A Bayesian approach for multi-model downscaling: Seasonal forecasting of regional rainfall and river flows in South America

This study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean-atmosphere climate models. It examines the feasibility Of using a Bayesian procedure for producing combined, well-calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow forecasts for the Parana river in the south of Brazil and the Tocantins river in the north of Brazil. These forecasts are important for national electricity generation management and planning. A Bayesian procedure, referred to here as forecast assimilation, is used to combine and calibrate the rainfall predictions produced by three climate models. Forecast assimilation is able to improve the skill of 3-month lead November-December-January multi-model rainfall predictions over the two South American regions. Improvements are noted in forecast seasonal mean values and uncertainty estimates. River flow forecasts are less skilful than rainfall forecasts. This is partially because natural river flow is a derived quantity that is sensitive to hydrological as well as meteorological processes, and to human intervention in the form of reservoir management.

Characterisation of soils containing naturally occurring radioactive material (NORM) using in situ and rapid laboratory techniques. Case study: South Terras, Cornwall

In situ analysis has become increasingly important for contaminated land investigation and remediation. At present, portable techniques are used mainly as scanning tools to assess the spread and magnitude of the contamination, and are an adjunct to conventional laboratory analyses. A site in Cornwall, containing naturally occurring radioactive material (NORM), provided an opportunity for Reading University PhD student Anna Kutner to compare analytical data collected in situ with data generated by laboratory-based methods. The preliminary results in this paper extend the author‟s poster presentation at last September‟s GeoSpec2010 conference held in Lancaster.

Animal disease and the limits of local knowledge: dealing with ticks and tick-borne diseases in South Africa

Some proponents of local knowledge, such as Sillitoe (2010), have expressed second thoughts about its capacity to effect development on the ‘revolutionary’ scale once predicted. Our argument in this article follows a similar route. Recent research into the management of livestock in South Africa makes clear that rural African livestock farmers experience uncertainty in relation to the control of stock diseases. State provision of veterinary services has been significantly reduced over the past decade. Both white and African livestock owners are to a greater extent left to their own devices. In some areas of animal disease management, African livestock owners have recourse to tried-and-tested local remedies, which are largely plant-based. But especially in the critical sphere of tick control, efficacious treatments are less evident, and livestock owners struggle to find adequate solutions to high tickloads. This is particularly important in South Africa in the early twenty-first century because land reform and the freedom to purchase land in the post-apartheid context affords African stockowners opportunities to expand livestock holdings. Our research suggests that the limits of local knowledge in dealing with ticks is one of the central problems faced by African livestock owners. We judge this not only in relation to efficacy but also the perceptions of livestock owners themselves. While confidence and practice varies, and there is increasing resort of chemical acaricides we were struck by the uncertainty of livestock owners over the best strategies.