1000 resultados para SSTA pattern


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Based on the data analysis, this study further explores the characteristics of East Asian winter monsoon (hereafter, EAWM, for brevity) as well as the related air-sea-land system, and illustrates how and to what degree anomalous signals of the subsequent Asian summer monsoon are rooted in the preceding EAWM activity. We identified an important air-sea coupled mode, i.e., the EAWM mode illustrated in Section 3. In cold seasons, strong EAWM-related air-sea two-way interaction is responsible for the development and persistence of the SSTA pattern of EAWM mode. As a consequence, the key regions, i.e., the western Pacific and South China Sea (hereafter, SCS, for brevity), are dominated by such an SSTA pattern from the winter to the following summer. In the strong EAWM years, the deficient snow cover dominates eastern Tibetan Plateau in winter, and in spring, this anomaly pattern is further strengthened and extended to the northwestern side of Tibetan Plateau. Thus, the combined effect of strong EAWM-related SSTA and Tibetan snow cover constitutes an important factor in modulating the Asian monsoon circulation. The active role of the EAWM activity as well as the related air-sea-land interaction would, in the subsequent seasons, lead to: 1) the enhancement of SCS monsoon and related stronger rainfall; 2) the northward displacement of subtropical high during Meiyu period and the related deficient rainfall over Meiyu rainband; 3) above-normal precipitation over the regions from northern Japan to northeastern China in summer; 4) more rainfall over the Arabian Sea and Northeast India, while less rainfall over southwest India and the Bay of Bengal. The strong EAWM-related air-sea interaction shows, to some degree, precursory signals to the following Asian summer monsoon. However, the mechanism for the variability of Indian summer monsoon subsequent to the strong EAWM years remains uncertain.

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Based on analysis of NCEP reanalysis data and SST indices of the recent 50 years, decadal changes of the potential predictability of ENSO and interannual climate anomalies were investigated. Autocorrelation of Nino3 SST anomalies (SSTA) and correlation between atmospheric anomalies fields and Nino3 SSTA exhibit obvious variation in different decades, which indicates that Nino3 SSTA-related potential predictability of ENSO and interannual climate anomalies has significant decadal changes. Time around 1977 is not only a shift point of climate on the interdecadal time scale but also a catastrophe point of potential predictability of ENSO and interannual climate. As a whole, ENSO and the PNA pattern in boreal winter are more predictable in 1980s than in 1960s and 1970s, while the Nino3 SSTA-related potential predictability of the Indian monsoon and the East Asian Monsoon is lower in 1980s than in 1960s and 1970s.

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Enterprise Application Integration (EAI) is a challenging area that is attracting growing attention from the software industry and the research community. A landscape of languages and techniques for EAI has emerged and is continuously being enriched with new proposals from different software vendors and coalitions. However, little or no effort has been dedicated to systematically evaluate and compare these languages and techniques. The work reported in this paper is a first step in this direction. It presents an in-depth analysis of a language, namely the Business Modeling Language, specifically developed for EAI. The framework used for this analysis is based on a number of workflow and communication patterns. This framework provides a basis for evaluating the advantages and drawbacks of EAI languages with respect to recurrent problems and situations.

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Cat’s claw creeper, Macfadyena unguis-cati (L.) Gentry (Bignoniaceae) is a major environmental weed of riparian areas, rainforest communities and remnant natural vegetation in coastal Queensland and New South Wales, Australia. In densely infested areas, it smothers standing vegetation, including large trees, and causes canopy collapse. Quantitative data on the ecology of this invasive vine are generally lacking. The present study examines the underground tuber traits of M. unguis-cati and explores their links with aboveground parameters at five infested sites spanning both riparian and inland vegetation. Tubers were abundant in terms of density (~1000 per m2), although small in size and low in level of interconnectivity. M. unguis-cati also exhibits multiple stems per plant. Of all traits screened, the link between stand (stem density) and tuber density was the most significant and yielded a promising bivariate relationship for the purposes of estimation, prediction and management of what lies beneath the soil surface of a given M. unguis-cati infestation site. The study also suggests that new recruitment is primarily from seeds, not from vegetative propagation as previously thought. The results highlight the need for future biological-control efforts to focus on introducing specialist seed- and pod-feeding insects to reduce seed-output.

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Computational biology increasingly demands the sharing of sophisticated data and annotations between research groups. Web 2.0 style sharing and publication requires that biological systems be described in well-defined, yet flexible and extensible formats which enhance exchange and re-use. In contrast to many of the standards for exchange in the genomic sciences, descriptions of biological sequences show a great diversity in format and function, impeding the definition and exchange of sequence patterns. In this presentation, we introduce BioPatML, an XML-based pattern description language that supports a wide range of patterns and allows the construction of complex, hierarchically structured patterns and pattern libraries. BioPatML unifies the diversity of current pattern description languages and fills a gap in the set of XML-based description languages for biological systems. We discuss the structure and elements of the language, and demonstrate its advantages on a series of applications, showing lightweight integration between the BioPatML parser and search engine, and the SilverGene genome browser. We conclude by describing our site to enable large scale pattern sharing, and our efforts to seed this repository.

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Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

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In the region of self-organized criticality (SOC) interdependency between multi-agent system components exists and slight changes in near-neighbor interactions can break the balance of equally poised options leading to transitions in system order. In this region, frequency of events of differing magnitudes exhibits a power law distribution. The aim of this paper was to investigate whether a power law distribution characterized attacker-defender interactions in team sports. For this purpose we observed attacker and defender in a dyadic sub-phase of rugby union near the try line. Videogrammetry was used to capture players’ motion over time as player locations were digitized. Power laws were calculated for the rate of change of players’ relative position. Data revealed that three emergent patterns from dyadic system interactions (i.e., try; unsuccessful tackle; effective tackle) displayed a power law distribution. Results suggested that pattern forming dynamics dyads in rugby union exhibited SOC. It was concluded that rugby union dyads evolve in SOC regions suggesting that players’ decisions and actions are governed by local interactions rules.