Advancing tephrochronology as a global dating tool: Applications in volcanology, archaeology, and palaeoclimatic research

Layers of far-travelled volcanic ash (tephra) from explosive volcanic eruptions provide stratigraphic and numerical dating horizons in sedimentary and volcanic sequences. Such tephra layers may be dispersed over tens to thousands of kilometres from source, reaching far beyond individual volcanic regions. Tephrochronology is consequently a truly global dating tool, with applications increasingly widespread across a range of Quaternary and geoscience disciplines. This special issue of the International Focus Group on Tephrochronology and Volcanism (INTAV) showcases some of the many recent advances in tephrochronology, from methodological developments to diverse applications across volcanological, archaeological, and palaeoclimatological research

Skillful long-range prediction of European and North American winters

This is the final version. Available from AGU via the DOI in this recordUntil recently, long-range forecast systems showed only modest levels of skill in predicting surface winter climate around the Atlantic Basin and associated fluctuations in the North Atlantic Oscillation at seasonal lead times. Here we use a new forecast system to assess seasonal predictability of winter North Atlantic climate. We demonstrate that key aspects of European and North American winter climate and the surface North Atlantic Oscillation are highly predictable months ahead. We demonstrate high levels of prediction skill in retrospective forecasts of the surface North Atlantic Oscillation, winter storminess, near-surface temperature, and wind speed, all of which have high value for planning and adaptation to extreme winter conditions. Analysis of forecast ensembles suggests that while useful levels of seasonal forecast skill have now been achieved, key sources of predictability are still only partially represented and there is further untapped predictability. Key Points The winter NAO can be skilfully predicted months ahead The signal-to-noise ratio of the predictable signal is anomalously low Predictions of the risk of regional winter extremes are possibleThis work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), the UK Public Weather Service research program, and the European Union Framework 7 SPECS project. Leon Hermanson was funded as part of his Research Fellowship by Willis as part of Willis Research Network (WRN)

Modified Habitats Influence Kelp Epibiota via Direct and Indirect Effects

Addition of man-made structures alters abiotic and biotic characteristics of natural habitats, which can influence abundances of biota directly and/or indirectly, by altering the ecology of competitors or predators. Marine epibiota in modified habitats were used to test hypotheses to distinguish between direct and indirect processes. In Sydney Harbour, kelps on pier-pilings supported greater covers of bryozoans, particularly of the non-indigenous species Membranipora membranacea, than found on natural reefs. Pilings influenced these patterns and processes directly due to the provision of shade and indirectly by altering abundances of sea-urchins which, in turn, affected covers of bryozoans. Indirect effects were more important than direct effects. This indicates that artificial structures affect organisms living on secondary substrata in complex ways, altering the biodiversity and indirectly affecting abundances of epibiota. Understanding how these components of habitats affect ecological processes is necessary to allow sensible prediction of the effects of modifying habitats on the ecology of organisms

First discovery of Holocene cryptotephra in Amazonia

The use of volcanic ash layers for dating and correlation (tephrochronology) is widely applied in the study of past environmental changes. We describe the first cryptotephra (non-visible volcanic ash horizon) to be identified in the Amazon basin, which is tentatively attributed to a source in the Ecuadorian Eastern Cordillera (0–1°S, 78-79°W), some 500-600 km away from our field site in the Peruvian Amazon. Our discovery 1) indicates that the Amazon basin has been subject to volcanic ash fallout during the recent past; 2) highlights the opportunities for using cryptotephras to date palaeoenvironmental records in the Amazon basin and 3) indicates that cryptotephra layers are preserved in a dynamic Amazonian peatland, suggesting that similar layers are likely to be present in other peat sequences that are important for palaeoenvironmental reconstruction. The discovery of cryptotephra in an Amazonian peatland provides a baseline for further investigation of Amazonian tephrochronology and the potential impacts of volcanism on vegetation

Indian summer monsoon onset forecast skill in the UK Met Office initialized coupled seasonal forecasting system (GloSea5-GC2)

Accurate and precise forecasting of the Indian monsoon is important for the socio-economic security of India, with improvements in agriculture and associated sectors from prediction of the monsoon onset. In this study we establish the skill of the UK Met Office coupled initialized global seasonal forecasting system, GloSea5-GC2, in forecasting Indian monsoon onset. We build on previous work that has demonstrated the good skill of GloSea5 at forecasting interannual variations of the seasonal mean Indian monsoon using measures of large-scale circulation and local precipitation. We analyze the summer hindcasts from a set of three springtime start-dates in late April/early May for the 20-year hindcast period (1992-2011). The hindcast set features at least fifteen ensemble members for each year and is analyzed using five different objective monsoon indices. These indices are designed to examine large and local-scale measures of the monsoon circulation, hydrological changes, tropospheric temperature gradient, or rainfall for single value (area-averaged) or grid-point measures of the Indian monsoon onset. There is significant correlation between onset dates in the model and those found in reanalysis. Indices based on large-scale dynamic and thermodynamic indices are better at estimating monsoon onset in the model rather than local-scale dynamical and hydrological indices. This can be attributed to the model's better representation of large-scale dynamics compared to local-scale features. GloSea5 may not be able to predict the exact date of monsoon onset over India, but this study shows that the model has a good ability at predicting category-wise monsoon onset, using early, normal or late tercile categories. Using a grid-point local rainfall onset index, we note that the forecast skill is highest over parts of central India, the Gangetic plains, and parts of coastal India - all zones of extensive agriculture in India. El Niño Southern Oscillation (ENSO) forcing in the model improves the forecast skill of monsoon onset when using a large-scale circulation index, with late monsoon onset coinciding with El Niño conditions and early monsoon onset more common in La Niña years. The results of this study suggest that GloSea5's ensemble-mean forecast may be used for reliable Indian monsoon onset prediction a month in advance despite systematic model errors

Emerging IT risks: insights from German banking

How do German banks manage the emerging risks stemming from IT innovations such as cyber risk? With a focus on process, roles and responsibilities, field data from ten banks participating in the 2014 ECB stress test were collected by interviewing IT managers, risk managers and external experts. Current procedures for handling emerging risks in German banks were identified from the interviews and analysed, guided by the extant literature. A clear gap was found between enterprise risk management (ERM) as a general approach to risks threatening firms’ objectives and ERM’s neglect of emerging risks, such as those associated with IT innovations. The findings suggest that ERM should be extended towards the collection and sharing of knowledge to allow for an initial understanding and description of emerging risks, as opposed to the traditional ERM approach involving estimates of impact and probability. For example, as cyber risks emerge from an IT innovation, the focus may need to switch towards reducing uncertainty through knowledge acquisition. Since individual managers seldom possess all relevant knowledge of an IT innovation, various stakeholders may need to be involved to exploit their expertise

Tephrochronology

Tephrochronology is the use of primary, characterized tephras or cryptotephras as chronostratigraphic marker beds to connect and synchronize geological, paleoenvironmental, or archaeological sequences or events, or soils/paleosols, and, uniquely, to transfer relative or numerical ages or dates to them using stratigraphic and age information together with mineralogical and geochemical compositional data, especially from individual glass-shard analyses, obtained for the tephra/cryptotephra deposits. To function as an age-equivalent correlation and chronostratigraphic dating tool, tephrochronology may be undertaken in three steps: (i) mapping and describing tephras and determining their stratigraphic relationships, (ii) characterizing tephras or cryptotephras in the laboratory, and (iii) dating them using a wide range of geochronological methods. Tephrochronology is also an important tool in volcanology, informing studies on volcanic petrology, volcano eruption histories and hazards, and volcano-climate forcing. Although limitations and challenges remain, multidisciplinary applications of tephrochronology continue to grow markedly

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2

Science shaping the future?

Full report `Science shaping the future? Technology Foresight and its impact' held at GPE/0987SIGLEAvailable from British Library Document Supply Centre-DSC:7673.163(97) / BLDSC - British Library Document Supply CentreGBUnited Kingdo