooling post-impact plasma plumes of HVIs in the interstellar medium (ISM), the protosolar nebula (PSN), and the early solar system comprise pervasive conditions for organic synthesis. Such plasma synthesis (PS) can operate over many length scales (from nm-scale dust to planets) and energy scales (from molecular rearrangement to atomization and recondensation). HVI experiments with the flexibility to probe the highest velocities and distinguish synthetic routes are a high priority to understand the relevance of PS to exobiology. We describe here recent studies of PS at small spatial scales and extremely high velocities with pulsed laser ablation (PLA). PLA can simulate the extreme plasma conditions generated in impacts of dust particles at speeds of up to 100 km/s or more. When applied to carbonaceous solids, new and pre-biotically relevant molecular species are formed with high efficiency [1,2].
ERIC Educational Resources Information Center
Cintas, Holly Lea; Parks, Rebecca; Don, Sarah; Gerber, Lynn
2011-01-01
Content validity and reliability of the Brief Assessment of Motor Function (BAMF) Upper Extremity Gross Motor Scale (UEGMS) were evaluated in this prospective, descriptive study. The UEGMS is one of five BAMF ordinal scales designed for quick documentation of gross, fine, and oral motor skill levels. Designed to be independent of age and…
NASA Astrophysics Data System (ADS)
Renschler, C.; Sheridan, M. F.; Patra, A. K.
2008-05-01
The impact and consequences of extreme geophysical events (hurricanes, floods, wildfires, volcanic flows, mudflows, etc.) on properties and processes should be continuously assessed by a well-coordinated interdisciplinary research and outreach approach addressing risk assessment and resilience. Communication between various involved disciplines and stakeholders is the key to a successful implementation of an integrated risk management plan. These issues become apparent at the level of decision support tools for extreme events/disaster management in natural and managed environments. The Geospatial Project Management Tool (GeoProMT) is a collaborative platform for research and training to document and communicate the fundamental steps in transforming information for extreme events at various scales for analysis and management. GeoProMT is an internet-based interface for the management of shared geo-spatial and multi-temporal information such as measurements, remotely sensed images, and other GIS data. This tool enhances collaborative research activities and the ability to assimilate data from diverse sources by integrating information management. This facilitates a better understanding of natural processes and enhances the integrated assessment of resilience against both the slow and fast onset of hazard risks. Fundamental to understanding and communicating complex natural processes are: (a) representation of spatiotemporal variability, extremes, and uncertainty of environmental properties and processes in the digital domain, (b) transformation of their spatiotemporal representation across scales (e.g. interpolation, aggregation, disaggregation.) during data processing and modeling in the digital domain, and designing and developing tools for (c) geo-spatial data management, and (d) geo-spatial process modeling and effective implementation, and (e) supporting decision- and policy-making in natural resources and hazard management at various spatial and temporal scales of interest. GeoProMT is useful for researchers, practitioners, and decision-makers, because it provides an integrated environmental system assessment and data management approach that considers the spatial and temporal scales and variability in natural processes. Particularly in the occurrence or onset of extreme events it can utilize the latest data sources that are available at variable scales, combine them with existing information, and update assessment products such as risk and vulnerability assessment maps. Because integrated geo-spatial assessment requires careful consideration of all the steps in utilizing data, modeling and decision-making formats, each step in the sequence must be assessed in terms of how information is being scaled. At the process scale various geophysical models (e.g. TITAN, LAHARZ, or many other examples) are appropriate for incorporation in the tool. Some examples that illustrate our approach include: 1) coastal parishes impacted by Hurricane Rita (Southwestern Louisiana), 2) a watershed affected by extreme rainfall induced debris-flows (Madison County, Virginia; Panabaj, Guatemala; Casita, Nicaragua), and 3) the potential for pyroclastic flows to threaten a city (Tungurahua, Ecuador). This research was supported by the National Science Foundation.
NASA Astrophysics Data System (ADS)
Herath, Sujeewa Malwila; Sarukkalige, Ranjan; Nguyen, Van Thanh Van
2018-01-01
Understanding the relationships between extreme daily and sub-daily rainfall events and their governing factors is important in order to analyse the properties of extreme rainfall events in a changing climate. Atmospheric temperature is one of the dominant climate variables which has a strong relationship with extreme rainfall events. In this study, a temperature-rainfall binning technique is used to evaluate the dependency of extreme rainfall on daily maximum temperature. The Clausius-Clapeyron (C-C) relation was found to describe the relationship between daily maximum temperature and a range of rainfall durations from 6 min up to 24 h for seven Australian weather stations, the stations being located in Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth and Sydney. The analysis shows that the rainfall - temperature scaling varies with location, temperature and rainfall duration. The Darwin Airport station shows a negative scaling relationship, while the other six stations show a positive relationship. To identify the trend in scaling relationship over time the same analysis is conducted using data covering 10 year periods. Results indicate that the dependency of extreme rainfall on temperature also varies with the analysis period. Further, this dependency shows an increasing trend for more extreme short duration rainfall and a decreasing trend for average long duration rainfall events at most stations. Seasonal variations of the scale changing trends were analysed by categorizing the summer and autumn seasons in one group and the winter and spring seasons in another group. Most of 99th percentile of 6 min, 1 h and 24 h rain durations at Perth, Melbourne and Sydney stations show increasing trend for both groups while Adelaide and Darwin show decreasing trend. Furthermore, majority of scaling trend of 50th percentile are decreasing for both groups.
Extreme-volatility dynamics in crude oil markets
NASA Astrophysics Data System (ADS)
Jiang, Xiong-Fei; Zheng, Bo; Qiu, Tian; Ren, Fei
2017-02-01
Based on concepts and methods from statistical physics, we investigate extreme-volatility dynamics in the crude oil markets, using the high-frequency data from 2006 to 2010 and the daily data from 1986 to 2016. The dynamic relaxation of extreme volatilities is described by a power law, whose exponents usually depend on the magnitude of extreme volatilities. In particular, the relaxation before and after extreme volatilities is time-reversal symmetric at the high-frequency time scale, but time-reversal asymmetric at the daily time scale. This time-reversal asymmetry is mainly induced by exogenous events. However, the dynamic relaxation after exogenous events exhibits the same characteristics as that after endogenous events. An interacting herding model both with and without exogenous driving forces could qualitatively describe the extreme-volatility dynamics.
NASA Astrophysics Data System (ADS)
Lewis, Sophie; Karoly, David
2013-04-01
Changes in extreme climate events pose significant challenges for both human and natural systems. Some climate extremes are likely to become "more frequent, more widespread and/or more intense during the 21st century" (Intergovernmental Panel on Climate Change, 2007) due to anthropogenic climate change. Particularly in Australia, El Niño-Southern Oscillation (ENSO) has a relationship to the relative frequency of temperature and precipitation extremes. In this study, we investigate the record high two-summer rainfall observed in Australia (2010-2011 and 2011-2012). This record rainfall occurred in association with a two year extended La Niña event and resulted in severe and extensive flooding. We examine simulated changes in seasonal-scale rainfall extremes in the Australian region in a suite of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). In particular, we utilise the novel CMIP5 detection and attribution historical experiments with various forcings (natural forcings only and greenhouse gas forcings only) to examine the impact of various anthropogenic forcings on seasonal-scale extreme rainfall across Australia. Using these standard detection and attribution experiments over the period of 1850 to 2005, we examine La Niña contributions to the 2-season record rainfall, as well as the longer-term climate change contribution to rainfall extremes. Was there an anthropogenic influence in the record high Australian summer rainfall over 2010 to 2012, and if so, how much influence? Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report on the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.
Resolution dependence of precipitation statistical fidelity in hindcast simulations
O'Brien, Travis A.; Collins, William D.; Kashinath, Karthik; ...
2016-06-19
This article is a U.S. Government work and is in the public domain in the USA. Numerous studies have shown that atmospheric models with high horizontal resolution better represent the physics and statistics of precipitation in climate models. While it is abundantly clear from these studies that high-resolution increases the rate of extreme precipitation, it is not clear whether these added extreme events are “realistic”; whether they occur in simulations in response to the same forcings that drive similar events in reality. In order to understand whether increasing horizontal resolution results in improved model fidelity, a hindcast-based, multiresolution experimental designmore » has been conceived and implemented: the InitiaLIzed-ensemble, Analyze, and Develop (ILIAD) framework. The ILIAD framework allows direct comparison between observed and simulated weather events across multiple resolutions and assessment of the degree to which increased resolution improves the fidelity of extremes. Analysis of 5 years of daily 5 day hindcasts with the Community Earth System Model at horizontal resolutions of 220, 110, and 28 km shows that: (1) these hindcasts reproduce the resolution-dependent increase of extreme precipitation that has been identified in longer-duration simulations, (2) the correspondence between simulated and observed extreme precipitation improves as resolution increases; and (3) this increase in extremes and precipitation fidelity comes entirely from resolved-scale precipitation. Evidence is presented that this resolution-dependent increase in precipitation intensity can be explained by the theory of Rauscher et al. (), which states that precipitation intensifies at high resolution due to an interaction between the emergent scaling (spectral) properties of the wind field and the constraint of fluid continuity.« less
Resolution dependence of precipitation statistical fidelity in hindcast simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
O'Brien, Travis A.; Collins, William D.; Kashinath, Karthik
This article is a U.S. Government work and is in the public domain in the USA. Numerous studies have shown that atmospheric models with high horizontal resolution better represent the physics and statistics of precipitation in climate models. While it is abundantly clear from these studies that high-resolution increases the rate of extreme precipitation, it is not clear whether these added extreme events are “realistic”; whether they occur in simulations in response to the same forcings that drive similar events in reality. In order to understand whether increasing horizontal resolution results in improved model fidelity, a hindcast-based, multiresolution experimental designmore » has been conceived and implemented: the InitiaLIzed-ensemble, Analyze, and Develop (ILIAD) framework. The ILIAD framework allows direct comparison between observed and simulated weather events across multiple resolutions and assessment of the degree to which increased resolution improves the fidelity of extremes. Analysis of 5 years of daily 5 day hindcasts with the Community Earth System Model at horizontal resolutions of 220, 110, and 28 km shows that: (1) these hindcasts reproduce the resolution-dependent increase of extreme precipitation that has been identified in longer-duration simulations, (2) the correspondence between simulated and observed extreme precipitation improves as resolution increases; and (3) this increase in extremes and precipitation fidelity comes entirely from resolved-scale precipitation. Evidence is presented that this resolution-dependent increase in precipitation intensity can be explained by the theory of Rauscher et al. (), which states that precipitation intensifies at high resolution due to an interaction between the emergent scaling (spectral) properties of the wind field and the constraint of fluid continuity.« less
NASA Astrophysics Data System (ADS)
Mauger, G. S.; Lorente-Plazas, R.; Salathe, E. P., Jr.; Mitchell, T. P.; Simmonds, J.; Lee, S. Y.; Hegewisch, K.; Warner, M.; Won, J.
2017-12-01
King County has experienced 12 federally declared flood disasters since 1990, and tens of thousands of county residents commute through, live, and work in floodplains. In addition to flooding, stormwater is a critical management challenge, exacerbated by aging infrastructure, combined sewer and drainage systems, and continued development. Even absent the effects of climate change these are challenging management issues. Recent studies clearly point to an increase in precipitation extremes for the Pacific Northwest (e.g., Warner et al. 2015). Yet very little information is available on the magnitude and spatial distribution of this change. Others clearly show that local-scale changes in extreme precipitation can only be accurately quantified with dynamical downscaling, i.e.: using a regional climate model. This talk will describe a suite of research and adaptation efforts developed in a close collaboration between King County and the UW Climate Impacts Group. Building on past collaborations, research efforts were defined in collaboration with King County managers, addressing three key science questions: (1) How are the mesoscale variations in extreme precipitation modulated by changes in large-scale weather conditions? (2) How will precipitation extremes change? This was assessed via two new high-resolution regional model projections using the Weather Research and Forecasting (WRF) mesoscale model (Skamarock et al. 2005). (3) What are the implications for stormwater and flooding in King County? This was assessed by both exploring the statistics of hourly precipitation extremes in the new projections, as well as new hydrologic modeling to assess the implications for river flooding. The talk will present results from these efforts, review the implications for King County planning and infrastructure, and synthesize lessons learned and opportunities for additional work.
Web-based Visual Analytics for Extreme Scale Climate Science
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steed, Chad A; Evans, Katherine J; Harney, John F
In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less
Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative
NASA Astrophysics Data System (ADS)
Frank, Dorothea; Reichstein, Markus
2017-04-01
The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.
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.
Characterization of extreme precipitation within atmospheric river events over California
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jeon, S.; Prabhat,; Byna, S.
Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less
Characterization of extreme precipitation within atmospheric river events over California
Jeon, S.; Prabhat,; Byna, S.; ...
2015-11-17
Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less
xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heroux, Michael A.; Bartlett, Roscoe; Demeshko, Irina
Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundationmore » for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.« less
xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit
Heroux, Michael A.; Bartlett, Roscoe; Demeshko, Irina; ...
2017-03-01
Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundationmore » for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.« less
Role of absorbing aerosols on hot extremes in India in a GCM
NASA Astrophysics Data System (ADS)
Mondal, A.; Sah, N.; Venkataraman, C.; Patil, N.
2017-12-01
Temperature extremes and heat waves in North-Central India during the summer months of March through June are known for causing significant impact in terms of human health, productivity and mortality. While greenhouse gas-induced global warming is generally believed to intensify the magnitude and frequency of such extremes, aerosols are usually associated with an overall cooling, by virtue of their dominant radiation scattering nature, in most world regions. Recently, large-scale atmospheric conditions leading to heat wave and extreme temperature conditions have been analysed for the North-Central Indian region. However, the role of absorbing aerosols, including black carbon and dust, is still not well understood, in mediating hot extremes in the region. In this study, we use 30-year simulations from a chemistry-coupled atmosphere-only General Circulation Model (GCM), ECHAM6-HAM2, forced with evolving aerosol emissions in an interactive aerosol module, along with observed sea surface temperatures, to examine large-scale and mesoscale conditions during hot extremes in India. The model is first validated with observed gridded temperature and reanalysis data, and is found to represent observed variations in temperature in the North-Central region and concurrent large-scale atmospheric conditions during high temperature extremes realistically. During these extreme events, changes in near surface properties include a reduction in single scattering albedo and enhancement in short-wave solar heating rate, compared to climatological conditions. This is accompanied by positive anomalies of black carbon and dust aerosol optical depths. We conclude that the large-scale atmospheric conditions such as the presence of anticyclones and clear skies, conducive to heat waves and high temperature extremes, are exacerbated by absorbing aerosols in North-Central India. Future air quality regulations are expected to reduce sulfate particles and their masking of GHG warming. It is concurrently important to mitigate emissions of warming black carbon particles, to manage future climate change-induced hot extremes.
Approaching the exa-scale: a real-world evaluation of rendering extremely large data sets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Patchett, John M; Ahrens, James P; Lo, Li - Ta
2010-10-15
Extremely large scale analysis is becoming increasingly important as supercomputers and their simulations move from petascale to exascale. The lack of dedicated hardware acceleration for rendering on today's supercomputing platforms motivates our detailed evaluation of the possibility of interactive rendering on the supercomputer. In order to facilitate our understanding of rendering on the supercomputing platform, we focus on scalability of rendering algorithms and architecture envisioned for exascale datasets. To understand tradeoffs for dealing with extremely large datasets, we compare three different rendering algorithms for large polygonal data: software based ray tracing, software based rasterization and hardware accelerated rasterization. We presentmore » a case study of strong and weak scaling of rendering extremely large data on both GPU and CPU based parallel supercomputers using Para View, a parallel visualization tool. Wc use three different data sets: two synthetic and one from a scientific application. At an extreme scale, algorithmic rendering choices make a difference and should be considered while approaching exascale computing, visualization, and analysis. We find software based ray-tracing offers a viable approach for scalable rendering of the projected future massive data sizes.« less
Xiang, Yang; Lu, Kewei; James, Stephen L.; Borlawsky, Tara B.; Huang, Kun; Payne, Philip R.O.
2011-01-01
The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. PMID:22154838
Xiang, Yang; Lu, Kewei; James, Stephen L; Borlawsky, Tara B; Huang, Kun; Payne, Philip R O
2012-04-01
The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. Copyright © 2011 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Wada, Y.
2017-12-01
Increased occurrence of extreme climate events is one of the most damaging consequences of global climate change today and in the future. Estimating the impacts of such extreme events on global and regional water resources is therefore crucial for quantifying increasing risks from climate change. The quest for water security has been a struggle throughout human history. Only in recent years has the scale of this quest moved beyond the local, to the national and regional scales and to the planet itself. Absent or unreliable water supply, sanitation and irrigation services, unmitigated floods and droughts, and degraded water environments severely impact half of the planet's population. The scale and complexity of the water challenges faced by society, particularly but not only in the world's poorest regions, are now recognized, as is the imperative of overcoming these challenges for a stable and equitable world. IIASA's Water Futures and Solutions Initiative (WFAS) is an unprecedented inter-disciplinary scientific initiative to identify robust and adaptive portfolios of optional solutions across different economic sectors, including agriculture, energy and industry, and to test these solution-portfolios with multi-model ensembles of hydrologic and sector models to obtain a clearer picture of the trade-offs, risks, and opportunities. The results of WFaS scenarios and models provide a basis for long-term strategic planning of water resource development under changing environments and increasing climate extremes. And given the complexity of the water system, WFaS uniquely provides policy makers with optional sets of solutions that work together and that can be easily adapted as circumstances change in the future. As WFaS progresses, it will establish a network involving information exchange, mutual learning and horizontal cooperation across teams of researchers, public and private decision makers and practitioners exploring solutions at regional, national and local scales. The initiative includes a major stakeholder consultation component, to inform and guide the science and to test and refine policy and business outcome.
Chenjie Huang; Y.L. Lin; M.L. Kaplan; Joseph J.J. Charney
2009-01-01
This study has employed both observational data and numerical simulation results to diagnose the synoptic-scale and mesoscale environments conducive to forest fires during the October 2003 extreme fire event in southern California. A three-stage process is proposed to illustrate the coupling of the synoptic-scale forcing that is evident from the observations,...
Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America.
Vörösmarty, Charles J; Bravo de Guenni, Lelys; Wollheim, Wilfred M; Pellerin, Brian; Bjerklie, David; Cardoso, Manoel; D'Almeida, Cassiano; Green, Pamela; Colon, Lilybeth
2013-11-13
Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960-2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.
Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016
NASA Astrophysics Data System (ADS)
Li, Chunxiang; Tian, Qinhua; Yu, Rong; Zhou, Baiquan; Xia, Jiangjiang; Burke, Claire; Dong, Buwen; Tett, Simon F. B.; Freychet, Nicolas; Lott, Fraser; Ciavarella, Andrew
2018-01-01
May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961-2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Niño years have been found to be correlated with extreme rainfall in the Yangtze River region in previous studies—the strong El Niño of 2015-2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south.
Climate change impacts on rainfall extremes and urban drainage: state-of-the-art review
NASA Astrophysics Data System (ADS)
Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van
2013-04-01
Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions; adaptive approach that provides inherent flexibility and reversibility and avoids closing off options; importance of active learning. References: Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012). Impacts of climate change on rainfall extremes and urban drainage. IWA Publishing, 252 p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263 Willems, P., Arnbjerg-Nielsen, K., Olsson, J., Nguyen, V.T.V. (2012), 'Climate change impact assessment on urban rainfall extremes and urban drainage: methods and shortcomings', Atmospheric Research, 103, 106-118
NASA Technical Reports Server (NTRS)
Mckay, Charles W.; Feagin, Terry; Bishop, Peter C.; Hallum, Cecil R.; Freedman, Glenn B.
1987-01-01
The principle focus of one of the RICIS (Research Institute for Computing and Information Systems) components is computer systems and software engineering in-the-large of the lifecycle of large, complex, distributed systems which: (1) evolve incrementally over a long time; (2) contain non-stop components; and (3) must simultaneously satisfy a prioritized balance of mission and safety critical requirements at run time. This focus is extremely important because of the contribution of the scaling direction problem to the current software crisis. The Computer Systems and Software Engineering (CSSE) component addresses the lifestyle issues of three environments: host, integration, and target.
Stable time filtering of strongly unstable spatially extended systems
Grote, Marcus J.; Majda, Andrew J.
2006-01-01
Many contemporary problems in science involve making predictions based on partial observation of extremely complicated spatially extended systems with many degrees of freedom and with physical instabilities on both large and small scale. Various new ensemble filtering strategies have been developed recently for these applications, and new mathematical issues arise. Because ensembles are extremely expensive to generate, one such issue is whether it is possible under appropriate circumstances to take long time steps in an explicit difference scheme and violate the classical Courant–Friedrichs–Lewy (CFL)-stability condition yet obtain stable accurate filtering by using the observations. These issues are explored here both through elementary mathematical theory, which provides simple guidelines, and the detailed study of a prototype model. The prototype model involves an unstable finite difference scheme for a convection–diffusion equation, and it is demonstrated below that appropriate observations can result in stable accurate filtering of this strongly unstable spatially extended system. PMID:16682626
Stable time filtering of strongly unstable spatially extended systems.
Grote, Marcus J; Majda, Andrew J
2006-05-16
Many contemporary problems in science involve making predictions based on partial observation of extremely complicated spatially extended systems with many degrees of freedom and with physical instabilities on both large and small scale. Various new ensemble filtering strategies have been developed recently for these applications, and new mathematical issues arise. Because ensembles are extremely expensive to generate, one such issue is whether it is possible under appropriate circumstances to take long time steps in an explicit difference scheme and violate the classical Courant-Friedrichs-Lewy (CFL)-stability condition yet obtain stable accurate filtering by using the observations. These issues are explored here both through elementary mathematical theory, which provides simple guidelines, and the detailed study of a prototype model. The prototype model involves an unstable finite difference scheme for a convection-diffusion equation, and it is demonstrated below that appropriate observations can result in stable accurate filtering of this strongly unstable spatially extended system.
NASA Astrophysics Data System (ADS)
SUN, N.; Yearsley, J. R.; Lettenmaier, D. P.
2013-12-01
Recent research shows that precipitation extremes in many of the largest U.S. urban areas have increased over the last 60 years. These changes have important implications for stormwater runoff and water quality, which in urban areas are dominated by the most extreme precipitation events. We assess the potential implications of changes in extreme precipitation and changing land cover in urban and urbanizing watersheds at the regional scale using a combination of hydrology and water quality models. Specifically, we describe the integration of a spatially distributed hydrological model - the Distributed Hydrology Soil Vegetation Model (DHSVM), the urban water quality model in EPA's Storm Water Management Model (SWMM), the semi-Lagrangian stream temperature model RBM10, and dynamical and statistical downscaling methods applied to global climate predictions. Key output water quality parameters include total suspended solids (TSS), toal nitrogen, total phosphorous, fecal coliform bacteria and stream temperature. We have evaluated the performance of the modeling system in the highly urbanized Mercer Creek watershed in the rapidly growing Bellevue urban area in WA, USA. The results suggest that the model is able to (1) produce reasonable streamflow predictions at fine temporal and spatial scales; (2) provide spatially distributed water temperature predictions that mostly agree with observations throughout a complex stream network, and characterize impacts of climate, landscape, near-stream vegetation change on stream temperature at local and regional scales; and (3) capture plausibly the response of water quality constituents to varying magnitude of precipitation events in urban environments. Next we will extend the scope of the study from the Mercer Creek watershed to include the entire Puget Sound Basin, WA, USA.
NASA Astrophysics Data System (ADS)
O'Neill, B. C.; Kauffman, B.; Lawrence, P.
2016-12-01
Integrated analysis of questions regarding land, water, and energy resources often requires integration of models of different types. One type of integration is between human and earth system models, since both societal and physical processes influence these resources. For example, human processes such as changes in population, economic conditions, and policies govern the demand for land, water and energy, while the interactions of these resources with physical systems determine their availability and environmental consequences. We have begun to develop and use a toolkit for linking human and earth system models called the Toolbox for Human-Earth System Integration and Scaling (THESIS). THESIS consists of models and software tools to translate, scale, and synthesize information from and between human system models and earth system models (ESMs), with initial application to linking the NCAR integrated assessment model, iPETS, with the NCAR earth system model, CESM. Initial development is focused on urban areas and agriculture, sectors that are both explicitly represented in both CESM and iPETS. Tools are being made available to the community as they are completed (see https://www2.cgd.ucar.edu/sections/tss/iam/THESIS_tools). We discuss four general types of functions that THESIS tools serve (Spatial Distribution, Spatial Properties, Consistency, and Outcome Evaluation). Tools are designed to be modular and can be combined in order to carry out more complex analyses. We illustrate their application to both the exposure of population to climate extremes and to the evaluation of climate impacts on the agriculture sector. For example, projecting exposure to climate extremes involves use of THESIS tools for spatial population, spatial urban land cover, the characteristics of both, and a tool to bring urban climate information together with spatial population information. Development of THESIS tools is continuing and open to the research community.
Large Scale Landslide Database System Established for the Reservoirs in Southern Taiwan
NASA Astrophysics Data System (ADS)
Tsai, Tsai-Tsung; Tsai, Kuang-Jung; Shieh, Chjeng-Lun
2017-04-01
Typhoon Morakot seriously attack southern Taiwan awaken the public awareness of large scale landslide disasters. Large scale landslide disasters produce large quantity of sediment due to negative effects on the operating functions of reservoirs. In order to reduce the risk of these disasters within the study area, the establishment of a database for hazard mitigation / disaster prevention is necessary. Real time data and numerous archives of engineering data, environment information, photo, and video, will not only help people make appropriate decisions, but also bring the biggest concern for people to process and value added. The study tried to define some basic data formats / standards from collected various types of data about these reservoirs and then provide a management platform based on these formats / standards. Meanwhile, in order to satisfy the practicality and convenience, the large scale landslide disasters database system is built both provide and receive information abilities, which user can use this large scale landslide disasters database system on different type of devices. IT technology progressed extreme quick, the most modern system might be out of date anytime. In order to provide long term service, the system reserved the possibility of user define data format /standard and user define system structure. The system established by this study was based on HTML5 standard language, and use the responsive web design technology. This will make user can easily handle and develop this large scale landslide disasters database system.
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.
2013-08-01
enamel paint. Under extreme plastic deformation, the relative deformation of the coating could cause the coating to separate resulting in loss of...point for one to be found. If a discontinuity, such as a crack , occurs through the object separating speckle pattern, then the strain data will only
Runtime Systems for Extreme Scale Platforms
2013-12-01
Programming in Java, PPPJ ’11, (New York, NY, USA), pp. 51–61, ACM, 2011. [76] Y. Guo, R. Barik , R. Raman, and V. Sarkar, “Work-first and help-first...95] R. Barik , J. Zhao, D. Grove, I. Peshansky, Z. Budimlić, and V. Sarkar, “Commu- nication Optimizations for Distributed-Memory X10 Programs,” in
NASA Astrophysics Data System (ADS)
Demir, I.; Sermet, M. Y.
2016-12-01
Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.
NASA Astrophysics Data System (ADS)
Shih, Hong-Yan; Goldenfeld, Nigel
Experiments on transitional turbulence in pipe flow seem to show that turbulence is a transient metastable state since the measured mean lifetime of turbulence puffs does not diverge asymptotically at a critical Reynolds number. Yet measurements reveal that the lifetime scales with Reynolds number in a super-exponential way reminiscent of extreme value statistics, and simulations and experiments in Couette and channel flow exhibit directed percolation type scaling phenomena near a well-defined transition. This universality class arises from the interplay between small-scale turbulence and a large-scale collective zonal flow, which exhibit predator-prey behavior. Why is asymptotically divergent behavior not observed? Using directed percolation and a stochastic individual level model of predator-prey dynamics related to transitional turbulence, we investigate the relation between extreme value statistics and power law critical behavior, and show that the paradox is resolved by carefully defining what is measured in the experiments. We theoretically derive the super-exponential scaling law, and using finite-size scaling, show how the same data can give both super-exponential behavior and power-law critical scaling.
NASA Technical Reports Server (NTRS)
Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin; Bosilovich, Michael G.; Lee, Jaechoul; Wehner, Michael F.; Collow, Allison
2016-01-01
This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC) U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.
NASA Astrophysics Data System (ADS)
Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer
2018-02-01
Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.
NASA Astrophysics Data System (ADS)
Rytuba, J. J.
2015-12-01
An increase in intensity and frequency of extreme events resulting from climate change is expected to result in extreme precipitation events on both regional and local scales. Extreme precipitation events have the potential to mobilize large volumes of mercury (Hg) mine tailings in watersheds where tailings reside in the floodplain downstream from historic Hg mines. The California Hg mineral belt produced one third of the worlds Hg from over 100 mines from the 1850's to 1972. In the absence of environmental regulations, tailings were disposed of into streams adjacent to the mines in order to have them transported from the mine site during storm events. Thus most of the tailings no longer reside at the mine site. Addition of tailings to the streams resulted in stream aggradation, increased over-bank flow, and deposition of tailings in the floodplain for up to 25 kms downstream from the mines. After cessation of mining, the decrease in tailings entering the streams resulted in degradation, incision of the streams into the floodplain, and inability of the streams to access the floodplain. Thus Hg tailings have remained stored in the floodplain since cessation of mining. Hg phases in these tailings consist of cinnabar, metacinnabar and montroydite based on EXAFS analysis. Size analysis indicates that Hg phases are fine grained, less than 1 um. The last regional scale extreme precipitation events to effect the entire area of the California Hg mineral belt were the ARkStorm events of 1861-1862 that occurred prior to large scale Hg mining. Extreme regional ARkStorm precipitation events as well as local summer storms, such as the July 2006 flood in the Clear Creek Hg mining district, are expected to increase in frequency and have the potential to remobilize the large volume of tailings stored in floodplain deposits. Although Hg mine remediation has decreased Hg release from mine sites in a period of benign climate, no remediation efforts have addressed the large source of Hg residing in floodplain deposits. This Hg source in a period of climate change poses a significant environmental risk to aquatic systems downstream from Hg mine-impacted watersheds. An extreme ARkStorm event is estimated to potentially remobilize an amount of Hg equivalent to that released in the past during the peak period of unregulated Hg mining in California.
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…
NASA Astrophysics Data System (ADS)
Schroeer, K.; Kirchengast, G.
2016-12-01
Relating precipitation intensity to temperature is a popular approach to assess potential changes of extreme events in a warming climate. Potential increases in extreme rainfall induced hazards, such as flash flooding, serve as motivation. It has not been addressed whether the temperature-precipitation scaling approach is meaningful on a regional to local level, where the risk of climate and weather impact is dealt with. Substantial variability of temperature sensitivity of extreme precipitation has been found that results from differing methodological assumptions as well as from varying climatological settings of the study domains. Two aspects are consistently found: First, temperature sensitivities beyond the expected consistency with the Clausius-Clapeyron (CC) equation are a feature of short-duration, convective, sub-daily to sub-hourly high-percentile rainfall intensities at mid-latitudes. Second, exponential growth ceases or reverts at threshold temperatures that vary from region to region, as moisture supply becomes limited. Analyses of pooled data, or of single or dispersed stations over large areas make it difficult to estimate the consequences in terms of local climate risk. In this study we test the meaningfulness of the scaling approach from an impact scale perspective. Temperature sensitivities are assessed using quantile regression on hourly and sub-hourly precipitation data from 189 stations in the Austrian south-eastern Alpine region. The observed scaling rates vary substantially, but distinct regional and seasonal patterns emerge. High sensitivity exceeding CC-scaling is seen on the 10-minute scale more than on the hourly scale, in storms shorter than 2 hours duration, and in shoulder seasons, but it is not necessarily a significant feature of the extremes. To be impact relevant, change rates need to be linked to absolute rainfall amounts. We show that high scaling rates occur in lower temperature conditions and thus have smaller effect on absolute precipitation intensities. While reporting of mere percentage numbers can be misleading, scaling studies can add value to process understanding on the local scale, if the factors that influence scaling rates are considered from both a methodological and a physical perspective.
NASA Astrophysics Data System (ADS)
Rodríguez, Estiven; Salazar, Juan Fernando; Villegas, Juan Camilo; Mercado-Bettín, Daniel
2018-07-01
Extreme flows are key components of river flow regimes that affect manifold hydrological, geomorphological and ecological processes with societal relevance. One fundamental characteristic of extreme flows in river basins is that they exhibit scaling properties which can be identified through scaling (power) laws. Understanding the physical mechanisms behind such scaling laws is a continuing challenge in hydrology, with potential implications for the prediction of river flow regimes in a changing environment and ungauged basins. After highlighting that the scaling properties are sensitive to environmental change, we develop a physical interpretation of how temporal changes in scaling exponents relate to the capacity of river basins to regulate extreme river flows. Regulation is defined here as the basins' capacity to either dampen high flows or to enhance low flows. Further, we use this framework to infer temporal changes in the regulation capacity of five large basins in tropical South America. Our results indicate that, during the last few decades, the Amazon river basin has been reducing its capacity to enhance low flows, likely as a consequence of pronounced environmental change in its south and south-eastern sub-basins. The proposed framework is widely applicable to different basins, and provides foundations for using scaling laws as empirical tools for inferring temporal changes of hydrological regulation, particularly relevant for identifying and managing hydrological consequences of environmental change.
Versatile, High Quality and Scalable Continuous Flow Production of Metal-Organic Frameworks
Rubio-Martinez, Marta; Batten, Michael P.; Polyzos, Anastasios; Carey, Keri-Constanti; Mardel, James I.; Lim, Kok-Seng; Hill, Matthew R.
2014-01-01
Further deployment of Metal-Organic Frameworks in applied settings requires their ready preparation at scale. Expansion of typical batch processes can lead to unsuccessful or low quality synthesis for some systems. Here we report how continuous flow chemistry can be adapted as a versatile route to a range of MOFs, by emulating conditions of lab-scale batch synthesis. This delivers ready synthesis of three different MOFs, with surface areas that closely match theoretical maxima, with production rates of 60 g/h at extremely high space-time yields. PMID:24962145
Impact of the topology of global macroeconomic network on the spreading of economic crises.
Lee, Kyu-Min; Yang, Jae-Suk; Kim, Gunn; Lee, Jaesung; Goh, Kwang-Il; Kim, In-mook
2011-03-31
Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more "globalized" random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises.
Impact of the Topology of Global Macroeconomic Network on the Spreading of Economic Crises
Lee, Kyu-Min; Yang, Jae-Suk; Kim, Gunn; Lee, Jaesung; Goh, Kwang-Il; Kim, In-mook
2011-01-01
Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more “globalized” random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises. PMID:21483794
Downwind pre-aligned rotors for extreme-scale wind turbines
Loth, Eric; Steele, Adam; Qin, Chao; ...
2017-03-08
Downwind force angles are small for current turbines systems (1-5 MW) such that they may be readily accommodated by conventional upwind configurations. However, analysis indicates that extreme-scale systems (10-20 MW) will have larger angles that may benefit from downwind-aligned configurations. To examine potential rotor mass reduction, the pre-alignment concept was investigated a two-bladed configuration by keeping the structural and aerodynamic characteristics of each blade fixed (to avoids a complete blade re-design). Simulations for a 13.2 MW rated rotor at steady-state conditions show that this concept-level two-bladed design may yield 25% rotor mass savings while also reducing average blade stress overmore » all wind speeds. These results employed a pre-alignment on the basis of a wind speed of 1.25 times the rated wind speed. The downwind pre-aligned concept may also reduce damage equivalent loads on the blades by 60% for steady rated wind conditions. Even higher mass and damage equivalent load savings (relative to conventional upwind designs) may be possible for larger systems (15-20 MW) for which load-alignment angles become even larger. Furthermore, much more work is needed to determine whether this concept can be translated into a practical design that must meet a wide myriad of other criteria.« less
Downwind pre-aligned rotors for extreme-scale wind turbines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Loth, Eric; Steele, Adam; Qin, Chao
Downwind force angles are small for current turbines systems (1-5 MW) such that they may be readily accommodated by conventional upwind configurations. However, analysis indicates that extreme-scale systems (10-20 MW) will have larger angles that may benefit from downwind-aligned configurations. To examine potential rotor mass reduction, the pre-alignment concept was investigated a two-bladed configuration by keeping the structural and aerodynamic characteristics of each blade fixed (to avoids a complete blade re-design). Simulations for a 13.2 MW rated rotor at steady-state conditions show that this concept-level two-bladed design may yield 25% rotor mass savings while also reducing average blade stress overmore » all wind speeds. These results employed a pre-alignment on the basis of a wind speed of 1.25 times the rated wind speed. The downwind pre-aligned concept may also reduce damage equivalent loads on the blades by 60% for steady rated wind conditions. Even higher mass and damage equivalent load savings (relative to conventional upwind designs) may be possible for larger systems (15-20 MW) for which load-alignment angles become even larger. Furthermore, much more work is needed to determine whether this concept can be translated into a practical design that must meet a wide myriad of other criteria.« less
NASA Astrophysics Data System (ADS)
Rosendahl, D. H.; Ćwik, P.; Martin, E. R.; Basara, J. B.; Brooks, H. E.; Furtado, J. C.; Homeyer, C. R.; Lazrus, H.; Mcpherson, R. A.; Mullens, E.; Richman, M. B.; Robinson-Cook, A.
2017-12-01
Extreme precipitation events cause significant damage to homes, businesses, infrastructure, and agriculture, as well as many injures and fatalities as a result of fast-moving water or waterborne diseases. In the USA, these natural hazard events claimed the lives of more than 300 people during 2015 - 2016 alone, with total damage reaching $24.4 billion. Prior studies of extreme precipitation events have focused on the sub-daily to sub-weekly timeframes. However, many decisions for planning, preparing and resilience-building require sub-seasonal to seasonal timeframes (S2S; 14 to 90 days), but adequate forecasting tools for prediction do not exist. Therefore, the goal of this newly funded project is an enhancement in understanding of the large-scale forcing and dynamics of S2S extreme precipitation events in the United States, and improved capability for modeling and predicting such events. Here, we describe the project goals, objectives, and research activities that will take place over the next 5 years. In this project, a unique team of scientists and stakeholders will identify and understand weather and climate processes connected with the prediction of S2S extreme precipitation events by answering these research questions: 1) What are the synoptic patterns associated with, and characteristic of, S2S extreme precipitation evens in the contiguous U.S.? 2) What role, if any, do large-scale modes of climate variability play in modulating these events? 3) How predictable are S2S extreme precipitation events across temporal scales? 4) How do we create an informative prediction of S2S extreme precipitation events for policymaking and planing? This project will use observational data, high-resolution radar composites, dynamical climate models and workshops that engage stakeholders (water resource managers, emergency managers and tribal environmental professionals) in co-production of knowledge. The overarching result of this project will be predictive models to reduce of the societal and economic impacts of extreme precipitation events. Another outcome will include statistical and co-production frameworks, which could be applied across other meteorological extremes, all time scales and in other parts of the world to increase resilience to extreme meteorological events.
A Fault-Oblivious Extreme-Scale Execution Environment (FOX)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van Hensbergen, Eric; Speight, William; Xenidis, Jimi
IBM Research’s contribution to the Fault Oblivious Extreme-scale Execution Environment (FOX) revolved around three core research deliverables: • collaboration with Boston University around the Kittyhawk cloud infrastructure which both enabled a development and deployment platform for the project team and provided a fault-injection testbed to evaluate prototypes • operating systems research focused on exploring role-based operating system technologies through collaboration with Sandia National Labs on the NIX research operating system and collaboration with the broader IBM Research community around a hybrid operating system model which became known as FusedOS • IBM Research also participated in an advisory capacity with themore » Boston University SESA project, the core of which was derived from the K42 operating system research project funded in part by DARPA’s HPCS program. Both of these contributions were built on a foundation of previous operating systems research funding by the Department of Energy’s FastOS Program. Through the course of the X-stack funding we were able to develop prototypes, deploy them on production clusters at scale, and make them available to other researchers. As newer hardware, in the form of BlueGene/Q, came online, we were able to port the prototypes to the new hardware and release the source code for the resulting prototypes as open source to the community. In addition to the open source coded for the Kittyhawk and NIX prototypes, we were able to bring the BlueGene/Q Linux patches up to a more recent kernel and contribute them for inclusion by the broader Linux community. The lasting impact of the IBM Research work on FOX can be seen in its effect on the shift of IBM’s approach to HPC operating systems from Linux and Compute Node Kernels to role-based approaches as prototyped by the NIX and FusedOS work. This impact can be seen beyond IBM in follow-on ideas being incorporated into the proposals for the Exasacale Operating Systems/Runtime program.« less
NASA Astrophysics Data System (ADS)
Knist, Sebastian; Goergen, Klaus; Simmer, Clemens
2018-02-01
We perform simulations with the WRF regional climate model at 12 and 3 km grid resolution for the current and future climates over Central Europe and evaluate their added value with a focus on the daily cycle and frequency distribution of rainfall and the relation between extreme precipitation and air temperature. First, a 9 year period of ERA-Interim driven simulations is evaluated against observations; then global climate model runs (MPI-ESM-LR RCP4.5 scenario) are downscaled and analyzed for three 12-year periods: a control, a mid-of-century and an end-of-century projection. The higher resolution simulations reproduce both the diurnal cycle and the hourly intensity distribution of precipitation more realistically compared to the 12 km simulation. Moreover, the observed increase of the temperature-extreme precipitation scaling from the Clausius-Clapeyron (C-C) scaling rate of 7% K-1 to a super-adiabatic scaling rate for temperatures above 11 °C is reproduced only by the 3 km simulation. The drop of the scaling rates at high temperatures under moisture limited conditions differs between sub-regions. For both future scenario time spans both simulations suggest a slight decrease in mean summer precipitation and an increase in hourly heavy and extreme precipitation. This increase is stronger in the 3 km runs. Temperature-extreme precipitation scaling curves in the future climate are projected to shift along the 7% K-1 trajectory to higher peak extreme precipitation values at higher temperatures. The curves keep their typical shape of C-C scaling followed by super-adiabatic scaling and a drop-off at higher temperatures due to moisture limitation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Gang
Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very widemore » range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chow, Edmond
Solving sparse problems is at the core of many DOE computational science applications. We focus on the challenge of developing sparse algorithms that can fully exploit the parallelism in extreme-scale computing systems, in particular systems with massive numbers of cores per node. Our approach is to express a sparse matrix factorization as a large number of bilinear constraint equations, and then solving these equations via an asynchronous iterative method. The unknowns in these equations are the matrix entries of the factorization that is desired.
Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B.; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali
2017-01-01
The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications. PMID:28545077
Andreadis, Konstantinos M; Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali
2017-01-01
The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications.
Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States
NASA Technical Reports Server (NTRS)
Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.
2014-01-01
In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.
Predictors of Upper-Extremity Physical Function in Older Adults.
Hermanussen, Hugo H; Menendez, Mariano E; Chen, Neal C; Ring, David; Vranceanu, Ana-Maria
2016-10-01
Little is known about the influence of habitual participation in physical exercise and diet on upper-extremity physical function in older adults. To assess the relationship of general physical exercise and diet to upper-extremity physical function and pain intensity in older adults. A cohort of 111 patients 50 or older completed a sociodemographic survey, the Rapid Assessment of Physical Activity (RAPA), an 11-point ordinal pain intensity scale, a Mediterranean diet questionnaire, and three Patient- Reported Outcomes Measurement Information System (PROMIS) based questionnaires: Pain Interference to measure inability to engage in activities due to pain, Upper-Extremity Physical Function, and Depression. Multivariable linear regression modeling was used to characterize the association of physical activity, diet, depression, and pain interference to pain intensity and upper-extremity function. Higher general physical activity was associated with higher PROMIS Upper-Extremity Physical Function and lower pain intensity in bivariate analyses. Adherence to the Mediterranean diet did not correlate with PROMIS Upper-Extremity Physical Function or pain intensity in bivariate analysis. In multivariable analyses factors associated with higher PROMIS Upper-Extremity Physical Function were male sex, non-traumatic diagnosis and PROMIS Pain Interference, with the latter accounting for most of the observed variability (37%). Factors associated with greater pain intensity in multivariable analyses included fewer years of education and higher PROMIS Pain Interference. General physical activity and diet do not seem to be as strongly or directly associated with upper-extremity physical function as pain interference.
NASA Astrophysics Data System (ADS)
Matsui, T.; Mocko, D. M.
2015-12-01
We examine radar-gauge merged 1/8-degree hourly precipitation data from the North American Land Data Assimilation System (NLDAS) Phase-II datasets from 1997 to 2013. For each 1/8 grid, we derived statistics of single-event storm duration, total accumulated precipitation, and dry period between each storm events during cold (Oct-Mar) seasons, and histogram of event-by-event statistics are used to estimate the thresholds for extreme (below-1%) and very extreme (below-0.1%) events. In this way, we constructed unique climatology maps of the extreme precipitation-drought frequencies and probability density functions. This climatology map depicted that cold-season extremely heavy precipitation events are populated over West Coast, Deep South, and coastal zone of North East, suggesting impacts of land-falling maritime storm systems. Simultaneously, datasets depicts that long-extended precipitation events are mostly populated over North West, and lower Mississippi Basin up to North East centered at Appalachian Mountains, resembling east Pacific storm tracks and nor'easter storm tracks, respectively. Furthermore, season-by-season statistics of these extreme events were examined for each National Climate Assessment (NCA) regimes in comparison with a number of major atmospheric oscillations and teleconnection patterns as well as Arctic Amplifications. Index of Arctic Amplification includes variability of 500mb zonal wind speed and pole-to-midlatitude differences in atmospheric thickness, linking to the phase speed of the Rossby wave. Finally, we present ensemble correlations scores, and discuss the physical processes and underlying mechanisms for their key characteristics as well as the predictive skill and predictability of the extreme events from sub-seasonal to interannual scales during cold seasons.
Eco-friendly Energy Storage System: Seawater and Ionic Liquid Electrolyte.
Kim, Jae-Kwang; Mueller, Franziska; Kim, Hyojin; Jeong, Sangsik; Park, Jeong-Sun; Passerini, Stefano; Kim, Youngsik
2016-01-08
As existing battery technologies struggle to meet the requirements for widespread use in the field of large-scale energy storage, novel concepts are urgently needed concerning batteries that have high energy densities, low costs, and high levels of safety. Here, a novel eco-friendly energy storage system (ESS) using seawater and an ionic liquid is proposed for the first time; this represents an intermediate system between a battery and a fuel cell, and is accordingly referred to as a hybrid rechargeable cell. Compared to conventional organic electrolytes, the ionic liquid electrolyte significantly enhances the cycle performance of the seawater hybrid rechargeable system, acting as a very stable interface layer between the Sn-C (Na storage) anode and the NASICON (Na3 Zr2 Si2 PO12) ceramic solid electrolyte, making this system extremely promising for cost-efficient and environmentally friendly large-scale energy storage. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Extreme Geohazards: Reducing Disaster Risk and Increasing Resilience
NASA Astrophysics Data System (ADS)
Plag, Hans-Peter; Stein, Seth; Brocklebank, Sean; Jules-Plag, Shelley; Campus, Paola
2014-05-01
Extreme natural hazards have the potential to cause global disasters and to lead to an escalation of the global sustainability crisis. Floods and droughts pose threats that could reach planetary extent, particularly through secondary economic and social impacts. Earthquakes and tsunamis cause disasters that could exceed the immediate coping capacity of the global economy, particularly in hazardous areas containing megacities, that can be particularly vulnerable to natural hazards if proper emergency protocols and infrastructures are not set in place. Recent events illustrate the destruction extreme hazards can inflict, both directly and indirectly, through domino effects resulting from the interaction with the built environment. Unfortunately, the more humanity learns to cope with relatively frequent (50 to 100 years) natural hazard events, the less concerns remain about the low-probability (one in a few hundred or more years) high-impact events. As a consequence, threats from low-probability extreme floods, droughts, and volcanic eruptions are not appropriately accounted for in Disaster Risk Reduction (DRR) discussions. With the support of the European Science Foundation (ESF), the Geohazards Community of Practice (GHCP) of the Group on Earth Observations (GEO) has developed a White Paper (WP) on the risk associated with low-probability, high-impact geohazards. These events are insufficiently addressed in risk management, although their potential impacts are comparable to those of a large asteroid impact, a global pandemic, or an extreme drought. The WP aims to increase awareness of the risk associated with these events as a basis for a comprehensive risk management. Extreme geohazards have occurred regularly throughout the past, but mostly did not cause major disasters because the exposure of human assets to such hazards and the global population density were much lower than today. The most extreme events during the last 2,000 years would cause today unparalleled damage on a global scale for a globally connected and stressed society. In particular, large volcanic eruptions could impact climate, damage anthropogenic infrastructure and interrupt resource supplies on a global scale. The occurrence of one or more of the largest volcanic eruptions that took place during the last 2,000 years under today's conditions would likely cause global disasters or catastrophes challenging civilization. Integration of these low-probability, high-impact events in DRR requires an approach focused on resilience and antifragility, as well as the ability to cope with, and recover from failure of infrastructures and social systems. Resilience results from social capital even more than from the robustness of infrastructure. While it is important to understand the hazards through the contribution of geosciences, it is equally important to understand through the contribution of social sciences and engineering the societal processes involved with coping with hazards or leading to failure. For comprehensive development of resilience to natural hazards and, in particular, extreme geohazards, synergy between geosciences, engineering and social sciences, jointed to an improved science-policy relationship is key to success. For example, a simple cost-benefit analysis shows that a comprehensive monitoring system that could identify the onset of an extreme volcanic eruption with sufficient lead time to allow for a globally coordinated preparation makes economic sense. The WP recommends implementation of such a monitoring system with global coverage, assesses the existing assets in current monitoring systems, and illustrates many benefits, besides providing early warning for extreme volcanic eruptions. However, such a monitoring system can provide resilience only via the capability of the global community to react to early warnings. The WP recommends achieving this through the establishment of a global coordination platform comparable to IPCC's role in addressing climate-change related issues to assess knowledge and related adaptive capabilities for disasters due to extreme geohazards.
NASA Astrophysics Data System (ADS)
Lindsey, Rebecca; Goldman, Nir; Fried, Laurence
Understanding chemistry at extreme conditions is crucial in fields including geochemistry, astrobiology, and alternative energy. First principles methods can provide valuable microscopic insights into such systems while circumventing the risks of physical experiments, however the time and length scales associated with chemistry at extreme conditions (ns and μm, respectively) largely preclude extension of such models to molecular dynamics. In this work, we develop a simulation approach that retains the accuracy of density functional theory (DFT) while decreasing computational effort by several orders of magnitude. We generate n-body descriptions for atomic interactions by mapping forces arising from short density functional theory (DFT) trajectories on to simple Chebyshev polynomial series. We examine the importance of including greater than 2-body interactions, model transferability to different state points, and discuss approaches to ensure smooth and reasonable model shape outside of the distance domain sampled by the DFT training set. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
The analysis of dependence between extreme rainfall and storm surge in the coastal zone
NASA Astrophysics Data System (ADS)
Zheng, F.; Westra, S.
2012-12-01
Flooding in coastal catchments can be caused by runoff generated by an extreme rainfall event, elevated sea levels due to an extreme storm surge event, or the combination of both processes occurring simultaneously or in close succession. Dependence in extreme rainfall and storm surge arises because common meteorological forcings often drive both variables; for example, cyclonic systems may produce extreme rainfall, strong onshore winds and an inverse barometric effect simultaneously, which the former factor influencing catchment discharge and the latter two factors influencing storm surge. Nevertheless there is also the possibility that only one of the variables is extreme at any given time, so that the dependence between rainfall and storm surge is not perfect. Quantification of the strength of dependence between these processes is critical in evaluating the magnitude of flood risk in the coastal zone. This may become more important in the future as the majority of the coastal areas are threatened by the sea level rise due to the climate change. This research uses the most comprehensive record of rainfall and storm surge along the coastline of Australia collected to-date to investigate the strength of dependence between the extreme rainfall and storm surge along the Australia coastline. A bivariate logistic threshold-excess model was employed to this end to carry out the dependence analysis. The strength of the estimated dependence is then evaluated as a function of several factors including: the distance between the tidal gauge and the rain gauge; the lag between the extreme precipitation event and extreme surge event; and the duration of the maximum storm burst. The results show that the dependence between the extreme rainfall and storm surge along the Australia coastline is statistically significant, although some locations clearly exhibit stronger dependence than others. We hypothesize that this is due to a combination of large-scale meteorological effects as well as local scale bathymetry. Additionally, significant dependence can be observed over spatial distances of up to several hundred kilometers, implying that meso-scale meteorological forcings may play an important role in driving the dependence. This is also consistent with the result which shows that significant dependence often remaining for lags of up to one or two days between extremal rainfall and storm surge events. The influence of storm burst duration can also be observed, with rainfall extremes lasting more than several hours typically being more closely associated with storm surge compared with sub-hourly rainfall extremes. These results will have profound implications for how flood risk is evaluated along the coastal zone in Australia, with the strength of dependence varying depending on: (1) the dominant meteorological conditions; (2) the local estuary configuration, influencing the strength of the surge; and (3) the catchment attributes, influencing the duration of the storm burst that will deliver the peak flood events. Although a strong random component remains, we show that the probability of an extreme storm surge during an extreme rainfall event (or vice versa) can be up to ten times greater than under the situation under which there is no dependence, suggesting that failure to account for these interactions can result in a substantial underestimation of flood risk.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mishchenko, L; Khan, M; Aizenberg, J
Certain natural organisms use micro-patterned surface chemistry, or ice-nucleating species, to control water condensation and ice nucleation for survival under extreme conditions. As an analogy to these biological approaches, it is shown that functionalized, hydrophilic polymers and particles deposited on the tips of superhydrophobic posts induce precise topographical control over water condensation and freezing at the micrometer scale. A bottom-up deposition process is used to take advantage of the limited contact area of a non-wetting aqueous solution on a superhydrophobic surface. Hydrophilic polymer deposition on the tips of these geometrical structures allows spatial control over the nucleation, growth, and coalescencemore » of micrometer-scale water droplets. The hydrophilic tips nucleate water droplets with extremely uniform nucleation and growth rates, uniform sizes, an increased stability against coalescence, and asymmetric droplet morphologies. Control of freezing behavior is also demonstrated via deposition of ice-nucleating AgI nanoparticles on the tips of these structures. This combination of the hydrophilic polymer and AgI particles on the tips was used to achieve templating of ice nucleation at the micrometer scale. Preliminary results indicate that control over ice crystal size, spatial symmetry, and position might be possible with this method. This type of approach can serve as a platform for systematically analyzing micrometer-scale condensation and freezing phenomena, and as a model for natural systems.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mishchenko, Lidiya; Khan, M.; Aizenberg, Joanna
Certain natural organisms use micro-patterned surface chemistry, or ice-nucleating species, to control water condensation and ice nucleation for survival under extreme conditions. As an analogy to these biological approaches, it is shown that functionalized, hydrophilic polymers and particles deposited on the tips of superhydrophobic posts induce precise topographical control over water condensation and freezing at the micrometer scale. A bottom-up deposition process is used to take advantage of the limited contact area of a non-wetting aqueous solution on a superhydrophobic surface. Hydrophilic polymer deposition on the tips of these geometrical structures allows spatial control over the nucleation, growth, and coalescencemore » of micrometer-scale water droplets. The hydrophilic tips nucleate water droplets with extremely uniform nucleation and growth rates, uniform sizes, an increased stability against coalescence, and asymmetric droplet morphologies. Furthermore, control of freezing behavior is also demonstrated via deposition of ice-nucleating AgI nanoparticles on the tips of these structures. The combination of the hydrophilic polymer and AgI particles on the tips was used to achieve templating of ice nucleation at the micrometer scale. Preliminary results indicate that control over ice crystal size, spatial symmetry, and position might be possible with this method. This type of approach can serve as a platform for systematically analyzing micrometer-scale condensation and freezing phenomena, and as a model for natural systems.« less
Page, Stephen J; Hill, Valerie; White, Susan
2013-06-01
To compare the efficacy of a repetitive task-specific practice regimen integrating a portable, electromyography-controlled brace called the 'Myomo' versus usual care repetitive task-specific practice in subjects with chronic, moderate upper extremity impairment. Sixteen subjects (7 males; mean age 57.0 ± 11.02 years; mean time post stroke 75.0 ± 87.63 months; 5 left-sided strokes) exhibiting chronic, stable, moderate upper extremity impairment. Subjects were administered repetitive task-specific practice in which they participated in valued, functional tasks using their paretic upper extremities. Both groups were supervised by a therapist and were administered therapy targeting their paretic upper extremities that was 30 minutes in duration, occurring 3 days/week for eight weeks. One group participated in repetitive task-specific practice entirely while wearing the portable robotic, while the other performed the same activity regimen manually. The upper extremity Fugl-Meyer, Canadian Occupational Performance Measure and Stroke Impact Scale were administered on two occasions before intervention and once after intervention. After intervention, groups exhibited nearly identical Fugl-Meyer score increases of ≈2.1 points; the group using robotics exhibited larger score changes on all but one of the Canadian Occupational Performance Measure and Stroke Impact Scale subscales, including a 12.5-point increase on the Stroke Impact Scale recovery subscale. Findings suggest that therapist-supervised repetitive task-specific practice integrating robotics is as efficacious as manual practice in subjects with moderate upper extremity impairment.
(Almost) Dark Galaxies in the ALFALFA Survey: HI-bearing Ultra-Diffuse Galaxies, and Beyond
NASA Astrophysics Data System (ADS)
Leisman, Luke; Haynes, Martha P.; Giovanelli, Riccardo; ALFALFA Almost Darks Team
2017-01-01
Scaling relations between HI and stars in galaxies suggest strong ties between their atomic gas content and star formation laws. The Arecibo Legacy Fast ALFA (ALFALFA) blind extragalactic HI survey is well positioned to locate very low surface brightness sources that lie off these relations, the most extreme of which may fall below optical detection limits. Thus, the ALFALFA (Almost) Darks Project has been investigating extreme outliers from these relations by studying the ~1% of ALFALFA sources without apparent stellar counterparts in major optical surveys. We have obtained deep HI and optical imaging of 25 of these candidate "dark" sources. We find that most "dark" sources are not extreme "(almost) dark" galaxies. A few are rare OH Megamasers, redshifted into the ALFALFA bandpass, and many are part of large galactic plumes, stretching as far as 600 kpc from their host galaxy. However, a small handful of sources appear to be galaxies with extreme stellar systems. We find multiple systems with HI mass to stellar mass ratios an order of magnitude larger than typical gas rich dwarfs. Further, we find an isolated population of HI-bearing "ultra diffuse" galaxies (UDGs), with stellar masses of dwarfs, but HI and optical radii of L* galaxies. We suggest that these sources may be related to recently reported gas poor, quiescent UDGs.
Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model
NASA Astrophysics Data System (ADS)
O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.
2015-12-01
Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.
A Unified Data-Driven Approach for Programming In Situ Analysis and Visualization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aiken, Alex
The placement and movement of data is becoming the key limiting factor on both performance and energy efficiency of high performance computations. As systems generate more data, it is becoming increasingly difficult to actually move that data elsewhere for post-processing, as the rate of improvements in supporting I/O infrastructure is not keeping pace. Together, these trends are creating a shift in how we think about exascale computations, from a viewpoint that focuses on FLOPS to one that focuses on data and data-centric operations as fundamental to the reasoning about, and optimization of, scientific workflows on extreme-scale architectures. The overarching goalmore » of our effort was the study of a unified data-driven approach for programming applications and in situ analysis and visualization. Our work was to understand the interplay between data-centric programming model requirements at extreme-scale and the overall impact of those requirements on the design, capabilities, flexibility, and implementation details for both applications and the supporting in situ infrastructure. In this context, we made many improvements to the Legion programming system (one of the leading data-centric models today) and demonstrated in situ analyses on real application codes using these improvements.« less
Managing the Nation's water in a changing climate
Lins, H.F.; Stakhiv, E.Z.
1998-01-01
Among the many concerns associated with global climate change, the potential effects on water resources are frequently cited as the most worrisome. In contrast, those who manage water resources do not rate climatic change among their top planning and operational concerns. The difference in these views can be associated with how water managers operate their systems and the types of stresses, and the operative time horizons, that affect the Nation's water resources infrastructure. Climate, or more precisely weather, is an important variable in the management of water resources at daily to monthly time scales because water resources systems generally are operated on a daily basis. At decadal to centennial time scales, though, climate is much less important because (1) forecasts, particularly of regional precipitation, are extremely uncertain over such time periods, and (2) the magnitude of effects due to changes in climate on water resources is small relative to changes in other variables such as population, technology, economics, and environmental regulation. Thus, water management agencies find it difficult to justify changing design features or operating rules on the basis of simulated climatic change at the present time, especially given that reservoir-design criteria incorporate considerable buffering capacity for extreme meteorological and hydrological events.
A centennial tribute to G.K. Gilbert's Hydraulic Mining Débris in the Sierra Nevada
NASA Astrophysics Data System (ADS)
James, L. A.; Phillips, J. D.; Lecce, S. A.
2017-10-01
G.K. Gilbert's (1917) classic monograph, Hydraulic-Mining Débris in the Sierra Nevada, is described and put into the context of modern geomorphic knowledge. The emphasis here is on large-scale applied fluvial geomorphology, but other key elements-e.g., coastal geomorphology-are also briefly covered. A brief synopsis outlines key elements of the monograph, followed by discussions of highly influential aspects including the integrated watershed perspective, the extreme example of anthropogenic sedimentation, computation of a quantitative, semidistributed sediment budget, and advent of sediment-wave theory. Although Gilbert did not address concepts of equilibrium and grade in much detail, the rivers of the northwestern Sierra Nevada were highly disrupted and thrown into a condition of nonequilibrium. Therefore, concepts of equilibrium and grade-for which Gilbert's early work is often cited-are discussed. Gilbert's work is put into the context of complex nonlinear dynamics in geomorphic systems and how these concepts can be used to interpret the nonequilibrium systems described by Gilbert. Broad, basin-scale studies were common in the period, but few were as quantitative and empirically rigorous or employed such a range of methodologies as PP105. None demonstrated such an extreme case of anthropogeomorphic change.
Moore, Ernest E; Moore, Frederick A
2010-12-01
The purpose of a scaling system for specific injuries is to provide a common language to facilitate the clinical decisions and the investigative basis for this decision making. This brief overview describes the evolution of the Organ Injury Scaling (OIS) system developed by the American Association for the Surgery of Trauma. The OIS system is based on the magnitude of anatomic disruption and is graded as 1 (minimal), 2 (mild), 3 (moderate), 4 (severe), 5 (massive), and 6 (lethal). To date, the American Association for the Surgery of Trauma OIS system has been developed for visceral and vascular injuries of the neck, chest, abdomen, and extremities. The fundamental objective of OIS is to provide a common language to describe specific organ injuries. The primary purpose of OIS is to facilitate clinical decision making and the necessary research endeavors to improve this process. A good example of this concept is the tumor, node, metastasis classification for solid organ malignancies: a system used worldwide to guide patient care and clinical investigation.
Asymmetric noise-induced large fluctuations in coupled systems
NASA Astrophysics Data System (ADS)
Schwartz, Ira B.; Szwaykowska, Klimka; Carr, Thomas W.
2017-10-01
Networks of interacting, communicating subsystems are common in many fields, from ecology, biology, and epidemiology to engineering and robotics. In the presence of noise and uncertainty, interactions between the individual components can lead to unexpected complex system-wide behaviors. In this paper, we consider a generic model of two weakly coupled dynamical systems, and we show how noise in one part of the system is transmitted through the coupling interface. Working synergistically with the coupling, the noise on one system drives a large fluctuation in the other, even when there is no noise in the second system. Moreover, the large fluctuation happens while the first system exhibits only small random oscillations. Uncertainty effects are quantified by showing how characteristic time scales of noise-induced switching scale as a function of the coupling between the two coupled parts of the experiment. In addition, our results show that the probability of switching in the noise-free system scales inversely as the square of reduced noise intensity amplitude, rendering the virtual probability of switching an extremely rare event. Our results showing the interplay between transmitted noise and coupling are also confirmed through simulations, which agree quite well with analytic theory.
NASA Astrophysics Data System (ADS)
Tecza, Matthias; Thatte, Niranjan; Clarke, Fraser; Lynn, James; Freeman, David; Roberts, Jennifer; Dekany, Richard
2012-09-01
When commissioned in November 2008 at the Palomar 200 inch Hale Telescope, the Oxford SWIFT I and z band integral field spectrograph, fed by the adaptive optics system PALAO, provided a wide (3×) range of spatial resolutions: three plate scales of 235 mas, 160 mas, and 80 mas per spaxel over a contiguous field-of-view of 89×44 pixels. Depending on observing conditions and guide star brightness we can choose a seeing limited scale of 235 mas per spaxel, or 160 mas and 80 mas per spaxel for very bright guide star AO with substantial increase of enclosed energy. Over the last two years PALAO was upgraded to PALM-3000: an extreme, high-order adaptive optics system with two deformable mirrors with more than 3000 actuators, promising diffraction limited performance in SWIFT's wavelength range. In order to take advantage of this increased spatial resolution we upgraded SWIFT with new pre-optics allowing us to spatially Nyquist sample the diffraction limited PALM-3000 point spread function with 16 mas resolution, reducing the spaxel scale by another factor of 5×. We designed, manufactured, integrated and tested the new pre-optics in the first half of 2011 and commissioned it in December 2011. Here we present the opto-mechanical design and assembly of the new scale changing optics, as well as laboratory and on-sky commissioning results. In optimal observing conditions we achieve substantial Strehl ratios, delivering the near diffraction limited spatial resolution in the I and z bands.
The NASA Energy and Water Cycle Extreme (NEWSE) Integration Project
NASA Technical Reports Server (NTRS)
House, P. R.; Lapenta, W.; Schiffer, R.
2008-01-01
Skillful predictions of water and energy cycle extremes (flood and drought) are elusive. To better understand the mechanisms responsible for water and energy extremes, and to make decisive progress in predicting these extremes, the collaborative NASA Energy and Water cycle Extremes (NEWSE) Integration Project, is studying these extremes in the U.S. Southern Great Plains (SGP) during 2006-2007, including their relationships with continental and global scale processes, and assessment of their predictability on multiple space and time scales. It is our hypothesis that an integrative analysis of observed extremes which reflects the current understanding of the role of SST and soil moisture variability influences on atmospheric heating and forcing of planetary waves, incorporating recently available global and regional hydro- meteorological datasets (i.e., precipitation, water vapor, clouds, etc.) in conjunction with advances in data assimilation, can lead to new insights into the factors that lead to persistent drought and flooding. We will show initial results of this project, whose goals are to provide an improved definition, attribution and prediction on sub-seasonal to interannual time scales, improved understanding of the mechanisms of decadal drought and its predictability, including the impacts of SST variability and deep soil moisture variability, and improved monitoring/attributions, with transition to applications; a bridging of the gap between hydrological forecasts and stakeholders (utilization of probabilistic forecasts, education, forecast interpretation for different sectors, assessment of uncertainties for different sectors, etc.).
Trends in mean and extreme temperatures over Ibadan, Southwest Nigeria
NASA Astrophysics Data System (ADS)
Abatan, Abayomi A.; Osayomi, Tolulope; Akande, Samuel O.; Abiodun, Babatunde J.; Gutowski, William J.
2018-02-01
In recent times, Ibadan has been experiencing an increase in mean temperature which appears to be linked to anthropogenic global warming. Previous studies have indicated that the warming may be accompanied by changes in extreme events. This study examined trends in mean and extreme temperatures over Ibadan during 1971-2012 at annual and seasonal scales using the high-resolution atmospheric reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) twentieth-century dataset (ERA-20C) at 15 grid points. Magnitudes of linear trends in mean and extreme temperatures and their statistical significance were calculated using ordinary least squares and Mann-Kendall rank statistic tests. The results show that Ibadan has witnessed an increase in annual and seasonal mean minimum temperatures. The annual mean maximum temperature exhibited a non-significant decline in most parts of Ibadan. While trends in cold extremes at annual scale show warming, trends in coldest night show greater warming than in coldest day. At the seasonal scale, we found that Ibadan experienced a mix of positive and negative trends in absolute extreme temperature indices. However, cold extremes show the largest trend magnitudes, with trends in coldest night showing the greatest warming. The results compare well with those obtained from a limited number of stations. This study should inform decision-makers and urban planners about the ongoing warming in Ibadan.
Gutreuter, S.
2004-01-01
Habitat rehabilitation efforts are predicated on the frequently untested assumption that habitat is limiting to populations. These efforts are typically costly and will be ineffective if habitat is not limiting. Therefore it is important to assess, rather than assume, habitat limitation wherever habitat rehabilitation projects are considered. Catch-count data from a standardized probability-based stratified-random monitoring programme were examined for indirect evidence of backwater habitat limitation by centrarchid fishes in the Upper Mississippi River System. The monitoring design enabled fitting statistical models of the association between mean catch at the spatial scale of tens of river kilometres and the percentage of contiguous aquatic area in backwater at least 1 m deep by maximizing a stratum-area weighted negative binomial log-likelihood function. Statistical models containing effects for backwater limitation failed to account for substantial variation in the data. However, 95% confidence intervals on the backwater parameter estimates excluded zero, indicating that population abundance may be limited by backwater prevalence where backwaters are extremely scarce. The combined results indicate, at most, a weak signal of backwater limitation where backwaters are extremely scarce in the lower reaches, but not elsewhere in the Upper Mississippi River System. This suggests that habitat restoration projects designed to increase the area of backwaters suitable for winter survival of centrarchids are unlikely to produce measurable benefits over intermediate spatial scales in much of the Upper Mississippi River System, and indicates the importance of correct identification of limiting processes. Published in 2004 by John Wiley and Sons, Ltd.
NASA Astrophysics Data System (ADS)
O’Donoghue, D.; Frizzell, R.; Punch, J.
2018-07-01
Vibration energy harvesters (VEHs) offer an alternative to batteries for the autonomous operation of low-power electronics. Understanding the influence of scaling on VEHs is of great importance in the design of reduced scale harvesters. The nonlinear harvesters investigated here employ velocity amplification, a technique used to increase velocity through impacts, to improve the power output of multiple-degree-of-freedom VEHs, compared to linear resonators. Such harvesters, employing electromagnetic induction, are referred to as velocity amplified electromagnetic generators (VAEGs), with gains in power achieved by increasing the relative velocity between the magnet and coil in the transducer. The influence of scaling on a nonlinear 2-DoF VAEG is presented. Due to the increased complexity of VAEGs, compared to linear systems, linear scaling theory cannot be directly applied to VAEGs. Therefore, a detailed nonlinear scaling method is utilised. Experimental and numerical methods are employed. This nonlinear scaling method can be used for analysing the scaling behaviour of all nonlinear electromagnetic VEHs. It is demonstrated that the electromagnetic coupling coefficient degrades more rapidly with scale for systems with larger displacement amplitudes, meaning that systems operating at low frequencies will scale poorly compared to those operating at higher frequencies. The load power of the 2-DoF VAEG is predicted to scale as {P}L\\propto {s}5.51 (s = volume1/3), suggesting that achieving high power densities in a VAEG with low device volume is extremely challenging.
NASA Astrophysics Data System (ADS)
Li, Xin; Babovic, Vladan
2016-04-01
Flood and drought are hydrologic extreme events that have significant impact on human and natural systems. Characterization of flood and drought in terms of their start, duration and strength, and investigation of the impact of natural climate variability (i.e., ENSO) and anthropogenic climate change on them can help decision makers to facilitate adaptions to mitigate potential enormous economic costs. To date, numerous studies in this area have been conducted, however, they are primarily focused on extra-tropical regions. Therefore, this study presented a detailed framework to characterize flood and drought events in a tropical urban city-state (i.e., Singapore), based on daily data from 26 precipitation stations. Flood and drought events are extracted from standardized precipitation anomalies from monthly to seasonal time scales. Frequency, duration and magnitude of flood and drought at all the stations are analyzed based on crossing theory. In addition, spatial variation of flood and drought characteristics in Singapore is investigated using ordinary kriging method. Lastly, the impact of ENSO condition on flood and drought characteristics is analyzed using regional regression method. The results show that Singapore can be prone to extreme flood and drought events at both monthly and seasonal time scales. ENSO has significant influence on flood and drought characteristics in Singapore, but mainly during the South West Monsoon season. During the El Niño phase, drought can become more extreme. The results have implications for water management practices in Singapore.
Grassland responses to precipitation extremes
USDA-ARS?s Scientific Manuscript database
Grassland ecosystems are naturally subjected to periods of prolonged drought and sequences of wet years. Climate change is expected to enhance the magnitude and frequency of extreme events at the intraannual and multiyear scales. Are grassland responses to extreme precipitation simply a response to ...
Present-day irrigation mitigates heat extremes
NASA Astrophysics Data System (ADS)
Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; Hirsch, Annette L.; Hauser, Mathias; Seneviratne, Sonia I.
2017-02-01
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 ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. 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 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. Our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.
Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America
Vorosmarty, Charles J.; de Guenni, Lelys Bravo; Wollheim, Wilfred M.; Pellerin, Brian A.; Bjerklie, David M.; Cardoso, Manoel; D'Almeida, Cassiano; Colon, Lilybeth
2013-01-01
Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.
NASA Astrophysics Data System (ADS)
Barthel, Roland; Haaf, Ezra
2016-04-01
Regional hydrogeology is becoming increasingly important, but at the same time, scientifically sound, universal solutions for typical groundwater problems encountered on the regional scale are hard to find. While managers, decision-makers and state agencies operating on regional and national levels have always shown a strong interest in regional scale hydrogeology, researchers from academia tend to avoid the subject, focusing instead on local scales. Additionally, hydrogeology has always had a tendency to regard every problem as unique to its own site- and problem-specific context. Regional scale hydrogeology is therefore pragmatic rather than aiming at developing generic methodology (Barthel, 2014; Barthel and Banzhaf, 2016). One of the main challenges encountered on the regional scale in hydrogeology is the extreme heterogeneity that generally increases with the size of the studied area - paired with relative data scarcity. Even in well-monitored regions of the world, groundwater observations are usually clustered, leaving large areas without any direct data. However, there are many good reasons for assessing the status and predicting the behavior of groundwater systems under conditions of global change even for those areas and aquifers without observations. This is typically done by using rather coarsely discretized and / or poorly parameterized numerical models, or by using very simplistic conceptual hydrological models that do not take into account the complex three-dimensional geological setup. Numerical models heavily rely on local data and are resource-demanding. Conceptual hydrological models only deliver reliable information on groundwater if the geology is extremely simple. In this contribution, we present an approach to derive statistically relevant information for un-monitored areas, making use of existing information from similar localities that are or have been monitored. The approach combines site-specific knowledge with conceptual assumptions on the behavior of groundwater systems. It is based on the hypothesis that similar groundwater systems respond similarly to similar impacts. At its core is the classification of (i) static hydrogeological characteristics (such as aquifer geometry and hydraulic properties), (ii) dynamic changes of the boundary conditions (such as recharge, water levels in surface waters), and (iii) dynamic groundwater system responses (groundwater head and chemical parameters). The dependencies of system responses on explanatory variables are used to map knowledge from observed locations to areas without measurements. Classification of static and dynamic system features combined with information about known system properties and their dependencies provide insight into system behavior that cannot be directly derived through the analysis of raw data. Classification and dependency analysis could finally lead to a new framework for groundwater system assessment on the regional scale as a replacement or supplement to numerical groundwater models and catchment scale hydrological models. This contribution focusses on the main hydrogeological concepts underlying the approach while another EGU contribution (Haaf and Barthel, 2016) explains the methodologies used to classify groundwater systems. References: Barthel, R., 2014. A call for more fundamental science in regional hydrogeology. Hydrogeol J, 22(3): 507-510. Barthel, R., Banzhaf, S., 2016. Groundwater and Surface Water Interaction at the Regional-scale - A Review with Focus on Regional Integrated Models. Water Resour Manag, 30(1): 1-32. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs. Abstract submitted to EGU General Assembly 2016, Vienna, Austria.
Extreme warming challenges sentinel status of kelp forests as indicators of climate change.
Reed, Daniel; Washburn, Libe; Rassweiler, Andrew; Miller, Robert; Bell, Tom; Harrer, Shannon
2016-12-13
The desire to use sentinel species as early warning indicators of impending climate change effects on entire ecosystems is attractive, but we need to verify that such approaches have sound biological foundations. A recent large-scale warming event in the North Pacific Ocean of unprecedented magnitude and duration allowed us to evaluate the sentinel status of giant kelp, a coastal foundation species that thrives in cold, nutrient-rich waters and is considered sensitive to warming. Here, we show that giant kelp and the majority of species that associate with it did not presage ecosystem effects of extreme warming off southern California despite giant kelp's expected vulnerability. Our results challenge the general perception that kelp-dominated systems are highly vulnerable to extreme warming events and expose the more general risk of relying on supposed sentinel species that are assumed to be very sensitive to climate change.
Extreme warming challenges sentinel status of kelp forests as indicators of climate change
NASA Astrophysics Data System (ADS)
Reed, Daniel; Washburn, Libe; Rassweiler, Andrew; Miller, Robert; Bell, Tom; Harrer, Shannon
2016-12-01
The desire to use sentinel species as early warning indicators of impending climate change effects on entire ecosystems is attractive, but we need to verify that such approaches have sound biological foundations. A recent large-scale warming event in the North Pacific Ocean of unprecedented magnitude and duration allowed us to evaluate the sentinel status of giant kelp, a coastal foundation species that thrives in cold, nutrient-rich waters and is considered sensitive to warming. Here, we show that giant kelp and the majority of species that associate with it did not presage ecosystem effects of extreme warming off southern California despite giant kelp's expected vulnerability. Our results challenge the general perception that kelp-dominated systems are highly vulnerable to extreme warming events and expose the more general risk of relying on supposed sentinel species that are assumed to be very sensitive to climate change.
HACC: Extreme Scaling and Performance Across Diverse Architectures
NASA Astrophysics Data System (ADS)
Habib, Salman; Morozov, Vitali; Frontiere, Nicholas; Finkel, Hal; Pope, Adrian; Heitmann, Katrin
2013-11-01
Supercomputing is evolving towards hybrid and accelerator-based architectures with millions of cores. The HACC (Hardware/Hybrid Accelerated Cosmology Code) framework exploits this diverse landscape at the largest scales of problem size, obtaining high scalability and sustained performance. Developed to satisfy the science requirements of cosmological surveys, HACC melds particle and grid methods using a novel algorithmic structure that flexibly maps across architectures, including CPU/GPU, multi/many-core, and Blue Gene systems. We demonstrate the success of HACC on two very different machines, the CPU/GPU system Titan and the BG/Q systems Sequoia and Mira, attaining unprecedented levels of scalable performance. We demonstrate strong and weak scaling on Titan, obtaining up to 99.2% parallel efficiency, evolving 1.1 trillion particles. On Sequoia, we reach 13.94 PFlops (69.2% of peak) and 90% parallel efficiency on 1,572,864 cores, with 3.6 trillion particles, the largest cosmological benchmark yet performed. HACC design concepts are applicable to several other supercomputer applications.
NASA Astrophysics Data System (ADS)
Bao, Jiawei; Sherwood, Steven C.; Colin, Maxime; Dixit, Vishal
2017-10-01
The behavior of tropical extreme precipitation under changes in sea surface temperatures (SSTs) is investigated with the Weather Research and Forecasting Model (WRF) in three sets of idealized simulations: small-domain tropical radiative-convective equilibrium (RCE), quasi-global "aquapatch", and RCE with prescribed mean ascent from the tropical band in the aquapatch. We find that, across the variations introduced including SST, large-scale circulation, domain size, horizontal resolution, and convective parameterization, the change in the degree of convective organization emerges as a robust mechanism affecting extreme precipitation. Higher ratios of change in extreme precipitation to change in mean surface water vapor are associated with increases in the degree of organization, while lower ratios correspond to decreases in the degree of organization. The spread of such changes is much larger in RCE than aquapatch tropics, suggesting that small RCE domains may be unreliable for assessing the temperature-dependence of extreme precipitation or convective organization. When the degree of organization does not change, simulated extreme precipitation scales with surface water vapor. This slightly exceeds Clausius-Clapeyron (CC) scaling, because the near-surface air warms 10-25% faster than the SST in all experiments. Also for simulations analyzed here with convective parameterizations, there is an increasing trend of organization with SST.
Inter-annual Variability of Temperature and Extreme Heat Events during the Nairobi Warm Season
NASA Astrophysics Data System (ADS)
Scott, A.; Misiani, H. O.; Zaitchik, B. F.; Ouma, G. O.; Anyah, R. O.; Jordan, A.
2016-12-01
Extreme heat events significantly stress all organisms in the ecosystem, and are likely to be amplified in peri-urban and urban areas. Understanding the variability and drivers behind these events is key to generating early warnings, yet in Equatorial East Africa, this information is currently unavailable. This study uses daily maximum and minimum temperature records from weather stations within Nairobi and its surroundings to characterize variability in daily minimum temperatures and the number of extreme heat events. ERA-Interim reanalysis is applied to assess the drivers of these events at event and seasonal time scales. At seasonal time scales, high temperatures in Nairobi are a function of large scale climate variability associated with the Atlantic Multi-decadal Oscillation (AMO) and Global Mean Sea Surface Temperature (GMSST). Extreme heat events, however, are more strongly associated with the El Nino Southern Oscillation (ENSO). For instance, the persistence of AMO and ENSO, in particular, provide a basis for seasonal prediction of extreme heat events/days in Nairobi. It is also apparent that the temporal signal from extreme heat events in tropics differs from classic heat wave definitions developed in the mid-latitudes, which suggests that a new approach for defining these events is necessary for tropical regions.
Precipitation extreme changes exceeding moisture content increases in MIROC and IPCC climate models
Sugiyama, Masahiro; Shiogama, Hideo; Emori, Seita
2010-01-01
Precipitation extreme changes are often assumed to scale with, or are constrained by, the change in atmospheric moisture content. Studies have generally confirmed the scaling based on moisture content for the midlatitudes but identified deviations for the tropics. In fact half of the twelve selected Intergovernmental Panel on Climate Change (IPCC) models exhibit increases faster than the climatological-mean precipitable water change for high percentiles of tropical daily precipitation, albeit with significant intermodel scatter. Decomposition of the precipitation extreme changes reveals that the variations among models can be attributed primarily to the differences in the upward velocity. Both the amplitude and vertical profile of vertical motion are found to affect precipitation extremes. A recently proposed scaling that incorporates these dynamical effects can capture the basic features of precipitation changes in both the tropics and midlatitudes. In particular, the increases in tropical precipitation extremes significantly exceed the precipitable water change in Model for Interdisciplinary Research on Climate (MIROC), a coupled general circulation model with the highest resolution among IPCC climate models whose precipitation characteristics have been shown to reasonably match those of observations. The expected intensification of tropical disturbances points to the possibility of precipitation extreme increases beyond the moisture content increase as is found in MIROC and some of IPCC models. PMID:20080720
White, Richard S A; Wintle, Brendan A; McHugh, Peter A; Booker, Douglas J; McIntosh, Angus R
2017-06-14
Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-to-extinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local time-to-extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity, and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming. © 2017 The Author(s).
To manage inland fisheries is to manage at the social-ecological watershed scale.
Nguyen, Vivian M; Lynch, Abigail J; Young, Nathan; Cowx, Ian G; Beard, T Douglas; Taylor, William W; Cooke, Steven J
2016-10-01
Approaches to managing inland fisheries vary between systems and regions but are often based on large-scale marine fisheries principles and thus limited and outdated. Rarely do they adopt holistic approaches that consider the complex interplay among humans, fish, and the environment. We argue that there is an urgent need for a shift in inland fisheries management towards holistic and transdisciplinary approaches that embrace the principles of social-ecological systems at the watershed scale. The interconnectedness of inland fisheries with their associated watershed (biotic, abiotic, and humans) make them extremely complex and challenging to manage and protect. For this reason, the watershed is a logical management unit. To assist management at this scale, we propose a framework that integrates disparate concepts and management paradigms to facilitate inland fisheries management and sustainability. We contend that inland fisheries need to be managed as social-ecological watershed system (SEWS). The framework supports watershed-scale and transboundary governance to manage inland fisheries, and transdisciplinary projects and teams to ensure relevant and applicable monitoring and research. We discuss concepts of social-ecological feedback and interactions of multiple stressors and factors within/between the social-ecological systems. Moreover, we emphasize that management, monitoring, and research on inland fisheries at the watershed scale are needed to ensure long-term sustainable and resilient fisheries. Copyright © 2016. Published by Elsevier Ltd.
Extreme reaction times determine fluctuation scaling in human color vision
NASA Astrophysics Data System (ADS)
Medina, José M.; Díaz, José A.
2016-11-01
In modern mental chronometry, human reaction time defines the time elapsed from stimulus presentation until a response occurs and represents a reference paradigm for investigating stochastic latency mechanisms in color vision. Here we examine the statistical properties of extreme reaction times and whether they support fluctuation scaling in the skewness-kurtosis plane. Reaction times were measured for visual stimuli across the cardinal directions of the color space. For all subjects, the results show that very large reaction times deviate from the right tail of reaction time distributions suggesting the existence of dragon-kings events. The results also indicate that extreme reaction times are correlated and shape fluctuation scaling over a wide range of stimulus conditions. The scaling exponent was higher for achromatic than isoluminant stimuli, suggesting distinct generative mechanisms. Our findings open a new perspective for studying failure modes in sensory-motor communications and in complex networks.
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;
2016-01-01
Extreme events are the aspects of climate to which human society is most sensitive. Due to both their severity and their rarity, extreme events can challenge the capacity of physical, social, economic and political infrastructures, turning natural events into human disasters. Yet, because they are low frequency events, the science of extreme events is very challenging. Among the challenges is the difficulty of connecting extreme events to longer-term, large-scale variability and trends in the climate system, including anthropogenic climate change. How can we best quantify the risks posed by extreme weather events, both in the current climate and in the warmer and different climates to come? How can we better predict them? What can we do to reduce the harm done by such events? In response to these questions, the Initiative on Extreme Weather and Climate has been created at Columbia University in New York City (extreme weather.columbia.edu). This Initiative is a University-wide activity focused on understanding the risks to human life, property, infrastructure, communities, institutions, ecosystems, and landscapes from extreme weather events, both in the present and future climates, and on developing solutions to mitigate those risks. In May 2015,the Initiative held its first science workshop, entitled Extreme Weather and Climate: Hazards, Impacts, Actions. The purpose of the workshop was to define the scope of the Initiative and tremendously broad intellectual footprint of the topic indicated by the titles of the presentations (see Table 1). The intent of the workshop was to stimulate thought across disciplinary lines by juxtaposing talks whose subjects differed dramatically. Each session concluded with question and answer panel sessions. Approximately, 150 people were in attendance throughout the day. Below is a brief synopsis of each presentation. The synopses collectively reflect the variety and richness of the emerging extreme event research agenda.
Climate teleconnections, weather extremes, and vector-borne disease outbreaks
USDA-ARS?s Scientific Manuscript database
Fluctuations in climate lead to extremes in temperature, rainfall, flooding, and droughts. These climate extremes create ideal ecological conditions that promote mosquito-borne disease transmission that impact global human and animal health. One well known driver of such global scale climate fluctua...
Toward a theoretical framework for trustworthy cyber sensing
NASA Astrophysics Data System (ADS)
Xu, Shouhuai
2010-04-01
Cyberspace is an indispensable part of the economy and society, but has been "polluted" with many compromised computers that can be abused to launch further attacks against the others. Since it is likely that there always are compromised computers, it is important to be aware of the (dynamic) cyber security-related situation, which is however challenging because cyberspace is an extremely large-scale complex system. Our project aims to investigate a theoretical framework for trustworthy cyber sensing. With the perspective of treating cyberspace as a large-scale complex system, the core question we aim to address is: What would be a competent theoretical (mathematical and algorithmic) framework for designing, analyzing, deploying, managing, and adapting cyber sensor systems so as to provide trustworthy information or input to the higher layer of cyber situation-awareness management, even in the presence of sophisticated malicious attacks against the cyber sensor systems?
Assessing the Regional Frequency, Intensity, and Spatial Extent of Tropical Cyclone Rainfall
NASA Astrophysics Data System (ADS)
Bosma, C.; Wright, D.; Nguyen, P.
2017-12-01
While the strength of a hurricane is generally classified based on its wind speed, the unprecedented rainfall-driven flooding experienced in southeastern Texas during Hurricane Harvey clearly highlights the need for better understanding of the hazards associated with extreme rainfall from hurricanes and other tropical systems. In this study, we seek to develop a framework for describing the joint probabilistic and spatio-temporal properties of extreme rainfall from hurricanes and other tropical systems. Furthermore, we argue that commonly-used terminology - such as the "500-year storm" - fail to convey the true properties of tropical cyclone rainfall occurrences in the United States. To quantify the magnitude and spatial extent of these storms, a database consisting of hundreds of unique rainfall volumetric shapes (or "voxels") was created. Each voxel is a four-dimensional object, created by connecting, in both space and time, gridded rainfall observations from the daily, gauge-based NOAA CPC-Unified precipitation dataset. Individual voxels were then associated with concurrent tropical cyclone tracks from NOAA's HURDAT-2 archive, to create distinct representations of the rainfall associated with every Atlantic tropical system making landfall over (or passing near) the United States since 1948. Using these voxels, a series of threshold-excess extreme value models were created to estimate the recurrence intervals of extreme tropical cyclone rainfall, both nationally and locally, for single and multi-day timescales. This voxel database also allows for the "indexing" of past events, placing recent extremes - such as the 50+ inches of rain observed during Hurricane Harvey - into a national context and emphasizing how rainfall totals that are rare at the point scale may be more frequent from a regional perspective.
NASA Astrophysics Data System (ADS)
Khosronejad, Ali; Sotiropoulos, Fotis; Stony Brook University Team
2016-11-01
We present a coupled flow and morphodynamic simulations of extreme flooding in 3 km long and 300 m wide reach of the Mississippi River in Minnesota, which includes three islands and hydraulic structures. We employ the large-eddy simulation (LES) and bed-morphodynamic modules of the VFS-Geophysics model to investigate the flow and bed evolution of the river during a 500 year flood. The coupling of the two modules is carried out via a fluid-structure interaction approach using a nested domain approach to enhance the resolution of bridge scour predictions. The geometrical data of the river, islands and structures are obtained from LiDAR, sub-aqueous sonar and in-situ surveying to construct a digital map of the river bathymetry. Our simulation results for the bed evolution of the river reveal complex sediment dynamics near the hydraulic structures. The numerically captured scour depth near some of the structures reach a maximum of about 10 m. The data-driven simulation strategy we present in this work exemplifies a practical simulation-based-engineering-approach to investigate the resilience of infrastructures to extreme flood events in intricate field-scale riverine systems. This work was funded by a Grant from Minnesota Dept. of Transportation.
Climate Variability and Weather Extremes: Model-Simulated and Historical Data. Chapter 9
NASA Technical Reports Server (NTRS)
Schubert, Siegfried D.; Lim, Young-Kwon
2012-01-01
Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).
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 accessible to a broader audience.
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.
Spatial variability of extreme rainfall at radar subpixel scale
NASA Astrophysics Data System (ADS)
Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo
2018-01-01
Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.
Paolucci, Teresa; Piccinini, Giulia; Nusca, Sveva Maria; Marsilli, Gabriella; Mannocci, Alice; La Torre, Giuseppe; Saraceni, Vincenzo Maria; Vulpiani, Maria Chiara; Villani, Ciro
2018-01-01
[Purpose] The aim of this study was to investigate the clinical effects of a nutraceutical composed (Xinepa®) combined with extremely-low-frequency electromagnetic fields in the carpal tunnel syndrome. [Subjects and Methods] Thirty-one patients with carpal tunnel syndrome were randomized into group 1-A (N=16) (nutraceutical + extremely-low-frequency electromagnetic fields) and group 2-C (n=15) (placebo + extremely-low-frequency electromagnetic fields). The dietary supplement with nutraceutical was twice daily for one month in the 1-A group and both groups received extremely-low-frequency electromagnetic fields at the level of the carpal tunnel 3 times per week for 12 sessions. The Visual Analogue Scale for pain, the Symptoms Severity Scale and Functional Severity Scale of the Boston Carpal Tunnel Questionnaire were used at pre-treatment (T0), after the end of treatment (T1) and at 3 months post-treatment (T2). [Results] At T1 and T2 were not significant differences in outcome measures between the two groups. In group 1-A a significant improvement in the scales were observed at T1 and T2. In group 2-C it was observed only at T1. [Conclusion] Significant clinical effects from pre-treatment to the end of treatment were shown in both groups. Only in group 1-A they were maintained at 3 months post-treatment.
Page, Stephen J.; Hill, Valerie; White, Susan
2013-01-01
Objective To compare the efficacy of a repetitive task specific practice regimen integrating a portable, electromyography-controlled brace called the “Myomo” versus usual care repetitive task specific practice in subjects with chronic, moderate upper extremity impairment. Subjects 16 subjects (7 males; mean age = 57.0 ± 11.02 years; mean time post stroke = 75.0 ± 87.63 months; 5 left-sided strokes) exhibiting chronic, stable, moderate upper extremity impairment. Interventions Subjects were administered repetitive task specific practice in which they participated in valued, functional tasks using their paretic upper extremities. Both groups were supervised by a therapist and were administered therapy targeting their paretic upper extremities that was 30-minutes in duration, occurring 3 days/week for 8 weeks. However, one group participated in repetitive task specific practice entirely while wearing the portable robotic while the other performed the same activity regimen manually.. Main Outcome Measures The upper extremity Fugl-Meyer, Canadian Occupational Performance measure and Stroke Impact Scale were administered on two occasions before intervention and once after intervention. Results After intervention, groups exhibited nearly-identical Fugl-Meyer score increases of ≈ 2.1 points; the group using robotics exhibited larger score changes on all but one of the Canadian occupational performance measure and Stroke Impact Scale subscales, including a 12.5-point increase on the Stroke Impact Scale recovery subscale. Conclusions Findings suggest that therapist-supervised repetitive task specific practice integrating robotics is as efficacious as manual in subjects with moderate upper extremity impairment. PMID:23147552
Lightweight computational steering of very large scale molecular dynamics simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beazley, D.M.; Lomdahl, P.S.
1996-09-01
We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show howmore » this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages.« less
Ensemble Kalman filters for dynamical systems with unresolved turbulence
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grooms, Ian, E-mail: grooms@cims.nyu.edu; Lee, Yoonsang; Majda, Andrew J.
Ensemble Kalman filters are developed for turbulent dynamical systems where the forecast model does not resolve all the active scales of motion. Coarse-resolution models are intended to predict the large-scale part of the true dynamics, but observations invariably include contributions from both the resolved large scales and the unresolved small scales. The error due to the contribution of unresolved scales to the observations, called ‘representation’ or ‘representativeness’ error, is often included as part of the observation error, in addition to the raw measurement error, when estimating the large-scale part of the system. It is here shown how stochastic superparameterization (amore » multiscale method for subgridscale parameterization) can be used to provide estimates of the statistics of the unresolved scales. In addition, a new framework is developed wherein small-scale statistics can be used to estimate both the resolved and unresolved components of the solution. The one-dimensional test problem from dispersive wave turbulence used here is computationally tractable yet is particularly difficult for filtering because of the non-Gaussian extreme event statistics and substantial small scale turbulence: a shallow energy spectrum proportional to k{sup −5/6} (where k is the wavenumber) results in two-thirds of the climatological variance being carried by the unresolved small scales. Because the unresolved scales contain so much energy, filters that ignore the representation error fail utterly to provide meaningful estimates of the system state. Inclusion of a time-independent climatological estimate of the representation error in a standard framework leads to inaccurate estimates of the large-scale part of the signal; accurate estimates of the large scales are only achieved by using stochastic superparameterization to provide evolving, large-scale dependent predictions of the small-scale statistics. Again, because the unresolved scales contain so much energy, even an accurate estimate of the large-scale part of the system does not provide an accurate estimate of the true state. By providing simultaneous estimates of both the large- and small-scale parts of the solution, the new framework is able to provide accurate estimates of the true system state.« less
NASA Astrophysics Data System (ADS)
Yoshimoto, Masahiro; Nakano, Toshiyuki; Komatani, Ryosuke; Kawahara, Hiroaki
2017-10-01
Automatic nuclear emulsion readout systems have seen remarkable progress since the original idea was developed almost 40 years ago. After the success of its full application to a large-scale neutrino experiment, OPERA, a much faster readout system, the hyper-track selector (HTS), has been developed. HTS, which has an extremely wide-field objective lens, reached a scanning speed of 4700 cm^2/h, which is nearly 100 times faster than the previous system and therefore strongly promotes many new experimental projects. We will describe the concept, specifications, system structure, and achieved performance in this paper.
[Invariants of the anthropometrical proportions].
Smolianinov, V V
2012-01-01
In this work a general interpretation of a modulor as scales of segments proportions of anthropometrical modules (extremities and a body) is made. The objects of this study were: 1) to reason the idea of the growth modulor; 2) using the modern empirical data, to prove the validity of a principle of linear similarity for anthropometrical segments; 3) to specify the system of invariants for constitutional anthropometrics.
A Review of Recent Advances in Research on Extreme Heat Events
NASA Technical Reports Server (NTRS)
Horton, Radley M.; Mankin, Justin S.; Lesk, Corey; Coffel, Ethan; Raymond, Colin
2016-01-01
Reviewing recent literature, we report that changes in extreme heat event characteristics such as magnitude, frequency, and duration are highly sensitive to changes in mean global-scale warming. Numerous studies have detected significant changes in the observed occurrence of extreme heat events, irrespective of how such events are defined. Further, a number of these studies have attributed present-day changes in the risk of individual heat events and the documented global-scale increase in such events to anthropogenic-driven warming. Advances in process-based studies of heat events have focused on the proximate land-atmosphere interactions through soil moisture anomalies, and changes in occurrence of the underlying atmospheric circulation associated with heat events in the mid-latitudes. While evidence for a number of hypotheses remains limited, climate change nevertheless points to tail risks of possible changes in heat extremes that could exceed estimates generated from model outputs of mean temperature. We also explore risks associated with compound extreme events and nonlinear impacts associated with extreme heat.
Pynamic: the Python Dynamic Benchmark
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, G L; Ahn, D H; de Supinksi, B R
2007-07-10
Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, wemore » present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.« less
Final Technical Report for DE-SC0005467
DOE Office of Scientific and Technical Information (OSTI.GOV)
Broccoli, Anthony J.
2014-09-14
The objective of this project is to gain a comprehensive understanding of the key atmospheric mechanisms and physical processes associated with temperature extremes in order to better interpret and constrain uncertainty in climate model simulations of future extreme temperatures. To achieve this objective, we first used climate observations and a reanalysis product to identify the key atmospheric circulation patterns associated with extreme temperature days over North America during the late twentieth century. We found that temperature extremes were associated with distinctive signatures in near-surface and mid-tropospheric circulation. The orientations and spatial scales of these circulation anomalies vary with latitude, season,more » and proximity to important geographic features such as mountains and coastlines. We next examined the associations between daily and monthly temperature extremes and large-scale, recurrent modes of climate variability, including the Pacific-North American (PNA) pattern, the northern annular mode (NAM), and the El Niño-Southern Oscillation (ENSO). The strength of the associations are strongest with the PNA and NAM and weaker for ENSO, and also depend upon season, time scale, and location. The associations are stronger in winter than summer, stronger for monthly than daily extremes, and stronger in the vicinity of the centers of action of the PNA and NAM patterns. In the final stage of this project, we compared climate model simulations of the circulation patterns associated with extreme temperature days over North America with those obtained from observations. Using a variety of metrics and self-organizing maps, we found the multi-model ensemble and the majority of individual models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) generally capture the observed patterns well, including their strength and as well as variations with latitude and season. The results from this project indicate that current models are capable of simulating the large-scale meteorological patterns associated with daily temperature extremes and they suggest that such models can be used to evaluate the extent to which changes in atmospheric circulation will influence future changes in temperature extremes.« less
Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge
NASA Astrophysics Data System (ADS)
Demir, I.; Sermet, M. Y.
2017-12-01
Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.
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.…
Temporal variability in the suspended sediment load and streamflow of the Doce River
NASA Astrophysics Data System (ADS)
Oliveira, Kyssyanne Samihra Santos; Quaresma, Valéria da Silva
2017-10-01
Long-term records of streamflow and suspended sediment load provide a better understanding of the evolution of a river mouth, and its adjacent waters and a support for mitigation programs associated with extreme events and engineering projects. The aim of this study is to investigate the temporal variability in the suspended sediment load and streamflow of the Doce River to the Atlantic Ocean, between 1990 and 2013. Streamflow and suspended sediment load were analyzed at the daily, seasonal, and interannual scales. The results showed that at the daily scale, Doce River flood events are due to high intensity and short duration rainfalls, which means that there is a flashy response to rainfall. At the monthly and season scales, approximately 94% of the suspended sediment supply occurs during the wet season. Extreme hydrological events are important for the interannual scale for Doce River sediment supply to the Atlantic Ocean. The results suggest that a summation of anthropogenic interferences (deforestation, urbanization and soil degradation) led to an increase of extreme hydrological events. The findings of this study shows the importance of understanding the typical behavior of the Doce River, allowing the detection of extreme hydrological conditions, its causes and possible environmental and social consequences.
Capturing rogue waves by multi-point statistics
NASA Astrophysics Data System (ADS)
Hadjihosseini, A.; Wächter, Matthias; Hoffmann, N. P.; Peinke, J.
2016-01-01
As an example of a complex system with extreme events, we investigate ocean wave states exhibiting rogue waves. We present a statistical method of data analysis based on multi-point statistics which for the first time allows the grasping of extreme rogue wave events in a highly satisfactory statistical manner. The key to the success of the approach is mapping the complexity of multi-point data onto the statistics of hierarchically ordered height increments for different time scales, for which we can show that a stochastic cascade process with Markov properties is governed by a Fokker-Planck equation. Conditional probabilities as well as the Fokker-Planck equation itself can be estimated directly from the available observational data. With this stochastic description surrogate data sets can in turn be generated, which makes it possible to work out arbitrary statistical features of the complex sea state in general, and extreme rogue wave events in particular. The results also open up new perspectives for forecasting the occurrence probability of extreme rogue wave events, and even for forecasting the occurrence of individual rogue waves based on precursory dynamics.
The impact of anthropogenic land use and land cover change on regional climate extremes.
Findell, Kirsten L; Berg, Alexis; Gentine, Pierre; Krasting, John P; Lintner, Benjamin R; Malyshev, Sergey; Santanello, Joseph A; Shevliakova, Elena
2017-10-20
Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.
ExM:System Support for Extreme-Scale, Many-Task Applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katz, Daniel S
The ever-increasing power of supercomputer systems is both driving and enabling the emergence of new problem-solving methods that require the effi cient execution of many concurrent and interacting tasks. Methodologies such as rational design (e.g., in materials science), uncertainty quanti fication (e.g., in engineering), parameter estimation (e.g., for chemical and nuclear potential functions, and in economic energy systems modeling), massive dynamic graph pruning (e.g., in phylogenetic searches), Monte-Carlo- based iterative fi xing (e.g., in protein structure prediction), and inverse modeling (e.g., in reservoir simulation) all have these requirements. These many-task applications frequently have aggregate computing needs that demand the fastestmore » computers. For example, proposed next-generation climate model ensemble studies will involve 1,000 or more runs, each requiring 10,000 cores for a week, to characterize model sensitivity to initial condition and parameter uncertainty. The goal of the ExM project is to achieve the technical advances required to execute such many-task applications efficiently, reliably, and easily on petascale and exascale computers. In this way, we will open up extreme-scale computing to new problem solving methods and application classes. In this document, we report on combined technical progress of the collaborative ExM project, and the institutional financial status of the portion of the project at University of Chicago, over the rst 8 months (through April 30, 2011)« less
Extreme events as foundation of Lévy walks with varying velocity
NASA Astrophysics Data System (ADS)
Kutner, Ryszard
2002-11-01
In this work we study the role of extreme events [E.W. Montroll, B.J. West, in: J.L. Lebowitz, E.W. Montrell (Eds.), Fluctuation Phenomena, SSM, vol. VII, North-Holland, Amsterdam, 1979, p. 63; J.-P. Bouchaud, M. Potters, Theory of Financial Risks from Statistical Physics to Risk Management, Cambridge University Press, Cambridge, 2001; D. Sornette, Critical Phenomena in Natural Sciences. Chaos, Fractals, Selforganization and Disorder: Concepts and Tools, Springer, Berlin, 2000] in determining the scaling properties of Lévy walks with varying velocity. This model is an extension of the well-known Lévy walks one [J. Klafter, G. Zumofen, M.F. Shlesinger, in M.F. Shlesinger, G.M. Zaslavsky, U. Frisch (Eds.), Lévy Flights and Related Topics ion Physics, Lecture Notes in Physics, vol. 450, Springer, Berlin, 1995, p. 196; G. Zumofen, J. Klafter, M.F. Shlesinger, in: R. Kutner, A. Pȩkalski, K. Sznajd-Weron (Eds.), Anomalous Diffusion. From Basics to Applications, Lecture Note in Physics, vol. 519, Springer, Berlin, 1999, p. 15] introduced in the context of chaotic dynamics where a fixed value of the walker velocity is assumed for simplicity. Such an extension seems to be necessary when the open and/or complex system is studied. The model of Lévy walks with varying velocity is spanned on two coupled velocity-temporal hierarchies: the first one consisting of velocities and the second of corresponding time intervals which the walker spends between the successive turning points. Both these hierarchical structures are characterized by their own self-similar dimensions. The extreme event, which can appear within a given time interval, is defined as a single random step of the walker having largest length. By finding power-laws which describe the time-dependence of this displacement and its statistics we obtained two independent diffusion exponents, which are related to the above-mentioned dimensions and which characterize the extreme event kinetics. In this work we show the principal influence of extreme events on the basic quantities (one-step distributions and moments as well as two-step correlation functions) of the continuous-time random walk formalism. Besides, we construct both the waiting-time distribution and sojourn probability density directly in a real space and time in the scaling form by proper component analysis which takes into account all possible fluctuations of the walker steps in contrast to the extreme event analysis. In this work we pay our attention to the basic quantities, since the summarized multi-step ones were already discussed earlier [Physica A 264 (1999) 107; Comp. Phys. Commun. 147 (2002) 565]. Moreover, we study not only the scaling phenomena but also, assuming a finite number of hierarchy levels, the breaking of scaling and its dependence on control parameters. This seems to be important for studying empirical systems the more so as there are still no closed formulae describing this phenomenon except the one for truncated Lévy flights [Phys. Rev. Lett. 73 (1994) 2946]. Our formulation of the model made possible to develop an efficient Monte Carlo algorithm [Physica A 264 (1999) 107; Comp. Phys. Commun. 147 (2002) 565] where no MC step is lost.
Impact of delayed information in sub-second complex systems
NASA Astrophysics Data System (ADS)
Manrique, Pedro D.; Zheng, Minzhang; Johnson Restrepo, D. Dylan; Hui, Pak Ming; Johnson, Neil F.
What happens when you slow down the delivery of information in large-scale complex systems that operate faster than the blink of an eye? This question just adopted immediate commercial, legal and political importance following U.S. regulators' decision to allow an intentional 350 microsecond delay to be added in the ultrafast network of financial exchanges. However there is still no scientific understanding available to policymakers of the potential system-wide impact of such delays. Here we take a first step in addressing this question using a minimal model of a population of competing, heterogeneous, adaptive agents which has previously been shown to produce similar statistical features to real markets. We find that while certain extreme system-level behaviors can be prevented by such delays, the duration of others is increased. This leads to a highly non-trivial relationship between delays and system-wide instabilities which warrants deeper empirical investigation. The generic nature of our model suggests there should be a fairly wide class of complex systems where such delay-driven extreme behaviors can arise, e.g. sub-second delays in brain function possibly impacting individuals' behavior, and sub-second delays in navigational systems potentially impacting the safety of driverless vehicles.
NASA Astrophysics Data System (ADS)
Thompson, C. J.; Croke, J. C.; Grove, J. R.
2012-04-01
Non-linearity in physical systems provides a conceptual framework to explain complex patterns and form that are derived from complex internal dynamics rather than external forcings, and can be used to inform modeling and improve landscape management. One process that has been investigated previously to explore the existence of self-organised critical system (SOC) in river systems at the basin-scale is bank failure. Spatial trends in bank failure have been previously quantified to determine if the distribution of bank failures at the basin scale exhibit the necessary power law magnitude/frequency distributions. More commonly bank failures are investigated at a small-scale using several cross-sections with strong emphasis on local-scale factors such as bank height, cohesion and hydraulic properties. Advancing our understanding of non-linearity in such processes, however, requires many more studies where both the spatial and temporal measurements of the process can be used to investigate the existence or otherwise of non-linearity and self-organised criticality. This study presents measurements of bank failure throughout the Lockyer catchment in southeast Queensland, Australia, which experienced an extreme flood event in January 2011 resulting in the loss of human lives and geomorphic channel change. The most dominant form of fluvial adjustment consisted of changes in channel geometry and notably widespread bank failures, which were readily identifiable as 'scalloped' shaped failure scarps. The spatial extents of these were mapped using high-resolution LiDAR derived digital elevation model and were verified by field surveys and air photos. Pre-flood event LiDAR coverage for the catchment also existed allowing direct comparison of the magnitude and frequency of bank failures from both pre and post-flood time periods. Data were collected and analysed within a GIS framework and investigated for power-law relationships. Bank failures appeared random and occurred throughout the basin but plots of magnitude and frequency did display power-law scaling of failures. In addition, there was a lack of site specific correlations between bank failure and other factors such channel width, bank height and stream power. The data are used here to discuss the existence of SOC in fluvial systems and the relative role of local and basin-wide processes in influencing their distribution in space and time.
Large-scale drivers of local precipitation extremes in convection-permitting climate simulations
NASA Astrophysics Data System (ADS)
Chan, Steven C.; Kendon, Elizabeth J.; Roberts, Nigel M.; Fowler, Hayley J.; Blenkinsop, Stephen
2016-04-01
The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.
NASA Technical Reports Server (NTRS)
Pulkkinen, Antti; Bernabeu, Emanuel; Eichner, Jan; Viljanen, Ari; Ngwira, Chigomezyo
2015-01-01
Motivated by the needs of the high-voltage power transmission industry, we use data from the high-latitude IMAGE magnetometer array to study characteristics of extreme geoelectric fields at regional scales. We use 10-s resolution data for years 1993-2013, and the fields are characterized using average horizontal geoelectric field amplitudes taken over station groups that span about 500-km distance. We show that geoelectric field structures associated with localized extremes at single stations can be greatly different from structures associated with regionally uniform geoelectric fields, which are well represented by spatial averages over single stations. Visual extrapolation and rigorous extreme value analysis of spatially averaged fields indicate that the expected range for 1-in-100-year extreme events are 3-8 V/km and 3.4-7.1 V/km, respectively. The Quebec reference ground model is used in the calculations.
NASA Astrophysics Data System (ADS)
Schroeer, K.; Kirchengast, G.
2018-06-01
Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.
NASA Astrophysics Data System (ADS)
Yang, Y.; Gan, T. Y.; Tan, X.
2017-12-01
In the past few decades, there have been more extreme climate events around the world, and Canada has also suffered from numerous extreme precipitation events. In this paper, trend analysis, change point analysis, probability distribution function, principal component analysis and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation in Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data from 164 gauging stations. Several large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Pacific-North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective Available Potential Energy (CAPE), specific humidity, and surface temperature were employed to investigate the potential causes of the trends.The results show statistically significant positive trends for most indices, which indicate increasing extreme precipitation. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominate in the central Canadian Prairies (CP). In addition, strong connections are found between the extreme precipitation and climate indices and the effects of climate pattern differ for each region. The seasonal CAPE, specific humidity, and temperature are found to be closely related to Canadian extreme precipitation.
The role of Natural Flood Management in managing floods in large scale basins during extreme events
NASA Astrophysics Data System (ADS)
Quinn, Paul; Owen, Gareth; ODonnell, Greg; Nicholson, Alex; Hetherington, David
2016-04-01
There is a strong evidence database showing the negative impacts of land use intensification and soil degradation in NW European river basins on hydrological response and to flood impact downstream. However, the ability to target zones of high runoff production and the extent to which we can manage flood risk using nature-based flood management solution are less known. A move to planting more trees and having less intense farmed landscapes is part of natural flood management (NFM) solutions and these methods suggest that flood risk can be managed in alternative and more holistic ways. So what local NFM management methods should be used, where in large scale basin should they be deployed and how does flow is propagate to any point downstream? Generally, how much intervention is needed and will it compromise food production systems? If we are observing record levels of rainfall and flow, for example during Storm Desmond in Dec 2015 in the North West of England, what other flood management options are really needed to complement our traditional defences in large basins for the future? In this paper we will show examples of NFM interventions in the UK that have impacted at local scale sites. We will demonstrate the impact of interventions at local, sub-catchment (meso-scale) and finally at the large scale. These tools include observations, process based models and more generalised Flood Impact Models. Issues of synchronisation and the design level of protection will be debated. By reworking observed rainfall and discharge (runoff) for observed extreme events in the River Eden and River Tyne, during Storm Desmond, we will show how much flood protection is needed in large scale basins. The research will thus pose a number of key questions as to how floods may have to be managed in large scale basins in the future. We will seek to support a method of catchment systems engineering that holds water back across the whole landscape as a major opportunity to management water in large scale basins in the future. The broader benefits of engineering landscapes to hold water for pollution control, sediment loss and drought minimisation will also be shown.
NASA Astrophysics Data System (ADS)
Abaurrea, J.; Asín, J.; Cebrián, A. C.
2018-02-01
The occurrence of extreme heat events in maximum and minimum daily temperatures is modelled using a non-homogeneous common Poisson shock process. It is applied to five Spanish locations, representative of the most common climates over the Iberian Peninsula. The model is based on an excess over threshold approach and distinguishes three types of extreme events: only in maximum temperature, only in minimum temperature and in both of them (simultaneous events). It takes into account the dependence between the occurrence of extreme events in both temperatures and its parameters are expressed as functions of time and temperature related covariates. The fitted models allow us to characterize the occurrence of extreme heat events and to compare their evolution in the different climates during the observed period. This model is also a useful tool for obtaining local projections of the occurrence rate of extreme heat events under climate change conditions, using the future downscaled temperature trajectories generated by Earth System Models. The projections for 2031-60 under scenarios RCP4.5, RCP6.0 and RCP8.5 are obtained and analysed using the trajectories from four earth system models which have successfully passed a preliminary control analysis. Different graphical tools and summary measures of the projected daily intensities are used to quantify the climate change on a local scale. A high increase in the occurrence of extreme heat events, mainly in July and August, is projected in all the locations, all types of event and in the three scenarios, although in 2051-60 the increase is higher under RCP8.5. However, relevant differences are found between the evolution in the different climates and the types of event, with a specially high increase in the simultaneous ones.
Reconstructing metabolic flux vectors from extreme pathways: defining the alpha-spectrum.
Wiback, Sharon J; Mahadevan, Radhakrishnan; Palsson, Bernhard Ø
2003-10-07
The move towards genome-scale analysis of cellular functions has necessitated the development of analytical (in silico) methods to understand such large and complex biochemical reaction networks. One such method is extreme pathway analysis that uses stoichiometry and thermodynamic irreversibly to define mathematically unique, systemic metabolic pathways. These extreme pathways form the edges of a high-dimensional convex cone in the flux space that contains all the attainable steady state solutions, or flux distributions, for the metabolic network. By definition, any steady state flux distribution can be described as a nonnegative linear combination of the extreme pathways. To date, much effort has been focused on calculating, defining, and understanding these extreme pathways. However, little work has been performed to determine how these extreme pathways contribute to a given steady state flux distribution. This study represents an initial effort aimed at defining how physiological steady state solutions can be reconstructed from a network's extreme pathways. In general, there is not a unique set of nonnegative weightings on the extreme pathways that produce a given steady state flux distribution but rather a range of possible values. This range can be determined using linear optimization to maximize and minimize the weightings of a particular extreme pathway in the reconstruction, resulting in what we have termed the alpha-spectrum. The alpha-spectrum defines which extreme pathways can and cannot be included in the reconstruction of a given steady state flux distribution and to what extent they individually contribute to the reconstruction. It is shown that accounting for transcriptional regulatory constraints can considerably shrink the alpha-spectrum. The alpha-spectrum is computed and interpreted for two cases; first, optimal states of a skeleton representation of core metabolism that include transcriptional regulation, and second for human red blood cell metabolism under various physiological, non-optimal conditions.
Sensitivity of Rainfall Extremes Under Warming Climate in Urban India
NASA Astrophysics Data System (ADS)
Ali, H.; Mishra, V.
2017-12-01
Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.
NASA Astrophysics Data System (ADS)
Matyas, Cs.; Berki, I.; Drüszler, A.; Eredics, A.; Galos, B.; Moricz, N.; Rasztovits, E.
2012-04-01
In whole Central Europe agricultural production is highly vulnerable and sensitive to impacts of projected climatic changes. The low-elevation regions of the Carpathian Basin (most of the territory of Hungary), where precipitation is the minimum factor of production, are especially exposed to climatic extremes, especially to droughts. Rainfed agriculture, animal husbandry on nature-close pastures and nature-close forestry are the most sensitive sectors due to limited possibilities to counterbalance moisture supply constraints. These sectors have to be best prepared to frequency increase of extreme events, disasters and economic losses. So far, there is a lack of information about the middle and long term consequences on regional and local level. Therefore the importance of complex, long term management planning and of land use optimation is increasing. The aim of the initiative is to set up a fine-scale, GIS-based, complex, integrated system for the definition of the most important regional and local challenges and tasks of climate change adaptation and mitigation in agriculture, forestry, animal husbandry and also nature protection. The Service Center for Climate Change Adaptation in Agriculture is planned to provide the following services: § Complex, GIS-supported database, which integrates the basic information about present and projected climates, extremes, hydrology and soil conditions; § Evaluation of existing satellite-based and earth-based monitoring systems; § GIS-supported information about the future trends of climate change impacts on the agroecological potential and sensitivity status on regional and local level (e.g. land cover/use and expectable changes, production, water and carbon cycle, biodiversity and other ecosystem services, potential pests and diseases, tolerance limits etc.) in fine-scale horizontal resolution, based first of all on natural produce, including also social and economic consequences; § Complex decision supporting system on regional and local scale for middle- and long term adaptation and mitigation strategies, providing information on optimum technologies and energy balances. Cooperation with already existing Climate Service Centres and national and international collaboration in monitoring and research are important elements of the activity of the Centre. In the future, the Centre is planned to form part of a national information system on climate change adaptation and mitigation, supported by the Ministry of Development. Keywords: climate change impacts, forestry, rainfed agriculture, animal husbandry
NASA Astrophysics Data System (ADS)
Xie, Zunyi; Huete, Alfredo; Ma, Xuanlong; Restrepo-Coupe, Natalia; Devadas, Rakhesh; Clarke, Kenneth; Lewis, Megan
2016-12-01
Arid wetlands are important for biodiversity conservation, but sensitive and vulnerable to climate variability and hydroclimatic events. Amplification of the water cycle, including the increasing frequency and severity of droughts and wet extremes, is expected to alter spatial and temporal hydrological patterns in arid wetlands globally, with potential threats to ecosystem services and their functioning. Despite these pressing challenges, the ecohydrological interactions and resilience of arid wetlands to highly variable water regimes over long time periods remain largely unknown. Recent broad-scale drought and floods over Australia provide unique opportunities to improve our understanding of arid wetland ecosystem responses to hydroclimatic extremes. Here we analysed the ecohydrological dynamics of the Coongie Lakes arid wetland in central Australia, one of the world's largest Ramsar-designated wetlands, using more than two decades (1988-2011) of vegetation and floodwater extent retrievals derived from Landsat satellite observations. To explore the impacts of large-scale hydrological fluctuations on the arid wetland, we further coupled Landsat measurements with Total Water Storage Anomaly (TWSA) data obtained from the Gravity Recovery and Climate Experiment (GRACE) satellites. Pronounced seasonal and inter-annual variabilities of flood and vegetation activities were observed over the wetland, with variations in vegetation growth extent highly correlated with flood extent (r = 0.64, p < 0.05) that ranged from nearly zero to 3456 km2. We reported the hydrological dynamics and associated ecosystem responses to be largely driven by the two phases (El Niño and La Niña) of the El Nino-Southern Oscillation (ENSO) ocean-atmosphere system. Changes in flood and vegetation extent were better explained by GRACE-TWSA (r = 0.8, lag = 0 month) than rainfall (r = 0.34, lag = 3 months) over the water source area, demonstrating that TWS is a valuable hydrological indicator for complex dryland river systems. The protracted Millennium Drought from 2001 to 2009 resulted in long-term absence of major flood events, which substantially suppressed wetland vegetation growth. However, the 2010-11 La Niña induced flooding events led to an exceptionally large resurgence of vegetation, with a mean vegetation growth extent anomaly exceeding the historical average (1988-2011) by more than 1.5 standard deviations, suggesting a significant resilience of arid wetland ecosystems to climate variability. This study showed the ecological functioning of arid wetlands is particularly sensitive to large-scale hydrological fluctuations and extreme drought conditions, and vulnerable to future altered water regimes due to climate change. The methods developed herein can be applied to arid wetlands located in other dryland river systems across the globe.
Frank, Dorothea; Reichstein, Markus; Bahn, Michael; Thonicke, Kirsten; Frank, David; Mahecha, Miguel D; Smith, Pete; van der Velde, Marijn; Vicca, Sara; Babst, Flurin; Beer, Christian; Buchmann, Nina; Canadell, Josep G; Ciais, Philippe; Cramer, Wolfgang; Ibrom, Andreas; Miglietta, Franco; Poulter, Ben; Rammig, Anja; Seneviratne, Sonia I; Walz, Ariane; Wattenbach, Martin; Zavala, Miguel A; Zscheischler, Jakob
2015-01-01
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon–climate feedbacks. PMID:25752680
Frank, Dorothea; Reichstein, Markus; Bahn, Michael; Thonicke, Kirsten; Frank, David; Mahecha, Miguel D; Smith, Pete; van der Velde, Marijn; Vicca, Sara; Babst, Flurin; Beer, Christian; Buchmann, Nina; Canadell, Josep G; Ciais, Philippe; Cramer, Wolfgang; Ibrom, Andreas; Miglietta, Franco; Poulter, Ben; Rammig, Anja; Seneviratne, Sonia I; Walz, Ariane; Wattenbach, Martin; Zavala, Miguel A; Zscheischler, Jakob
2015-08-01
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon-climate feedbacks. © 2015 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
2013-01-01
The purpose of this study was to characterize responses in oxygen uptake ( V·O2), heart rate (HR), perceived exertion (OMNI scale) and integrated electromyogram (iEMG) readings during incremental Nordic walking (NW) and level walking (LW) on a treadmill. Ten healthy adults (four men, six women), who regularly engaged in physical activity in their daily lives, were enrolled in the study. All subjects were familiar with NW. Each subject began walking at 60 m/min for 3 minutes, with incremental increases of 10 m/min every 2 minutes up to 120 m/min V·O2 , V·E and HR were measured every 30 seconds, and the OMNI scale was used during the final 15 seconds of each exercise. EMG readings were recorded from the triceps brachii, vastus lateralis, biceps femoris, gastrocnemius, and tibialis anterior muscles. V·O2 was significantly higher during NW than during LW, with the exception of the speed of 70 m/min (P < 0.01). V·E and HR were higher during NW than LW at all walking speeds (P < 0.05 to 0.001). OMNI scale of the upper extremities was significantly higher during NW than during LW at all speeds (P < 0.05). Furthermore, the iEMG reading for the VL was lower during NW than during LW at all walking speeds, while the iEMG reading for the BF and GA muscles were significantly lower during NW than LW at some speeds. These data suggest that the use of poles in NW attenuates muscle activity in the lower extremities during the stance and push-off phases, and decreases that of the lower extremities and increase energy expenditure of the upper body and respiratory system at certain walking speeds. PMID:23406834
Monitoring and evaluating civil structures using measured vibration
NASA Astrophysics Data System (ADS)
Straser, Erik G.; Kiremidjian, Anne S.
1996-04-01
The need for a rapid assessment of the state of critical and conventional civil structures, such as bridges, control centers, airports, and hospitals, among many, has been amply demonstrated during recent natural disasters. Research is underway at Stanford University to develop a state-of-the-art automated damage monitoring system for long term and extreme event monitoring based on both ambient and forced response measurements. Such research requires a multi-disciplinary approach harnessing the talents and expertise of civil, electrical, and mechanical engineering to arrive at a novel hardware and software solution. Recent advances in silicon micro-machining and microprocessor design allow for the economical integration of sensing, processing, and communication components. Coupling these technological advances with parameter identification algorithms allows for the realization of extreme event damage monitoring systems for civil structures. This paper addresses the first steps toward the development of a near real-time damage diagnostic and monitoring system based on structural response to extreme events. Specifically, micro-electro-mechanical- structures (MEMS) and microcontroller embedded systems (MES) are demonstrated to be an effective platform for the measurement and analysis of civil structures. Experimental laboratory tests with small scale model specimens and a preliminary sensor module are used to evaluate hardware and obtain structural response data from input accelerograms. A multi-step analysis procedure employing ordinary least squares (OLS), extended Kalman filtering (EKF), and a substructuring approach is conducted to extract system characteristics of the model. Results from experimental tests and system identification (SI) procedures as well as fundamental system design issues are presented.
NASA Astrophysics Data System (ADS)
Pulkkinen, A. A.; Bernabeu, E.; Weigel, R. S.; Kelbert, A.; Rigler, E. J.; Bedrosian, P.; Love, J. J.
2017-12-01
Development of realistic storm scenarios that can be played through the exposed systems is one of the key requirements for carrying out quantitative space weather hazards assessments. In the geomagnetically induced currents (GIC) and power grids context, these scenarios have to quantify the spatiotemporal evolution of the geoelectric field that drives the potentially hazardous currents in the system. In response to the Federal Energy Regulatory Commission (FERC) order 779, a team of scientists and engineers that worked under the auspices of North American Electric Reliability Corporation (NERC), has developed extreme geomagnetic storm and geoelectric field benchmark(s) that use various scaling factors that account for geomagnetic latitude and ground structure of the locations of interest. These benchmarks, together with the information generated in the National Space Weather Action Plan, are the foundation for the hazards assessments that the industry will be carrying out in response to the FERC order and under the auspices of the National Science and Technology Council. While the scaling factors developed in the past work were based on the best available information, there is now significant new information available for parts of the U.S. pertaining to the ground response to external geomagnetic field excitation. The significant new information includes the results magnetotelluric surveys that have been conducted over the past few years across the contiguous US and results from previous surveys that have been made available in a combined online database. In this paper, we distill this new information in the framework of the NERC benchmark and in terms of updated ground response scaling factors thereby allowing straightforward utilization in the hazard assessments. We also outline the path forward for improving the overall extreme event benchmark scenario(s) including generalization of the storm waveforms and geoelectric field spatial patterns.
Multiscale Resilience of Complex Systems
NASA Astrophysics Data System (ADS)
Tchiguirinskaia, I.; Schertzer, D. J. M.; Giangola-Murzyn, A.; Hoang Cong, T.
2014-12-01
We first argue the need for well defined resilience metrics to better evaluate the resilience of complex systems such as (peri-)urban flood management systems. We review both the successes and limitations of resilience metrics in the framework of dynamical systems and their generalization in the framework of the viability theory. We then point out that the most important step to achieve is to define resilience across scales instead of doing it at a given scale. Our preliminary, critical analysis of the series of attempts to define an operational resilience metrics led us to consider a scale invariant metrics based on the scale independent codimension of extreme singularities. Multifractal downscaling of climate scenarios can be considered as a first illustration. We focussed on a flood scenario evaluation method with the help of two singularities γ_s and γ_Max, corresponding respectively to an effective and a probable maximum singularity, that yield an innovative framework to address the issues of flood resilience systems in a scale independent manner. Indeed, the stationarity of the universal multifractal parameters would result into a rather stable value of probable maximum singularity γ_s. By fixing the limit of acceptability for a maximum flood water depth at a given scale, with a corresponding singularity, we effectively fix the threshold of the probable maximum singularity γ_s as a criterion of the flood resilience we accept. Then various scenarios of flood resilient measures could be simulated with the help of Multi-Hydro under upcoming climat scenarios. The scenarios that result in estimates of either γ_Max or γ_s below the pre-selected γ_s value will assure the effective flood resilience of the whole modeled system across scales. The research for this work was supported, in part, by the EU FP7 SMARTesT and INTERREG IVB RainGain projects.
A Harder Rain is Going to Fall: Challenges for Actionable Projections of Extremes
NASA Astrophysics Data System (ADS)
Collins, W.
2014-12-01
Hydrometeorological extremes are projected to increase in both severity and frequency as the Earth's surface continues to warm in response to anthropogenic emissions of greenhouse gases. These extremes will directly affect the availability and reliability of water and other critical resources. The most comprehensive suite of multi-model projections has been assembled under the Coupled Model Intercomparison Project version 5 (CMIP5) and assessed in the Fifth Assessment (AR5) of the Intergovernmental Panel on Climate Change (IPCC). In order for these projections to be actionable, the projections should exhibit consistency and fidelity down to the local length and timescales required for operational resource planning, for example the scales relevant for water allocations from a major watershed. In this presentation, we summarize the length and timescales relevant for resource planning and then use downscaled versions of the IPCC simulations over the contiguous United States to address three questions. First, over what range of scales is there quantitative agreement between the simulated historical extremes and in situ measurements? Second, does this range of scales in the historical and future simulations overlap with the scales relevant for resource management and adaptation? Third, does downscaling enhance the degree of multi-model consistency at scales smaller than the typical global model resolution? We conclude by using these results to highlight requirements for further model development to make the next generation of models more useful for planning purposes.
NASA Astrophysics Data System (ADS)
Switzer, A.; Yap, W.; Lauro, F.; Gouramanis, C.; Dominey-Howes, D.; Labbate, M.
2016-12-01
This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.
NASA Astrophysics Data System (ADS)
Sorooshian, S.; Nguyen, P.; Hsu, K. L.
2017-12-01
This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.
Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiu, Dongbin
2017-03-03
The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.
van der Linden, Marietta L; Jahed, Sadaf; Tennant, Nicola; Verheul, Martine H G
2018-03-01
RaceRunning enables athletes with limited or no walking ability to propel themselves independently using a three-wheeled running bike that has a saddle and a chest plate for support but no pedals. For RaceRunning to be included as a Para athletics event, an evidence-based classification system is required. Therefore, the aim of this study was to assess the association between a range of impairment measures and RaceRunning performance. The following impairment measures were recorded: lower limb muscle strength assessed using Manual Muscle Testing (MMT), selective voluntary motor control assessed using the Selective Control Assessment of the Lower Extremity (SCALE), spasticity recorded using both the Australian Spasticity Assessment Score (ASAS) and Modified Ashworth Scale (MAS), passive range of motion (ROM) of the lower extremities and the maximum static step length achieved on a stationary bike (MSSL). Associations between impairment measures and 100-meter race speed were assessed using Spearman's correlation coefficients. Sixteen male and fifteen female athletes (27 with cerebral palsy), aged 23 (SD = 7) years, Gross Motor Function Classification System levels ranging from II to V, participated. The MSSL averaged over both legs and the ASAS, MAS, SCALE, and MMT summed over all joints and both legs, significantly correlated with 100 m race performance (rho: 0.40-0.54). Passive knee extension was the only ROM measure that was significantly associated with race speed (rho = 0.48). These results suggest that lower limb spasticity, isometric leg strength, selective voluntary motor control and passive knee extension impact performance in RaceRunning athletes. This supports the potential use of these measures in a future evidence-based classification system. Copyright © 2018 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilson, Mark A.; Baljon, Arlette R. C.
The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves show nonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topologymore » resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Lastly, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.« less
ScaleNet: a literature-based model of scale insect biology and systematics
García Morales, Mayrolin; Denno, Barbara D.; Miller, Douglass R.; Miller, Gary L.; Ben-Dov, Yair; Hardy, Nate B.
2016-01-01
Scale insects (Hemiptera: Coccoidea) are small herbivorous insects found on all continents except Antarctica. They are extremely invasive, and many species are serious agricultural pests. They are also emerging models for studies of the evolution of genetic systems, endosymbiosis and plant-insect interactions. ScaleNet was launched in 1995 to provide insect identifiers, pest managers, insect systematists, evolutionary biologists and ecologists efficient access to information about scale insect biological diversity. It provides comprehensive information on scale insects taken directly from the primary literature. Currently, it draws from 23 477 articles and describes the systematics and biology of 8194 valid species. For 20 years, ScaleNet ran on the same software platform. That platform is no longer viable. Here, we present a new, open-source implementation of ScaleNet. We have normalized the data model, begun the process of correcting invalid data, upgraded the user interface, and added online administrative tools. These improvements make ScaleNet easier to use and maintain and make the ScaleNet data more accurate and extendable. Database URL: http://scalenet.info PMID:26861659
Shock compression response of forsterite above 250 GPa
Sekine, Toshimori; Ozaki, Norimasa; Miyanishi, Kohei; Asaumi, Yuto; Kimura, Tomoaki; Albertazzi, Bruno; Sato, Yuya; Sakawa, Youichi; Sano, Takayoshi; Sugita, Seiji; Matsui, Takafumi; Kodama, Ryosuke
2016-01-01
Forsterite (Mg2SiO4) is one of the major planetary materials, and its behavior under extreme conditions is important to understand the interior structure of large planets, such as super-Earths, and large-scale planetary impact events. Previous shock compression measurements of forsterite indicate that it may melt below 200 GPa, but these measurements did not go beyond 200 GPa. We report the shock response of forsterite above ~250 GPa, obtained using the laser shock wave technique. We simultaneously measured the Hugoniot and temperature of shocked forsterite and interpreted the results to suggest the following: (i) incongruent crystallization of MgO at 271 to 285 GPa, (ii) phase transition of MgO at 285 to 344 GPa, and (iii) remelting above ~470 to 500 GPa. These exothermic and endothermic reactions are seen to occur under extreme conditions of pressure and temperature. They indicate complex structural and chemical changes in the system MgO-SiO2 at extreme pressures and temperatures and will affect the way we understand the interior processes of large rocky planets as well as material transformation by impacts in the formation of planetary systems. PMID:27493993
Temporal and spatial characterization of zenith total delay (ZTD) in North Europe
NASA Astrophysics Data System (ADS)
Stoew, B.; Elgered, G.
2003-04-01
The estimates of ZTD are often treated as realizations of random walk stochastic processes. We derive the corresponding process parameters for 34 different locations in North Europe using two measurement techniques - Global Positioning System (GPS) and Water Vapor Radiometer (WVR). GPS-estimated ZTD is an excellent candidate for data assimilation in numerical weather prediction (NWP) models in terms of both spatial and temporal resolution. We characterize the long term behavior of the ZTD as a function of site latitude and height. The spatial characteristics of the ZTD are studied as a function of site separation and season. We investigate the influence of the time-interpolated atmospheric pressure data used for the estimation of zenith wet delay (ZWD) from ZTD. Characterization of extreme atmospheric events can aid the development of an early warning system. We consider two types of extreme meteorological phenomena with regard to their spatial scales. The first type concerns larger regions (including several GPS sites); the extreme weather is characterized by intense precipitation which may result in a flood. The second type is related to local variations in the ZWD/ZTD and can be used for detection/monitoring of passing atmospheric fronts.
Quasi-real-time end-to-end simulations of ELT-scale adaptive optics systems on GPUs
NASA Astrophysics Data System (ADS)
Gratadour, Damien
2011-09-01
Our team has started the development of a code dedicated to GPUs for the simulation of AO systems at the E-ELT scale. It uses the CUDA toolkit and an original binding to Yorick (an open source interpreted language) to provide the user with a comprehensive interface. In this paper we present the first performance analysis of our simulation code, showing its ability to provide Shack-Hartmann (SH) images and measurements at the kHz scale for VLT-sized AO system and in quasi-real-time (up to 70 Hz) for ELT-sized systems on a single top-end GPU. The simulation code includes multiple layers atmospheric turbulence generation, ray tracing through these layers, image formation at the focal plane of every sub-apertures of a SH sensor using either natural or laser guide stars and centroiding on these images using various algorithms. Turbulence is generated on-the-fly giving the ability to simulate hours of observations without the need of loading extremely large phase screens in the global memory. Because of its performance this code additionally provides the unique ability to test real-time controllers for future AO systems under nominal conditions.
A Venus-mass Planet Orbiting a Brown Dwarf: A Missing Link between Planets and Moons
NASA Astrophysics Data System (ADS)
Udalski, A.; Jung, Y. K.; Han, C.; Gould, A.; Kozłowski, S.; Skowron, J.; Poleski, R.; Soszyński, I.; Pietrukowicz, P.; Mróz, P.; Szymański, M. K.; Wyrzykowski, Ł.; Ulaczyk, K.; Pietrzyński, G.; Shvartzvald, Y.; Maoz, D.; Kaspi, S.; Gaudi, B. S.; Hwang, K.-H.; Choi, J.-Y.; Shin, I.-G.; Park, H.; Bozza, V.
2015-10-01
The co-planarity of solar system planets led Kant to suggest that they formed from an accretion disk, and the discovery of hundreds of such disks around young stars as well as hundreds of co-planar planetary systems by the Kepler satellite demonstrate that this formation mechanism is extremely widespread. Many moons in the solar system, such as the Galilean moons of Jupiter, also formed out of the accretion disks that coalesced into the giant planets. Here we report the discovery of an intermediate system, OGLE-2013-BLG-0723LB/Bb, composed of a Venus-mass planet orbiting a brown dwarf, which may be viewed either as a scaled-down version of a planet plus a star or as a scaled-up version of a moon plus a planet orbiting a star. The latter analogy can be further extended since they orbit in the potential of a larger, stellar body. For ice-rock companions formed in the outer parts of accretion disks, like Uranus and Callisto, the scaled masses and separations of the three types of systems are similar, leading us to suggest that the formation processes of companions within accretion disks around stars, brown dwarfs, and planets are similar.
Non-Gaussian Nature of Fracture and the Survival of Fat-Tail Exponents
NASA Astrophysics Data System (ADS)
Tallakstad, Ken Tore; Toussaint, Renaud; Santucci, Stephane; Måløy, Knut Jørgen
2013-04-01
We study the fluctuations of the global velocity Vl(t), computed at various length scales l, during the intermittent mode-I propagation of a crack front. The statistics converge to a non-Gaussian distribution, with an asymmetric shape and a fat tail. This breakdown of the central limit theorem (CLT) is due to the diverging variance of the underlying local crack front velocity distribution, displaying a power law tail. Indeed, by the application of a generalized CLT, the full shape of our experimental velocity distribution at large scale is shown to follow the stable Levy distribution, which preserves the power law tail exponent under upscaling. This study aims to demonstrate in general for crackling noise systems how one can infer the complete scale dependence of the activity—and extreme event distributions—by measuring only at a global scale.
Present-day irrigation mitigates heat extremes
Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; ...
2017-02-16
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 ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » 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 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. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less
Nuclear Power - Post Fukushima
NASA Astrophysics Data System (ADS)
Reyes, Jose, Jr.
2011-10-01
The extreme events that led to the prolonged power outage at the Fukushima Daiicchi nuclear plant have highlighted the importance of assuring a means for stable long term cooling of the nuclear fuel and containment following a complete station blackout. Legislative bodies, regulatory agencies and industry are drawing lessons from those events and considering what changes, if any, are needed to nuclear power, post Fukushima. The enhanced safety of a new class of reactor designed by NuScale Power is drawing significant attention in light of the Fukushima events. During normal operation, each NuScale containment is fully immersed in a water-filled stainless steel lined concrete pool that resides underground. The pool, housed in a Seismic Category I building, is large enough to provided 30 days of core and containment cooling without adding water. After 30 days, the decay heat generations coupled with thermal radiation heat transfer is completely adequate to remove core decay heat for an unlimited period of time. These passive power systems can perform their function without requiring an external supply of water of power. An assessment of the NuScale passive systems is being performed through a comprehensive test program that includes the NuScale integral system test facility at Oregon State University
NASA Astrophysics Data System (ADS)
Watkins, N. W.
2013-01-01
I review the hierarchy of approaches to complex systems, focusing particularly on stochastic equations. I discuss how the main models advocated by the late Benoit Mandelbrot fit into this classification, and how they continue to contribute to cross-disciplinary approaches to the increasingly important problems of correlated extreme events and unresolved scales. The ideas have broad importance, with applications ranging across science areas as diverse as the heavy tailed distributions of intense rainfall in hydrology, after which Mandelbrot named the "Noah effect"; the problem of correlated runs of dry summers in climate, after which the "Joseph effect" was named; and the intermittent, bursty, volatility seen in finance and fluid turbulence.
Tambora and the mackerel year: phenology and fisheries during an extreme climate event
Alexander, Karen E.; Leavenworth, William B.; Hall, Carolyn; Mattocks, Steven; Bittner, Steven M.; Klein, Emily; Staudinger, Michelle D.; Bryan, Alexander; Rosset, Julianne; Willis, Theodore V.; Carr, Benjamin H.; Jordaan, Adrian
2017-01-01
Global warming has increased the frequency of extreme climate events, yet responses of biological and human communities are poorly understood, particularly for aquatic ecosystems and fisheries. Retrospective analysis of known outcomes may provide insights into the nature of adaptations and trajectory of subsequent conditions. We consider the 1815 eruption of the Indonesian volcano Tambora and its impact on Gulf of Maine (GoM) coastal and riparian fisheries in 1816. Applying complex adaptive systems theory with historical methods, we analyzed fish export data and contemporary climate records to disclose human and piscine responses to Tambora’s extreme weather at different spatial and temporal scales while also considering sociopolitical influences. Results identified a tipping point in GoM fisheries induced by concatenating social and biological responses to extreme weather. Abnormal daily temperatures selectively affected targeted fish species—alewives, shad, herring, and mackerel—according to their migration and spawning phenologies and temperature tolerances. First to arrive, alewives suffered the worst. Crop failure and incipient famine intensified fishing pressure, especially in heavily settled regions where dams already compromised watersheds. Insufficient alewife runs led fishers to target mackerel, the next species appearing in abundance along the coast; thus, 1816 became the “mackerel year.” Critically, the shift from riparian to marine fisheries persisted and expanded after temperatures moderated and alewives recovered. We conclude that contingent human adaptations to extraordinary weather permanently altered this complex system. Understanding how adaptive responses to extreme events can trigger unintended consequences may advance long-term planning for resilience in an uncertain future.
Tambora and the mackerel year: Phenology and fisheries during an extreme climate event
Alexander, Karen E.; Leavenworth, William B.; Willis, Theodore V.; Hall, Carolyn; Mattocks, Steven; Bittner, Steven M.; Klein, Emily; Staudinger, Michelle; Bryan, Alexander; Rosset, Julianne; Carr, Benjamin H.; Jordaan, Adrian
2017-01-01
Global warming has increased the frequency of extreme climate events, yet responses of biological and human communities are poorly understood, particularly for aquatic ecosystems and fisheries. Retrospective analysis of known outcomes may provide insights into the nature of adaptations and trajectory of subsequent conditions. We consider the 1815 eruption of the Indonesian volcano Tambora and its impact on Gulf of Maine (GoM) coastal and riparian fisheries in 1816. Applying complex adaptive systems theory with historical methods, we analyzed fish export data and contemporary climate records to disclose human and piscine responses to Tambora’s extreme weather at different spatial and temporal scales while also considering sociopolitical influences. Results identified a tipping point in GoM fisheries induced by concatenating social and biological responses to extreme weather. Abnormal daily temperatures selectively affected targeted fish species—alewives, shad, herring, and mackerel—according to their migration and spawning phenologies and temperature tolerances. First to arrive, alewives suffered the worst. Crop failure and incipient famine intensified fishing pressure, especially in heavily settled regions where dams already compromised watersheds. Insufficient alewife runs led fishers to target mackerel, the next species appearing in abundance along the coast; thus, 1816 became the “mackerel year.” Critically, the shift from riparian to marine fisheries persisted and expanded after temperatures moderated and alewives recovered. We conclude that contingent human adaptations to extraordinary weather permanently altered this complex system. Understanding how adaptive responses to extreme events can trigger unintended consequences may advance long-term planning for resilience in an uncertain future. PMID:28116356
FALCON reactor-pumped laser description and program overview
DOE Office of Scientific and Technical Information (OSTI.GOV)
None
1989-12-01
The FALCON (Fission Activated Laser CONcept) reactor-pumped laser program at Sandia National Laboratories is examining the feasibility of high-power systems pumped directly by the energy from a nuclear reactor. In this concept we use the highly energetic fission fragments from neutron induced fission to excite a large volume laser medium. This technology has the potential to scale to extremely large optical power outputs in a primarily self-powered device. A laser system of this type could also be relatively compact and capable of long run times without refueling.
ATHLETE: Trading Complexity for Mass in Roving Vehicles
NASA Technical Reports Server (NTRS)
Wilcox, Brian H.
2013-01-01
This paper describes a scaling analysis of ATHLETE for exploration of the moon, Mars and Near-Earth Asteroids (NEAs) in comparison to a more conventional vehicle configuration. Recently, the focus of human exploration beyond LEO has been on NEAs. A low gravity testbed has been constructed in the ATHLETE lab, with six computer-controlled winches able to lift ATHLETE and payloads so as to simulate the motion of the system in the vicinity of a NEA or to simulate ATHLETE on extreme terrain in lunar or Mars gravity. Test results from this system are described.
NASA Astrophysics Data System (ADS)
Potirakis, Stelios M.; Contoyiannis, Yiannis; Kopanas, John; Kalimeris, Anastasios; Antonopoulos, George; Peratzakis, Athanasios; Eftaxias, Konstantinos; Nomicos, Costantinos
2014-05-01
When one considers a phenomenon that is "complex" refers to a system whose phenomenological laws that describe the global behavior of the system, are not necessarily directly related to the "microscopic" laws that regulate the evolution of its elementary parts. The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe disparate problems ranging from particle physics to economies of societies. Several authors have suggested that earthquake (EQ) dynamics can be analyzed within similar mathematical frameworks with economy dynamics, and neurodynamics. A central property of the EQ preparation process is the occurrence of coherent large-scale collective behavior with a very rich structure, resulting from repeated nonlinear interactions among the constituents of the system. As a result, nonextensive statistics is an appropriate, physically meaningful, tool for the study of EQ dynamics. Since the fracture induced electromagnetic (EM) precursors are observable manifestations of the underlying EQ preparation process, the analysis of a fracture induced EM precursor observed prior to the occurrence of a large EQ can also be conducted within the nonextensive statistics framework. Within the frame of the investigation for universal principles that may hold for different dynamical systems that are related to the genesis of extreme events, we present here statistical similarities of the pre-earthquake EM emissions related to an EQ, with the pre-ictal electrical brain activity related to an epileptic seizure, and with the pre-crisis economic observables related to the collapse of a share. It is demonstrated the all three dynamical systems' observables can be analyzed in the frame of nonextensive statistical mechanics, while the frequency-size relations of appropriately defined "events" that precede the extreme event related to each one of these different systems present striking quantitative similarities. It is also demonstrated that, for the considered systems, the nonextensive parameter q increases as the extreme event approaches, which indicates that the strength of the long-memory / long-range interactions between the constituents of the system increases characterizing the dynamics of the system.
Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia
NASA Astrophysics Data System (ADS)
Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep
2014-05-01
Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the dates involving observations from multiple sites (rain gauges). The approach combines the POT (Peaks Over Threshold) with 'declustering' of the data to approximate independence based on the autocorrelation structure of each rainfall series. The cross correlation among sites is considered also to develop the event's criteria yielding a rational choice of the extreme dates given the 'spotty' nature of the intense convection. Based on the identified dates, we are developing a supporting tool for forecasting extreme rainfall based on the corresponding large-scale meteorological patterns (LSMPs). The LSMPs methodology focuses on the larger-scale patterns that the model are better able to forecast, as those larger-scale patterns create the conditions fostering the local EWE. Bootstrap resampling method is applied to highlight the key features that statistically significant with the extreme events. Grotjahn, R., and G. Faure. 2008: Composite Predictor Maps of Extraordinary Weather Events in the Sacramento California Region. Weather and Forecasting. 23: 313-335.
Ayachit, Utkarsh; Bauer, Andrew; Duque, Earl P. N.; ...
2016-11-01
A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. Our paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: Scalability, overhead,more » performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.« less
NASA Technical Reports Server (NTRS)
Britcher, C. P.
1983-01-01
Wind tunnel magnetic suspension and balance systems (MSBSs) have so far failed to find application at the large physical scales necessary for the majority of aerodynamic testing. Three areas of technology relevant to such application are investigated. Two variants of the Spanwise Magnet roll torque generation scheme are studied. Spanwise Permanent Magnets are shown to be practical and are experimentally demonstrated. Extensive computations of the performance of the Spanwise Iron Magnet scheme indicate powerful capability, limited principally be electromagnet technology. Aerodynamic testing at extreme attitudes is shown to be practical in relatively conventional MSBSs. Preliminary operation of the MSBS over a wide range of angles of attack is demonstrated. The impact of a requirement for highly reliable operation on the overall architecture of Large MSBSs is studied and it is concluded that system cost and complexity need not be seriously increased.
A new synoptic scale resolving global climate simulation using the Community Earth System Model
NASA Astrophysics Data System (ADS)
Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana
2014-12-01
High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."
Subsynoptic-scale features associated with extreme surface gusts in UK extratropical cyclone events
NASA Astrophysics Data System (ADS)
Earl, N.; Dorling, S.; Starks, M.; Finch, R.
2017-04-01
Numerous studies have addressed the mesoscale features within extratropical cyclones (ETCs) that are responsible for the most destructive winds, though few have utilized surface observation data, and most are based on case studies. By using a 39-station UK surface observation network, coupled with in-depth analysis of the causes of extreme gusts during the period 2008-2014, we show that larger-scale features (warm and cold conveyer belts) are most commonly associated with the top 1% of UK gusts but smaller-scale features generate the most extreme winds. The cold conveyor belt is far more destructive when joining the momentum of the ETC, rather than earlier in its trajectory, ahead of the approaching warm front. Sting jets and convective lines account for two thirds of severe surface gusts in the UK.
Springtime extreme moisture transport into the Arctic and its impact on sea ice concentration
NASA Astrophysics Data System (ADS)
Yang, Wenchang; Magnusdottir, Gudrun
2017-05-01
Recent studies suggest that springtime moisture transport into the Arctic can initiate sea ice melt that extends to a large area in the following summer and fall, which can help explain Arctic sea ice interannual variability. Yet the impact from an individual moisture transport event, especially the extreme ones, is unclear on synoptic to intraseasonal time scales and this is the focus of the current study. Springtime extreme moisture transport into the Arctic from a daily data set is found to be dominant over Atlantic longitudes. Lag composite analysis shows that these extreme events are accompanied by a substantial sea ice concentration reduction over the Greenland-Barents-Kara Seas that lasts around a week. Surface air temperature also becomes anomalously high over these seas and cold to the west of Greenland as well as over the interior Eurasian continent. The blocking weather regime over the North Atlantic is mainly responsible for the extreme moisture transport, occupying more than 60% of the total extreme days, while the negative North Atlantic Oscillation regime is hardly observed at all during the extreme transport days. These extreme moisture transport events appear to be preceded by eastward propagating large-scale tropical convective forcing by as long as 2 weeks but with great uncertainty due to lack of statistical significance.
Statistical downscaling modeling with quantile regression using lasso to estimate extreme rainfall
NASA Astrophysics Data System (ADS)
Santri, Dewi; Wigena, Aji Hamim; Djuraidah, Anik
2016-02-01
Rainfall is one of the climatic elements with high diversity and has many negative impacts especially extreme rainfall. Therefore, there are several methods that required to minimize the damage that may occur. So far, Global circulation models (GCM) are the best method to forecast global climate changes include extreme rainfall. Statistical downscaling (SD) is a technique to develop the relationship between GCM output as a global-scale independent variables and rainfall as a local- scale response variable. Using GCM method will have many difficulties when assessed against observations because GCM has high dimension and multicollinearity between the variables. The common method that used to handle this problem is principal components analysis (PCA) and partial least squares regression. The new method that can be used is lasso. Lasso has advantages in simultaneuosly controlling the variance of the fitted coefficients and performing automatic variable selection. Quantile regression is a method that can be used to detect extreme rainfall in dry and wet extreme. Objective of this study is modeling SD using quantile regression with lasso to predict extreme rainfall in Indramayu. The results showed that the estimation of extreme rainfall (extreme wet in January, February and December) in Indramayu could be predicted properly by the model at quantile 90th.
Revisiting the 1993 historical extreme precipitation and damaging flood event in Central Nepal
NASA Astrophysics Data System (ADS)
Marahatta, S.; Adhikari, L.; Pokharel, B.
2017-12-01
Nepal is ranked the fourth most climate-vulnerable country in the world and it is prone to different weather-related hazards including droughts, floods, and landslides [Wang et al., 2013; Gillies et al., 2013]. Although extremely vulnerable to extreme weather events, there are no extreme weather warning system established to inform public in Nepal. Nepal has witnessed frequent drought and flood events, however, the extreme precipitation that occurred on 19-20 July 1993 created a devastating flood and landslide making it the worst weather disaster in the history of Nepal. During the second week of July, Nepal and northern India experienced abnormal dry condition due to the shifting of the monsoon trough to central India. The dry weather changed to wet when monsoon trough moved northward towards foothills of the Himalayas. Around the same period, a low pressure center was located over the south-central Nepal. The surface low was supported by the mid-, upper-level shortwave and cyclonic vorticity. A meso-scale convective system created record breaking one day rainfall (540 mm) in the region. The torrential rain impacted the major hydropower reservoir, Bagmati barrage in Karmaiya and triggered many landslides and flash floods. The region had the largest hydropower (Kulekhani hydropower, 92 MW) of the country at that time and the storm event deposited extremely large amount of sediments that reduced one-fourth (4.8 million m3) of reservoir dead storage (12 million m3). The 1-in-1000 years flood damaged the newly constructed barrage and took more than 700 lives. Major highways were damaged cutting off supply of daily needed goods, including food and gas, in the capital city, Kathmandu, for more than a month. In this presentation, the meteorological conditions of the extreme event will be diagnosed and the impact of the sedimentation due to the flood on Kulekhani reservoir and hydropower generation will be discussed.
Study of multi-functional precision optical measuring system for large scale equipment
NASA Astrophysics Data System (ADS)
Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi
2017-10-01
The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.
Assessing the ability of operational snow models to predict snowmelt runoff extremes (Invited)
NASA Astrophysics Data System (ADS)
Wood, A. W.; Restrepo, P. J.; Clark, M. P.
2013-12-01
In the western US, the snow accumulation and melt cycle of winter and spring plays a critical role in the region's water management strategies. Consequently, the ability to predict snowmelt runoff at time scales from days to seasons is a key input for decisions in reservoir management, whether for avoiding flood hazards or supporting environmental flows through the scheduling of releases in spring, or for allocating releases for multi-state water distribution in dry seasons of year (using reservoir systems to provide an invaluable buffer for many sectors against drought). Runoff forecasts thus have important benefits at both wet and dry extremes of the climatological spectrum. The importance of the prediction of the snow cycle motivates an assessment of the strengths and weaknesses of the US's central operational snow model, SNOW17, in contrast to process-modeling alternatives, as they relate to simulating observed snowmelt variability and extremes. To this end, we use a flexible modeling approach that enables an investigation of different choices in model structure, including model physics, parameterization and degree of spatiotemporal discretization. We draw from examples of recent extreme events in western US watersheds and an overall assessment of retrospective model performance to identify fruitful avenues for advancing the modeling basis for the operational prediction of snow-related runoff extremes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thiery, Wim; Davin, Edouard L.; Lawrence, David M.
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 ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » 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 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. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less
NASA Astrophysics Data System (ADS)
Avanzi, Francesco; De Michele, Carlo; Gabriele, Salvatore; Ghezzi, Antonio; Rosso, Renzo
2015-04-01
Here, we show how atmospheric circulation and topography rule the variability of depth-duration-frequency (DDF) curves parameters, and we discuss how this variability has physical implications on the formation of extreme precipitations at high elevations. A DDF is a curve ruling the value of the maximum annual precipitation H as a function of duration D and the level of probability F. We consider around 1500 stations over the Italian territory, with at least 20 years of data of maximum annual precipitation depth at different durations. We estimated the DDF parameters at each location by using the asymptotic distribution of extreme values, i.e. the so-called Generalized Extreme Value (GEV) distribution, and considering a statistical simple scale invariance hypothesis. Consequently, a DDF curve depends on five different parameters. A first set relates H with the duration (namely, the mean value of annual maximum precipitation depth for unit duration and the scaling exponent), while a second set links H to F (namely, a scale, position and shape parameter). The value of the shape parameter has consequences on the type of random variable (unbounded, upper or lower bounded). This extensive analysis shows that the variability of the mean value of annual maximum precipitation depth for unit duration obeys to the coupled effect of topography and modal direction of moisture flux during extreme events. Median values of this parameter decrease with elevation. We called this phenomenon "reverse orographic effect" on extreme precipitation of short durations, since it is in contrast with general knowledge about the orographic effect on mean precipitation. Moreover, the scaling exponent is mainly driven by topography alone (with increasing values of this parameter at increasing elevations). Therefore, the quantiles of H(D,F) at durations greater than unit turn to be more variable at high elevations than at low elevations. Additionally, the analysis of the variability of the shape parameter with elevation shows that extreme events at high elevations appear to be distributed according to an upper bounded probability distribution. These evidences could be a characteristic sign of the formation of extreme precipitation events at high elevations.
Best geoscience approach to complex systems in environment
NASA Astrophysics Data System (ADS)
Mezemate, Yacine; Tchiguirinskaia, Ioulia; Schertzer, Daniel
2017-04-01
The environment is a social issue that continues to grow in importance. Its complexity, both cross-disciplinary and multi-scale, has given rise to a large number of scientific and technological locks, that complex systems approaches can solve. Significant challenges must met to achieve the understanding of the environmental complexes systems. There study should proceed in some steps in which the use of data and models is crucial: - Exploration, observation and basic data acquisition - Identification of correlations, patterns, and mechanisms - Modelling - Model validation, implementation and prediction - Construction of a theory Since the e-learning becomes a powerful tool for knowledge and best practice shearing, we use it to teach the environmental complexities and systems. In this presentation we promote the e-learning course dedicated for a large public (undergraduates, graduates, PhD students and young scientists) which gather and puts in coherence different pedagogical materials of complex systems and environmental studies. This course describes a complex processes using numerous illustrations, examples and tests that make it "easy to enjoy" learning process. For the seek of simplicity, the course is divided in different modules and at the end of each module a set of exercises and program codes are proposed for a best practice. The graphical user interface (GUI) which is constructed using an open source Opale Scenari offers a simple navigation through the different module. The course treats the complex systems that can be found in environment and their observables, we particularly highlight the extreme variability of these observables over a wide range of scales. Using the multifractal formalism through different applications (turbulence, precipitation, hydrology) we demonstrate how such extreme variability of the geophysical/biological fields should be used solving everyday (geo-)environmental chalenges.
NASA Astrophysics Data System (ADS)
Chetty, S.; Field, L. A.
2013-12-01
The Arctic ocean's continuing decrease of summer-time ice is related to rapidly diminishing multi-year ice due to the effects of climate change. Ice911 Research aims to develop environmentally respectful materials that when deployed will increase the albedo, enhancing the formation and/preservation of multi-year ice. Small scale deployments using various materials have been done in Canada, California's Sierra Nevada Mountains and a pond in Minnesota to test the albedo performance and environmental characteristics of these materials. SWIMS is a sophisticated autonomous sensor system being developed to measure the albedo, weather, water temperature and other environmental parameters. The system (SWIMS) employs low cost, high accuracy/precision sensors, high resolution cameras, and an extreme environment command and data handling computer system using satellite and terrestrial wireless communication. The entire system is solar powered with redundant battery backup on a floating buoy platform engineered for low temperature (-40C) and high wind conditions. The system also incorporates tilt sensors, sonar based ice thickness sensors and a weather station. To keep the costs low, each SWIMS unit measures incoming and reflected radiation from the four quadrants around the buoy. This allows data from four sets of sensors, cameras, weather station, water temperature probe to be collected and transmitted by a single on-board solar powered computer. This presentation covers the technical, logistical and cost challenges in designing, developing and deploying these stations in remote, extreme environments. Image captured by camera #3 of setting sun on the SWIMS station One of the images captured by SWIMS Camera #4
Extreme Precipitation and High-Impact Landslides
NASA Technical Reports Server (NTRS)
Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa
2012-01-01
It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing teleconnections from ENSO as likely contributors to regional precipitation variability. This work demonstrates the potential for using satellite-based precipitation estimates to identify potentially active landslide areas at the global scale in order to improve landslide cataloging and quantify landslide triggering at daily, monthly and yearly time scales.
Finding a roadmap to achieve large neuromorphic hardware systems
Hasler, Jennifer; Marr, Bo
2013-01-01
Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are reaching physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation. Toward this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time. PMID:24058330
Yu, Wenya; Lv, Yipeng; Hu, Chaoqun; Liu, Xu; Chen, Haiping; Xue, Chen; Zhang, Lulu
2018-01-01
Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise.
Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R
2012-01-01
Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carothers, Christopher D.; Meredith, Jeremy S.; Blanco, Marc
Performance modeling of extreme-scale applications on accurate representations of potential architectures is critical for designing next generation supercomputing systems because it is impractical to construct prototype systems at scale with new network hardware in order to explore designs and policies. However, these simulations often rely on static application traces that can be difficult to work with because of their size and lack of flexibility to extend or scale up without rerunning the original application. To address this problem, we have created a new technique for generating scalable, flexible workloads from real applications, we have implemented a prototype, called Durango, thatmore » combines a proven analytical performance modeling language, Aspen, with the massively parallel HPC network modeling capabilities of the CODES framework.Our models are compact, parameterized and representative of real applications with computation events. They are not resource intensive to create and are portable across simulator environments. We demonstrate the utility of Durango by simulating the LULESH application in the CODES simulation environment on several topologies and show that Durango is practical to use for simulation without loss of fidelity, as quantified by simulation metrics. During our validation of Durango's generated communication model of LULESH, we found that the original LULESH miniapp code had a latent bug where the MPI_Waitall operation was used incorrectly. This finding underscores the potential need for a tool such as Durango, beyond its benefits for flexible workload generation and modeling.Additionally, we demonstrate the efficacy of Durango's direct integration approach, which links Aspen into CODES as part of the running network simulation model. Here, Aspen generates the application-level computation timing events, which in turn drive the start of a network communication phase. Results show that Durango's performance scales well when executing both torus and dragonfly network models on up to 4K Blue Gene/Q nodes using 32K MPI ranks, Durango also avoids the overheads and complexities associated with extreme-scale trace files.« less
NASA Astrophysics Data System (ADS)
Akanda, A. S.; Jutla, A.; Huq, A.; Colwell, R. R.
2014-12-01
Cholera is a global disease, with significantly large outbreaks occurring since the 1990s, notably in Sub-Saharan Africa and South Asia and recently in Haiti, in the Caribbean. Critical knowledge gaps remain in the understanding of the annual recurrence in endemic areas and the nature of epidemic outbreaks, especially those that follow extreme hydroclimatic events. Teleconnections with large-scale climate phenomena affecting regional scale hydroclimatic drivers of cholera dynamics remain largely unexplained. For centuries, the Bengal delta region has been strongly influenced by the asymmetric availability of water in the rivers Ganges and the Brahmaputra. As these two major rivers are known to have strong contrasting affects on local cholera dynamics in the region, we argue that the role of El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), or other phenomena needs to be interpreted in the context of the seasonal role of individual rivers and subsequent impact on local environmental processes, not as a teleconnection having a remote and unified effect. We present a modified hypothesis that the influences of large-scale climate phenomena such as ENSO and IOD on Bengal cholera can be explicitly identified and incorporated through regional scale hydroclimatic drivers. Here, we provide an analytical review of the literature addressing cholera and climate linkages and present hypotheses, based on recent evidence, and quantification on the role of regional scale hydroclimatic drivers of cholera. We argue that the seasonal changes in precipitation and temperature, and resulting river discharge in the GBM basin region during ENSO and IOD events have a dominant combined effect on the endemic persistence and the epidemic vulnerability to cholera outbreaks in spring and fall seasons, respectively, that is stronger than the effect of localized hydrological and socio-economic sensitivities in Bangladesh. In addition, systematic identification of underlying seasonal hydroclimatic drivers will allow us to harness the inherent system memory of these processes to develop early warning systems and strengthen prevention measures.
NASA Astrophysics Data System (ADS)
Tadesse, T.; Zaitchik, B. F.; Habib, S.; Funk, C. C.; Senay, G. B.; Dinku, T.; Policelli, F. S.; Block, P.; Baigorria, G. A.; Beyene, S.; Wardlow, B.; Hayes, M. J.
2014-12-01
The development of effective strategies to adapt to changes in the character of droughts and floods in Africa will rely on improved seasonal prediction systems that are robust to an evolving climate baseline and can be integrated into disaster preparedness and response. Many efforts have been made to build models to improve seasonal forecasts in the Greater Horn of Africa region (GHA) using satellite and climate data, but these efforts and models must be improved and translated into future conditions under evolving climate conditions. This has considerable social significance, but is challenged by the nature of climate predictability and the adaptability of coupled natural and human systems facing exposure to climate extremes. To address these issues, work is in progress under a project funded by NASA. The objectives of the project include: 1) Characterize and explain large-scale drivers in the ocean-atmosphere-land system associated with years of extreme flood or drought in the GHA. 2) Evaluate the performance of state-of-the-art seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes. 3) Apply seasonal forecast systems to prediction of socially relevant impacts on crops, flood risk, and economic outcomes, and assess the value of these predictions to decision makers. 4) Evaluate the robustness of seasonal prediction systems to evolving climate conditions. The National Drought Mitigation Center (University of Nebraska-Lincoln, USA) is leading this project in collaboration with the USGS, Johns Hopkins University, University of Wisconsin-Madison, the International Research Institute for Climate and Society, NASA, and GHA local experts. The project is also designed to have active engagement of end users in various sectors, university researchers, and extension agents in GHA through workshops and/or webinars. This project is expected improve and implement new and existing climate- and remote sensing-based agricultural, meteorological, and hydrologic drought and flood monitoring products (or indicators) that can enhance the preparedness for extreme climate events and climate change adaptation and mitigation strategies in the GHA. Even though this project is in its first year, the preliminary results and future plans to carry out the objectives will be presented.
Rolex: Resilience-oriented language extensions for extreme-scale systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lucas, Robert F.; Hukerikar, Saurabh
Future exascale high-performance computing (HPC) systems will be constructed from VLSI devices that will be less reliable than those used today, and faults will become the norm, not the exception. This will pose significant problems for system designers and programmers, who for half-a-century have enjoyed an execution model that assumed correct behavior by the underlying computing system. The mean time to failure (MTTF) of the system scales inversely to the number of components in the system and therefore faults and resultant system level failures will increase, as systems scale in terms of the number of processor cores and memory modulesmore » used. However every error detected need not cause catastrophic failure. Many HPC applications are inherently fault resilient. Yet it is the application programmers who have this knowledge but lack mechanisms to convey it to the system. In this paper, we present new Resilience Oriented Language Extensions (Rolex) which facilitate the incorporation of fault resilience as an intrinsic property of the application code. We describe the syntax and semantics of the language extensions as well as the implementation of the supporting compiler infrastructure and runtime system. Furthermore, our experiments show that an approach that leverages the programmer's insight to reason about the context and significance of faults to the application outcome significantly improves the probability that an application runs to a successful conclusion.« less
Rolex: Resilience-oriented language extensions for extreme-scale systems
Lucas, Robert F.; Hukerikar, Saurabh
2016-05-26
Future exascale high-performance computing (HPC) systems will be constructed from VLSI devices that will be less reliable than those used today, and faults will become the norm, not the exception. This will pose significant problems for system designers and programmers, who for half-a-century have enjoyed an execution model that assumed correct behavior by the underlying computing system. The mean time to failure (MTTF) of the system scales inversely to the number of components in the system and therefore faults and resultant system level failures will increase, as systems scale in terms of the number of processor cores and memory modulesmore » used. However every error detected need not cause catastrophic failure. Many HPC applications are inherently fault resilient. Yet it is the application programmers who have this knowledge but lack mechanisms to convey it to the system. In this paper, we present new Resilience Oriented Language Extensions (Rolex) which facilitate the incorporation of fault resilience as an intrinsic property of the application code. We describe the syntax and semantics of the language extensions as well as the implementation of the supporting compiler infrastructure and runtime system. Furthermore, our experiments show that an approach that leverages the programmer's insight to reason about the context and significance of faults to the application outcome significantly improves the probability that an application runs to a successful conclusion.« less
Complexity-aware simple modeling.
Gómez-Schiavon, Mariana; El-Samad, Hana
2018-02-26
Mathematical models continue to be essential for deepening our understanding of biology. On one extreme, simple or small-scale models help delineate general biological principles. However, the parsimony of detail in these models as well as their assumption of modularity and insulation make them inaccurate for describing quantitative features. On the other extreme, large-scale and detailed models can quantitatively recapitulate a phenotype of interest, but have to rely on many unknown parameters, making them often difficult to parse mechanistically and to use for extracting general principles. We discuss some examples of a new approach-complexity-aware simple modeling-that can bridge the gap between the small-scale and large-scale approaches. Copyright © 2018 Elsevier Ltd. All rights reserved.
Laser interferometric high-precision geometry (angle and length) monitor for JASMINE
NASA Astrophysics Data System (ADS)
Niwa, Y.; Arai, K.; Ueda, A.; Sakagami, M.; Gouda, N.; Kobayashi, Y.; Yamada, Y.; Yano, T.
2008-07-01
The telescope geometry of JASMINE should be stabilized and monitored with the accuracy of about 10 to 100 pm or 10 to 100 prad of rms over about 10 hours. For this purpose, a high-precision interferometric laser metrology system is employed. Useful techniques for measuring displacements on extremely small scales are the wave-front sensing method and the heterodyne interferometrical method. Experiments for verification of measurement principles are well advanced.
2012-04-21
the photoelectric effect. The typical shortest wavelengths needed for ion traps range from 194 nm for Hg+ to 493 nm for Ba +, corresponding to 6.4-2.5...REPORT Comprehensive Materials and Morphologies Study of Ion Traps (COMMIT) for scalable Quantum Computation - Final Report 14. ABSTRACT 16. SECURITY...CLASSIFICATION OF: Trapped ion systems, are extremely promising for large-scale quantum computation, but face a vexing problem, with motional quantum
Estimates of expansion time scales
NASA Astrophysics Data System (ADS)
Jones, E. M.
Monte Carlo simulations of the expansion of a spacefaring civilization show that descendants of that civilization should be found near virtually every useful star in the Galaxy in a time much less than the current age of the Galaxy. Only extreme assumptions about local population growth rates, emigration rates, or ship ranges can slow or halt an expansion. The apparent absence of extraterrestrials from the solar system suggests that no such civilization has arisen in the Galaxy.
NASA Astrophysics Data System (ADS)
Munoz-Arriola, F.; Smith, K.; Corzo, G.; Chacon, J.; Carrillo-Cruz, C.
2015-12-01
A major challenge for water, energy and food security relies on the capability of agroecosyststems and ecosystems to adapt to a changing climate and land use changes. The interdependency of these forcings, understood through our ability to monitor and model processes across scales, indicate the "depth" of their impact on agroecosystems and ecosystems, and consequently our ability to predict the system's ability to return to a "normal" state. We are particularly interested in explore two questions: (1) how hydrometeorological and climate extreme events (HCEs) affect sub-seasonal to interannual changes in evapotranspiration and soil moisture? And (2) how agroecosystems recover from the effect of such events. To address those questions we use the land surface hydrologic Variable Infiltration Capacity (VIC) model and the Moderate Resolution Imaging Spectrometer-Leaf Area Index (MODIS-LAI) over two time spans (1950-2013 using a seasonal fixed LAI cycle) and 2001-2013 (an 8-day MODIS-LAI). VIC is forced by daily/16th degree resolution precipitation, minimum and maximum temperature, and wind speed. In this large-scale experiment, resiliency is defined by the capacity of a particular agroecosystem, represented by a grid cell's ET, SM, and LAI to return to a historical average. This broad, yet simplistic definition will contribute to identify the possible components and their scales involved in agroecosystems and ecosystems capacity to adapt to the incidence of HCEs and technologies used to intensify agriculture and diversify their use for food and energy production. Preliminary results show that dynamical changes in land use, tracked by MODIS data, require larger time spans to address properly the influence of technologic improvements in crop production as well as the competition for land for biofuel vs. food production. On the other hand, fixed seasonal changes in land use allow us just to identify hydrologic changes mainly due to climate variability.
Lattice QCD Thermodynamics and RHIC-BES Particle Production within Generic Nonextensive Statistics
NASA Astrophysics Data System (ADS)
Tawfik, Abdel Nasser
2018-05-01
The current status of implementing Tsallis (nonextensive) statistics on high-energy physics is briefly reviewed. The remarkably low freezeout-temperature, which apparently fails to reproduce the firstprinciple lattice QCD thermodynamics and the measured particle ratios, etc. is discussed. The present work suggests a novel interpretation for the so-called " Tsallis-temperature". It is proposed that the low Tsallis-temperature is due to incomplete implementation of Tsallis algebra though exponential and logarithmic functions to the high-energy particle-production. Substituting Tsallis algebra into grand-canonical partition-function of the hadron resonance gas model seems not assuring full incorporation of nonextensivity or correlations in that model. The statistics describing the phase-space volume, the number of states and the possible changes in the elementary cells should be rather modified due to interacting correlated subsystems, of which the phase-space is consisting. Alternatively, two asymptotic properties, each is associated with a scaling function, are utilized to classify a generalized entropy for such a system with large ensemble (produced particles) and strong correlations. Both scaling exponents define equivalence classes for all interacting and noninteracting systems and unambiguously characterize any statistical system in its thermodynamic limit. We conclude that the nature of lattice QCD simulations is apparently extensive and accordingly the Boltzmann-Gibbs statistics is fully fulfilled. Furthermore, we found that the ratios of various particle yields at extreme high and extreme low energies of RHIC-BES is likely nonextensive but not necessarily of Tsallis type.
North Indian heavy rainfall event during June 2013: diagnostics and extended range prediction
NASA Astrophysics Data System (ADS)
Joseph, Susmitha; Sahai, A. K.; Sharmila, S.; Abhilash, S.; Borah, N.; Chattopadhyay, R.; Pillai, P. A.; Rajeevan, M.; Kumar, Arun
2015-04-01
The Indian summer monsoon of 2013 covered the entire country by 16 June, one month earlier than its normal date. Around that period, heavy rainfall was experienced in the north Indian state of Uttarakhand, which is situated on the southern slope of Himalayan Ranges. The heavy rainfall and associated landslides caused serious damages and claimed many lives. This study investigates the scientific rationale behind the incidence of the extreme rainfall event in the backdrop of large scale monsoon environment. It is found that a monsoonal low pressure system that provided increased low level convergence and abundant moisture, and a midlatitude westerly trough that generated strong upper level divergence, interacted with each other and helped monsoon to cover the entire country and facilitated the occurrence of the heavy rainfall event in the orographic region. The study also examines the skill of an ensemble prediction system (EPS) in predicting the Uttarakhand event on extended range time scale. The EPS is implemented on both high (T382) and low (T126) resolution versions of the coupled general circulation model CFSv2. Although the models predicted the event 10-12 days in advance, they failed to predict the midlatitude influence on the event. Possible reasons for the same are also discussed. In both resolutions of the model, the event was triggered by the generation and northwestward movement of a low pressure system developed over the Bay of Bengal. The study advocates the usefulness of high resolution models in predicting extreme events.
Collective input/output under memory constraints
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Yin; Chen, Yong; Zhuang, Yu
2014-12-18
Compared with current high-performance computing (HPC) systems, exascale systems are expected to have much less memory per node, which can significantly reduce necessary collective input/output (I/O) performance. In this study, we introduce a memory-conscious collective I/O strategy that takes into account memory capacity and bandwidth constraints. The new strategy restricts aggregation data traffic within disjointed subgroups, coordinates I/O accesses in intranode and internode layers, and determines I/O aggregators at run time considering memory consumption among processes. We have prototyped the design and evaluated it with commonly used benchmarks to verify its potential. The evaluation results demonstrate that this strategy holdsmore » promise in mitigating the memory pressure, alleviating the contention for memory bandwidth, and improving the I/O performance for projected extreme-scale systems. Given the importance of supporting increasingly data-intensive workloads and projected memory constraints on increasingly larger scale HPC systems, this new memory-conscious collective I/O can have a significant positive impact on scientific discovery productivity.« less
Temporal and spatial scaling impacts on extreme precipitation
NASA Astrophysics Data System (ADS)
Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.
2015-01-01
Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.
Kim, Arim; Lee, Hye-Sun; Song, Chiang-Soon
2017-01-01
[Purpose] The purpose of this study was to examine the effects of interactive metronome training on the postural stability and upper extremity function of an individual with Parkinson's disease. [Subject and Methods] The participant of this case study was a 75-year-old female with Parkinson's disease diagnosed 7 years prior. This study was a single-subject research with an A-B-A design. She received IM training during the treatment phase (B phase) for 40 minutes per session. She was assessed pretest and posttest using the Berg balance scale and Wolf motor function test, and at baseline and the treatment phase using the measured box-and-block test and a Tetrax system. [Results] After training, the patient's static and dynamic balance, functional activity, and performance time of the upper extremity improved. Interactive metronome therapy improved the manual dexterity of both hands. Interactive metronome therapy also improved the limit of stability of the Parkinson's disease. [Conclusion] Though a case study, the results of this study suggest that IM therapy is effective at restoring the postural stability and upper extremity function of patients with Parkinson's disease.
Kim, Arim; Lee, Hye-Sun; Song, Chiang-Soon
2017-01-01
[Purpose] The purpose of this study was to examine the effects of interactive metronome training on the postural stability and upper extremity function of an individual with Parkinson’s disease. [Subject and Methods] The participant of this case study was a 75-year-old female with Parkinson’s disease diagnosed 7 years prior. This study was a single-subject research with an A-B-A design. She received IM training during the treatment phase (B phase) for 40 minutes per session. She was assessed pretest and posttest using the Berg balance scale and Wolf motor function test, and at baseline and the treatment phase using the measured box-and-block test and a Tetrax system. [Results] After training, the patient’s static and dynamic balance, functional activity, and performance time of the upper extremity improved. Interactive metronome therapy improved the manual dexterity of both hands. Interactive metronome therapy also improved the limit of stability of the Parkinson’s disease. [Conclusion] Though a case study, the results of this study suggest that IM therapy is effective at restoring the postural stability and upper extremity function of patients with Parkinson’s disease. PMID:28210066
Using Weather Types to Understand and Communicate Weather and Climate Impacts
NASA Astrophysics Data System (ADS)
Prein, A. F.; Hale, B.; Holland, G. J.; Bruyere, C. L.; Done, J.; Mearns, L.
2017-12-01
A common challenge in atmospheric research is the translation of scientific advancements and breakthroughs to decision relevant and actionable information. This challenge is central to the mission of NCAR's Capacity Center for Climate and Weather Extremes (C3WE, www.c3we.ucar.edu). C3WE advances our understanding of weather and climate impacts and integrates these advances with distributed information technology to create tools that promote a global culture of resilience to weather and climate extremes. Here we will present an interactive web-based tool that connects historic U.S. losses and fatalities from extreme weather and climate events to 12 large-scale weather types. Weather types are dominant weather situations such as winter high-pressure systems over the U.S. leading to very cold temperatures or summertime moist humid air masses over the central U.S. leading to severe thunderstorms. Each weather type has a specific fingerprint of economic losses and fatalities in a region that is quantified. Therefore, weather types enable a direct connection of observed or forecasted weather situation to loss of life and property. The presented tool allows the user to explore these connections, raise awareness of existing vulnerabilities, and build resilience to weather and climate extremes.
Full-Scale Accident Testing in Support of Used Nuclear Fuel Transportation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Durbin, Samuel G.; Lindgren, Eric R.; Rechard, Rob P.
2014-09-01
The safe transport of spent nuclear fuel and high-level radioactive waste is an important aspect of the waste management system of the United States. The Nuclear Regulatory Commission (NRC) currently certifies spent nuclear fuel rail cask designs based primarily on numerical modeling of hypothetical accident conditions augmented with some small scale testing. However, NRC initiated a Package Performance Study (PPS) in 2001 to examine the response of full-scale rail casks in extreme transportation accidents. The objectives of PPS were to demonstrate the safety of transportation casks and to provide high-fidelity data for validating the modeling. Although work on the PPSmore » eventually stopped, the Blue Ribbon Commission on America’s Nuclear Future recommended in 2012 that the test plans be re-examined. This recommendation was in recognition of substantial public feedback calling for a full-scale severe accident test of a rail cask to verify evaluations by NRC, which find that risk from the transport of spent fuel in certified casks is extremely low. This report, which serves as the re-assessment, provides a summary of the history of the PPS planning, identifies the objectives and technical issues that drove the scope of the PPS, and presents a possible path for moving forward in planning to conduct a full-scale cask test. Because full-scale testing is expensive, the value of such testing on public perceptions and public acceptance is important. Consequently, the path forward starts with a public perception component followed by two additional components: accident simulation and first responder training. The proposed path forward presents a series of study options with several points where the package performance study could be redirected if warranted.« less
NASA Astrophysics Data System (ADS)
Palus, Milan
2017-04-01
Deeper understanding of complex dynamics of the Earth atmosphere and climate is inevitable for sustainable development, mitigation and adaptation strategies for global change and for prediction of and resilience against extreme events. Traditional (linear) approaches cannot explain or even detect nonlinear interactions of dynamical processes evolving on multiple spatial and temporal scales. Combination of nonlinear dynamics and information theory explains synchronization as a process of adjustment of information rates [1] and causal relations (à la Granger) as information transfer [2]. Information born in dynamical complexity or information transferred among systems on a way to synchronization might appear as an abstract quantity, however, information transfer is tied to a transfer of mass and energy, as demonstrated in a recent study using directed (causal) climate networks [2]. Recently, an information transfer across scales of atmospheric dynamics has been observed [3]. In particular, a climate oscillation with the period around 7-8 years has been identified as a factor influencing variability of surface air temperature (SAT) on shorter time scales. Its influence on the amplitude of the SAT annual cycle was estimated in the range 0.7-1.4 °C and the effect on the overall variability of the SAT anomalies (SATA) leads to the changes 1.5-1.7 °C in the annual SATA means. The strongest effect of the 7-8 year cycle was observed in the winter SATA means where it reaches 4-5 °C in central European station and reanalysis data [4]. In the dynamics of El Niño-Southern Oscillation, three principal time scales have been identified: the annual cycle (AC), the quasibiennial (QB) mode(s) and the low-frequency (LF) variability. An intricate causal network of information flows among these modes helps to understand the occurrence of extreme El Niño events, characterized by synchronization of the QB modes and AC, and modulation of the QB amplitude by the LF mode. The latter also influences the phase of the AC and QB modes. These examples provide an inspiration for a discussion how novel data analysis methods, based on topics from nonlinear dynamical systems, their synchronization, (Granger) causality and information transfer, in combination with dynamical and statistical models of different complexity, can help in understanding and prediction of climate variability on different scales and in estimating probability of occurrence of extreme climate events. [1] M. Palus, V. Komarek, Z. Hrncir, K. Sterbova, Phys. Rev. E, 63(4), 046211 (2001) http://www.cs.cas.cz/mp/epr/sir1-a.html [2] J. Hlinka, N. Jajcay, D. Hartman, M. Palus, Smooth Information Flow in Temperature Climate Network Reflects Mass Transport, submitted to Chaos. http://www.cs.cas.cz/mp/epr/vetry-a.html [3] M. Palus, Phys. Rev. Lett. 112 078702 (2014) http://www.cs.cas.cz/mp/epr/xf1-a.html [4] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Palus, Geophys. Res. Lett. 43(2), 902-909 (2016) http://www.cs.cas.cz/mp/epr/xfgrl1-a.html
Negahban, Hossein; Hessam, Masumeh; Tabatabaei, Saeid; Salehi, Reza; Sohani, Soheil Mansour; Mehravar, Mohammad
2014-01-01
The aim was to culturally translate and validate the Persian lower extremity functional scale (LEFS) in a heterogeneous sample of outpatients with lower extremity musculoskeletal disorders (n = 304). This is a prospective methodological study. After a standard forward-backward translation, psychometric properties were assessed in terms of test-retest reliability, internal consistency, construct validity, dimensionality, and ceiling or floor effects. The acceptable level of intraclass correlation coefficient >0.70 and Cronbach's alpha coefficient >0.70 was obtained for the Persian LEFS. Correlations between Persian LEFS and Short-Form 36 Health Survey (SF-36) subscales of Physical Health component (rs range = 0.38-0.78) were higher than correlations between Persian LEFS and SF-36 subscales of Mental Health component (rs range = 0.15-0.39). A corrected item--total correlation of >0.40 (Spearman's rho) was obtained for all items of the Persian LEFS. Horn's parallel analysis detected a total of two factors. No ceiling or floor effects were detected for the Persian LEFS. The Persian version of the LEFS is a reliable and valid instrument that can be used to measure functional status in Persian-speaking patients with different musculoskeletal disorders of the lower extremity. Implications for Rehabilitation The Persian lower extremity functional scale (LEFS) is a reliable, internally consistent and valid instrument, with no ceiling or floor effects, to determine functional status of heterogeneous patients with musculoskeletal disorders of the lower extremity. The Persian version of the LEFS can be used in clinical and research settings to measure function in Iranian patients with different musculoskeletal disorders of the lower extremity.
Gravitational Waves From the Kerr/CFT Correspondence
NASA Astrophysics Data System (ADS)
Porfyriadis, Achilleas
Astronomical observation suggests the existence of near-extreme Kerr black holes in the sky. Properties of diffeomorphisms imply that dynamics of the near-horizon region of near-extreme Kerr are governed by an infinite-dimensional conformal symmetry. This symmetry may be exploited to analytically, rather than numerically, compute a variety of potentially observable processes. In this thesis we compute the gravitational radiation emitted by a small compact object that orbits in the near-horizon region and plunges into the horizon of a large rapidly rotating black hole. We study the holographically dual processes in the context of the Kerr/CFT correspondence and find our conformal field theory (CFT) computations in perfect agreement with the gravity results. We compute the radiation emitted by a particle on the innermost stable circular orbit (ISCO) of a rapidly spinning black hole. We confirm previous estimates of the overall scaling of the power radiated, but show that there are also small oscillations all the way to extremality. Furthermore, we reveal an intricate mode-by-mode structure in the flux to infinity, with only certain modes having the dominant scaling. The scaling of each mode is controlled by its conformal weight. Massive objects in adiabatic quasi-circular inspiral towards a near-extreme Kerr black hole quickly plunge into the horizon after passing the ISCO. The post-ISCO plunge trajectory is shown to be related by a conformal map to a circular orbit. Conformal symmetry of the near-horizon region is then used to compute analytically the gravitational radiation produced during the plunge phase. Most extreme-mass-ratio-inspirals of small compact objects into supermassive black holes end with a fast plunge from an eccentric last stable orbit. We use conformal transformations to analytically solve for the radiation emitted from various fast plunges into extreme and near-extreme Kerr black holes.
Attribution of Extreme Rainfall Events in the South of France Using EURO-CORDEX Simulations
NASA Astrophysics Data System (ADS)
Luu, L. N.; Vautard, R.; Yiou, P.
2017-12-01
The Mediterranean region regularly undergoes episodes of intense precipitation in the fall season that exceed 300mm a day. This study focuses on the role of climate change on the dynamics of the events that occur in the South of France. We used an ensemble of 10 EURO-CORDEX model simulations with two horizontal resolutions (EUR-11: 0.11° and EUR-44: 0.44°) for the attribution of extreme rainfall in the fall in the Cevennes mountain range (South of France). The biases of the simulations were corrected with simple scaling adjustment and a quantile correction (CDFt). This produces five datasets including EUR-44 and EUR-11 with and without scaling adjustment and CDFt-EUR-11, on which we test the impact of resolution and bias correction on the extremes. Those datasets, after pooling all of models together, are fitted by a stationary Generalized Extreme Value distribution for several periods to estimate a climate change signal in the tail of distribution of extreme rainfall in the Cévenne region. Those changes are then interpreted by a scaling model that links extreme rainfall with mean and maximum daily temperature. The results show that higher-resolution simulations with bias adjustment provide a robust and confident increase of intensity and likelihood of occurrence of autumn extreme rainfall in the area in current climate in comparison with historical climate. The probability (exceedance probability) of 1-in-1000-year event in historical climate may increase by a factor of 1.8 under current climate with a confident interval of 0.4 to 5.3 following the CDFt bias-adjusted EUR-11. The change of magnitude appears to follow the Clausius-Clapeyron relation that indicates a 7% increase in rainfall per 1oC increase in temperature.
Dynamical ocean-atmospheric drivers of floods and droughts
NASA Astrophysics Data System (ADS)
Perdigão, Rui A. P.; Hall, Julia
2014-05-01
The present study contributes to a better depiction and understanding of the "facial expression" of the Earth in terms of dynamical ocean-atmospheric processes associated to both floods and droughts. For this purpose, the study focuses on nonlinear dynamical and statistical analysis of ocean-atmospheric mechanisms contributing to hydrological extremes, broadening the analytical hydro-meteorological perspective of floods and hydrological droughts to driving mechanisms and feedbacks at the global scale. In doing so, the analysis of the climate-related causality of hydrological extremes is not limited to the synoptic situation in the region where the events take place. Rather, it goes further in the train of causality, peering into dynamical interactions between planetary-scale ocean and atmospheric processes that drive weather regimes and influence the antecedent and event conditions associated to hydrological extremes. In order to illustrate the approach, dynamical ocean-atmospheric drivers are investigated for a selection of floods and droughts. Despite occurring in different regions with different timings, common underlying mechanisms are identified for both kinds of hydrological extremes. For instance, several analysed events are seen to have resulted from a large-scale atmospheric situation consisting on standing planetary waves encircling the northern hemisphere. These correspond to wider vortices locked in phase, resulting in wider and more persistent synoptic weather patterns, i.e. with larger spatial and temporal coherence. A standing train of anticyclones and depressions thus encircled the mid and upper latitudes of the northern hemisphere. The stationary regime of planetary waves occurs when the mean eastward zonal flow decreases up to a point in which it no longer exceeds the westward phase propagation of the Rossby waves produced by the latitude-varying Coriolis effect. The ocean-atmospheric causes for this behaviour and consequences on hydrological extremes are investigated and the findings supported with spatiotemporal geostatistical analysis and nonlinear geophysical models. Overall, the study provides a three-fold contribution to the research on hydrological extremes: Firstly, it improves their physical attribution by better understanding the dynamical reasons behind the meteorological drivers. Secondly, it brings out fundamental early warning signs for potential hydrological extremes, by bringing out global ocean-atmospheric features that manifest themselves much earlier than the regional weather patterns. Thirdly, it provides tools for addressing and understanding hydrological regime changes at wider spatiotemporal scales, by providing links to planetary-scale dynamical processes that play a crucial role in multi-decadal global climate variability.
Using damage data to estimate the risk from summer convective precipitation extremes
NASA Astrophysics Data System (ADS)
Schroeer, Katharina; Tye, Mari
2017-04-01
This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical 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.
Exacerbated vulnerability of coupled socio-economic risk in complex networks
NASA Astrophysics Data System (ADS)
Zhang, Xin; Feng, Ling; Berman, Yonatan; Hu, Ning; Stanley, H. Eugene
2016-10-01
The study of risk contagion in economic networks has most often focused on the financial liquidities of institutions and assets. In practice the agents in a network affect each other through social contagion, i.e., through herd behavior and the tendency to follow leaders. We study the coupled risk between social and economic contagion and find it significantly more severe than when economic risk is considered alone. Using the empirical network from the China venture capital market we find that the system exhibits an extreme risk of abrupt phase transition and large-scale damage, which is in clear contrast to the smooth phase transition traditionally observed in economic contagion alone. We also find that network structure impacts market resilience and that the randomization of the social network of the market participants can reduce system fragility when there is herd behavior. Our work indicates that under coupled contagion mechanisms network resilience can exhibit a fundamentally different behavior, i.e., an abrupt transition. It also reveals the extreme risk when a system has coupled socio-economic risks, and this could be of interest to both policy makers and market practitioners.
[A case of systemic lupus erythematosus complicated with psoriasis vulgaris].
Shidara, Kumi; Soejima, Makoto; Shiseki, Mariko; Ohta, Syuji; Nishinarita, Makoto
2003-12-01
A 49-years-old female admitted to our hospital because of skin eruptions on the extremities in 1985. She had suffered from polyarthralgia, skin eruptions since 1983. Physical examinations revealed discoid lesion, central nervous system involvement, and polyarthritis. Laboratory tests revealed leukopenia, thrombocytopenia, and hypocomplementemia. Antinuclear antibody, ant-DNA antibody, LE test were positive. From these findings, she was diagnosed as systemic lupus erythematosus (SLE). She developed lupus peritonitis in 1990 and 1994, which was successfully treated by steroid pulse therapy. Since then, the activity of SLE was in good control under administration of prednisolone 10 mg/day. Chilblain lupus was seen from 1993, Raynaud's phenomenon from 1996, and she further developed subcutaneous induration on her chest, back and upper extremities in 1999. Skin biopsy findings were compatible with lupus panniculitis. In 2002, erythematous patches with scales were observed on her right hand and left knee, and these skin lesions were histologically diagnosed as psoriasis vulgaris. An autoimmune response similar to SLE is speculated in psoriasis. We describe a rare case of SLE with various skin lesions including psoriasis vulgaris.
Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model
NASA Astrophysics Data System (ADS)
Wang, Jie; Wang, Jun; Stanley, H. Eugene
2018-02-01
To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel-Ziv complexity (LZC) perform numerical research of the return intervals for two significant China's stock market indices and for the proposed model. The new MM-DCCA method is based on the Hurst surface and provides more interpretable cross-correlations of the dynamic mechanism between different return interval series. We scale the LZC method with different exponents to illustrate the complexity of return intervals in different scales. Empirical studies indicate that the proposed return intervals from the Potts system and the real stock market indices hold similar statistical properties.
Trend in frequency of extreme precipitation events over Ontario from ensembles of multiple GCMs
NASA Astrophysics Data System (ADS)
Deng, Ziwang; Qiu, Xin; Liu, Jinliang; Madras, Neal; Wang, Xiaogang; Zhu, Huaiping
2016-05-01
As one of the most important extreme weather event types, extreme precipitation events have significant impacts on human and natural environment. This study assesses the projected long term trends in frequency of occurrence of extreme precipitation events represented by heavy precipitation days, very heavy precipitation days, very wet days and extreme wet days over Ontario, based on results of 21 CMIP3 GCM runs. To achieve this goal, first, all model data are linearly interpolated onto 682 grid points (0.45° × 0.45°) in Ontario; Next, biases in model daily precipitation amount are corrected with a local intensity scaling method to make the total wet days and total wet day precipitation from each of the GCMs are consistent with that from the climate forecast system reanalysis data, and then the four indices are estimated for each of the 21 GCM runs for 1968-2000, 2046-2065 and 2081-2100. After that, with the assumption that the rate parameter of the Poisson process for the occurrence of extreme precipitation events may vary with time as climate changes, the Poisson regression model which expresses the log rate as a linear function of time is used to detect the trend in frequency of extreme events in the GCMs simulations; Finally, the trends and their uncertainty are estimated. The result shows that in the twenty-first century annual heavy precipitation days, very heavy precipitation days and very wet days and extreme wet days are likely to significantly increase over major parts of Ontario and particularly heavy precipitation days, very wet days are very likely to significantly increase in some sub-regions in eastern Ontario. However, trends of seasonal indices are not significant.
The National Extreme Events Data and Research Center (NEED)
NASA Astrophysics Data System (ADS)
Gulledge, J.; Kaiser, D. P.; Wilbanks, T. J.; Boden, T.; Devarakonda, R.
2014-12-01
The Climate Change Science Institute at Oak Ridge National Laboratory (ORNL) is establishing the National Extreme Events Data and Research Center (NEED), with the goal of transforming how the United States studies and prepares for extreme weather events in the context of a changing climate. NEED will encourage the myriad, distributed extreme events research communities to move toward the adoption of common practices and will develop a new database compiling global historical data on weather- and climate-related extreme events (e.g., heat waves, droughts, hurricanes, etc.) and related information about impacts, costs, recovery, and available research. Currently, extreme event information is not easy to access and is largely incompatible and inconsistent across web sites. NEED's database development will take into account differences in time frames, spatial scales, treatments of uncertainty, and other parameters and variables, and leverage informatics tools developed at ORNL (i.e., the Metadata Editor [1] and Mercury [2]) to generate standardized, robust documentation for each database along with a web-searchable catalog. In addition, NEED will facilitate convergence on commonly accepted definitions and standards for extreme events data and will enable integrated analyses of coupled threats, such as hurricanes/sea-level rise/flooding and droughts/wildfires. Our goal and vision is that NEED will become the premiere integrated resource for the general study of extreme events. References: [1] Devarakonda, Ranjeet, et al. "OME: Tool for generating and managing metadata to handle BigData." Big Data (Big Data), 2014 IEEE International Conference on. IEEE, 2014. [2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.
Carbone, V; Fluit, R; Pellikaan, P; van der Krogt, M M; Janssen, D; Damsgaard, M; Vigneron, L; Feilkas, T; Koopman, H F J M; Verdonschot, N
2015-03-18
When analyzing complex biomechanical problems such as predicting the effects of orthopedic surgery, subject-specific musculoskeletal models are essential to achieve reliable predictions. The aim of this paper is to present the Twente Lower Extremity Model 2.0, a new comprehensive dataset of the musculoskeletal geometry of the lower extremity, which is based on medical imaging data and dissection performed on the right lower extremity of a fresh male cadaver. Bone, muscle and subcutaneous fat (including skin) volumes were segmented from computed tomography and magnetic resonance images scans. Inertial parameters were estimated from the image-based segmented volumes. A complete cadaver dissection was performed, in which bony landmarks, attachments sites and lines-of-action of 55 muscle actuators and 12 ligaments, bony wrapping surfaces, and joint geometry were measured. The obtained musculoskeletal geometry dataset was finally implemented in the AnyBody Modeling System (AnyBody Technology A/S, Aalborg, Denmark), resulting in a model consisting of 12 segments, 11 joints and 21 degrees of freedom, and including 166 muscle-tendon elements for each leg. The new TLEM 2.0 dataset was purposely built to be easily combined with novel image-based scaling techniques, such as bone surface morphing, muscle volume registration and muscle-tendon path identification, in order to obtain subject-specific musculoskeletal models in a quick and accurate way. The complete dataset, including CT and MRI scans and segmented volume and surfaces, is made available at http://www.utwente.nl/ctw/bw/research/projects/TLEMsafe for the biomechanical community, in order to accelerate the development and adoption of subject-specific models on large scale. TLEM 2.0 is freely shared for non-commercial use only, under acceptance of the TLEMsafe Research License Agreement. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie
2016-07-01
This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.
NASA Astrophysics Data System (ADS)
Setty, V.; Sharma, A.
2013-12-01
Characterization of extreme conditions of space weather is essential for potential mitigation strategies. The non-equilibrium nature of magnetosphere makes such efforts complicated and new techniques to understand its extreme event distribution are required. The heavy tail distribution in such systems can be a modeled using Stable distribution whose stability parameter is a measure of scaling in the cumulative distribution and is related to the Hurst exponent. This exponent can be readily measured in stationary time series using several techniques and detrended fluctuation analysis (DFA) is widely used in the presence of non-stationarities. However DFA has severe limitations in cases with non-linear and atypical trends. We propose a new technique that utilizes nonlinear dynamical predictions as a measure of trends and estimates the Hurst exponents. Furthermore, such a measure provides us with a new way to characterize predictability, as perfectly detrended data have no long term memory akin to Gaussian noise Ab initio calculation of weekly Hurst exponents using the auroral electrojet index AL over a span of few decades shows that these exponents are time varying and so is its fractal structure. Such time series data with time varying Hurst exponents are modeled well using multifractional Brownian motion and it is shown that DFA estimates a single time averaged value for Hurst exponent in such data. Our results show that using time varying Hurst exponent structure, we can (a) Estimate stability parameter, -a measure of scaling in heavy tails, (b) Define and identify epochs when the magnetosphere switches between regimes with and without extreme events, and, (c) Study the dependence of the Hurst exponents on the solar activity.
NASA Astrophysics Data System (ADS)
Viereck, R. A.; Azeem, S. I.
2017-12-01
One of the goals of the National Space Weather Action Plan is to establish extreme event benchmarks. These benchmarks are estimates of environmental parameters that impact technologies and systems during extreme space weather events. Quantitative assessment of anticipated conditions during these extreme space weather event will enable operators and users of affected technologies to develop plans for mitigating space weather risks and improve preparedness. The ionosphere is one of the most important regions of space because so many applications either depend on ionospheric space weather for their operation (HF communication, over-the-horizon radars), or can be deleteriously affected by ionospheric conditions (e.g. GNSS navigation and timing, UHF satellite communications, synthetic aperture radar, HF communications). Since the processes that influence the ionosphere vary over time scales from seconds to years, it continues to be a challenge to adequately predict its behavior in many circumstances. Estimates with large uncertainties, in excess of 100%, may result in operators of impacted technologies over or under preparing for such events. The goal of the next phase of the benchmarking activity is to reduce these uncertainties. In this presentation, we will focus on the sources of uncertainty in the ionospheric response to extreme geomagnetic storms. We will then discuss various research efforts required to better understand the underlying processes of ionospheric variability and how the uncertainties in ionospheric response to extreme space weather could be reduced and the estimates improved.
NASA Astrophysics Data System (ADS)
Lenderink, Geert; Barbero, Renaud; Loriaux, Jessica; Fowler, Hayley
2017-04-01
Present-day precipitation-temperature scaling relations indicate that hourly precipitation extremes may have a response to warming exceeding the Clausius-Clapeyron (CC) relation; for The Netherlands the dependency on surface dew point temperature follows two times the CC relation corresponding to 14 % per degree. Our hypothesis - as supported by a simple physical argument presented here - is that this 2CC behaviour arises from the physics of convective clouds. So, we think that this response is due to local feedbacks related to the convective activity, while other large scale atmospheric forcing conditions remain similar except for the higher temperature (approximately uniform warming with height) and absolute humidity (corresponding to the assumption of unchanged relative humidity). To test this hypothesis, we analysed the large-scale atmospheric conditions accompanying summertime afternoon precipitation events using surface observations combined with a regional re-analysis for the data in The Netherlands. Events are precipitation measurements clustered in time and space derived from approximately 30 automatic weather stations. The hourly peak intensities of these events again reveal a 2CC scaling with the surface dew point temperature. The temperature excess of moist updrafts initialized at the surface and the maximum cloud depth are clear functions of surface dew point temperature, confirming the key role of surface humidity on convective activity. Almost no differences in relative humidity and the dry temperature lapse rate were found across the dew point temperature range, supporting our theory that 2CC scaling is mainly due to the response of convection to increases in near surface humidity, while other atmospheric conditions remain similar. Additionally, hourly precipitation extremes are on average accompanied by substantial large-scale upward motions and therefore large-scale moisture convergence, which appears to accelerate with surface dew point. This increase in large-scale moisture convergence appears to be consequence of latent heat release due to the convective activity as estimated from the quasi-geostrophic omega equation. Consequently, most hourly extremes occur in precipitation events with considerable spatial extent. Importantly, this event size appears to increase rapidly at the highest dew point temperature range, suggesting potentially strong impacts of climatic warming.
Extreme Mississippi River Floods in the Late Holocene: Reconstructions and Simulations
NASA Astrophysics Data System (ADS)
Munoz, S. E.; Giosan, L.; Donnelly, J. P.; Dee, S.
2016-12-01
Extreme flooding of the Mississippi River is costly in both economic and social terms. Despite ambitious engineering projects conceived in the early 20th century to mitigate damage from extreme floods, economic losses due to flooding have increased over recent years. Forecasting extreme flood occurrence over seasonal or longer time-scales remains a major challenge - especially in light of shifts in hydroclimatic conditions expected in response to continued greenhouse forcing. Here, we present findings from a series of paleoflood records that span the late Holocene derived from laminated sediments deposited in abandoned channels of the Mississippi River. These sedimentary archives record individual overbank floods as unique events beds with upward fining that we identify using grain-size analysis, bulk geochemistry, and radiography. We use sedimentological characteristics to reconstruct flood magnitude by calibrating our records against instrumental streamflow data from nearby gauging stations. We also use the Last Millennium Experiments of the Community Earth System Model (CESM-LME) and historical reanalysis data to examine the state of climate system around river discharge extremes. Our paleo-flood records exhibit strong non-stationarities in flood frequency and magnitude that are associated with fluctuations in the frequency of the El Niño-Southern Oscillation (ENSO), because the warm ENSO phase is associated with increased surface water storage of the lower Mississippi basin that leads to enhanced runoff delivery to the main channel. We also show that the early 20th century was a period of anomalously high flood frequency and magnitude due to the combined effects of river engineering and natural climate variability. Our findings imply that flood risk along the lower Mississippi River is tightly coupled to the frequency of ENSO, highlighting the need for robust projections of ENSO variability under greenhouse warming.
Extreme-Scale Computing Project Aims to Advance Precision Oncology | FNLCR Staging
Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict dru
Forearm fracture bending risk functin for the 50th percentile male.
Santago, Anthony C; Cormier, Joseph M; Duma, Stefan M; Yoganandan, Narayan; Pintar, Frank A
2008-01-01
The increase in upper extremity injuries in automobile collisions, because of the widespread implantation of airbags, has lead to a better understanding of forearm injury criteria. Risk functions for upper extremity injury that can be used in instrumented upper extremities would be useful. This paper presents a risk function for forearm injury for the 50th percentile male based on bending fracture moment data gathered from previous studies. The data was scaled using two scaling factors, one for orientation and one for mass, and the Weibull survival analysis model was then used to develop the risk function. It was determined that a 25% risk of injury corresponds to an 82 Nm bending load, a 50% risk of injury corresponds to a 100 Nm bending load, and a 75% risk of injury corresponds to a 117 Nm bending load. It is believed the risk function can be used with an instrumented upper extremity during vehicle testing.
Humerus fracture bending risk function for the 50th percentile male.
Santago, Anthony C; Cormier, Joseph M; Duma, Stefan M
2008-01-01
The increase in upper extremity injuries in automobile collisions, because of the widespread implantation of airbags, has lead to an increased focus in humerus injury criteria. Risk functions for upper extremity injury that can be used in instrumented upper extremities would be useful. This paper presents a risk function for humerus injury for the 50th percentile male based on bending fracture moment data gathered from previous studies. The data was scaled using two scaling factors, one for mass and one for rate, and the Weibull survival analysis model was then used to develop the risk function. It was determined that a 25% risk of injury corresponds to a 214 Nm bending load, a 50% risk of injury corresponds to a 257 Nm bending load, and a 75% risk of injury corresponds to a 296 Nm bending load. It is believed the risk function can be used with an instrumented upper extremity during vehicle testing.
[Extreme Climatic Events in the Altai Republic According to Dendrochronological Data].
Barinov, V V; Myglan, V S; Nazarov, A N; Vaganov, E A; Agatova, A R; Nepop, R K
2016-01-01
The results of dating of extreme climatic events by damage to the anatomical structure and missing tree rings of the Siberian larch in the upper forest boundary of the Altai Republic are given. An analysis of the spatial distribution of the revealed dates over seven plots (Kokcy, Chind, Ak-ha, Jelo, Tute, Tara, and Sukor) allowed us to distinguish the extreme events on interregional (1700, 1783, 1788, 1812, 1814, 1884), regional (1724, 1775, 1784, 1835, 1840, 1847, 1850, 1852, 1854, 1869, 1871, 1910, 1917, 1927, 1938, 1958, 1961), and local (1702, 1736, 1751, 1785, 1842, 1843,1874, 1885, 1886, 1919, 2007, and 2009) scales. It was shown that the events of an interregional scale correspond with the dates of major volcanic eruptions (Grimsvotn, Lakagigar, Etna, Awu, Tambora, Soufriere St. Vinsent, Mayon, and Krakatau volcanos) and extreme climatic events, crop failures, lean years, etc., registered in historical sources.
Boo, Jung-A; Moon, Sang-Hyun; Lee, Sun-Min; Choi, Jung-Hyun; Park, Si-Eun
2016-01-01
[Purpose] The purpose of this study was to determine the effect of whole-body vibration exercise in a sitting position prior to therapy in stroke patients. [Subjects and Methods] Fourteen chronic stroke patients were included in this study. Prior to occupational therapy, whole-body exercise was performed for 10 minutes, 5 times per week, for a total of 8 weeks. Muscle tone and upper extremity function were measured. The Modified Ashworth Scale (MAS) was used to measure muscle tone, and the Manual Function Test (MFT) and Fugl-Meyer Assessment scale (FugM) were used to measure upper extremity function. [Results] MAS score was significantly decreased, and MFT and FugM were significantly increased. [Conclusion] These results indicate that whole-body vibration exercise in a sitting position prior to therapy had a positive effect on muscle tone, and upper extremity function in stroke patients.
Local finite-amplitude wave activity as an objective diagnostic of midlatitude extreme weather
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Gang; Lu, Jian; Burrows, Alex D.
Midlatitude extreme weather events are responsible for a large part of climate related damage, yet our understanding of these extreme events is limited, partly due to the lack of a theoretical basis for midlatitude extreme weather. In this letter, the local finite-amplitude wave activity (LWA) of Huang and Nakamura [2015] is introduced as a diagnostic of the 500-hPa geopotential height (Z500) to characterizing midlatitude weather events. It is found that the LWA climatology and its variability associated with the Arctic Oscillation (AO) agree broadly with the previously reported blocking frequency in literature. There is a strong seasonal and spatial dependencemore » in the trend13 s of LWA in recent decades. While there is no observational evidence for a hemispheric-scale increase in wave amplitude, robust trends in wave activity can be identified at the regional scales, with important implications for regional climate change.« less
Microhabitats in the tropics buffer temperature in a globally coherent manner
Scheffers, Brett R.; Evans, Theodore A.; Williams, Stephen E.; Edwards, David P.
2014-01-01
Vegetated habitats contain a variety of fine-scale features that can ameliorate temperate extremes. These buffered microhabitats may be used by species to evade extreme weather and novel climates in the future. Yet, the magnitude and extent of this buffering on a global scale remains unknown. Across all tropical continents and using 36 published studies, we assessed temperature buffering from within microhabitats across various habitat strata and structures (e.g. soil, logs, epiphytes and tree holes) and compared them to non-buffered macro-scale ambient temperatures (the thermal control). Microhabitats buffered temperature by 3.9°C and reduced maximum temperatures by 3.5°C. Buffering was most pronounced in tropical lowlands where temperatures were most variable. With the expected increase in extreme weather events, microhabitats should provide species with a local layer of protection that is not captured by traditional climate assessments, which are typically derived from macro-scale temperatures (e.g. satellites). Our data illustrate the need for a next generation of predictive models that account for species' ability to move within microhabitats to exploit favourable buffered microclimates. PMID:25540160
Cross-timescale Interference and Rainfall Extreme Events in South Eastern South America
NASA Astrophysics Data System (ADS)
Munoz, Angel G.
The physical mechanisms and predictability associated with extreme daily rainfall in South East South America (SESA) are investigated for the December-February season. Through a k-mean analysis, a robust set of daily circulation regimes is identified and then it is used to link the frequency of rainfall extreme events with large-scale potential predictors at subseasonal-to-seasonal scales. This basic set of daily circulation regimes is related to the continental and oceanic phases of the South Atlantic Convergence Zone (SACZ) and wave train patterns superimposed on the Southern Hemisphere Polar Jet. Some of these recurrent synoptic circulation types are conducive to extreme rainfall events in the region through synoptic control of different meso-scale physical features and, at the same time, are influenced by climate phenomena that could be used as sources of potential predictability. Extremely high rainfall (as measured by the 95th- and 99th-percentiles) is preferentially associated with two of these weather types, which are characterized by moisture advection intrusions from lower latitudes and the Pacific; another three weather types, characterized by above-normal moisture advection toward lower latitudes or the Andes, are preferentially associated with dry days (days with no rain). The analysis permits the identification of several subseasonal-to-seasonal scale potential predictors that modulate the occurrence of circulation regimes conducive to extreme rainfall events in SESA. It is conjectured that a cross-timescale interference between the different climate drivers improves the predictive skill of extreme precipitation in the region. The potential and real predictive skill of the frequency of extreme rainfall is then evaluated, finding evidence indicating that mechanisms of climate variability at one timescale contribute to the predictability at another scale, i.e., taking into account the interference of different potential sources of predictability at different timescales increases the predictive skill. This fact is in agreement with the Cross-timescale Interference Conjecture proposed in the first part of the thesis. At seasonal scale, a combination of those weather types tends to outperform all the other potential predictors explored, i.e., sea surface temperature patterns, phases of the Madden-Julian Oscillation, and combinations of both. Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for realtime predictions are attained with respect to standard models considering sea-surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed, based on probability forecasts of seasonal sequences of these weather types. The cross-validated realtime skill of the new probabilistic approach, as measured by the Hit Score and the Heidke Skill Score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season, but also in how, when and where those events will probably occur. In order to gain further understanding about how the cross-timescale interference occurs, an externally-forced Lorenz model is used to explore the impact of different kind of forcings, at inter-annual and decadal scales, in the establishment of constructive interactions associated with the simulated “extreme events”. Using a wavelet analysis, it is shown that this simple model is capable of reproducing the same kind of cross-timescale structures observed in the wavelet power spectrum of the Nino3.4 index only when it is externally forced by both inter-annual and decadal signals: the annual cycle and a decadal forcing associated with the natural solar variability. The nature of this interaction is non-linear, and it impacts both mean and extreme values in the time series. No predictive power was found when using metrics like standard deviation and auto-correlation. Nonetheless, it was proposed that an early warning signal for occurrence of extreme rainfall in SESA may be possible via a continuous monitoring of relative phases between the cross-timescale leading components.
[Validation of a scale measuring coping with extreme risks].
López-Vázquez, Esperanza; Marván, María Luisa
2004-01-01
The objective of this study was to validate, in Mexico, the French coping scale "Echelle Toulousaine de Coping". In the fall of 2001, the scale questionnaire was applied to 209 subjects living in different areas of Mexico, exposed to five different types of extreme natural or industrial risks. The discriminatory capacity of the items, as well as the factorial structure and internal consistency of the scale, were analyzed using Mann-Whitney's U test, principal components factorial analysis, and Cronbach's alpha. The final scale was composed of 26 items forming two groups: active coping and passive coping. Internal consistency of the instrument was high, both in the total sample and in the subsample of natural and industrial risks. The coping scale is reliable and valid for the Mexican population. The English version of this paper is available at: http://www.insp.mx/salud/index.html.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brown, Shaughnessy Brennan; Hashim, Akel; Gleason, Arianna
In this paper, we measure the shock drive capabilities of a 30 J, nanosecond, 527 nm laser system at the matter in extreme conditions hutch of the Linac Coherent Light Source. Using a velocity interferometer system for any reflector, we ascertain the maximum instantaneous ablation pressure and characterize its dependence on a drive laser spot size, spatial profile, and temporal profile. We also examine the effects of these parameters on shock spatial and temporal uniformity. Our analysis shows the drive laser capable of generating instantaneous ablation pressures exceeding 160 GPa while maintaining a 1D shock profile. We find that slopemore » pulses provide higher instantaneous ablation pressures than plateau pulses. Our results show instantaneous ablation pressures comparable to those measured at the Omega Laser Facility in Rochester, NY under similar optical drive parameters. In conclusion, we analyze how optical laser ablation pressures are compare with known scaling relations, accounting for variable laser wavelengths.« less
NASA Technical Reports Server (NTRS)
Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.
2011-01-01
The degree of coupling between the land surface and PBL in NWP models remains largely undiagnosed due to the complex interactions and feedbacks present across a range of scales. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with observations during the summers of 2006/7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which enables a suite of PBL and land surface model (LSM) options along provides a flexible and high-resolution representation and initialization of land surface physics and states. This coupling is one component of a larger project to develop a NASA-Unified WRF (NU-WRF) system. A range of diagnostics exploring the feedbacks between soil moisture and precipitation are examined for the dry/wet extremes, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture.
Brown, Shaughnessy Brennan; Hashim, Akel; Gleason, Arianna; ...
2017-10-23
In this paper, we measure the shock drive capabilities of a 30 J, nanosecond, 527 nm laser system at the matter in extreme conditions hutch of the Linac Coherent Light Source. Using a velocity interferometer system for any reflector, we ascertain the maximum instantaneous ablation pressure and characterize its dependence on a drive laser spot size, spatial profile, and temporal profile. We also examine the effects of these parameters on shock spatial and temporal uniformity. Our analysis shows the drive laser capable of generating instantaneous ablation pressures exceeding 160 GPa while maintaining a 1D shock profile. We find that slopemore » pulses provide higher instantaneous ablation pressures than plateau pulses. Our results show instantaneous ablation pressures comparable to those measured at the Omega Laser Facility in Rochester, NY under similar optical drive parameters. In conclusion, we analyze how optical laser ablation pressures are compare with known scaling relations, accounting for variable laser wavelengths.« less
Generalized IRT Models for Extreme Response Style
ERIC Educational Resources Information Center
Jin, Kuan-Yu; Wang, Wen-Chung
2014-01-01
Extreme response style (ERS) is a systematic tendency for a person to endorse extreme options (e.g., strongly disagree, strongly agree) on Likert-type or rating-scale items. In this study, we develop a new class of item response theory (IRT) models to account for ERS so that the target latent trait is free from the response style and the tendency…
Contributions of natural climate changes and human activities to the trend of extreme precipitation
NASA Astrophysics Data System (ADS)
Gao, Lu; Huang, Jie; Chen, Xingwei; Chen, Ying; Liu, Meibing
2018-06-01
This study focuses on the analysis of the nonstationarity characteristics of extreme precipitation and their attributions in the southeastern coastal region of China. The maximum daily precipitation (MDP) series is extracted from observations at 79 meteorological stations in the study area during the first flood season (April-June) from 1960 to 2012. The trends of the mean (Mn) and variance (Var) of MDP are detected using the Generalized Additive Models for Location, Scale, and Shape parameters (GAMLSS) and Mann-Kendall test. The contributions of natural climate change and human activities to the Mn and Var changes of MDP are investigated using six large-scale circulation variables and emissions of four greenhouse gases based on GAMLSS and a contribution analysis method. The results demonstrate that the nonstationarity of extreme precipitation on local scales is significant. The Mn and Var of extreme precipitation increase in the north of Zhejiang, the middle of Fujian, and the south of Guangdong. In general, natural climate change contributes more to Mn from 1960 to 2012 than to Var. However, human activities cause a greater Var in the rapid socioeconomic development period (1986-2012) than in the slow socioeconomic development period (1960-1985), especially in Zhejiang and Guangdong. The community should pay more attention to the possibility of extreme precipitation events and associated disasters triggered by human activities.
ScaleNet: a literature-based model of scale insect biology and systematics.
García Morales, Mayrolin; Denno, Barbara D; Miller, Douglass R; Miller, Gary L; Ben-Dov, Yair; Hardy, Nate B
2016-01-01
Scale insects (Hemiptera: Coccoidea) are small herbivorous insects found on all continents except Antarctica. They are extremely invasive, and many species are serious agricultural pests. They are also emerging models for studies of the evolution of genetic systems, endosymbiosis and plant-insect interactions. ScaleNet was launched in 1995 to provide insect identifiers, pest managers, insect systematists, evolutionary biologists and ecologists efficient access to information about scale insect biological diversity. It provides comprehensive information on scale insects taken directly from the primary literature. Currently, it draws from 23,477 articles and describes the systematics and biology of 8194 valid species. For 20 years, ScaleNet ran on the same software platform. That platform is no longer viable. Here, we present a new, open-source implementation of ScaleNet. We have normalized the data model, begun the process of correcting invalid data, upgraded the user interface, and added online administrative tools. These improvements make ScaleNet easier to use and maintain and make the ScaleNet data more accurate and extendable. Database URL: http://scalenet.info. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.
Microstructural Origins of Nonlinear Response in Associating Polymers under Oscillatory Shear
Wilson, Mark A.; Baljon, Arlette R. C.
2017-10-26
The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves show nonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topologymore » resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Lastly, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Malony, Allen D; Shende, Sameer
This is the final progress report for the FastOS (Phase 2) (FastOS-2) project with Argonne National Laboratory and the University of Oregon (UO). The project started at UO on July 1, 2008 and ran until April 30, 2010, at which time a six-month no-cost extension began. The FastOS-2 work at UO delivered excellent results in all research work areas: * scalable parallel monitoring * kernel-level performance measurement * parallel I/0 system measurement * large-scale and hybrid application performance measurement * onlne scalable performance data reduction and analysis * binary instrumentation
NASA Technical Reports Server (NTRS)
Baker, V. R.
1985-01-01
Geomorphology is entering a new era of discovery and scientific excitement centered on expanding scales of concern in both time and space. The catalysts for this development include technological advances in global remote sensing systems, mathematical modeling, and the dating of geomorphic surfaces and processes. Even more important are new scientific questions centered on comparative planetary geomorphology, the interaction of tectonism with landscapes, the dynamics of late Cenozoic climatic changes, the influence of cataclysmic processes, the recognition of extremely ancient landforms, and the history of the world's hydrologic systems. These questions all involve feedback relationships with allied sciences that have recently yielded profound developments.
Research on power market technical analysis index system employing high-low matching mechanism
NASA Astrophysics Data System (ADS)
Li, Tao; Wang, Shengyu
2018-06-01
The power market trading technical analysis refers to a method that takes the bidding behavior of members in the power market as the research object, sums up some typical market rules and price trends by applying mathematical and logical methods, and finally can effectively assist members in the power market to make more reasonable trading decisions. In this paper, the following four indicators have been proposed: bidding price difference scale, extreme bidding price rate, dispersion of bidding price and monthly transaction satisfaction of electricity trading, which are the core of the index system.
Remembrance of ecohydrologic extremes past
NASA Astrophysics Data System (ADS)
Band, L. E.; Hwang, T.
2013-12-01
Ecohydrological systems operate at time scales that span several orders of magnitude. Significant processes and feedbacks range from subdaily physiologic response to meteorological drivers, to soil forming and geomorphic processes ranging up through 10^3-10^4 years. While much attention in ecohydrology has focused on ecosystem optimization paradigms, these systems can show significant transience in structure and function, with apparent memory of hydroclimate extremes and regime shifts. While optimization feedbacks can be reconciled with system transience, a better understanding of the time scales and mechanisms of adjustment to increased hydroclimate variability and to specific events is required to understand and predict dynamics and vulnerability of ecosystems. Under certain circumstances of slowly varying hydroclimate, we hypothesize that ecosystems can remain adjusted to changing climate regimes, without displaying apparent system memory. Alternatively, rapid changes in hydroclimate and increased hydroclimate variability, amplified with well expressed non-linearity in the processes controlling feedbacks between water, carbon and nutrients, can move ecosystems far from adjusted states. The Coweeta Hydrological Laboratory is typical of humid, broadleaf forests in eastern North America, with a range of forest biomes from northern hardwoods at higher elevations, to oak-pine assemblages at lower elevations. The site provides almost 80 years of rainfall-runoff records for a set of watersheds under different management, along with multi-decadal forest plot structural information, soil moisture conditions and stream chemistry. An initial period of multi-decadal cooling, was followed by three decades of warming and increased hydroclimate variability. While mean temperature has risen over this time period, precipitation shows no long term trends in the mean, but has had a significant rise in variability with repeated extreme drought and wet periods. Over this latter period, intra and interannual shifts of canopy structure and phenology are discernable, along with long term canopy adjustment. We use a combination of field observations, long term remote sensing records and distributed ecohydrological modeling to investigate transient behavior, apparent memory and mechanisms of ecosystem adjustment to hydroclimate variability and change over the range of biomes in the watershed.
Gravity and Extreme Magnetism SMEX
NASA Technical Reports Server (NTRS)
Swank, Jean; Kallman, Timothy R.; Jahoda, Keith M.
2008-01-01
Gas accreting ont,o black holes and neutron stars form a dynamic system generating X-rays with spectroscopic signatures and varying on time scales determined by the system. The radiation from various parts of these systems is surely polarized and compact sources have been calculated to give rise to net polarization from the unresolved sum of the radiation from the systems. Polarization has been looked to for some time as also bearing the imprint of strong gravity and providing complementary information that could resolve ambiguities between the physical models that can give rise to frequencies, time delays, and spectra. In the cases of both stellar black holes and supermassive black holes the net polarizations predicted for probable disk and corona models are less than 10 needed. This sensitivity can be achieved, even for sources as faint as 1 milliCrab, in the Gravity and Extreme Magnetism SMEX (GEMS) mission that uses foil mirrors and Time Projection Chamber detectors. Similarities have been pointed out between the timing and the spectral characteristics of low mass X-ray binaries and stellar black hole sources. Polarization measurements for these sources could play a role in determining the configuration of the disk and the neutron star.
Predictors of Drought Recovery across Forest Ecosystems
NASA Astrophysics Data System (ADS)
Anderegg, W.
2016-12-01
The impacts of climate extremes on terrestrial ecosystems are poorly understood but central for predicting carbon cycle feedbacks to climate change. Coupled climate-carbon cycle models typically assume that vegetation recovery from extreme drought is immediate and complete, which conflicts with basic plant physiological understanding. Here, we discuss what we have learned about forest ecosystem recovery from extreme drought across spatial and temporal scales, drawing on inference from tree rings, eddy covariance data, large scale gross primary productivity products, and ecosystem models. In tree rings, we find pervasive and substantial "legacy effects" of reduced growth and incomplete recovery for 1-4 years after severe drought, and that legacy effects are most prevalent in dry ecosystems, Pinaceae, and species with low hydraulic safety margins. At larger scales, we see relatively rapid recovery of ecosystem fluxes, with strong influences of ecosystem productivity and diversity and longer recovery periods in high latidue forests. In contrast, no or limited legacy effects are simulated in current climate-vegetation models after drought, and we highlight some of the key missing mechanisms in dynamic vegetation models. Our results reveal hysteresis in forest ecosystem carbon cycling and delayed recovery from climate extremes and help advance a predictive understanding of ecosystem recovery.
Liu, Xu; Chen, Haiping; Xue, Chen
2018-01-01
Objectives Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. Methods This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Results Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. Conclusion The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise. PMID:29440876
NASA Astrophysics Data System (ADS)
OBrien, J. P.; O'Brien, T. A.
2015-12-01
Single climatic extremes have a strong and disproportionate effect on society and the natural environment. However, the joint occurrence of two or more concurrent extremes has the potential to negatively impact these areas of life in ways far greater than any single event could. California, USA, home to nearly 40 million people and the largest agricultural producer in the United States, is currently experiencing an extreme drought, which has persisted for several years. While drought is commonly thought of in terms of only precipitation deficits, above average temperatures co-occurring with precipitation deficits greatly exacerbate drought conditions. The 2014 calendar year in California was characterized both by extremely low precipitation and extremely high temperatures, which has significantly deepened the already extreme drought conditions leading to severe water shortages and wildfires. While many studies have shown the statistics of 2014 temperature and precipitation anomalies as outliers, none have demonstrated a connection with large-scale, long-term climate trends, which would provide useful relationships for predicting the future trajectory of California climate and water resources. We focus on understanding non-stationarity in the joint distribution of California temperature and precipitation anomalies in terms of large-scale, low-frequency trends in climate such as global mean temperature rise and oscillatory indices such as ENSO and the Pacific Decadal Oscillation among others. We consider temperature and precipitation data from the seven distinct climate divisions in California and employ a novel, high-fidelity kernel density estimation method to directly infer the multivariate distribution of temperature and precipitation anomalies conditioned on the large-scale state of the climate. We show that the joint distributions and associated statistics of temperature and precipitation are non-stationary and vary regionally in California. Further, we show that recurrence intervals of extreme concurrent events vary as a function of time and of teleconnections. This research has implications for predicting and forecasting future temperature and precipitation anomalies, which is critically important for city, water, and agricultural planning in California.
Changing Pattern of Indian Monsoon Extremes: Global and Local Factors
NASA Astrophysics Data System (ADS)
Ghosh, Subimal; Shastri, Hiteshri; Pathak, Amey; Paul, Supantha
2017-04-01
Indian Summer Monsoon Rainfall (ISMR) extremes have remained a major topic of discussion in the field of global change and hydro-climatology over the last decade. This attributes to multiple conclusions on changing pattern of extremes along with poor understanding of multiple processes at global and local scales associated with monsoon extremes. At a spatially aggregate scale, when number of extremes in the grids are summed over, a statistically significant increasing trend is observed for both Central India (Goswami et al., 2006) and all India (Rajeevan et al., 2008). However, such a result over Central India does not satisfy flied significance test of increase and no decrease (Krishnamurthy et al., 2009). Statistically rigorous extreme value analysis that deals with the tail of the distribution reveals a spatially non-uniform trend of extremes over India (Ghosh et al., 2012). This results into statistically significant increasing trend of spatial variability. Such an increase of spatial variability points to the importance of local factors such as deforestation and urbanization. We hypothesize that increase of spatial average of extremes is associated with the increase of events occurring over large region, while increase in spatial variability attributes to local factors. A Lagrangian approach based dynamic recycling model reveals that the major contributor of moisture to wide spread extremes is Western Indian Ocean, while land surface also contributes around 25-30% of moisture during the extremes in Central India. We further test the impacts of local urbanization on extremes and find the impacts are more visible over West central, Southern and North East India. Regional atmospheric simulations coupled with Urban Canopy Model (UCM) shows that urbanization intensifies extremes in city areas, but not uniformly all over the city. The intensification occurs over specific pockets of the urban region, resulting an increase in spatial variability even within the city. This also points to the need of setting up multiple weather stations over the city at a finer resolution for better understanding of urban extremes. We conclude that the conventional method of considering large scale factors is not sufficient for analysing the monsoon extremes and characterization of the same needs a blending of both global and local factors. Ghosh, S., Das, D., Kao, S-C. & Ganguly, A. R. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Clim. Change 2, 86-91 (2012) Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S. & Xavier, P. K. Increasing trend of extreme rain events over India in a warming environment. Science 314, 1442-1445 (2006). Krishnamurthy, C. K. B., Lall, U. & Kwon, H-H. Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Clim. 22, 4737-4746 (2009). Rajeevan, M., Bhate, J. & Jaswal, A. K. Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys. Res. Lett. 35, L18707 (2008).
NASA Astrophysics Data System (ADS)
Gao, X.; Schlosser, C. A.
2013-12-01
Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency and intensity distribution of precipitation, especially at the regional scale. In this study, gridded data from a dense network of surface precipitation gauges and a global atmospheric analysis at a coarser scale are combined to develop a diagnostic framework for the large-scale meteorological conditions (i.e. flow features, moisture supply) that dominate during extreme precipitation. Such diagnostic framework is first evaluated with the late 20th century simulations from an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and is found to produce more consistent (and less uncertain) total and interannaul number of extreme days with the observations than the model-based precipitation over the south-central United States and the Western United States examined in this study. The framework is then applied to the CMIP5 multi-model projections for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5) to assess the potential future changes in the probability of precipitation extremes over the same study regions. We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.
Assessing changes in extreme convective precipitation from a damage perspective
NASA Astrophysics Data System (ADS)
Schroeer, K.; Tye, M. R.
2016-12-01
Projected increases in high-intensity short-duration convective precipitation are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to which, not only are extreme events rare, but such small scale events are likely to be underreported where they don't coincide with the observation network. Rather than focus solely on the convective precipitation, understanding the characteristics of these extremes which drive damage may be more effective to assess future risks. Two sources of data are used in this study. First, sub-daily precipitation observations over the Southern Alps enable an examination of seasonal and regional patterns in high-intensity convective precipitation and their relationship with weather types. Secondly, reports of private loss and damage on a household scale are used to identify which events are most damaging, or what conditions potentially enhance the vulnerability to these extremes.This study explores the potential added value from including recorded loss and damage data to understand the risks from summertime convective precipitation events. By relating precipitation generating weather types to the severity of damage we hope to develop a mechanism to assess future risks. A further benefit would be to identify from damage reports the likely occurrence of precipitation extremes where no direct observations are available and use this information to validate remotely sensed observations.
Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William
2016-01-01
Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.
Space Radiation Effects in Advanced Flash Memories
NASA Technical Reports Server (NTRS)
Johnston, A. H.
2001-01-01
Memory storage requirements in space systems have steadily increased, much like storage requirements in terrestrial systems. Large arrays of dynamic memories (DRAMs) have been used in solid-state recorders, relying on a combination of shielding and error-detection-and correction (EDAC) to overcome the extreme sensitivity of DRAMs to space radiation. For example, a 2-Gbit memory (with 4-Mb DRAMs) used on the Clementine mission functioned perfectly during its moon mapping mission, in spite of an average of 71 memory bit flips per day from heavy ions. Although EDAC worked well with older types of memory circuits, newer DRAMs use extremely complex internal architectures which has made it increasingly difficult to implement EDAC. Some newer DRAMs have also exhibited catastrophic latchup. Flash memories are an intriguing alternative to DRAMs because of their nonvolatile storage and extremely high storage density, particularly for applications where writing is done relatively infrequently. This paper discusses radiation effects in advanced flash memories, including general observations on scaling and architecture as well as the specific experience obtained at the Jet Propulsion Laboratory in evaluating high-density flash memories for use on the NASA mission to Europa, one of Jupiter's moons. This particular mission must pass through the Jovian radiation belts, which imposes a very demanding radiation requirement.
Extreme flood impact on estuarine and coastal biogeochemistry: the 2013 Elbe flood
NASA Astrophysics Data System (ADS)
Voynova, Yoana G.; Brix, Holger; Petersen, Wilhelm; Weigelt-Krenz, Sieglinde; Scharfe, Mirco
2017-02-01
Within the context of the predicted and observed increase in droughts and floods with climate change, large summer floods are likely to become more frequent. These extreme events can alter typical biogeochemical patterns in coastal systems. The extreme Elbe River flood in June 2013 not only caused major damages in several European countries but also generated large-scale biogeochemical changes in the Elbe estuary and the adjacent German Bight. The high-frequency monitoring network within the Coastal Observing System for Northern and Arctic Seas (COSYNA) captured the flood influence on the German Bight. Data from a FerryBox station in the Elbe estuary (Cuxhaven) and from a FerryBox platform aboard the M/V Funny Girl ferry (traveling between Büsum and Helgoland) documented the salinity changes in the German Bight, which persisted for about 2 months after the peak discharge. The Elbe flood generated a large influx of nutrients and dissolved and particulate organic carbon on the coast. These conditions subsequently led to the onset of a phytoplankton bloom, observed by dissolved oxygen supersaturation, and higher than usual pH in surface coastal waters. The prolonged stratification also led to widespread bottom water dissolved oxygen depletion, unusual for the southeastern German Bight in the summer.
NASA Technical Reports Server (NTRS)
Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Feng, Zhe; Entin, Jared K.; Houser, Paul R.; Schiffer, Robert A.; LEucyer, Tristan; Olson, William S.; Hsu, Kuo-lin;
2010-01-01
Hydrological years 2006 (HY06, 10/2005-09/2006) and 2007 (HY07, 10/2006-09/2007) provide a unique opportunity to examine hydrological extremes in the central US because there are no other examples of two such highly contrasting precipitation extremes occurring in consecutive years at the Southern Great Plains (SGP) in recorded history. The HY06 annual precipitation in the state of Oklahoma, as observed by the Oklahoma Mesonet, is around 61% of the normal (92.84 cm, based on the 1921-2008 climatology), which results in HY06 the second-driest year in the record. In particular, the total precipitation during the winter of 2005-06 is only 27% of the normal, and this winter ranks as the driest season. On the other hand, the HY07 annual precipitation amount is 121% of the normal and HY07 ranks as the seventh-wettest year for the entire state and the wettest year for the central region of the state. Summer 2007 is the second-wettest season for the state. Large-scale dynamics play a key role in these extreme events. During the extreme dry period (10/2005-02/2006), a dipole pattern in the 500-hPa GH anomaly existed where an anomalous high was over the southwestern U.S. region and an anomalous low was over the Great Lakes. This pattern is associated with inhibited moisture transport from the Gulf of Mexico and strong sinking motion over the SGP, both contributing to the extreme dryness. The precipitation deficit over the SGP during the extreme dry period is clearly linked to significantly suppressed cyclonic activity over the southwestern U.S., which shows robust relationship with the Western Pacific (WP) teleconnection pattern. The precipitation events during the extreme wet period (May-July 2007) were initially generated by active synoptic weather patterns, linked with moisture transport from the Gulf of Mexico by the northward low level jet, and enhanced by the mesoscale convective systems. Although the drought and pluvial conditions are dominated by large-scale dynamic patterns, we have demonstrated that the two positive feedback processes during the extreme dry and wet periods found in this study play a key role to maintain and reinforce the length and severity of existing drought and flood events. For example, during the extreme dry period, with less clouds, LWP, PWV, precipitation, and thinner Cu cloud thickness, more net radiation was absorbed and used to evaporate water from the ground. The evaporated moisture, however, was removed by low-level divergence. Thus, with less precipitation and removed atmospheric moisture, more absorbed incoming solar radiation was used to increase surface temperature and to make the ground drier.
Modeling extreme sea levels due to tropical and extra-tropical cyclones at the global-scale
NASA Astrophysics Data System (ADS)
Muis, S.; Lin, N.; Verlaan, M.; Winsemius, H.; Ward, P.; Aerts, J.
2017-12-01
Extreme sea levels, a combination of storm surges and astronomical tides, can cause catastrophic floods. Due to their intense wind speeds and low pressure, tropical cyclones (TCs) typically cause higher storm surges than extra-tropical cyclones (ETCs), but ETCs may still contribute significantly to the overall flood risk. In this contribution, we show a novel approach to model extreme sea levels due to both tropical and extra-tropical cyclones at the global-scale. Using a global hydrodynamic model we have developed the Global Tide and Surge Reanalysis (GTSR) dataset (Muis et al., 2016), which provides daily maximum timeseries of storm tide from 1979 to 2014. GTSR is based on wind and pressure fields from the ERA-Interim climate reanalysis (Dee at al., 2011). A severe limitation of the GTSR dataset is the underrepresentation of TCs. This is due to the relatively coarse grid resolution of ERA-Interim, which means that the strong intensities of TCs are not fully included. Furthermore, the length of ERA-Interim is too short to estimate the probabilities of extreme TCs in a reliable way. We will discuss potential ways to address this limitation, and demonstrate how to improve the global GTSR framework. We will apply the improved framework to the east coast of the United States. First, we improve our meteorological forcing by applying a parametric hurricane model (Holland 1980), and we improve the tide and surge reanalysis dataset (Muis et al., 2016) by explicitly modeling the historical TCs in the Extended Best Track dataset (Demuth et al., 2006). Second, we improve our sampling by statistically extending the observed TC record to many thousands of years (Emanuel et al., 2006). The improved framework allows for the mapping of probabilities of extreme sea levels, including extremes TC events, for the east coast of the United States. ReferencesDee et al (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553-97. Emanuel et al (2006). A Statistical Deterministic Approach to Hurricane Risk Assessment/ Bull. Am. Meteorol. Soc. 87, 299-314. Holland (1980). An analytic model of the wind and pressure profiles in hurricanes. Mon. Weather Rev. 108, 1212-1218. Muis et al (2016). A global reanalysis of storm surge and extreme sea levels. Nat. Commun. 7, 1-11
Spatial correlation of the dynamic propensity of a glass-forming liquid
NASA Astrophysics Data System (ADS)
Razul, M. Shajahan G.; Matharoo, Gurpreet S.; Poole, Peter H.
2011-06-01
We present computer simulation results on the dynamic propensity (as defined by Widmer-Cooper et al 2004 Phys. Rev. Lett. 93 135701) in a Kob-Andersen binary Lennard-Jones liquid system consisting of 8788 particles. We compute the spatial correlation function for the dynamic propensity as a function of both the reduced temperature T, and the time scale on which the particle displacements are measured. For T <= 0.6, we find that non-zero correlations occur at the largest length scale accessible in our system. We also show that a cluster-size analysis of particles with extremal values of the dynamic propensity, as well as 3D visualizations, reveal spatially correlated regions that approach the size of our system as T decreases, consistently with the behavior of the spatial correlation function. Next, we define and examine the 'coordination propensity', the isoconfigurational average of the coordination number of the minority B particles around the majority A particles. We show that a significant correlation exists between the spatial fluctuations of the dynamic and coordination propensities. In addition, we find non-zero correlations of the coordination propensity occurring at the largest length scale accessible in our system for all T in the range 0.466 < T < 1.0. We discuss the implications of these results for understanding the length scales of dynamical heterogeneity in glass-forming liquids.
NASA Technical Reports Server (NTRS)
Kirschbaum, Dalia; Adler, Robert; Adler, David; Peters-Lidard, Christa; Huffman, George
2012-01-01
It is well known that extreme or prolonged rainfall is the dominant trigger of landslides worldwide. While research has evaluated the spatiotemporal distribution of extreme rainfall and landslides at local or regional scales using in situ data, few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This study uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from TRMM data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurrence of precipitation and landslides globally. Evaluation of the GLC indicates that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This study characterizes the variability of satellite precipitation data and reported landslide activity at the globally scale in order to improve landslide cataloging, forecasting and quantify potential triggering sources at daily, monthly and yearly time scales.
Identification and characterization of extraordinary rainstorms in Italy
NASA Astrophysics Data System (ADS)
Libertino, Andrea; Ganora, Daniele; Claps, Pierluigi
2017-04-01
Despite its generally mild climate, Italy, as most of the Mediterranean region, is prone to the development of "super-extreme" events with extraordinary rainfall intensities. The main triggering mechanisms of these events is nowadays quite well known, but more research is needed to transform this knowledge in directions to build updated rainstorm hazard maps at the national scale. Moreover, a precise definition of "super-extremes" is still lacking, since the original suggestion of a second specific EV1 component made with the TCEV distribution. The above considerations led us to consider Italy a peculiar and challenging case study, where the geographic and orographic settings, associated with recurring storm-induced disasters, require an updated assessment of the "super-extreme" rainfall hazard at the country scale. Until now, the lack of a unique dataset of rainfall extremes has made the above task difficult to reach. In this work we report the results of the analysis made on a comprehensive and uniform set of rainfall annual maxima, collected from the different authorities in charge, representing the reference dataset of extremes from 1 to 24 hours duration. The database includes more than 6000 measuring points nationwide, spanning the period 1916 - 2014. Our analysis aims at identifying a meaningful population of records deviating from an "ordinary" definition of extreme value distribution, and assessing the stationarity in the timing of these events at the national scale. The first problems that need to be overcome are related to the not uniform distribution of data in time and space. Then the evaluation of meaningful relative thresholds aimed at selecting significant samples for the trend assessment has to be addressed. A first investigation attempt refers to the events exceeding a threshold that identify an average of one occurrence per year all over Italy, i.e. with a 1/1000 overall probability of exceedance. Geographic representation of these "outliers", scaled on local averages, demonstrates some prevailing clustering on the Thyrrenian coastal areas. Subsequent application of quantile regressions, aimed at minimizing the temporal non-uniformity of samples, shows significant increasing trends on the extremes of very short duration. Further efforts have been undertaken to explore the selection of a common national set of higher order parameters all over Italy, that would make less arduous to identify the probability of occurrence of "super-extremes" in the country.
NASA Astrophysics Data System (ADS)
Dugger, A. L.; Zhang, Y.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L.; Rafieeinasab, A.; Sampson, K. M.; Salas, F.; Read, L.; Pan, L.; Yates, D. N.; Cosgrove, B.; Clark, E. P.
2017-12-01
Streamflow extremes (lows and peaks) tend to have disproportionately higher impacts on the human and natural systems compared to mean streamflow. Examining and understanding the spatiotemporal distributions of streamflow extremes is of significant interests to both the research community and the water resources management. In this work, the output from the 24-year (1993 through 2016) retrospective runs of the National Water Model (NWM) version of WRF-Hydro will be analyzed for streamflow extremes over the CONUS domain. The CONUS domain was configured at 1-km resolution for land surface grid and 250-m resolution for terrain routing. The WRF-Hydro runs were forced by the regridded and downscaled NLDAS2 data. The analyses focus on daily mean streamflow values over the full water year and within the summer and winter seasons. Connections between NWM streamflow and other hydrologic variables (e.g. snowpack, soil moisture/saturation and ET) with variations in large-scale climate phenomena, e.g., El Niño - Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and North American monsoon are examined. The CONUS domain has a diverse environment and is characterized by complex terrain, heterogeneous land surfaces and ecosystems, and numerous hydrological basins. The potential dependence of streamflow extremes on regional terrain character, climatic conditions, and ecologic zones will also be investigated.
Uehara, Kosuke; Ogura, Koichi; Akiyama, Toru; Shinoda, Yusuke; Iwata, Shintaro; Kobayashi, Eisuke; Tanzawa, Yoshikazu; Yonemoto, Tsukasa; Kawano, Hirotaka; Kawai, Akira
2017-09-01
The Musculoskeletal Tumor Society (MSTS) scoring system developed in 1993 is a widely used disease-specific evaluation tool for assessment of physical function in patients with musculoskeletal tumors; however, only a few studies have confirmed its reliability and validity. The aim of this study was to validate the MSTS scoring system for the upper extremity (MSTS-UE) in Japanese patients with musculoskeletal tumors for use by others in research. Does the MSTS-UE have: (1) sufficient reliability and internal consistency; (2) adequate construct validity; and (3) reasonable criterion validity in comparison to the Toronto Extremity Salvage Score (TESS) or SF-36? Reliability was performed using test-retest analysis, and internal consistency was evaluated with Cronbach's alpha coefficient. Construct validity was evaluated using a scree plot to confirm the construct number and the Akaike information criterion network. Criterion validity was evaluated by comparing the MSTS-UE with the TESS and SF-36. The test-retest reliability with intraclass correlation coefficient (0.95; 95% CI, 0.91-0.97) was excellent, and internal consistency with Cronbach's α (0.7; 95% CI, 0.53-0.81) was acceptable. There were no ceiling and floor effects. The Akaike Information Criterion network showed that lifting ability, pain, and dexterity played central roles among the components. The MSTS-UE showed substantial correlation with the TESS scoring scale (r = 0.75; p < 0.001) and fair correlation with the SF-36 physical component summary (r = 0.37; p = 0.007). Although the MSTS-UE showed slight correlation with the SF-36 mental component summary, the emotional acceptance component of the MSTS-UE showed fair correlation (r = 0.29; p = 0.039). We can conclude that the MSTS is not an adequate measure of general health-related quality of life; however, this system was designed mainly to be a simple measure of function in a single extremity. To evaluate the mental state of patients with musculoskeletal tumors in the upper extremity, further study is needed.
21st Century Changes in Precipitation Extremes Based on Resolved Atmospheric Patterns
NASA Astrophysics Data System (ADS)
Gao, X.; Schlosser, C. A.; O'Gorman, P. A.; Monier, E.
2014-12-01
Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency distribution of precipitation, especially at the regional scale. In this study, a validated analogue method is employed to diagnose the potential future shifts in the probability of extreme precipitation over the United States under global warming. The method is based on the use of the resolved large-scale meteorological conditions (i.e. flow features, moisture supply) to detect the occurrence of extreme precipitation. The CMIP5 multi-model projections have been compiled for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The application of such analogue method to detect other types of hazard events, i.e. landslides is also explored. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.
Lejiang Yu; Shiyuan Zhong; Lisi Pei; Xindi (Randy) Bian; Warren E. Heilman
2016-01-01
The mean global climate has warmed as a result of the increasing emission of greenhouse gases induced by human activities. This warming is considered the main reason for the increasing number of extreme precipitation events in the US. While much attention has been given to extreme precipitation events occurring over several days, which are usually responsible for...
Variations/Changes in Daily Precipitation Extremes Derived from Satellite-Based Products
NASA Astrophysics Data System (ADS)
Gu, G.; Adler, R. F.
2017-12-01
Interannual/decadal-scale variations/changes in daily precipitation extremes are investigated by means of satellite-based high-spatiotemporal resolution precipitation products, including TRMM-TMPA, PERSIANN-CDR-Daily, GPCP 1DD, etc. Extreme precipitation indices at grids are first defined, including the maximum daily precipitation amount (Rx1day), the simple precipitation intensity index (SDII), the conditional (Rcond) daily precipitation rate (Pr>0 mm day-1), and monthly frequencies of rainy (FOCc) and wet (FOCw) days. Other two precipitation intensity indices, i.e., mean daily precipitation rates for Pr ≥10 mm day-1 (Pr10II) and for Pr ≥ 20 mm day-1 (Pr20II), are also constructed. Consistency analyses of daily extreme indices among these data sets are then performed by comparing corresponding averages over large domains such as tropical (30oN-30oS) land, ocean, land+ocean, for their common period (post-1997). This can provide a preliminary uncertainty analysis of these data sets in describing daily extreme precipitation events. Discrepancies can readily be found among these products regarding the magnitudes of area-averaged extreme indices. However, generally consistent temporal variations can be found among the indices derived from different satellite products. Interannual variability in daily precipitation extremes are then examined and compared at grids by exploring their relations with the El Nino-Southern Oscillation (ENSO). Linear correlation and composite analyses are used to examine the impact of ENSO on these extreme indices at grids and over large domains during the post-1997 period. Decadal-scale variability/change in daily extreme events is further examined by using the PERSIANN-CDR-Daily that can cover the entire post-1983 period, based on its general consistency with other two products during the post-1979 period. We specifically focus on exploring and discriminating the effects of decadal-scale internal variability such as the Pacific Decadal Oscillation (PDO) and anthropogenic forcings including the greenhouse-gases (GHG) related warming. Comparisons are also made over global land with the results from two gridded daily rain-gauge products, GPCC Full-record daily (1988-2013) and NOAA/CPC Unified daily (1979-present).
Crawford, H J; Brown, A M; Moon, C E
1993-11-01
Relations between sustained attentional and disattentional abilities and hypnotic susceptibility (Harvard Group Scale of Hypnotic Susceptibility: Form A; Stanford Hypnotic Susceptibility Scale: Form C) were examined in 38 low (0-3) and 39 highly (10-12) hypnotizable college students. Highs showed greater sustained attention on Necker cube and autokinetic movement tasks and self-reported greater absorption (Tellegen Absorption Scale) and extremely focused attentional (Differential Attentional Processes Inventory) styles. Hypnotizability was unrelated to dichotic selective attention (A. Karlin, 1979) and random number generation (C. Graham & F. J. Evans, 1977) tasks. Discriminant analysis correctly classified 74% of the lows and 69% of the highs. Results support H. J. Crawford and J. H. Gruzelier's (1992) neuropsychophysiological model of hypnosis that proposes that highly hypnotizable persons have a more efficient far frontolimbic sustained attentional and disattentional system.
Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict dru
Extreme-Scale Computing Project Aims to Advance Precision Oncology | Poster
Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict drug response, and improve treatments for patients.
NASA Astrophysics Data System (ADS)
Rosenzweig, B.; Vorosmarty, C. J.; Stewart, R. J.; Miara, A.; Lu, X.; Kicklighter, D. W.; Ehsani, N.; Wollheim, W. M.; Melillo, J. M.; Fekete, B. M.; Dilekli, N.; Duchin, F.; Gross, B.; Bhatt, V.
2014-12-01
'Megaregions' have been identified as an important new scale of geography for policy decision-making in the United States. These regions extend beyond local boundaries (ie. cities, states) to incorporate areas with linked economies, infrastructure and land-use patterns and shared climate and environmental systems, such as watersheds. The corridor of densely connected metropolitan areas and surrounding hinterlands along the U.S. east coast from Maine to Virginia is the archetype of this type of unit: The Northeast Megaregion. The Northeast faces a unique set of policy challenges including: projections of a wetter, more extreme climate, aging and underfunded infrastructure and economically distressed rural areas. Megaregion-scale policy efforts such as the Regional Greenhouse Gas Initiative (RGGI) and support for a regional food system have been recognized as strategic tools for climate change mitigation and adaptation, but decision-makers have limited information on the potential consequences of these strategies on the complex natural-human system of the Northeast, under various scenarios of global climate change. We have developed a Northeast Regional Earth System Model (NE-RESM) as a framework to provide this type of information. We integrate terrestrial ecosystem, hydrologic, energy system and economic models to investigate scenarios of paired regional socioeconomic pathways and global climate projections. Our initial results suggest that megaregion-scale strategic decisions in the Northeast may have important consequences for both local water management and global climate change mitigation.
Uswatte, Gitendra; Taub, Edward; Morris, David; Vignolo, Mary; McCulloch, Karen
2005-11-01
In research on Constraint-Induced Movement (CI) therapy, a structured interview, the Motor Activity Log (MAL), is used to assess how stroke survivors use their more-impaired arm outside the laboratory. This article examines the psychometrics of the 14-item version of this instrument in 2 chronic stroke samples with mild-to-moderate upper-extremity hemiparesis. Participants (n=41) in the first study completed MALs before and after CI therapy or a placebo control procedure. In addition, caregivers independently completed a MAL on the participants. Participants (n=27) in the second study completed MALs and wore accelerometers that monitored their arm movements for 3 days outside the laboratory before and after an automated form of CI therapy. Validity of the participant MAL Quality of Movement (QOM) scale was supported. Correlations between pretreatment-to-posttreatment change scores on the participant QOM scale and caregiver MAL QOM scale, caregiver MAL amount of use (AOU) scale, and accelerometer recordings were 0.70, 0.73, and 0.91 (P<0.01), respectively. Internal consistency (alpha>0.81), test-retest reliability (r>0.91), stability, and responsiveness (ratio>3) of the participant QOM scale were also supported. The participant AOU and caregiver QOM and AOU scales were internally consistent, stable, and sensitive, but were not reliable. The participant MAL QOM scale can be used exclusively to reliably and validly measure real-world, upper-extremity rehabilitation outcome and functional status in chronic stroke patients with mild-to-moderate hemiparesis.
NASA Astrophysics Data System (ADS)
Agel, Laurie; Barlow, Mathew; Colby, Frank; Binder, Hanin; Catto, Jennifer L.; Hoell, Andrew; Cohen, Judah
2018-05-01
Previous work has identified six large-scale meteorological patterns (LSMPs) of dynamic tropopause height associated with extreme precipitation over the Northeast US, with extreme precipitation defined as the top 1% of daily station precipitation. Here, we examine the three-dimensional structure of the tropopause LSMPs in terms of circulation and factors relevant to precipitation, including moisture, stability, and synoptic mechanisms associated with lifting. Within each pattern, the link between the different factors and extreme precipitation is further investigated by comparing the relative strength of the factors between days with and without the occurrence of extreme precipitation. The six tropopause LSMPs include two ridge patterns, two eastern US troughs, and two troughs centered over the Ohio Valley, with a strong seasonality associated with each pattern. Extreme precipitation in the ridge patterns is associated with both convective mechanisms (instability combined with moisture transport from the Great Lakes and Western Atlantic) and synoptic forcing related to Great Lakes storm tracks and embedded shortwaves. Extreme precipitation associated with eastern US troughs involves intense southerly moisture transport and strong quasi-geostrophic forcing of vertical velocity. Ohio Valley troughs are associated with warm fronts and intense warm conveyor belts that deliver large amounts of moisture ahead of storms, but little direct quasi-geostrophic forcing. Factors that show the largest difference between days with and without extreme precipitation include integrated moisture transport, low-level moisture convergence, warm conveyor belts, and quasi-geostrophic forcing, with the relative importance varying between patterns.
How much do different global GPP products agree in distribution and magnitude of GPP extremes?
NASA Astrophysics Data System (ADS)
Kim, S.; Ryu, Y.; Jiang, C.
2016-12-01
To evaluate uncertainty of global Gross Primary Productivity (GPP) extremes, we compare three global GPP datasets derived from different data processing methods (e.g. MPI-BGC: machine-learning, MODIS GPP (MOD17): semi-empirical, Breathing Earth System Simulator (BESS): process based). We preprocess the datasets following the method from Zscheischler et al., (2012) to detect GPP extremes which occur in less than 1% of the number of whole pixels, and to identify 3D-connected spatiotemporal GPP extremes. We firstly analyze global patterns and the magnitude of GPP extremes with MPI-BGC, MOD17, and BESS over 2001-2011. For consistent analysis in the three products, spatial and temporal resolution were set at 50 km and a monthly scale, respectively. Our results indicated that the global patterns of GPP extremes derived from MPI-BGC and BESS agreed with each other by showing hotspots in Northeastern Brazil and Eastern Texas. However, the extreme events detected from MOD17 were concentrated in tropical forests (e.g. Southeast Asia and South America). The amount of GPP reduction caused by climate extremes considerably differed across the products. For example, Russian heatwave in 2010 led to 100 Tg C uncertainty (198.7 Tg C in MPI-BGC, 305.6 Tg C in MOD17, and 237.8 Tg C in BESS). Moreover, the duration of extreme events differ among the three GPP datasets for the Russian heatwave (MPI-BGC: May-Sep, MOD17: Jun-Aug, and BESS: May-Aug). To test whether Sun induced Fluorescence (SiF), a proxy of GPP, can capture GPP extremes, we investigate global distribution of GPP extreme events in BESS, MOD17 and GOME-2 SiF between 2008 and 2014 when SiF data is available. We found that extreme GPP events in GOME-2 SiF and MOD17 appear in tropical forests whereas those in BESS emerged in Northeastern Brazil and Eastern Texas. The GPP extremes by severe 2011 US drought were detected by BESS and MODIS, but not by SiF. Our findings highlight that different GPP datasets could result in varying duration and intensity of GPP extremes and distribution of hotspots, and this study could contribute to quantifying uncertainties in GPP extremes.
NASA Astrophysics Data System (ADS)
Vocke, Robert; Rabb, Savelas
2015-04-01
All isotope amount ratios (hereafter referred to as isotope ratios) produced and measured on any mass spectrometer are biased. This unfortunate situation results mainly from the physical processes in the source area where ions are produced. Because the ionized atoms in poly-isotopic elements have different masses, such processes are typically mass dependent and lead to what is commonly referred to as mass fractionation (for thermal ionization and electron impact sources) and mass bias (for inductively coupled plasma sources.) This biasing process produces a measured isotope ratio that is either larger or smaller than the "true" ratio in the sample. This has led to the development of numerous fractionation "laws" that seek to correct for these effects, many of which are not based on the physical processes giving rise to the biases. The search for tighter and reproducible precisions has led to two isotope ratio measurement systems that exist side-by-side. One still seeks to measure "absolute" isotope ratios while the other utilizes an artifact based measurement system called a delta-scale. The common element between these two measurement systems is the utilization of isotope reference materials (iRMs). These iRMs are used to validate a fractionation "law" in the former case and function as a scale anchor in the latter. Many value assignments of iRMs are based on "best measurements" by the original groups producing the reference material, a not entirely satisfactory approach. Other iRMs, with absolute isotope ratio values, have been produced by calibrated measurements following the Atomic Weight approach (AW) pioneered by NBS nearly 50 years ago. Unfortunately, the AW is not capable of calibrating the new generation of iRMs to sufficient precision. So how do we get iRMs with isotope ratios of sufficient precision and without bias? Such a focus is not to denigrate the extremely precise delta-scale measurements presently being made on non-traditional and tradition stable isotope systems. But even absolute isotope ratio measurements have an important role to play in delta-scale schemes. Highly precise and unbiased measurements of the artifact anchor for any scale facilitates the replacement of that scale's anchor once the initial supply of the iRM is exhausted. Absolute isotope ratio measurements of artifacts at the positive and negative extremes of a delta-scale will allow the appropriate assignment of delta-values to these normalizing iRMs, thereby minimizing any scale contractions or expansions to either side of the anchor artifact. And finally, absolute values for critical iRMs with also allow delta-scale results to be used in other scientific disciplines that employ other units of measure. Precise absolute isotope ratios of Si has been one of the consequences of the Avogadro Project (an international effort to replace the original kilogram artifact with a natural constant, the Planck constant.) We will present the results of applying such measurements to the principal iRMs for the Si isotope system (SRM 990, Big Batch and Diatomite) and its consequences for their delta-Si29 and delta-Si30 values.
Intra-seasonal Characteristics of Wintertime Extreme Cold Events over South Korea
NASA Astrophysics Data System (ADS)
Park, Taewon; Jeong, Jeehoon; Choi, Jahyun
2017-04-01
The present study reveals the changes in the characteristics of extreme cold events over South Korea for boreal winter (November to March) in terms of the intra-seasonal variability of frequency, duration, and atmospheric circulation pattern. Influences of large-scale variabilities such as the Siberian High activity, the Arctic Oscillation (AO), and the Madden-Julian Oscillation (MJO) on extreme cold events are also investigated. In the early and the late of the winter during November and March, the upper-tropospheric wave-train for a life-cycle of the extreme cold events tends to pass quickly over East Asia. In addition, compared with the other months, the intensity of the Siberian High is weaker and the occurrences of strong negative AO are less frequent. It lead to events with weak amplitude and short duration. On the other hand, the amplified Siberian High and the strong negative AO occur more frequently in the mid of the winter from December to February. The extreme cold events are mainly characterized by a well-organized anticyclonic blocking around the Ural Mountain and the Subarctic. These large-scale circulation makes the extreme cold events for the midwinter last long with strong amplitude. The MJO phases 2-3 which provide a suitable condition for the amplification of extreme cold events occur frequently for November to January when the frequencies are more than twice those for February and March. While the extreme cold events during March have the least frequency, the weakest amplitude, and the shortest duration due to weak impacts of the abovementioned factors, the strong activities of the factors for January force the extreme cold events to be the most frequent, the strongest, and the longest among the boreal winter. Keywords extreme cold event, wave-train, blocking, Siberian High, AO, MJO
Extreme gaseous outflows in radio-loud narrow-line Seyfert 1 galaxies
NASA Astrophysics Data System (ADS)
Komossa, S.; Xu, D. W.; Wagner, A. Y.
2018-07-01
We present four radio-loud narrow-line Seyfert 1 (NLS1) galaxies with extreme emission-line shifts, indicating radial outflow velocities of the ionized gas of up to 2450 km s-1, above the escape velocity of the host galaxies. The forbidden lines show strong broadening, up to 2270 km s-1. An ionization stratification (higher line shift at higher ionization potential) implies that we see a large-scale outflow rather than single, localized jet-cloud interactions. Similarly, the paucity of zero-velocity [O III] λ5007 emitting gas implies the absence of a second narrow-line region (NLR) component at rest, and therefore a large part of the high-ionization NLR is affected by the outflow. Given the radio loudness of these NLS1 galaxies, the observations are consistent with a pole on view onto their central engines, so that the effects of polar outflows are maximized. In addition, a very efficient driving mechanism is required to reach the high observed velocities. We explore implications from recent hydrodynamic simulations of the interaction between fast winds or jets with the large-scale NLR. Overall, the best agreement with observations (and especially the high outflow speeds of the [Ne V] emitting gas) can be reached if the NLS1 galaxies are relatively young sources with lifetimes not much exceeding 1 Myr. These systems represent sites of strong feedback at NLR scales at work, well below redshift one.
Extreme Gaseous Outflows in Radio-Loud Narrow-Line Seyfert 1 Galaxies
NASA Astrophysics Data System (ADS)
Komossa, S.; Xu, D. W.; Wagner, A. Y.
2018-04-01
We present four radio-loud NLS1 galaxies with extreme emission-line shifts, indicating radial outflow velocities of the ionized gas of up to 2450 km/s, above the escape velocity of the host galaxies. The forbidden lines show strong broadening, up to 2270 km/s. An ionization stratification (higher line shift at higher ionization potential) implies that we see a large-scale outflow rather than single, localized jet-cloud interactions. Similarly, the paucity of zero-velocity [OIII]λ5007 emitting gas implies the absence of a second narrow-line region (NLR) component at rest, and therefore a large part of the high-ionization NLR is affected by the outflow. Given the radio loudness of these NLS1 galaxies, the observations are consistent with a pole on view onto their central engines, so that the effects of polar outflows are maximized. In addition, a very efficient driving mechanism is required, to reach the high observed velocities. We explore implications from recent hydrodynamic simulations of the interaction between fast winds or jets with the large-scale NLR. Overall, the best agreement with observations (and especially the high outflow speeds of the [NeV] emitting gas) can be reached if the NLS1 galaxies are relatively young sources with lifetimes not much exceeding 1 Myr. These systems represent sites of strong feedback at NLR scales at work, well below redshift one.
The structure and large-scale organization of extreme cold waves over the conterminous United States
NASA Astrophysics Data System (ADS)
Xie, Zuowei; Black, Robert X.; Deng, Yi
2017-12-01
Extreme cold waves (ECWs) occurring over the conterminous United States (US) are studied through a systematic identification and documentation of their local synoptic structures, associated large-scale meteorological patterns (LMPs), and forcing mechanisms external to the US. Focusing on the boreal cool season (November-March) for 1950‒2005, a hierarchical cluster analysis identifies three ECW patterns, respectively characterized by cold surface air temperature anomalies over the upper midwest (UM), northwestern (NW), and southeastern (SE) US. Locally, ECWs are synoptically organized by anomalous high pressure and northerly flow. At larger scales, the UM LMP features a zonal dipole in the mid-tropospheric height field over North America, while the NW and SE LMPs each include a zonal wave train extending from the North Pacific across North America into the North Atlantic. The Community Climate System Model version 4 (CCSM4) in general simulates the three ECW patterns quite well and successfully reproduces the observed enhancements in the frequency of their associated LMPs. La Niña and the cool phase of the Pacific Decadal Oscillation (PDO) favor the occurrence of NW ECWs, while the warm PDO phase, low Arctic sea ice extent and high Eurasian snow cover extent (SCE) are associated with elevated SE-ECW frequency. Additionally, high Eurasian SCE is linked to increases in the occurrence likelihood of UM ECWs.
NASA Astrophysics Data System (ADS)
Quinn, J.; Reed, P. M.; Giuliani, M.; Castelletti, A.; Oyler, J.; Nicholas, R.
2017-12-01
Multi-reservoir systems require robust and adaptive control policies capable of managing evolving hydroclimatic variability and human demands across a wide range of time scales. This is especially true for systems with high intra-annual and inter-annual variability, such as monsoonal river systems that need to buffer against seasonal droughts while also managing extreme floods. Moreover, the timing, intensity, duration, and frequency of these hydrologic extremes may be affected by deeply uncertain changes in socioeconomic and climatic pressures. This study contributes an innovative method for exploring how possible changes in the timing and magnitude of monsoonal seasonal extremes impact the robustness of reservoir operating policies optimized to historical conditions assuming stationarity. We illustrate this analysis on the Red River basin in Vietnam, where reservoirs and dams serve as important sources of hydropower production, irrigable water supply, and flood protection for the capital city of Hanoi. Applying our scenario discovery approach, we find food-energy-water tradeoffs are exacerbated by potential hydrologic shifts, with wetter worlds threatening the ability of operating strategies to manage flood risk and drier worlds threatening their ability to provide sufficient water supply and hydropower production, especially if demands increase. Most notably, though, amplification of the within-year monsoonal cycle and increased inter-annual variability threaten all of the above. These findings highlight the importance of considering changes in both lower order moments of annual streamflow and intra-annual monsoonal behavior when evaluating the robustness of alternative water systems control strategies for managing deeply uncertain futures.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Baker, Gavin Matthew; Bettencourt, Matthew Tyler; Bova, Steven W.
2015-09-01
This report provides in-depth information and analysis to help create a technical road map for developing next- generation Orogramming mocleN and runtime systemsl that support Advanced Simulation and Computing (ASC) work- load requirements. The focus herein is on 4synchronous many-task (AMT) model and runtime systems, which are of great interest in the context of "Oriascale7 computing, as they hold the promise to address key issues associated with future extreme-scale computer architectures. This report includes a thorough qualitative and quantitative examination of three best-of-class AIM] runtime systemsHCharm-HE, Legion, and Uintah, all of which are in use as part of the Centers.more » The studies focus on each of the runtimes' programmability, performance, and mutability. Through the experiments and analysis presented, several overarching Predictive Science Academic Alliance Program II (PSAAP-II) Ascl findings emerge. From a performance perspective, AIVT11runtimes show tremendous potential for addressing extreme- scale challenges. Empirical studies show an AM11 runtime can mitigate performance heterogeneity inherent to the machine itself and that Message Passing Interface (MP1) and AM11runtimes perform comparably under balanced con- ditions. From a programmability and mutability perspective however, none of the runtimes in this study are currently ready for use in developing production-ready Sandia ASCIapplications. The report concludes by recommending a co- design path forward, wherein application, programming model, and runtime system developers work together to define requirements and solutions. Such a requirements-driven co-design approach benefits the community as a whole, with widespread community engagement mitigating risk for both application developers developers. and high-performance computing inntime systein« less
Large Scale Processes and Extreme Floods in Brazil
NASA Astrophysics Data System (ADS)
Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.
2016-12-01
Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).
How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?
Hagos, Samson; Ruby Leung, L.; Zhao, Chun; ...
2018-02-10
Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less
How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hagos, Samson; Ruby Leung, L.; Zhao, Chun
Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less
Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan
2017-12-20
A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.
Structural health monitoring of pipelines rehabilitated with lining technology
NASA Astrophysics Data System (ADS)
Farhidzadeh, Alireza; Dehghan-Niri, Ehsan; Salamone, Salvatore
2014-03-01
Damage detection of pipeline systems is a tedious and time consuming job due to digging requirement, accessibility, interference with other facilities, and being extremely wide spread in metropolitans. Therefore, a real-time and automated monitoring system can pervasively reduce labor work, time, and expenditures. This paper presents the results of an experimental study aimed at monitoring the performance of full scale pipe lining systems, subjected to static and dynamic (seismic) loading, using Acoustic Emission (AE) technique and Guided Ultrasonic Waves (GUWs). Particularly, two damage mechanisms are investigated: 1) delamination between pipeline and liner as the early indicator of damage, and 2) onset of nonlinearity and incipient failure of the liner as critical damage state.
Peter, Frank J.; Dalton, Larry J.; Plummer, David W.
2002-01-01
A new class of mechanical code comparators is described which have broad potential for application in safety, surety, and security applications. These devices can be implemented as micro-scale electromechanical systems that isolate a secure or otherwise controlled device until an access code is entered. This access code is converted into a series of mechanical inputs to the mechanical code comparator, which compares the access code to a pre-input combination, entered previously into the mechanical code comparator by an operator at the system security control point. These devices provide extremely high levels of robust security. Being totally mechanical in operation, an access control system properly based on such devices cannot be circumvented by software attack alone.
A study of the parallel algorithm for large-scale DC simulation of nonlinear systems
NASA Astrophysics Data System (ADS)
Cortés Udave, Diego Ernesto; Ogrodzki, Jan; Gutiérrez de Anda, Miguel Angel
Newton-Raphson DC analysis of large-scale nonlinear circuits may be an extremely time consuming process even if sparse matrix techniques and bypassing of nonlinear models calculation are used. A slight decrease in the time required for this task may be enabled on multi-core, multithread computers if the calculation of the mathematical models for the nonlinear elements as well as the stamp management of the sparse matrix entries are managed through concurrent processes. This numerical complexity can be further reduced via the circuit decomposition and parallel solution of blocks taking as a departure point the BBD matrix structure. This block-parallel approach may give a considerable profit though it is strongly dependent on the system topology and, of course, on the processor type. This contribution presents the easy-parallelizable decomposition-based algorithm for DC simulation and provides a detailed study of its effectiveness.
Watering Graphene for Devices and Electricity
NASA Astrophysics Data System (ADS)
Guo, Wanlin; Yin, Jun; Li, Xuemei; Zhang, Zhuhua
2013-03-01
Graphene bring us into a fantastic two-dimensional (2D) age of nanotechnology, which can be fabricated and applied at wafer scale, visible at single layer but showing exceptional properties distinguished from its bulk form graphite, linking the properties of atomic layers with the engineering scale of our mankind. We shown that flow-induced-voltage in graphene can be 20 folds higher than in graphite, not only due to the giant Seebeck coefficient of single layer graphene, but also the exceptional interlayer interaction in few layer graphene. Extremely excitingly, water flow over graphene can generate electricity through unexpected interaction of the ions in the water with the graphene. We also find extraordinary mechanical-electric-magnetic coupling effects in graphene and BN systems. Such extraordinary multifield coupling effects in graphene and functional nanosystems open up new vistas in nanotechnology for efficient energy conversion, self-powering flexible devices and novel functional systems.
Ravindran, Sindhu; Jambek, Asral Bahari; Muthusamy, Hariharan; Neoh, Siew-Chin
2015-01-01
A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.
Machine Learning Toolkit for Extreme Scale
DOE Office of Scientific and Technical Information (OSTI.GOV)
2014-03-31
Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are consideredmore » in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets« less
NASA Astrophysics Data System (ADS)
Leung, L. R.; Houze, R.; Feng, Z.; Yang, Q.
2017-12-01
Mesoscale convective systems (MCSs) are important precipitation producers that account for 30-70% of warm season rainfall between the Rocky Mountains and Mississippi River and some 50-60% of tropical rainfall. Besides the tendency to produce floods, MCSs also carry with them a variety of attendant severe weather phenomena. Our recent analysis found that observed increases in springtime total and extreme rainfall in the central United States in the past 35 years are dominated by increased frequency and intensity of long-lasting MCSs. Understanding the environmental conditions producing long-lived MCSs is therefore a priority in determining how heavy precipitation events might change in character and location in a changing climate. Continental-scale convection-permitting simulations of the warm seasons using the WRF model reproduce realistic structure and frequency distribution of lifetime and event mean precipitation of MCSs over the central United States. The simulations show that MCSs systematically form over the central Great Plains ahead of a trough in the westerlies in combination with an enhanced low-level moist jet from the Gulf of Mexico. These environmental properties at the time of storm initiation are most prominent for the MCSs that persist for the longest times. MCSs reaching lifetimes of 9 h or more occur closer to the approaching trough than shorter-lived MCSs. These long-lived MCSs exhibit the strongest feedback to the environment through diabatic heating in the trailing regions of the MCSs that helps to maintain them over a long period of time. The identified large-scale and mesoscale ingredients provide a framework for understanding and modeling the potential changes in MCSs and associated hydrometeorological extremes in the future.
NASA Astrophysics Data System (ADS)
Konduri, Aditya
Many natural and engineering systems are governed by nonlinear partial differential equations (PDEs) which result in a multiscale phenomena, e.g. turbulent flows. Numerical simulations of these problems are computationally very expensive and demand for extreme levels of parallelism. At realistic conditions, simulations are being carried out on massively parallel computers with hundreds of thousands of processing elements (PEs). It has been observed that communication between PEs as well as their synchronization at these extreme scales take up a significant portion of the total simulation time and result in poor scalability of codes. This issue is likely to pose a bottleneck in scalability of codes on future Exascale systems. In this work, we propose an asynchronous computing algorithm based on widely used finite difference methods to solve PDEs in which synchronization between PEs due to communication is relaxed at a mathematical level. We show that while stability is conserved when schemes are used asynchronously, accuracy is greatly degraded. Since message arrivals at PEs are random processes, so is the behavior of the error. We propose a new statistical framework in which we show that average errors drop always to first-order regardless of the original scheme. We propose new asynchrony-tolerant schemes that maintain accuracy when synchronization is relaxed. The quality of the solution is shown to depend, not only on the physical phenomena and numerical schemes, but also on the characteristics of the computing machine. A novel algorithm using remote memory access communications has been developed to demonstrate excellent scalability of the method for large-scale computing. Finally, we present a path to extend this method in solving complex multi-scale problems on Exascale machines.
Measuring water fluxes in forests: The need for integrative platforms of analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ward, Eric J.
To understand the importance of analytical tools such as those provided by Berdanier et al. (2016) in this issue of Tree Physiology, one must understand both the grand challenges facing Earth system modelers, as well as the minutia of engaging in ecophysiological research in the field. It is between these two extremes of scale that many ecologists struggle to translate empirical research into useful conclusions that guide our understanding of how ecosystems currently function and how they are likely to change in the future. Likewise, modelers struggle to build complexity into their models that match this sophisticated understanding of howmore » ecosystems function, so that necessary simplifications required by large scales do not themselves change the conclusions drawn from these simulations. As both monitoring technology and computational power increase, along with the continual effort in both empirical and modeling research, the gap between the scale of Earth system models and ecological observations continually closes. In addition, this creates a need for platforms of model–data interaction that incorporate uncertainties in both simulations and observations when scaling from one to the other, moving beyond simple comparisons of monthly or annual sums and means.« less
Measuring water fluxes in forests: The need for integrative platforms of analysis
Ward, Eric J.
2016-08-09
To understand the importance of analytical tools such as those provided by Berdanier et al. (2016) in this issue of Tree Physiology, one must understand both the grand challenges facing Earth system modelers, as well as the minutia of engaging in ecophysiological research in the field. It is between these two extremes of scale that many ecologists struggle to translate empirical research into useful conclusions that guide our understanding of how ecosystems currently function and how they are likely to change in the future. Likewise, modelers struggle to build complexity into their models that match this sophisticated understanding of howmore » ecosystems function, so that necessary simplifications required by large scales do not themselves change the conclusions drawn from these simulations. As both monitoring technology and computational power increase, along with the continual effort in both empirical and modeling research, the gap between the scale of Earth system models and ecological observations continually closes. In addition, this creates a need for platforms of model–data interaction that incorporate uncertainties in both simulations and observations when scaling from one to the other, moving beyond simple comparisons of monthly or annual sums and means.« less
Scales and kinetics of granular flows.
Goldhirsch, I.
1999-09-01
When a granular material experiences strong forcing, as may be the case, e.g., for coal or gravel flowing down a chute or snow (or rocks) avalanching down a mountain slope, the individual grains interact by nearly instantaneous collisions, much like in the classical model of a gas. The dissipative nature of the particle collisions renders this analogy incomplete and is the source of a number of phenomena which are peculiar to "granular gases," such as clustering and collapse. In addition, the inelasticity of the collisions is the reason that granular gases, unlike atomic ones, lack temporal and spatial scale separation, a fact manifested by macroscopic mean free paths, scale dependent stresses, "macroscopic measurability" of "microscopic fluctuations" and observability of the effects of the Burnett and super-Burnett "corrections." The latter features may also exist in atomic fluids but they are observable there only under extreme conditions. Clustering, collapse and a kinetic theory for rapid flows of dilute granular systems, including a derivation of boundary conditions, are described alongside the mesoscopic properties of these systems with emphasis on the effects, theoretical conclusions and restrictions imposed by the lack of scale separation. (c) 1999 American Institute of Physics.
Optimal crop selection and water allocation under limited water supply in irrigation
NASA Astrophysics Data System (ADS)
Stange, Peter; Grießbach, Ulrike; Schütze, Niels
2015-04-01
Due to climate change, extreme weather conditions such as droughts may have an increasing impact on irrigated agriculture. To cope with limited water resources in irrigation systems, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand at the same time. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from optimized agronomic response on farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF). These functions take into account different soil types, crops and stochastically generated climate scenarios. The SCWPF's are used to compute the water demand considering different conditions, e.g., variable and fixed costs. This generic approach enables the consideration of both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance IRrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies.
NASA Astrophysics Data System (ADS)
Büntgen, Ulf; Brázdil, Rudolf; Heussner, Karl-Uwe; Hofmann, Jutta; Kontic, Raymond; Kyncl, Tomáš; Pfister, Christian; Chromá, Kateřina; Tegel, Willy
2011-12-01
A predicted rise in anthropogenic greenhouse gas emissions and associated effects on the Earth's climate system likely imply more frequent and severe weather extremes with alternations in hydroclimatic parameters expected to be most critical for ecosystem functioning, agricultural yield, and human health. Evaluating the return period and amplitude of modern climatic extremes in light of pre-industrial natural changes is, however, limited by generally too short instrumental meteorological observations. Here we introduce and analyze 11,873 annually resolved and absolutely dated ring width measurement series from living and historical fir ( Abies alba Mill.) trees sampled across France, Switzerland, Germany, and the Czech Republic, which continuously span the AD 962-2007 period. Even though a dominant climatic driver of European fir growth was not found, ring width extremes were evidently triggered by anomalous variations in Central European April-June precipitation. Wet conditions were associated with dynamic low-pressure cells, whereas continental-scale droughts coincided with persistent high-pressure between 35 and 55°N. Documentary evidence independently confirms many of the dendro signals over the past millennium, and further provides insight on causes and consequences of ambient weather conditions related to the reconstructed extremes. A fairly uniform distribution of hydroclimatic extremes throughout the Medieval Climate Anomaly, Little Ice Age and Recent Global Warming may question the common believe that frequency and severity of such events closely relates to climate mean stages. This joint dendro-documentary approach not only allows extreme climate conditions of the industrial era to be placed against the backdrop of natural variations, but also probably helps to constrain climate model simulations over exceptional long timescales.
Penn, Colin A.; Bearup, Lindsay A.; Maxwell, Reed M.; Clow, David W.
2016-01-01
The effects of mountain pine beetle (MPB)-induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high-resolution computational grid. Simulations of MPB-affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB-affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope-scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field-based studies and previous modeling work. Hillslope-scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB-induced tree mortality was offset by increased late-summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB-induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long-term gage observations that are complicated by inter-annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB-affected area or a water year with above average snowpack.
Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses
NASA Technical Reports Server (NTRS)
Wu, Huan; Huang, Maoyi; Tang, Qiuhong; Kirschbaum, Dalia B.; Ward, Philip
2017-01-01
Hydrometeorological hazards are caused by extreme meteorological and climate events, such as floods, droughts, hurricanes,tornadoes, or landslides. They account for a dominant fraction of natural hazards and occur in all regions of the world, although the frequency and intensity of certain hazards and societies vulnerability to them differ between regions. Severe storms, strong winds, floods, and droughts develop at different spatial and temporal scales, but all can become disasters that cause significant infrastructure damage and claim hundreds of thousands of lives annually worldwide. Oftentimes, multiple hazards can occur simultaneously or trigger cascading impacts from one extreme weather event. For example, in addition to causing injuries, deaths, and material damage, a tropical storm can also result in flooding and mudslides, which can disrupt water purification and sewage disposal systems, cause overflow of toxic wastes, andincrease propagation of mosquito-borne diseases.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Huan; Huang, Maoyi; Tang, Qiuhong
Hydrometeorological hazards are caused by extreme meteorological and climate events, such as floods, droughts, hurricanes, tornadoes, or landslides. They account for a dominant fraction of natural hazards and occur in all regions of the world, although the frequency and intensity of certain hazards, and society’s vulnerability to them, differs between regions. Severe storms, strong winds, floods and droughts develop at different spatial and temporal scales, but all can become disasters that cause significant infrastructure damage and claim hundreds of thousands of lives annually worldwide. Oftentimes, multiple hazards can occur simultaneously or trigger cascading impacts from one extreme weather event. Formore » example, in addition to causing injuries, deaths and material damage, a tropical storm can also result in flooding and mudslides, which can disrupt water purification and sewage disposal systems, cause overflow of toxic wastes, and increase propagation of mosquito-borne diseases.« less
Scalable domain decomposition solvers for stochastic PDEs in high performance computing
Desai, Ajit; Khalil, Mohammad; Pettit, Chris; ...
2017-09-21
Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less
Scalable domain decomposition solvers for stochastic PDEs in high performance computing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Desai, Ajit; Khalil, Mohammad; Pettit, Chris
Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less
Hierarchical Data Distribution Scheme for Peer-to-Peer Networks
NASA Astrophysics Data System (ADS)
Bhushan, Shashi; Dave, M.; Patel, R. B.
2010-11-01
In the past few years, peer-to-peer (P2P) networks have become an extremely popular mechanism for large-scale content sharing. P2P systems have focused on specific application domains (e.g. music files, video files) or on providing file system like capabilities. P2P is a powerful paradigm, which provides a large-scale and cost-effective mechanism for data sharing. P2P system may be used for storing data globally. Can we implement a conventional database on P2P system? But successful implementation of conventional databases on the P2P systems is yet to be reported. In this paper we have presented the mathematical model for the replication of the partitions and presented a hierarchical based data distribution scheme for the P2P networks. We have also analyzed the resource utilization and throughput of the P2P system with respect to the availability, when a conventional database is implemented over the P2P system with variable query rate. Simulation results show that database partitions placed on the peers with higher availability factor perform better. Degradation index, throughput, resource utilization are the parameters evaluated with respect to the availability factor.
Phytoremediation of 1,4-dioxane-containing recovered groundwater.
Ferro, Ari M; Kennedy, Jean; LaRue, James C
2013-01-01
The results of a pilot-scale phytoremediation study are reported in this paper. Small plots of trees established on a closed municipal waste landfill site were irrigated with recovered groundwater containing 1,4-dioxane (dioxane) and other volatile organic compounds (VOCs). The plots were managed to minimize the leaching of irrigation water, and leaching was quantified by the use of bromide tracer. Results indicated that the dioxane (2.5 microg/L) was effectively removed, probably via phytovolatilization, and that a full-scale phytoremediation system could be used. A system is now in place at the site in which the recovered groundwater can be treated using two different approaches. A physical treatment system (PTS) will be used during the winter months, and a 12 ha phytoremediation system (stands of coniferous trees) will be used during the growing season. The PTS removes VOCs using an air-stripper, and destroys dioxane using a photo-catalytic oxidation process. Treated water will be routed to the local sewer system. The phytoremediation system, located on the landfill, will be irrigated with effluent from the PTS air-stripper containing dioxane. Seasonal use of the phytoremediation system will reduce reliance on the photo-catalytic oxidation process that is extremely energy consumptive and expensive to operate.
NASA Astrophysics Data System (ADS)
Chen, Ajiao; He, Xinguang; Guan, Huade; Cai, Yi
2018-04-01
In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960-2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960-1986 and 1987-2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4-year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices. Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide significant power at the 4-year period, which are mainly found during 1970-1980 and after 1992.
NASA Astrophysics Data System (ADS)
Greer, A. T.; Woodson, C. B.
2016-02-01
Because of the complexity and extremely large size of marine ecosystems, research attention has a strong focus on modelling the system through space and time to elucidate processes driving ecosystem state. One of the major weaknesses of current modelling approaches is the reliance on a particular grid cell size (usually 10's of km in the horizontal & water column mean) to capture the relevant processes, even though empirical research has shown that marine systems are highly structured on fine scales, and this structure can persist over relatively long time scales (days to weeks). Fine-scale features can have a strong influence on the predator-prey interactions driving trophic transfer. Here we apply a statistic, the AB ratio, used to quantify increased predator production due to predator-prey overlap on fine scales in a manner that is computationally feasible for larger scale models. We calculated the AB ratio for predator-prey distributions throughout the scientific literature, as well as for data obtained with a towed plankton imaging system, demonstrating that averaging across a typical model grid cell neglects the fine-scale predator-prey overlap that is an essential component of ecosystem productivity. Organisms from a range of trophic levels and oceanographic regions tended to overlap with their prey both in the horizontal and vertical dimensions. When predator swimming over a diel cycle was incorporated, the amount of production indicated by the AB ratio increased substantially. For the plankton image data, the AB ratio was higher with increasing sampling resolution, especially when prey were highly aggregated. We recommend that ecosystem models incorporate more fine-scale information both to more accurately capture trophic transfer processes and to capitalize on the increasing sampling resolution and data volume from empirical studies.
NASA Astrophysics Data System (ADS)
Staneva, Joanna; Wahle, Kathrin
2015-04-01
This study addresses the coupling between wind wave and circulation models on the example of the German Bight and its coastal area called the Wadden Sea (the area between the barrier islands and the coast). This topic reflects the increased interest in operational oceanography to reduce prediction errors of state estimates at coastal scales. The uncertainties in most of the presently used models result from the nonlinear feedback between strong tidal currents and wind-waves, which can no longer be ignored, in particular in the coastal zone where its role seems to be dominant. A nested modelling system is used in the Helmholtz-Zentrum Geesthacht to producing reliable now- and short-term forecasts of ocean state variables, including wind waves and hydrodynamics. In this study we present analysis of wave and hydrographic observations, as well as the results of numerical simulations. The data base includes ADCP observations and continuous measurements from data stations. The individual and collective role of wind, waves and tidal forcing are quantified. The performance of the forecasting system is illustrated for the cases of several extreme events. Effects of ocean waves on coastal circulation and SST simulations are investigated considering wave-dependent stress and wave breaking parameterization during extreme events, e.g. hurricane Xavier in December, 2013. Also the effect which the circulation exerts on the wind waves is tested for the coastal areas using different parameterizations. The improved skill resulting from the new developments in the forecasting system, in particular during extreme events, justifies further enhancements of the coastal pre-operational system for the North Sea and German Bight.
Yoon, Jisun; Chun, Min Ho; Lee, Sook Joung; Kim, Bo Ryun
2015-06-01
The aim of this study was to evaluate the benefit of virtual reality-based rehabilitation on upper-extremity function in patients with brain tumor. Patients with upper-extremity dysfunction were divided into age-matched and tumor type-matched two groups. The intervention group performed the virtual reality program 30 mins per session for 9 sessions and conventional occupational therapy 30 mins per session for 6 sessions for 3 wks, whereas the control group received conventional occupational therapy alone 30 mins per session for 15 sessions for 3 wks. The Box and Block test, the Manual Function test, and the Fugl-Meyer scale were used to evaluate upper-extremity function. The Korean version of the Modified Barthel Index was used to assess activities of daily living. Forty patients completed the study (20 for each group). Each group exhibited significant posttreatment improvements in the Box and Block test, Manual Function test, Fugl-Meyer scale, and Korean version of the Modified Barthel Index scores. The Box and Block test, the Fugl-Meyer scale, and the Manual Function test showed greater improvements in shoulder/elbow/forearm function in the intervention group and hand function in the control group. Virtual reality-based rehabilitation combined with conventional occupational therapy may be more effective than conventional occupational therapy, especially for proximal upper-extremity function in patients with brain tumor. Further studies considering hand function, such as use of virtual reality programs that targeting hand use, are required.
Development of laser interferometric high-precision geometry monitor for JASMINE
NASA Astrophysics Data System (ADS)
Niwa, Yoshito; Arai, Koji; Ueda, Akitoshi; Sakagami, Masaaki; Gouda, Naoteru; Kobayashi, Yukiyasu; Yamada, Yoshiyuki; Yano, Taihei
2008-07-01
The telescope geometry of JASMINE should be stabilized and monitored with the accuracy of about 10 to 100 picometer or 10 to 100 picoradian in root-mean-square over about 10 hours. For this purpose, a high-precision interferometric laser metrology system is employed. One of useful techniques for measuring displacements in extremely minute scales is the heterodyne interferometrical method. Experiment for verification of multi degree of freedom measurement was performed and mirror motions were successfully monitored with three degree of freedom.
Estimates of expansion time scales. [Settlement of Galaxy by spacefaring civilization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, E.M.
1979-01-01
Monte Carlo simulations of the expansion of a spacefaring civilization show that descendants of that civilization should be found near virtually every useful star in the Galaxy in a time much less than the current age of the Galaxy. Only extreme assumptions about local population growth rates, emigration rates, or ship ranges can slow or halt an expansion. The apparent absence of extraterrestrials from the solar system suggests that no such civilization has arisen in the Galaxy. 1 figure.
1987-07-01
yearly trends, and the effect of population size and abiotic factors on growth will be completed when the 1984-1986 scales are completed. Fish condition...settling of suspended particles on substrates in its absence. The pumps were powered by a heavy duty marine battery which had to be exchanged and...computer using procedures available in SPSS (Hull and Nie 1981) and programs available in the BIOM statistical package (Rohlf). Sokal and Rohlf (1981
Analysis of Atmospheric Moisture Transport over the Himalaya-Karakoram-Hindukush Region
NASA Astrophysics Data System (ADS)
Minallah, S.; Ivanov, V. Y.
2017-12-01
The high-altitude region of the Himalaya-Karakoram-Hindukush (HKH) ranges is susceptible to natural disasters due to their extreme topographic features and climatic conditions. The region, where large population resides in deep valleys and mountain foothills, is prone to riverine flooding, flash floods, and extreme precipitation events whose frequency is perceived to be increasing, often with attribution to climate change. It is thus imperative to study the causation using modern hydrometeorological products. In this study, we identify regions with documented trends in extreme flooding and precipitation and carry out a statistical analysis of the atmospheric moisture transport at the synoptic scale for these regions using ERA-Interim and NASA MERRA-2 reanalysis products. We focus on the two main sources for the atmospheric moisture in the region: the summer South-East Asian Monsoon and the winter Westerlies, and explore how variations in these systems affect the moisture convergence and divergence over the region. Our findings indicate that the Monsoon precipitation has been intensifying in the western Himalayas over the past decade and a half and that these changes are likely related to moisture advection into the region.
NASA Astrophysics Data System (ADS)
Lindsey, Rebecca; Goldman, Nir; Fried, Laurence
2017-06-01
Atomistic modeling of chemistry at extreme conditions remains a challenge, despite continuing advances in computing resources and simulation tools. While first principles methods provide a powerful predictive tool, the time and length scales associated with chemistry at extreme conditions (ns and μm, respectively) largely preclude extension of such models to molecular dynamics. In this work, we develop a simulation approach that retains the accuracy of density functional theory (DFT) while decreasing computational effort by several orders of magnitude. We generate n-body descriptions for atomic interactions by mapping forces arising from short density functional theory (DFT) trajectories on to simple Chebyshev polynomial series. We examine the importance of including greater than 2-body interactions, model transferability to different state points, and discuss approaches to ensure smooth and reasonable model shape outside of the distance domain sampled by the DFT training set. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
NASA Astrophysics Data System (ADS)
Brunsell, N. A.; Nippert, J. B.
2011-12-01
As the climate warms, it is generally acknowledged that the number and magnitude of extreme weather events will increase. We examined an ecophysiological model's responses to precipitation and temperature anomalies in relation to the mean and variance of annual precipitation along a pronounced precipitation gradient from eastern to western Kansas. This natural gradient creates a template of potential responses for both the mean and variance of annual precipitation to compare the timescales of carbon and water fluxes. Using data from several Ameriflux sites (KZU and KFS) and a third eddy covariance tower (K4B) along the gradient, BIOME-BGC was used to characterize water and carbon cycle responses to extreme weather events. Changes in the extreme value distributions were based on SRES A1B and A2 scenarios using an ensemble mean of 21 GCMs for the region, downscaled using a stochastic weather generator. We focused on changing the timing and magnitude of precipitation and altering the diurnal and seasonal temperature ranges. Biome-BGC was then forced with daily output from the stochastic weather generator, and we examined how potential changes in these extreme value distributions impact carbon and water cycling at the sites across the Kansas precipitation gradient at time scales ranging from daily to interannual. To decompose the time scales of response, we applied a wavelet based information theory analysis approach. Results indicate impacts in soil moisture memory and carbon allocation processes, which vary in response to both the mean and variance of precipitation along the precipitation gradient. These results suggest a more pronounced focus ecosystem responses to extreme events across a range of temporal scales in order to fully characterize the water and carbon cycle responses to global climate change.
Application of Multi-Model CMIP5 Analysis in Future Drought Adaptation Strategies
NASA Astrophysics Data System (ADS)
Casey, M.; Luo, L.; Lang, Y.
2014-12-01
Drought influences the efficacy of numerous natural and artificial systems including species diversity, agriculture, and infrastructure. Global climate change raises concerns that extend well beyond atmospheric and hydrological disciplines - as climate changes with time, the need for system adaptation becomes apparent. Drought, as a natural phenomenon, is typically defined relative to the climate in which it occurs. Typically a 30-year reference time frame (RTF) is used to determine the severity of a drought event. This study investigates the projected future droughts over North America with different RTFs. Confidence in future hydroclimate projection is characterized by the agreement of long term (2005-2100) multi-model precipitation (P) and temperature (T) projections within the Coupled model Intercomparison Project Phase 5 (CMIP5). Drought severity and the propensity of extreme conditions are measured by the multi-scalar, probabilistic, RTF-based Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI). SPI considers only P while SPEI incorporates Evapotranspiration (E) via T; comparing the two reveals the role of temperature change in future hydroclimate change. Future hydroclimate conditions, hydroclimate extremity, and CMIP5 model agreement are assessed for each Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, 8.5) in regions throughout North America for the entire year and for the boreal seasons. In addition, multiple time scales of SPI and SPEI are calculated to characterize drought at time scales ranging from short to long term. The study explores a simple, standardized method for considering adaptation in future drought assessment, which provides a novel perspective to incorporate adaptation with climate change. The result of the analysis is a multi-dimension, probabilistic summary of the hydrological (P, E) environment a natural or artificial system must adapt to over time. Studies similar to this with specified criteria (SPI/SPEI value, time scale, RCP, etc.) can provide professionals in a variety of disciplines with necessary climatic insight to develop adaptation strategies.
Wan, Shixiang; Zou, Quan
2017-01-01
Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.
NASA Astrophysics Data System (ADS)
Do, Hong; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth; Senerivatne, Sonia
2017-04-01
In-situ observations of daily streamflow with global coverage are a crucial asset for understanding large-scale freshwater resources which are an essential component of the Earth system and a prerequisite for societal development. Here we present the Global Streamflow Indices and Metadata archive (G-SIM), a collection indices derived from more than 20,000 daily streamflow time series across the globe. These indices are designed to support global assessments of change in wet and dry extremes, and have been compiled from 12 free-to-access online databases (seven national databases and five international collections). The G-SIM archive also includes significant metadata to help support detailed understanding of streamflow dynamics, with the inclusion of drainage area shapefile and many essential catchment properties such as land cover type, soil and topographic characteristics. The automated procedure in data handling and quality control of the project makes G-SIM a reproducible, extendible archive and can be utilised for many purposes in large-scale hydrology. Some potential applications include the identification of observational trends in hydrological extremes, the assessment of climate change impacts on streamflow regimes, and the validation of global hydrological models.
Real-time and sub-wavelength ultrafast coherent diffraction imaging in the extreme ultraviolet.
Zürch, M; Rothhardt, J; Hädrich, S; Demmler, S; Krebs, M; Limpert, J; Tünnermann, A; Guggenmos, A; Kleineberg, U; Spielmann, C
2014-12-08
Coherent Diffraction Imaging is a technique to study matter with nanometer-scale spatial resolution based on coherent illumination of the sample with hard X-ray, soft X-ray or extreme ultraviolet light delivered from synchrotrons or more recently X-ray Free-Electron Lasers. This robust technique simultaneously allows quantitative amplitude and phase contrast imaging. Laser-driven high harmonic generation XUV-sources allow table-top realizations. However, the low conversion efficiency of lab-based sources imposes either a large scale laser system or long exposure times, preventing many applications. Here we present a lensless imaging experiment combining a high numerical aperture (NA = 0.8) setup with a high average power fibre laser driven high harmonic source. The high flux and narrow-band harmonic line at 33.2 nm enables either sub-wavelength spatial resolution close to the Abbe limit (Δr = 0.8λ) for long exposure time, or sub-70 nm imaging in less than one second. The unprecedented high spatial resolution, compactness of the setup together with the real-time capability paves the way for a plethora of applications in fundamental and life sciences.
Osu, Rieko; Otaka, Yohei; Ushiba, Junichi; Sakata, Sachiko; Yamaguchi, Tomofumi; Fujiwara, Toshiyuki; Kondo, Kunitsugu; Liu, Meigen
2012-01-01
For the recovery of hemiparetic hand function, a therapy was developed called contralateral homonymous muscle activity stimulated electrical stimulation (CHASE), which combines electrical stimulation and bilateral movements, and its feasibility was studied in three chronic stroke patients with severe hand hemiparesis. Patients with a subcortical lesion were asked to extend their wrist and fingers bilaterally while an electromyogram (EMG) was recorded from the extensor carpi radialis (ECR) muscle in the unaffected hand. Electric stimulation was applied to the homonymous wrist and finger extensors of the affected side. The intensity of the electrical stimulation was computed based on the EMG and scaled so that the movements of the paretic hand looked similar to those of the unaffected side. The patients received 30-minutes of therapy per day for 2 weeks. Improvement in the active range of motion of wrist extension was observed for all patients. There was a decrease in the scores of modified Ashworth scale in the flexors. Fugl-Meyer assessment scores of motor function of the upper extremities improved in two of the patients. The results suggest a positive outcome can be obtained using the CHASE system for upper extremity rehabilitation of patients with severe hemiplegia.
Efficacy of extremely low-frequency magnetic field in fibromyalgia pain: A pilot study.
Paolucci, Teresa; Piccinini, Giulia; Iosa, Marco; Piermattei, Cristina; de Angelis, Simona; Grasso, Maria Rosaria; Zangrando, Federico; Saraceni, Vincenzo Maria
2016-01-01
The purpose of this pilot study was to determine the efficacy of an extremely low-frequency magnetic field (ELF-MF) in decreasing chronic pain in fibromyalgia (FM) patients. Thirty-seven females were recruited and randomized into two groups: one group was first exposed to systemic ELF-MF therapy (100 microtesla, 1 to 80 Hz) and then to sham therapy, and the other group received the opposite sequence of intervention. Pain, FM-related symptoms, and the ability to perform daily tasks were measured using the Visual Analog Scale, Fibromyalgia Impact Questionnaire (FIQ), Fibromyalgia Assessment Scale (FAS), and Health Assessment Questionnaire (HAQ) at baseline, end of first treatment cycle, beginning of second treatment cycle (after 1 mo washout), end of second treatment cycle, and end of 1 mo follow-up. ELF-MF treatment significantly reduced pain, which increased on cessation of therapy but remained significantly lower than baseline levels. Short-term benefits were also observed in FIQ, FAS, and HAQ scores, with less significant effects seen in the medium term. ELF-MF therapy can be recommended as part of a multimodal approach for mitigating pain in FM subjects and improving the efficacy of drug therapy or physiotherapy.
Time Burden of Standardized Hip Questionnaires.
Chughtai, Morad; Khlopas, Anton; Mistry, Jaydev B; Gwam, Chukwuweike U; Elmallah, Randa K; Mont, Michael A
2016-04-01
Many standardized scales and questionnaires have been developed to assess outcomes of patients undergoing total hip arthroplasty (THA). However, these surveys can be a burden to both patients and orthopaedists as some are time-inefficient. In addition, there is a paucity of reports assessing the time it takes to complete them. In this study we aimed to: (1) assess how long it takes to complete the most common standardized hip questionnaires; (2) determine the presence of variation in completion time; and (3) evaluate the effects of age, gender, and level of education on completion time. Based on a previous study, we selected the seven most commonly used hip scoring systems-Western Ontario and McMaster Universities Hip Outcome Assessment (WOMAC), Harris Hip Score (HHS), Hip Disability and Osteoarthritis Outcome Score (HOOS), Larson Score, Short-form 36 (SF-36), modified Merle d'Aubigne and Postel Score (MDA), and Lower Extremity Functional Scale (LEFS). The standardized scales and questionnaires were randomly administered to 70 subjects. The subjects were unaware that they were being timed during completion of the questionnaire. We obtained the coefficients of variation of time for each questionnaire. The mean time to complete the questionnaire was then stratified and compared based on age, gender, and level of education. The mean time to complete each of the systems is listed in ascending order: Modified Merle d'Aubigne and Postel Score (MDA), Lower Extremity Functional Scale (LEFS), Western Ontario and McMaster Universities Hip Outcome Assessment (WOMAC), Harris Hip Score (HHS), Larson Score, Hip Disability and Osteoarthritis Outcome Score (HOOS), and Short-form 36 (SF-36). The WOMAC and Larson Score coefficients of variation were the largest, and the HOOS and MDA were the smallest. There was a significantly higher mean time to completion in those who were above or equal to the age of 55 years as compared to those who were below the age of 55 (227 vs. 166 seconds). There was no significant association found in time of completion between gender or education level. Standardized scales and questionnaire which assess THA patients can be burdensome and time-inefficient, which may lead to task-induced fatigue. This may result in inaccurate THA patient assessments, which do not reflect the patient's true state. Future studies should aim to create an encompassing questionnaire that is time efficient and can replace all currently used validated systems.
Microhabitats in the tropics buffer temperature in a globally coherent manner.
Scheffers, Brett R; Evans, Theodore A; Williams, Stephen E; Edwards, David P
2014-12-01
Vegetated habitats contain a variety of fine-scale features that can ameliorate temperate extremes. These buffered microhabitats may be used by species to evade extreme weather and novel climates in the future. Yet, the magnitude and extent of this buffering on a global scale remains unknown. Across all tropical continents and using 36 published studies, we assessed temperature buffering from within microhabitats across various habitat strata and structures (e.g. soil, logs, epiphytes and tree holes) and compared them to non-buffered macro-scale ambient temperatures (the thermal control). Microhabitats buffered temperature by 3.9 °C and reduced maximum temperatures by 3.5 °C. Buffering was most pronounced in tropical lowlands where temperatures were most variable. With the expected increase in extreme weather events, microhabitats should provide species with a local layer of protection that is not captured by traditional climate assessments, which are typically derived from macro-scale temperatures (e.g. satellites). Our data illustrate the need for a next generation of predictive models that account for species' ability to move within microhabitats to exploit favourable buffered microclimates. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Extremely high wall-shear stress events in a turbulent boundary layer
NASA Astrophysics Data System (ADS)
Pan, Chong; Kwon, Yongseok
2018-04-01
The present work studies the fluctuating characteristics of the streamwise wall-shear stress in a DNS of a turbulent boundary layer at Re τ =1500 from a structural view. The two-dimensional field of the fluctuating friction velocity u‧ τ (x,z) is decomposed into the large- and small-scale components via a recently proposed scale separation algorithm, Quasi-bivariate Variational Mode Decomposition (QB-VMD). Both components are found to be dominated by streak-like structures, which can be regarded as the wall signature of the inner-layer streaks and the outer-layer LSMs, respectively. Extreme positive/negative wall-shear stress fluctuation events are detected in the large-scale component. The former’s occurrence frequency is nearly one order of magnitude higher than the latter; therefore, they contribute a significant portion of the long tail of the wall-shear stress distribution. Both two-point correlations and conditional averages show that these extreme positive wall-shear stress events are embedded in the large-scale positive u‧ τ streaks. They seem to be formed by near-wall ‘splatting’ process, which are related to strong finger-like sweeping (Q4) events originated from the outer-layer positive LSMs.
Caldwell-Harris, Catherine L; Ayçiçegi, Ayse
2006-09-01
Because humans need both autonomy and interdependence, persons with either an extreme collectivist orientation (allocentrics) or extreme individualist values (idiocentrics) may be at risk for possession of some features of psychopathology. Is an extreme personality style a risk factor primarily when it conflicts with the values of the surrounding society? Individualism-collectivism scenarios and a battery of clinical and personality scales were administered to nonclinical samples of college students in Boston and Istanbul. For students residing in a highly individualistic society (Boston), collectivism scores were positively correlated with depression, social anxiety, obsessive-compulsive disorder and dependent personality. Individualism scores, particularly horizontal individualism, were negatively correlated with these same scales. A different pattern was obtained for students residing in a collectivist culture, Istanbul. Here individualism (and especially horizontal individualism) was positively correlated with scales for paranoid, schizoid, narcissistic, borderline and antisocial personality disorder. Collectivism (particularly vertical collectivism) was associated with low report of symptoms on these scales. These results indicate that having a personality style which conflicts with the values of society is associated with psychiatric symptoms. Having an orientation inconsistent with societal values may thus be a risk factor for poor mental health.
Assessing the impact of future climate extremes on the US corn and soybean production
NASA Astrophysics Data System (ADS)
Jin, Z.
2015-12-01
Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.
NASA Astrophysics Data System (ADS)
Farrah, Duncan
2017-08-01
Luminous starbursts, systems with SFRs exceeding 1000Msun yr-1, are predicted to be extremely rare at z>3. However, recent observations find such systems at rates of tens to hundreds above predictions. This discrepancy is extremely difficult to explain. Case studies of such luminous starbursts are thus of profound importance to understand how star formation is triggered and quenched at z > 3, and help reconcile models with observations. Our group has been intensively studying the quasar SDSS J160705.16, at z = 3.65 (or 1.7Gyr after the Big Bang). This quasar is an excellent case study of luminous star formation at z > 3, and how AGN activity may affect such star formation. SDSS J160705.16 harbors both a broad-line, luminous quasar and an extremely high star formation rate, with an AGN luminosity of 10^47 ergs s-1 and an SFR of 2000 Msol yr-1. Sub-mm interferometry has further revealed that the star formation is highly spatially extended on scales up to 40kpc. Furthermore, VLA observations show an emerging 4kpc radio jet.We here propose WFC3 imaging with the following goals: (1) to set precise constraints on any lensing magnification, (2) to determine the morphology and color structure of the extended star formation, (3) to compare the optical morphology of the star formation to that seen in the sub-mm data, and (4) to search for evidence that SDSS J160705.16 resides in a protocluster.
Dynamical properties and extremes of Northern Hemisphere climate fields over the past 60 years
NASA Astrophysics Data System (ADS)
Faranda, Davide; Messori, Gabriele; Alvarez-Castro, M. Carmen; Yiou, Pascal
2017-12-01
Atmospheric dynamics are described by a set of partial differential equations yielding an infinite-dimensional phase space. However, the actual trajectories followed by the system appear to be constrained to a finite-dimensional phase space, i.e. a strange attractor. The dynamical properties of this attractor are difficult to determine due to the complex nature of atmospheric motions. A first step to simplify the problem is to focus on observables which affect - or are linked to phenomena which affect - human welfare and activities, such as sea-level pressure, 2 m temperature, and precipitation frequency. We make use of recent advances in dynamical systems theory to estimate two instantaneous dynamical properties of the above fields for the Northern Hemisphere: local dimension and persistence. We then use these metrics to characterize the seasonality of the different fields and their interplay. We further analyse the large-scale anomaly patterns corresponding to phase-space extremes - namely time steps at which the fields display extremes in their instantaneous dynamical properties. The analysis is based on the NCEP/NCAR reanalysis data, over the period 1948-2013. The results show that (i) despite the high dimensionality of atmospheric dynamics, the Northern Hemisphere sea-level pressure and temperature fields can on average be described by roughly 20 degrees of freedom; (ii) the precipitation field has a higher dimensionality; and (iii) the seasonal forcing modulates the variability of the dynamical indicators and affects the occurrence of phase-space extremes. We further identify a number of robust correlations between the dynamical properties of the different variables.
Remote sensing, global warming, and vector-borne disease
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wood, B.; Beck, L.; Dister, S.
1997-12-31
The relationship between climate change and the pattern of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are changes such as global warming, which are continental in scale and occur over periods of years, decades, or longer. At the opposite extreme are changes associated with severe weather events, which can occur at local and regional scales over periods of days, weeks, or months. Key ecological factors affecting the distribution of vector-borne diseases include temperature, precipitation, and habitat availability, and their impact on vectors, pathogens, reservoirs, and hosts. Global warming can potentially altermore » these factors, thereby affecting the spatial and temporal patterns of disease.« less
Extremes and bursts in complex multi-scale plasmas
NASA Astrophysics Data System (ADS)
Watkins, N. W.; Chapman, S. C.; Hnat, B.
2012-04-01
Quantifying the spectrum of sizes and durations of large and/or long-lived fluctuations in complex, multi-scale, space plasmas is a topic of both theoretical and practical importance. The predictions of inherently multi-scale physical theories such as MHD turbulence have given one direct stimulus for its investigation. There are also space weather implications to an improved ability to assess the likelihood of an extreme fluctuation of a given size. Our intuition as scientists tends to be formed on the familiar Gaussian "normal" distribution, which has a very low likelihood of extreme fluctuations. Perhaps surprisingly, there is both theoretical and observational evidence that favours non-Gaussian, heavier-tailed, probability distributions for some space physics datasets. Additionally there is evidence for the existence of long-ranged memory between the values of fluctuations. In this talk I will show how such properties can be captured in a preliminary way by a self-similar, fractal model. I will show how such a fractal model can be used to make predictions for experimental accessible quantities like the size and duration of a buurst (a sequence of values that exceed a given threshold), or the survival probability of a burst [c.f. preliminary results in Watkins et al, PRE, 2009]. In real-world time series scaling behaviour need not be "mild" enough to be captured by a single self-similarity exponent H, but might instead require a "wild" multifractal spectrum of scaling exponents [e.g. Rypdal and Rypdal, JGR, 2011; Moloney and Davidsen, JGR, 2011] to give a complete description. I will discuss preliminary work on extending the burst approach into the multifractal domain [see also Watkins et al, chapter in press for AGU Chapman Conference on Complexity and Extreme Events in the Geosciences, Hyderabad].
Greven, Corina U; Buitelaar, Jan K; Salum, Giovanni A
2018-03-01
Integration of positive psychology into clinical research and treatment has been slow. This integration can be facilitated by the conceptualisation of mental disorders as the high, symptomatic extreme of continuous normal variation. This assumes that there is also a low, positive extreme, which is, however, unchartered territory. This study aims to examine how well current measures capture the low extreme of mental disorder continua, using attention-deficit hyperactivity disorder (ADHD) as an example. The ability of three validated scales to capture ADHD as a continuous trait was examined using Item Response Theory in a sample of 9,882 adolescents from the UK population-representative Twins Early Development Study. These scales were: the Strengths and Weakness of ADHD Symptoms and Normal behaviour scale (SWAN), Strength and Difficulties Questionnaire (SDQ - hyperactivity subscale), and Conners' Parent Rating Scale (Conners). Only the SWAN reliably differentiated interindividual differences between participants lying at any level of the continuous ADHD latent trait, including the extreme low, positive end (z-scores from -3 to +3). The SDQ showed low reliability across the ADHD latent trait. In contrast, the Conners performed best at differentiating individuals scoring at or above the mean to the high symptomatic range (z-scores from 0 to +3). The SWAN was the only measure to provide indicators of 'positive mental health', endorsed in the presence of particularly good attentive abilities. Scales such as the SWAN that reliably capture ADHD as a continuous trait, including the positive end, are important for not missing meaningful variation in population-based studies. Indicators of positive mental health may be helpful in clinical practice, as positive attributes have been shown to directly influence as well as buffer negative effects of psychiatric symptoms. © 2017 Association for Child and Adolescent Mental Health.
Gemballa, Sven; Bartsch, Peter
2002-09-01
A bony ganoid squamation is the plesiomorphic type in actinopterygians. During evolution, it was replaced by weak and more flexible elasmoid scales. We provide a comparative description of the integument of "ganoid" fishes and "nonganoid" fishes that considers all dermal components of mechanical significance (stratum compactum, morphology of ganoid scales, and their regional differences) in order to develop a functional understanding of the ganoid integument as a whole. Data were obtained for the extant "ganoid" fishes (Polypteridae and Lepisosteidae) and for closely related "lower" actinopterygians (Acipenser ruthenus, Amia calva) and "lower" sarcopterygians (Latimeria chalumnae, Neoceratodus forsteri). Body curvatures during steady undulatory locomotion, sharp turns, prey-strikes, and fast starts in "ganoid" fishes were measured from videotapes. Extreme body curvatures as measured in anesthetized specimens are never reached during steady swimming, but are sometimes closely approached in certain situations (sharp turns, prey-strike). During extreme body curvatures we measured high values of lateral strain on the convex and on the concave side of the body. Scale overlap changes considerably (66-127% in Lepisosteus, 42-140% in Polypterus). The ganoid squamation forms a protective coat, but at the same time it permits extreme body curvatures. This is reflected in characteristic morphological features of the ganoid scales, such as an anterior process, concave anterior margin, and peg-and-socket articulation. These characters are most pronounced in the anterior body region, where maximum changes in scale overlap are required. The anterior processes and anterior concave margin, together with the attached stratum compactum, guide movements in a horizontal plane during bending. Displacements of scales relative to each other are possible for scales of different scale rows, but are impeded in scales of the same scale row due to the peg-and-socket articulation. Furthermore, ganoid scale rows, fibers of collagen layers of the stratum compactum, and the lateral myoseptal structures follow the same oblique orientation, which is needed to achieve extreme body curvatures. There is no evidence that body curvatures are limited by the ganoid squamation in Polypterus or Lepisosteus to any larger extent than by a type of integument devoid of ganoid scales in teleostomes of similar body shape. Our results essentially contradict former functional interpretations: 1) Ganoid scales do not especially limit body curvature during steady undulatory locomotion; 2) They do not act as torsion-resisting devices, but may be able to damp torsion together with the stratum compactum and internal body pressure. Copyright 2002 Wiley-Liss, Inc.