The geometry of decoupled line driven winds

Bjorkman & Cassinelli (1993) have proposed a mechanism that is expected to produce strong equatorial focusing of the radiation-driven winds from rapidly-rotating B stars. Here the possibility of the decoupling of the stellar radiation field and the outflow is considered. We find that greater equator to pole density ratios may be generated than the standard model, bringing it more into line with results implied by observations.     

Sedimentary macrofossil records reveal ecological change in English lakes: implications for conservation

Aquatic macrophytes play a key role in providing habitat, refuge and food for a range of biota in shallow lakes. However, many shallow lakes have experienced declines in macrophyte vegetation in recent decades, principally due to eutrophication. As changes in macrophyte composition and abundance can affect overall ecological structure and function of a lake, an assessment of the timing and nature of such changes is crucial to our understanding of the wider lake ecosystem. In the typical absence of historical plant records, the macro-remains of macrophytes preserved in lake sediments can be used to assess long-term changes in aquatic vegetation. We generated recent (150–200 years) plant macrofossil records for six English lakes subject to conservation protection to define past macrophyte communities, assess trajectories of ecological change and consider the implications of our findings for conservation targets and strategies. The data for all six lakes reveal a diverse submerged macrophyte community, with charophytes as a key component, in the early part of the sedimentary records. The stratigraphies indicate considerable change to the aquatic vegetation over the last two centuries with a general shift towards species more typically associated with eutrophic conditions. A common feature is the decline in abundance of low-growing charophytes and an increase in tall canopy-forming angiosperms such as fine-leaved Potamogeton species, Zannichellia palustris and Callitriche species. We hypothesise, based on findings from long-term datasets and palaeoecological records from enriched shallow lakes where plants are now absent, that the observed shifts provide a warning to managers that the lakes are on a pathway to complete macrophyte loss such that nutrient load reduction is urgently needed. It is the sound understanding of present-day plant ecology that affords such reliable interpretation of the fossil data which, in turn, provide valuable context for current conservation decisions.     

The impact of weather and climate on tourist demand: the case of Chester Zoo

Warmer, drier summer weather brought by global climate change should encourage use of outdoor leisure facilities. Yet few studies assess the effect of current weather and climate conditions upon visits to leisure attractions. Statistical time series models are used to analyse the short-run impact of weather and the long-run impact of climate upon visits to Chester Zoo, England. Temperature has a non-linear effect on visit levels. Daily visits rise with temperature up to a threshold around 21 °C. Thereafter visitor numbers drop on hot days. Visits are redistributed over time in accordance with the weather. Visitors discouraged by rainy weather one day turn up later when the weather improves. Otherwise, visitor behaviour is mainly influenced by the annual rhythm of the year and the pattern of public and school holidays. Out-of-sample tests suggest almost 70 % of the variation in visit levels can be explained by the combination of weather and time of year. Climate change is likely to redistribute visitors across the year. But it does not follow that “summer” visitor behaviour will transfer to spring and autumn. Day length, existing patterns of human activity and availability of leisure time constrain visit levels regardless of better weather. The main implication of potential climate change is the need for physical adaptation of the tourist environment as temperatures rise and rainfall diminishes in summer.     

Arctic sea ice and the Madden–Julian Oscillation (MJO)

Arctic sea ice responds to atmospheric forcing in primarily a top-down manner, whereby near-surface air circulation and temperature govern motion, formation, melting, and accretion. As a result, concentrations of sea ice vary with phases of many of the major modes of atmospheric variability, including the North Atlantic Oscillation, the Arctic Oscillation, and the El Niño-Southern Oscillation. However, until this present study, variability of sea ice by phase of the leading mode of atmospheric intraseasonal variability, the Madden–Julian Oscillation (MJO), which has been found to modify Arctic circulation and temperature, remained largely unstudied. Anomalies in daily change in sea ice concentration were isolated for all phases of the real-time multivariate MJO index during both summer (May–July) and winter (November–January) months. The three principal findings of the current study were as follows. (1) The MJO projects onto the Arctic atmosphere, as evidenced by statistically significant wavy patterns and consistent anomaly sign changes in composites of surface and mid-tropospheric atmospheric fields. (2) The MJO modulates Arctic sea ice in both summer and winter seasons, with the region of greatest variability shifting with the migration of the ice margin poleward (equatorward) during the summer (winter) period. Active regions of coherent ice concentration variability were identified in the Atlantic sector on days when the MJO was in phases 4 and 7 and the Pacific sector on days when the MJO was in phases 2 and 6, all supported by corresponding anomalies in surface wind and temperature. During July, similar variability in sea ice concentration was found in the North Atlantic sector during MJO phases 2 and 6 and Siberian sector during MJO phases 1 and 5, also supported by corresponding anomalies in surface wind. (3) The MJO modulates Arctic sea ice regionally, often resulting in dipole-shaped patterns of variability between anomaly centers. These results provide an important first look at intraseasonal variability of sea ice in the Arctic.     

Improving Bayesian analysis for LISA Pathfinder using an efficient Markov Chain Monte Carlo method

We present a parameter estimation procedure based on a Bayesian framework by applying a Markov Chain Monte Carlo algorithm to the calibration of the dynamical parameters of the LISA Pathfinder satellite. The method is based on the Metropolis-Hastings algorithm and a two-stage annealing treatment in order to ensure an effective exploration of the parameter space at the beginning of the chain. We compare two versions of the algorithm with an application to a LISA Pathfinder data analysis problem. The two algorithms share the same heating strategy but with one moving in coordinate directions using proposals from a multivariate Gaussian distribution, while the other uses the natural logarithm of some parameters and proposes jumps in the eigen-space of the Fisher Information matrix. The algorithm proposing jumps in the eigen-space of the Fisher Information matrix demonstrates a higher acceptance rate and a slightly better convergence towards the equilibrium parameter distributions in the application to LISA Pathfinder data. For this experiment, we return parameter values that are all within ～1σ of the injected values. When we analyse the accuracy of our parameter estimation in terms of the effect they have on the force-per-unit of mass noise, we find that the induced errors are three orders of magnitude less than the expected experimental uncertainty in the power spectral density.     

Probabilistic GIS-based method for delineation of urban flooding risk hotspots

Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia.     

Heavy Metal Concentrations in European Mosses: 2000/2001 Survey

The heavy metals in mosses survey was originally established in 1980 as a joint Danish–Swedish initiative under the leadership of Åke Rühling, Sweden and has, since then, been repeated at five-yearly intervals with an increasing number of countries and individuals participating. Twenty-eight European countries, almost 7000 sites and about 100 individuals have been involved in the most recent survey in 2000/2001. The survey provides data on concentrations of 10 heavy metals (arsenic, cadmium, chromium, copper, iron, lead, mercury, nickel, vanadium, zinc) in naturally growing mosses throughout Europe. The technique of moss analysis provides a surrogate measure of the spatial patterns of heavy metal deposition from the atmosphere to terrestrial systems, and is easier and cheaper than conventional precipitation analysis. The aims of the survey are to determine patterns of variation in the heavy metal concentration of mosses across Europe, identify the main polluted areas, produce regional maps and further develop the understanding of long-range transboundary pollution.As in previous surveys, there was an east/west decrease in heavy metal concentrations in mosses, related in particular to industrial emissions. Former industrial sites and historic mines accounted for the location of some high concentrations in areas without contemporary industries. Long-range transboundary transport appears to account for elevated concentrations of heavy metals in areas without emission sources, such as lead in southern Scandinavia (presumably from emission sources elsewhere in Europe).