Both black and symbolically white: The 'Bajan-Brit' return migrant as post-colonial hybrid

The research presented in this article centres on an under-researched demographic group of young return migrants, namely, second-generation Barbadians, or 'Bajan-Brits', who have decided to 'return' to the birthplace of their parents. Based on 51 in-depth interviews, the essay examines the experiences of second-generation return migrants from an interpretative perspective framed within post-colonial discourse. The article first considers the Bajan-Brits and issues of race in the UK before their decision to migrate. It is then demonstrated that on 'return', in certain respects, these young, black English migrants occupy a liminal position of cultural, racial and economic privilege, based on their 'symbolic' or 'token' whiteness within the post-colonial context of Barbados. But this very hybridity and inbetweeness means that they also face difficulties and associated feelings of social alienation and discrimination. The ambivalent status of this transnational group of migrants serves to challenge traditional notions of Barbadian racial identity.

Evaluation of two hybrid metric-conceptual models, for simulating phosphorus transfer from agricultural land in the river enborne, a lowland UK catchment

Across Europe, elevated phosphorus (P) concentrations in lowland rivers have made them particularly susceptible to eutrophication. This is compounded in southern and central UK by increasing pressures on water resources, which may be further enhanced by the potential effects of climate change. The EU Water Framework Directive requires an integrated approach to water resources management at the catchment scale and highlights the need for modelling tools that can distinguish relative contributions from multiple nutrient sources and are consistent with the information content of the available data. Two such models are introduced and evaluated within a stochastic framework using daily flow and total phosphorus concentrations recorded in a clay catchment typical of many areas of the lowland UK. Both models disaggregate empirical annual load estimates, derived from land use data, as a function of surface/near surface runoff, generated using a simple conceptual rainfall-runoff model. Estimates of the daily load from agricultural land, together with those from baseflow and point sources, feed into an in-stream routing algorithm. The first model assumes constant concentrations in runoff via surface/near surface pathways and incorporates an additional P store in the river-bed sediments, depleted above a critical discharge, to explicitly simulate resuspension. The second model, which is simpler, simulates P concentrations as a function of surface/near surface runoff, thus emphasising the influence of non-point source loads during flow peaks and mixing of baseflow and point sources during low flows. The temporal consistency of parameter estimates and thus the suitability of each approach is assessed dynamically following a new approach based on Monte-Carlo analysis. (c) 2004 Elsevier B.V. All rights reserved.

Computationally efficient expressions for the collision efficiency between electrically charged aerosol particles and cloud droplets

A multiple factor parametrization is described to permit the efficient calculation of collision efficiency (E) between electrically charged aerosol particles and neutral cloud droplets in numerical models of cloud and climate. The four-parameter representation summarizes the results obtained from a detailed microphysical model of E, which accounts for the different forces acting on the aerosol in the path of falling cloud droplets. The parametrization's range of validity is for aerosol particle radii of 0.4 to 10 mu m, aerosol particle densities of I to 2.0 g cm(-3), aerosol particle charges from neutral to 100 elementary charges and drop radii from 18.55 to 142 mu m. The parametrization yields values of E well within an order of magnitude of the detailed model's values, from a dataset of 3978 E values. Of these values 95% have modelled to parametrized ratios between 0.5 and 1.5 for aerosol particle sizes ranging between 0.4 and 2.0 mu m, and about 96% in the second size range. This parametrization speeds up the calculation of E by a factor of similar to 10(3) compared with the original microphysical model, permitting the inclusion of electric charge effects in numerical cloud and climate models.

Metrics for solar wind prediction models: Comparison of empirical, hybrid, and physics-based schemes with 8 years of L1 observations

Space weather effects on technological systems originate with energy carried from the Sun to the terrestrial environment by the solar wind. In this study, we present results of modeling of solar corona-heliosphere processes to predict solar wind conditions at the L1 Lagrangian point upstream of Earth. In particular we calculate performance metrics for (1) empirical, (2) hybrid empirical/physics-based, and (3) full physics-based coupled corona-heliosphere models over an 8-year period (1995–2002). L1 measurements of the radial solar wind speed are the primary basis for validation of the coronal and heliosphere models studied, though other solar wind parameters are also considered. The models are from the Center for Integrated Space-Weather Modeling (CISM) which has developed a coupled model of the whole Sun-to-Earth system, from the solar photosphere to the terrestrial thermosphere. Simple point-by-point analysis techniques, such as mean-square-error and correlation coefficients, indicate that the empirical coronal-heliosphere model currently gives the best forecast of solar wind speed at 1 AU. A more detailed analysis shows that errors in the physics-based models are predominately the result of small timing offsets to solar wind structures and that the large-scale features of the solar wind are actually well modeled. We suggest that additional “tuning” of the coupling between the coronal and heliosphere models could lead to a significant improvement of their accuracy. Furthermore, we note that the physics-based models accurately capture dynamic effects at solar wind stream interaction regions, such as magnetic field compression, flow deflection, and density buildup, which the empirical scheme cannot.

Variation of the mixing state of Saharan dust particles with atmospheric transport

Mineral dust is an important aerosol species in the Earth’s atmosphere and has a major source within North Africa, of which the Sahara forms the major part. Aerosol Time of Flight Mass Spectrometry (ATOFMS) is first used to determine the mixing state of dust particles collected from the land surface in the Saharan region, showing low abundance of species such as nitrate and sulphate internally mixed with the dust mineral matrix. These data are then compared with the ATOFMS single particle mass spectra of Saharan dust particles detected in the marine atmosphere in the vicinity of the Cape Verde islands, which are further compared with those from particles with longer atmospheric residence sampled at a coastal station at Mace Head, Ireland. Saharan dust particles collected near the Cape Verde Islands showed increased internally mixed nitrate but no sulphate, whilst Saharan dust particles collected on the coast of Ireland showed a very high degree of internally mixed secondary species including nitrate, sulphate and methanesulphonate. This uptake of secondary species will change the pH and hygroscopic properties of the aerosol dust and thus can influence the budgets of other reactive gases, as well as influencing the radiative properties of the particles and the availability of metals for dissolution.