Support for global climate reorganization during the "Medieval Climate Anomaly"

Widely distributed proxy records indicate that the Medieval Climate Anomaly (MCA; *900–1350 AD) was characterized by coherent shifts in large-scale Northern Hemisphere atmospheric circulation patterns. Although cooler sea surface temperatures in the central and eastern equatorial Pacific can explain some aspects of medieval circulation changes, they are not sufficient to account for other notable features, including widespread aridity through the Eurasian sub-tropics, stronger winter westerlies across the North Atlantic and Western Europe, and shifts in monsoon rainfall patterns across Africa and South Asia. We present results from a full-physics coupled climate model showing that a slight warming of the tropical Indian and western Pacific Oceans relative to the other tropical ocean basins can induce a broad range of the medieval circulation and climate changes indicated by proxy data, including many of those not explained by a cooler tropical Pacific alone. Important aspects of the results resemble those from previous simulations examining the climatic response to the rapid Indian Ocean warming during the late twentieth century, and to results from climate warming simulations—especially in indicating an expansion of the Northern Hemisphere Hadley circulation. Notably, the pattern of tropical Indo-Pacific sea surface temperature (SST) change responsible for producing the proxy-model similarity in our results agrees well with MCA-LIA SST differences obtained in a recent proxy-based climate field reconstruction. Though much remains unclear, our results indicate that the MCA was characterized by an enhanced zonal Indo-Pacific SST gradient with resulting changes in Northern Hemisphere tropical and extra-tropical circulation patterns and hydroclimate regimes, linkages that may explain the coherent regional climate shifts indicated by proxy records from across the planet. The findings provide new perspectives on the nature and possible causes of the MCA—a remarkable, yet incompletely understood episode of Late Holocene climatic change.

Evidence for a widespread climatic anomaly at around 9.2 ka before present.

The 8.2 ka event was triggered by a meltwater pulse (MWP) into the North Atlantic and resultant reduction of the thermohaline circulation (THC). This event was preceded by a series of at least 14 MWPs; their impact on early Holocene climate has remained almost unknown. A set of high-quality paleoclimate records from across the Northern Hemisphere shows evidence for a widespread and significant climatic anomaly at ∼9.2 ka B.P. This event has climatic anomaly patterns very similar to the 8.2 ka B.P. event, cooling occurred at high latitudes and midlatitudes and drying took place in the northern tropics, and is concurrent with an MWP of considerable volume (∼8100 km3). As the 9.2 ka MWP occurs at a time of enhanced baseline freshwater flow into the North Atlantic, this MWP may have been, despite its relatively small volume, sufficient to weaken THC and to induce the observed climate anomaly pattern.

Intensified anticyclonic anomaly over the western North Pacific during El Niño decaying summer under a weakened Atlantic thermohaline circulation

It has been well documented that there is an anticyclonic anomaly over the western North Pacific (WNPAC, hereafter) during El Niño decaying summer. This El Niño-WNPAC relationship is greatly useful for the seasonal prediction of summer climate in the WNP and East Asia. In this study, we investigate the modification of the El Niño-WNPAC relationship induced by a weakened Atlantic thermohaline circulation (THC) in a water-hosing experiment. The results suggest that the WNPAC during the El Niño decaying summer, as well as the associated precipitation anomaly over the WNP, is intensified under the weakened THC. On the one hand, this intensification is in response to the increased amplitude and frequency of El Niño events in the water-hosing experiment. On the other hand, this intensification is also because of greater climatological humidity over the western to central North Pacific under the weakened THC. We suggest that the increase of climatological humidity over the western to central North Pacific during summer under the weakened THC is favorable for enhanced interannual variability of precipitation, and therefore favorable for the intensification of the WNPAC during El Niño decaying summer. This study suggests a possible modulation of the El Niño–Southern Oscillation-WNP summer monsoon relationship by the low-frequency fluctuation of Atlantic sea surface temperature. The results offer an explanation for the observed modification of the multidecadal fluctuation of El Niño-WNPAC relationship by the Atlantic multidecadal oscillation.

Children’s and Adults’ Processing of Anomaly and Implausibility during Reading: Evidence from Eye Movements

The eye movements of 24 children and 24 adults were monitored to compare how they read sentences containing plausible, implausible, and anomalous thematic relations. In the implausible condition the incongruity occurred due to the incompatibility of two objects involved in the event denoted by the main verb. In the anomalous condition the direct object of the verb was not a possible verb argument. Adults exhibited immediate disruption with the anomalous sentences as compared to the implausible sentences as indexed by longer gaze durations on the target word. Children exhibited the same pattern of effects as adults as far as the anomalous sentences were concerned, but exhibited delayed effects of implausibility. These data indicate that while children and adults are alike in their basic thematic assignment processes during reading, children may be delayed in the efficiency with which they are able to integrate pragmatic and real world knowledge into their discourse representation.

Towards anomaly detection for increased security in multibiometric systems: spoofing-resistant 1-median fusion eliminating outliers

Multibiometrics aims at improving biometric security in presence of spoofing attempts, but exposes a larger availability of points of attack. Standard fusion rules have been shown to be highly sensitive to spoofing attempts – even in case of a single fake instance only. This paper presents a novel spoofing-resistant fusion scheme proposing the detection and elimination of anomalous fusion input in an ensemble of evidence with liveness information. This approach aims at making multibiometric systems more resistant to presentation attacks by modeling the typical behaviour of human surveillance operators detecting anomalies as employed in many decision support systems. It is shown to improve security, while retaining the high accuracy level of standard fusion approaches on the latest Fingerprint Liveness Detection Competition (LivDet) 2013 dataset.

The medieval climate anomaly and Byzantium: a review of the evidence on climatic fluctuations, economic performance and societal change

At the beginning of the Medieval Climate Anomaly, in the ninth and tenth century, the medieval eastern Roman empire, more usually known as Byzantium, was recovering from its early medieval crisis and experiencing favourable climatic conditions for the agricultural and demographic growth. Although in the Balkans and Anatolia such favourable climate conditions were prevalent during the eleventh century, parts of the imperial territories were facing significant challenges as a result of external political/military pressure. The apogee of medieval Byzantine socio-economic development, around AD 1150, coincides with a period of adverse climatic conditions for its economy, so it becomes obvious that the winter dryness and high climate variability at this time did not hinder Byzantine society and economy from achieving that level of expansion. Soon after this peak, towards the end of the twelfth century, the populations of the Byzantine world were experiencing unusual climatic conditions with marked dryness and cooler phases. The weakened Byzantine socio-political system must have contributed to the events leading to the fall of Constantinople in AD 1204 and the sack of the city. The final collapse of the Byzantine political control over western Anatolia took place half century later, thus contemporaneous with the strong cooling effect after a tropical volcanic eruption in AD 1257. We suggest that, regardless of a range of other influential factors, climate change was also an important contributing factor to the socio-economic changes that took place in Byzantium during the Medieval Climate Anomaly. Crucially, therefore, while the relatively sophisticated and complex Byzantine society was certainly influenced by climatic conditions, and while it nevertheless displayed a significant degree of resilience, external pressures as well as tensions within the Byzantine society more broadly contributed to an increasing vulnerability in respect of climate impacts. Our interdisciplinary analysis is based on all available sources of information on the climate and society of Byzantium, that is textual (documentary), archaeological, environmental, climate and climate model-based evidence about the nature and extent of climate variability in the eastern Mediterranean. The key challenge was, therefore, to assess the relative influence to be ascribed to climate variability and change on the one hand, and on the other to the anthropogenic factors in the evolution of Byzantine state and society (such as invasions, changes in international or regional market demand and patterns of production and consumption, etc.). The focus of this interdisciplinary

Bilateral anomaly in the style of Sciopemyia sordellii (Shannon & Del Ponte) (Diptera, Psychodidae)

This paper presents a male specimen of Sciopemyia sordellii with a rare bilateral anomaly, consisting in eight spines in a style and five in the other. This species has four spines in each style as its normal number. The specimen was captured using a CDC light trap, in a forested area in the State Park ""Floresta Estadual Edmundo Navarro de Andrade"", in May 2004, located in the city of Rio Claro, Sao Paulo State, Brazil. Similar anomaly was once described but this is the first specimen found with a bilateral alteration. It may cause confusion in taxonomic identification and even lead to description of new species, increasing the number of synonymies.

Virtual Pole from Magnetic Anomaly (VPMA): A procedure to estimate the age of a rock from its magnetic anomaly only

Virtual Pole from Magnetic Anomaly (VPMA) is a new multi-disciplinary methodology that estimates the age of a source rock from its magnetic anomaly, taken directly from available aeromagnetic data. The idea is to use those anomalies in which a strong remanent magnetic component is likely to occur. Once the total magnetization of the anomaly is computed through any of the currently available methods, the line that connects all virtual paleogeographic poles is related with the position, on a paleogeographic projection, of the appropriate age fragment of the APWT curve. We applied this procedure to five (5) well-known magnetic anomalies of the South American plate in SE Brazil, all of them associated to alkaline complexes of Mesozoic age. The apparent ages obtained from VPMA on three of the anomalies where the radiometric age of the source rock is known - Tapira, Araxa and Juquia were inside the error interval of the published ages. The VPMA apparent ages of the other two, where the age of the source rock is not known (Registro and Pariqueracu magnetic anomalies) were geologically coherent. We expect that the application of the VPMA methodology as a reconnaissance geochronological tool may contribute to geological knowledge over continental areas, especially when the source rocks of the magnetic anomalies am unknown or buried below superficial sediments. (C) 2009 Elsevier B.V. All rights reserved.

Infrared chiral anomaly at finite temperature

We study the Schwinger model at finite temperature and show that a temperature dependent chiral anomaly may arise from the long distance behavior of the electric field. At high temperature this anomaly depends linearly on the temperature T and is present not only in the two point function, but also in all even point amplitudes. (C) 2011 Elsevier B.V. All rights reserved.

Constructing detectors in schema complementary space for anomaly detection

This paper proposes an extended negative selection algorithm for anomaly detection. Unlike previously proposed negative selection algorithms which directly construct detectors in the complementary space of self-data space, our approach first evolves a number of common schemata through coevolutionary genetic algorithm in self-data space, and then constructs detectors in the complementary space of the schemata. These common schemata characterize self-data space and thus guide the generation of detection rules. By converting data space into schema space, we can efficiently generate an appropriate number of detectors with diversity for anomaly detection. The approach is tested for its effectiveness through experiment with the published data set iris.

An extended negative selection algorithm for anomaly detection

This paper proposes an extended negative selection algorithm for anomaly detection. Unlike previously proposed negative selection algorithms which do not make use of non-self data, the extended negative selection algorithm first acquires prior knowledge about the characteristics of the Problem space from the historial sample data by using machine learning techniques. Such data consists of both self data and non-self data. The acquired prior knowledge is represented in the form of production rules and thus viewed as common schemata which characterise the two subspaces: self-subspace and non-self-subspace, and provide important information to the generation of detection rules. One advantage of our approach is that it does not rely on the structured representation of the data and can be applied to general anomaly detection. To test the effectiveness, we test our approach through experiments with the public data set iris and KDDrsquo99 published data set.

Applying both positive and negative selection to supervised learning for anomaly detection

This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the normal class via co-evolutionary genetic algorithm, which is inspired from the positive selection, and then generates synthetic samples of the anomaly class, which is based on the negative selection in the immune system. Two algorithms about synthetic generation of the anomaly class are proposed. One deals with data sets containing a few anomalous samples; while the other deals with data sets containing no anomalous samples at all. The experimental results on some benchmark data sets from UCI data set repertory show that the detection rate is improved evidently, accompanied by a slight increase in false alarm rate via introducing novel synthetic samples of the anomaly class. The advantages of our method are the increased ability of classifiers in identifying both previously known and innovative anomalies, and the maximal degradation of overfitting phenomenon.

Immunology-based subspace detectors for anomaly detection

A key problem in high dimensional anomaly detection is that the time spent in constructing detectors by the means of generateand-test is tolerable. In fact, due to the high sparsity. of the data, it is ineffective to construct detectors in the whole data space. Previous investigations have shown that most essentIal patterns can be discovered in different subspaces. This inspires us to construct detectors in signIficant subspaces only for anomaly detection. We first use ENCLUS-based method to discover all significant subspaces and .then use a greedy-growth algorithm to construct detectors in each subspace. The elements used to constItute a detector are gods Instead of data points, which makes the time-consumption irrelevant to the size of the nonnal data. We test the effectiveness and efficiency of our method on both synthetic and benchmark datasets. The results reveal that our method is particularly useful in anomaly detection in high dimensional data spaces.