Clothing consumption in two recent EU Member States: a cross-cultural study

Marketing research efforts across Eastern European countries continue growing since the introduction of market reforms in this region. Nonetheless, questions remain unanswered as to cross-cultural differences in Eastern Europeans' consumer behavior. The present research addresses this knowledge gap by developing and testing hypotheses about cross-cultural variations in a number of clothing-related consumer behavior phenomena in the Czech Republic and Bulgaria. Our findings indicate significant differences regarding consumer interest in clothing, preference for utilitarian, self-expressive and hedonic meanings of clothing artifacts, preference for well-known clothing brands, brand loyalty, and importance of clothing attributes. The study advances research in marketing by investigating clothing value-expressive symbolism and consumption in the tworecentEUMember States. The study provides valuable insights to marketers for developing effective marketing strategies.

Climate change, extreme weather events and issues of human perception

The central proposition of Toby Pillatt is that in developing an understanding of past human affairs weather is as important as, or more so than, climate. Climate may be simply defined as average weather, whilst weather is the day-to-day occurrence of atmospheric phenomena which impact in perceptible ways on people's lives. The general proposition is sound enough; the challenges come in implementing these ideas in ways which advance our understanding of past people–environment relationships.

The child in wolf’s clothing: the meanings of the ‘wolf’ and questions of identity in Jack London’s White Fang

The criticism of Jack London’s work has been dominated by a reliance upon ideas of the ‘real’, the ‘authentic’ and the ‘archetypal’. One of the figures in London’s work around which these ideas crystallize is that of the ‘wolf’. This article will examine the way the wolf is mobilized both in the criticism of Jack London’s work and in an example of the work: the novel White Fang (1906). This novel, though it has often been read as clearly delimiting and demarcating the realms of nature and culture, can be read conversely as unpicking the deceptive simplicity of such categories, as troubling essentialist notions of identity (human/animal, male/female, white/Indian) and as engaging with the complexity of the journey in which a ‘small animal … becomes human-sexual by crossing the infinite divide that separates life from humanity, the biological from the historical, “nature” from “culture” ’ (Althusser 1971: 206).

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Tropical cyclone climatology in a 10-km global atmospheric GCM: toward weather-resolving climate modeling

Northern Hemisphere tropical cyclone (TC) activity is investigated in multiyear global climate simulations with theECMWFIntegrated Forecast System (IFS) at 10-km resolution forced by the observed records of sea surface temperature and sea ice. The results are compared to analogous simulationswith the 16-, 39-, and 125-km versions of the model as well as observations. In the North Atlantic, mean TC frequency in the 10-km model is comparable to the observed frequency, whereas it is too low in the other versions. While spatial distributions of the genesis and track densities improve systematically with increasing resolution, the 10-km model displays qualitatively more realistic simulation of the track density in the western subtropical North Atlantic. In the North Pacific, the TC count tends to be too high in thewest and too low in the east for all resolutions. These model errors appear to be associated with the errors in the large-scale environmental conditions that are fairly similar in this region for all model versions. The largest benefits of the 10-km simulation are the dramatically more accurate representation of the TC intensity distribution and the structure of the most intense storms. The model can generate a supertyphoon with a maximum surface wind speed of 68.4 m s21. The life cycle of an intense TC comprises intensity fluctuations that occur in apparent connection with the variations of the eyewall/rainband structure. These findings suggest that a hydrostatic model with cumulus parameterization and of high enough resolution could be efficiently used to simulate the TC intensity response (and the associated structural changes) to future climate change.

Whether weather affects music

The creative output of composers, writers, and artists is often influenced by their surroundings. To give a literary example, it has been claimed recently that some of the characters in Oliver Twist and A Christmas Carol were based on real-life people who lived near Charles Dickens in London [Richardson, 2012]. Of course, an important part of what we see and hear is not only the people with whom we interact but also our geophysical surroundings. Of all the geophysical phenomena to influence us, the weather is arguably the most significant because we are exposed to it directly and daily. The weather was a great source of inspiration for artists Claude Monet, John Constable, and William Turner, who are known for their scientifically accurate paintings of the skies [e.g., Baker and Thornes, 2006].

Ice formation and development in aged, wintertime cumulus over the UK: observations and modelling

In situ high resolution aircraft measurements of cloud microphysical properties were made in coordination with ground based remote sensing observations of a line of small cumulus clouds, using Radar and Lidar, as part of the Aerosol Properties, PRocesses And InfluenceS on the Earth's climate (APPRAISE) project. A narrow but extensive line (~100 km long) of shallow convective clouds over the southern UK was studied. Cloud top temperatures were observed to be higher than −8 °C, but the clouds were seen to consist of supercooled droplets and varying concentrations of ice particles. No ice particles were observed to be falling into the cloud tops from above. Current parameterisations of ice nuclei (IN) numbers predict too few particles will be active as ice nuclei to account for ice particle concentrations at the observed, near cloud top, temperatures (−7.5 °C). The role of mineral dust particles, consistent with concentrations observed near the surface, acting as high temperature IN is considered important in this case. It was found that very high concentrations of ice particles (up to 100 L−1) could be produced by secondary ice particle production providing the observed small amount of primary ice (about 0.01 L−1) was present to initiate it. This emphasises the need to understand primary ice formation in slightly supercooled clouds. It is shown using simple calculations that the Hallett-Mossop process (HM) is the likely source of the secondary ice. Model simulations of the case study were performed with the Aerosol Cloud and Precipitation Interactions Model (ACPIM). These parcel model investigations confirmed the HM process to be a very important mechanism for producing the observed high ice concentrations. A key step in generating the high concentrations was the process of collision and coalescence of rain drops, which once formed fell rapidly through the cloud, collecting ice particles which caused them to freeze and form instant large riming particles. The broadening of the droplet size-distribution by collision-coalescence was, therefore, a vital step in this process as this was required to generate the large number of ice crystals observed in the time available. Simulations were also performed with the WRF (Weather, Research and Forecasting) model. The results showed that while HM does act to increase the mass and number concentration of ice particles in these model simulations it was not found to be critical for the formation of precipitation. However, the WRF simulations produced a cloud top that was too cold and this, combined with the assumption of continual replenishing of ice nuclei removed by ice crystal formation, resulted in too many ice crystals forming by primary nucleation compared to the observations and parcel modelling.

Enhanced levels of cold shock proteins in Listeria monocytogenes LO28 upon exposure to low temperature and high hydrostatic pressure

Listeria monocytogenes is a psychrotrophic food-borne pathogen that is problematic for the food industry because of its ubiquitous distribution in nature and its ability to grow at low temperatures and in the presence of high salt concentrations. Here we demonstrate that the process of adaptation to low temperature after cold shock includes elevated levels of cold shock proteins (CSPs) and that the levels of CSPs are also elevated after treatment with high hydrostatic pressure (HHP). Two-dimensional gel electrophoresis combined with Western blotting performed with anti-CspB of Bacillus subtilis was used to identify four 7-kDa proteins, designated Csp1, Csp2, Csp3, and Csp4. In addition, Southern blotting revealed four chromosomal DNA fragments that reacted with a csp probe, which also indicated that a CSP family is present in L. monocytogenes LO28. After a cold shock in which the temperature was decreased from 37°C to 10°C the levels of Csp1 and Csp3 increased 10- and 3.5-fold, respectively, but the levels of Csp2 and Csp4 were not elevated. Pressurization of L. monocytogenes LO28 cells resulted in 3.5- and 2-fold increases in the levels of Csp1 and Csp2, respectively. Strikingly, the level of survival after pressurization of cold-shocked cells was 100-fold higher than that of cells growing exponentially at 37°C. These findings imply that cold-shocked cells are protected from HHP treatment, which may affect the efficiency of combined preservation techniques.

Using seasonal hindcasts to understand the origin of the equatorial cold tongue bias in CGCMs and its impact on ENSO

The cold equatorial SST bias in the tropical Pacific that is persistent in many coupled OAGCMs severely impacts the fidelity of the simulated climate and variability in this key region, such as the ENSO phenomenon. The classical bias analysis in these models usually concentrates on multi-decadal to centennial time series needed to obtain statistically robust features. Yet, this strategy cannot fully explain how the models errors were generated in the first place. Here, we use seasonal re-forecasts (hindcasts) to track back the origin of this cold bias. As such hindcasts are initialized close to observations, the transient drift leading to the cold bias can be analyzed to distinguish pre-existing errors from errors responding to initial ones. A time sequence of processes involved in the advent of the final mean state errors can then be proposed. We apply this strategy to the ENSEMBLES-FP6 project multi-model hindcasts of the last decades. Four of the five AOGCMs develop a persistent equatorial cold tongue bias within a few months. The associated systematic errors are first assessed separately for the warm and cold ENSO phases. We find that the models are able to reproduce either El Niño or La Niña close to observations, but not both. ENSO composites then show that the spurious equatorial cooling is maximum for El Niño years for the February and August start dates. For these events and at this time of the year, zonal wind errors in the equatorial Pacific are present from the beginning of the simulation and are hypothesized to be at the origin of the equatorial cold bias, generating too strong upwelling conditions. The systematic underestimation of the mixed layer depth in several models can also amplify the growth of the SST bias. The seminal role of these zonal wind errors is further demonstrated by carrying out ocean-only experiments forced by the AOCGCMs daily 10-meter wind. In a case study, we show that for several models, this forcing is sufficient to reproduce the main SST error patterns seen after 1 month in the AOCGCM hindcasts.