Assessing and understanding the impact of stratospheric dynamics and variability on the earth system

Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and Their Role in Climate (SPARC) DynVar activity to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multi-model datasets. First, roughly 10 models with a well resolved stratosphere are participating in the Coupled Model Intercomparison Project 5 (CMIP5), providing the first multi-model ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Historical Forecasting Project (SHFP) of WCRP's Climate Variability and predictability (CLIVAR) program is forming a multi-model set of seasonal hindcasts with stratosphere resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and SHFP model-data sets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections. Capsule New modeling efforts will provide unprecedented opportunities to harness our knowledge of the stratosphere to improve weather and climate prediction.

Prebiotics and the health benefits of fiber: current regulatory status, future research, and goals.

First defined in the mid-1990s, prebiotics, which alter the composition and activity of gastrointestinal (GI) microbiota to improve health and well-being, have generated scientific and consumer interest and regulatory debate. The Life Sciences Research Organization, Inc. (LSRO) held a workshop, Prebiotics and the Health Benefits of Fiber: Future Research and Goals, in February 2011 to assess the current state of the science and the international regulatory environment for prebiotics, identify research gaps, and create a strategy for future research. A developing body of evidence supports a role for prebiotics in reducing the risk and severity of GI infection and inflammation, including diarrhea, inflammatory bowel disease, and ulcerative colitis as well as bowel function disorders, including irritable bowel syndrome. Prebiotics also increase the bioavailability and uptake of minerals and data suggest that they reduce the risk of obesity by promoting satiety and weight loss. Additional research is needed to define the relationship between the consumption of different prebiotics and improvement of human health. New information derived from the characterization of the composition and function of different prebiotics as well as the interactions among and between gut microbiota and the human host would improve our understanding of the effects of prebiotics on health and disease and could assist in surmounting regulatory issues related to prebiotic use.

A new floating model level scheme for the assimilation of boundary layer top inversions: the univariate assimilation of temperature.

The assimilation of observations with a forecast is often heavily influenced by the description of the error covariances associated with the forecast. When a temperature inversion is present at the top of the boundary layer (BL), a significant part of the forecast error may be described as a vertical positional error (as opposed to amplitude error normally dealt with in data assimilation). In these cases, failing to account for positional error explicitly is shown t o r esult in an analysis for which the inversion structure is erroneously weakened and degraded. In this article, a new assimilation scheme is proposed to explicitly include the positional error associated with an inversion. This is done through the introduction of an extra control variable to allow position errors in the a priori to be treated simultaneously with the usual amplitude errors. This new scheme, referred to as the ‘floating BL scheme’, is applied to the one-dimensional (vertical) variational assimilation of temperature. The floating BL scheme is tested with a series of idealised experiments a nd with real data from radiosondes. For each idealised experiment, the floating BL scheme gives an analysis which has the inversion structure and position in agreement with the truth, and outperforms the a ssimilation which accounts only for forecast a mplitude error. When the floating BL scheme is used to assimilate a l arge sample of radiosonde data, its ability to give an analysis with an inversion height in better agreement with that observed is confirmed. However, it is found that the use of Gaussian statistics is an inappropriate description o f t he error statistics o f t he extra c ontrol variable. This problem is alleviated by incorporating a non-Gaussian description of the new control variable in the new scheme. Anticipated challenges in implementing the scheme operationally are discussed towards the end of the article.

Oligomeric pseudorotaxanes adopting infinite-chain lattice superstructures

Above a critical chain length, where oligomers contain five or more recognition units, apparently infinite donor–acceptor polypseudorotaxanes are formed in the solid state. X-ray crystallographic analyses of three different examples have shown that although the oligomeric chains are undoubtedly discrete and monodisperse, they nevertheless appear to be infinite in the crystal.

Beta event-related desynchronization as an index of individual differences in processing human facial expression: further investigations of autistic traits in typically developing adults

The human mirror neuron system (hMNS) has been associated with various forms of social cognition and affective processing including vicarious experience. It has also been proposed that a faulty hMNS may underlie some of the deficits seen in the autism spectrum disorders (ASDs). In the present study we set out to investigate whether emotional facial expressions could modulate a putative EEG index of hMNS activation (mu suppression) and if so, would this differ according to the individual level of autistic traits [high versus low Autism Spectrum Quotient (AQ) score]. Participants were presented with 3 s films of actors opening and closing their hands (classic hMNS mu-suppression protocol) while simultaneously wearing happy, angry, or neutral expressions. Mu-suppression was measured in the alpha and low beta bands. The low AQ group displayed greater low beta event-related desynchronization (ERD) to both angry and neutral expressions. The high AQ group displayed greater low beta ERD to angry than to happy expressions. There was also significantly more low beta ERD to happy faces for the low than for the high AQ group. In conclusion, an interesting interaction between AQ group and emotional expression revealed that hMNS activation can be modulated by emotional facial expressions and that this is differentiated according to individual differences in the level of autistic traits. The EEG index of hMNS activation (mu suppression) seems to be a sensitive measure of the variability in facial processing in typically developing individuals with high and low self-reported traits of autism.

On the lack of stratospheric dynamical variability in low-top versions of the CMIP5 models

We describe the main differences in simulations of stratospheric climate and variability by models within the fifth Coupled Model Intercomparison Project (CMIP5) that have a model top above the stratopause and relatively fine stratospheric vertical resolution (high-top), and those that have a model top below the stratopause (low-top). Although the simulation of mean stratospheric climate by the two model ensembles is similar, the low-top model ensemble has very weak stratospheric variability on daily and interannual time scales. The frequency of major sudden stratospheric warming events is strongly underestimated by the low-top models with less than half the frequency of events observed in the reanalysis data and high-top models. The lack of stratospheric variability in the low-top models affects their stratosphere-troposphere coupling, resulting in short-lived anomalies in the Northern Annular Mode, which do not produce long-lasting tropospheric impacts, as seen in observations. The lack of stratospheric variability, however, does not appear to have any impact on the ability of the low-top models to reproduce past stratospheric temperature trends. We find little improvement in the simulation of decadal variability for the high-top models compared to the low-top, which is likely related to the fact that neither ensemble produces a realistic dynamical response to volcanic eruptions.

Variation among Attic fine wares: the case of the Pan Painter's pelikai

This paper is a case study of the continuum between standardization and variation in the production of red-figure Athenian fine wares in the first half of the 5th century BC. An investigation of the Pan Painter's pelikai reveals that they fall into 3 distinct groups, according to size. While the pelikai in each group are also distinguishable from each other by shape, pattern, and iconography, the next clearest distinction between the groups (after size) is in their style of decoration. The pelikai in the largest group, which is comprised of small pelikai, are particularly distinct from the Pan Painter's broader oeuvre of ca. 220 vases insofar as they exemplify a lackadaisical painting style, which I have termed banausic, on account of its frequent use for images of craftsmen, women at work, and other such genre images. While this casual style is antithetical to the Pain Painter's refined style, for which he is better known, and which he employs for his large pelikai, affinities between the 2 styles—as judged by his confident line, anatomical details, and other technical features—permit the conclusion that this group of pelikai were executed by one and the same craftsman as the others. As with all of the vases attributed to this talented painter, however, the pelikai—whether large or small—are decorated with a great bariety of images. While most painted Athenian vases are understood to have been individually created, not mass-produced, the Pan Painter's coherent group of small pelikai seem to have been created en masse, in a uniform size and shape and with a distinct decorative style. This group of standardized vases represents a body of work executed under the influence or at the behest of a specific vase workshop. The form of the small pelikai in fact allows us to associate them with the Geras Painter. With his work on these small pelikai, perhaps in the latter part of his career, the Pan Painter may have intentionally minimized variability in favour of standardization, to meet market demands.

EU agricultural policies and European integration: a thematic review of the literature

The purpose of this chapter is to review the academic literature that has contributed to the debate on the European Union’s (EU’s) common agricultural policy (CAP), and the close links between the CAP and the process of economic integration.

Representation of model error in a convective-scale ensemble prediction system

In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.