Parallel discrete event simulation: A shared memory approach

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models

Regional Invasive Species & Climate Change Management Challenge: Prioritizing range-shifting invasive plants High-impact species coming to the Northeast

Prevention of new invasions is a cost-effective way to manage invasive species and is most effective when emerging invaders are identified and prioritized before they arrive. Climate change is projected to bring nearly 100 new invasive plants to the Northeast. However, these plants are likely to have different types of impacts, making some a higher concern than others. Here, we summarize the results of original RISCC research that identifies high priority, range-shifting invasive plants based on their potential impacts

Symmetry analysis of crystalline spin textures in dipolar spinor condensates

We study periodic crystalline spin textures in spinor condensates with dipolar interactions via a systematic symmetry analysis of the low-energy effective theory. By considering symmetry operations which combine real and spin space operations, we classify symmetry groups consistent with non-trivial experimental and theoretical constraints. Minimizing the energy within each symmetry class allows us to explore possible ground states.Comment: 19 pages, 4 figure

Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting

Copyright 2000 American Meteorological SocietyNext-Generation Weather Radar (NEXRAD) multisensor precipitation estimates will be used for a host of applications that include operational streamflow forecasting at the National Weather Service River Forecast Centers (RFCs) and nonoperational purposes such as studies of weather, climate, and hydrology. Given these expanding applications, it is important to understand the quality and error characteristics of NEXRAD multisensor products. In this paper, the issues involved in evaluating these products are examined through an assessment of a 5.5-yr record of multisensor estimates from the Arkansas–Red Basin RFC. The objectives were to examine how known radar biases manifest themselves in the multisensor product and to quantify precipitation estimation errors. Analyses included comparisons of multisensor estimates based on different processing algorithms, comparisons with gauge observations from the Oklahoma Mesonet and the Agricultural Research Service Micronet, and the application of a validation framework to quantify error characteristics. This study reveals several complications to such an analysis, including a paucity of independent gauge data. These obstacles are discussed and recommendations are made to help to facilitate routine verification of NEXRAD products

Characterizing the pulsations of the ZZ Ceti star KUV 02464+3239

We present the results on period search and modeling of the cool DAV star KUV 02464+3239. Our observations resolved the multiperiodic pulsational behaviour of the star. In agreement with its position near the red edge of the DAV instability strip, it shows large amplitude, long period pulsation modes, and has a strongly non-sinusoidal light curve. We determined 6 frequencies as normal modes and revealed remarkable short-term amplitude variations. A rigorous test was performed for the possible source of amplitude variation: beating of modes, effect of noise, unresolved frequencies or rotational triplets. Among the best-fit models resulting from a grid search, we selected 3 that gave l=1 solutions for the largest amplitude modes. These models had masses of 0.645, 0.650 and 0.680 M_Sun. The 3 `favoured' models have M_H between 2.5x10^-5 - 6.3x10^-6 M_* and give 14.2 - 14.8 mas seismological parallax. The 0.645 M_Sun (11400 K) model also matches the spectroscopic log g and T_eff within 1 sigma. We investigated the possibility of mode trapping and concluded that while it can explain high amplitude modes, it is not required.Comment: 11 pages, 8 figures, accepted for publication in MNRA

The Geology and Petrology of the Fifes Peak Formation in the Cliffdell Area, Central Cascades, Washington

The Fifes Peak Formation in the Cliffdell area is comprised of two structurally, lithologically and geochemically distinct members separated by a pronounced unconformity. The older member (Edgar Rock member) is comprised of highly brecciated lava flows, coarse laharic breccia and lesser volcaniclastic sediments and tuffs. A thickness of at least 1,800 m is exposed near Edgar Rock. K-Ar ages indicate a latest Oligocene age of about 24 to 27 Ma. Lava compositions range from basalt to dacite, but are mostly basaltic andesite. These lavas are typically highly porphyritic and contain an anhydrous phenocryst assemblage of plagioclase, olivine, minor clinopyroxene and magnetite. Gabbroic inclusions, various pyroxene clots and green spinel are present in some basaltic andesite flows. The most common type of laharic breccia contains clasts and matrix constituents petrographically similar to the abundant basaltic andesite lavas. A less cemmon type of lahar-like breccia contains abundant silicic lapilli and variable amounts of basaltic andesite. Clasts of non-Fifes Peak Fm. lithologies, including gabbroic plutonic rocks, sandstone and altered volcanic rocks, are most commonly associated with these units. Beds in the Edgar Rock member define the circular Edgar Rock dome. An extensive system of radial dikes, truncated at the top of the member, has a focal area near the structural center of the done. Dike compositions range from basaltic andesite to dacite and are petrographically diverse, indicating a history of multiple intrusions. Mafic dikes broadly resemble the mafic flows in the Edgar Rock member, but andesite and dacite dikes are petrographically distinct from flows of similar composition. The Edgar Rock dome is probably the site of a major volcanic center in tile Fifes Peak Fm. Present steep dips are a combination of primary depositional attitudes and syn- and post-depositional uplift, perhaps partly related to the intrusion of the radial dike system. Volcaniclastic interbeds and laharic breccias constrain primary attitudes in the dome from nearly horizontal up to about 15 degrees. The Edgar Rock member on the flanks of the dome represents the proximal apron facies of a cone, mostly removed by erosion, located near the focus of the dike system. The younger member of the Fifes Peak Fm. (Nile Creek Member) unconformably overlies the Edgar Rock dome. The Nile Creek member is comprised mostly of andesite flows and coarse laharic breccias. Lavas are petrographically uniform, highly porphyritic and contain phenocrysts of plagioclase, clinopyroxene, orthopyroxene, magnetite and olivine. K-Ar ages indicate an early Miocene age of about 24 to 19.5 Ma. An ash-flow tuff has a fission-track age of 23.3 Ma. The source of the Nile Creek lavas was not identified in this study. The principal structure of the study area, the Edgar Rock dome, formed during Fifes Peak time (pre-24 Ma). A NW-trending monocline offsets the Edgar Rock member and is coeval with the adjacent Little Naches Syncline. The Cliffdell area lavas and dikes have geochemical features common to continental margin, subduction-related lavas. Enrichments in K and related LIL and light-REE are characteristic of calc-alkaline lavas, but high FeO/MgO ratios, especially of the Edgar Rock suite, are typical of tholeiitic lavas. High AI2O3 and low MgO, Ni and Cr of mafic Edgar Rock lavas are characteristic of orogenic high—alumina basalts. Edgar Rock lavas and dikes are enriched in LIL, REE and HFS elements relative to the Nile Creek lavas. The Cliffdell suites, especially the Edgar Rock, are Fe-enriched relative to the coeval Cascade batholiths. Separate source regions or magmatic differentiation processes, or both, are indicated

Incorporating climate change into invasive species management: insights from managers

Invasive alien species are likely to interact with climate change, thus necessitating management that proactively addresses both global changes. However, invasive species managers’ concerns about the effects of climate change, the degree to which they incorporate climate change into their management, and what stops them from doing so remain unknown. Therefore, we surveyed natural resource managers addressing invasive species across the U.S. about their priorities, concerns, and management strategies in a changing climate. Of the 211 managers we surveyed, most were very concerned about the influence of climate change on invasive species management, but their organizations were significantly less so. Managers reported that lack of funding and personnel limited their ability to effectively manage invasive species, while lack of information limited their consideration of climate change in decision-making. Additionally, managers prioritized research that identifies range-shifting invasive species and native communities resilient to invasions and climate change. Managers also reported that this information would be most effectively communicated through conversations, research summaries, and meetings/symposia. Despite the need for more information, 65% of managers incorporate climate change into their invasive species management through strategic planning, preventative management, changing treatment and control, and increasing education and outreach. These results show the potential for incorporating climate change into management, but also highlight a clear and pressing need for more targeted research, accessible science communication, and two-way dialogue between researchers and managers focused on invasive species and climate change

A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed

The state of Iowa in the US Midwest is regularly affected by major floods and has seen a notable increase in agricultural land cover over the twentieth century. We present a novel statistical-dynamical approach for probabilistic seasonal streamflow forecasting using land cover and General Circulation Model (GCM) precipitation forecasts. Low to high flows are modelled and forecast for the Raccoon River at Van Meter, a 8900 km2 catchment located in central-western Iowa. Statistical model fits for each streamflow quantile (from seasonal minimum to maximum; predictands) are based on observed basin-averaged total seasonal precipitation, annual row crop (corn and soybean) production acreage, and observed precipitation from the month preceding each season (to characterize antecedent wetness conditions) (predictors). Model fits improve when including agricultural land cover and antecedent precipitation as predictors, as opposed to just precipitation. Using the dynamically-updated relationship between predictand and predictors every year, forecasts are computed from 1 to 10 months ahead of every season based on annual row crop acreage from the previous year (persistence forecast) and the monthly precipitation forecasts from eight GCMs of the North American Multi-Model Ensemble (NMME). The skill of our forecast streamflow is assessed in deterministic and probabilistic terms for all initialization months, flow quantiles, and seasons. Overall, the system produces relatively skillful streamflow forecasts from low to high flows, but the skill does not decrease uniformly with initialization time, suggesting that improvements can be gained by using different predictors for specific seasons and flow quantiles