Sources of sulphur in gypsiferous sediments and crusts and pathways of gypsum redistribution in southern Tunisia

Southern Tunisia contains one of the most extensive gypsum accumulations in Africa comprising Triassic, Cretaceous, Eocene and Mio-Pliocene marine evaporites, spring deposits, playa sediments, aeolian sands and gypsum crusts. Sulphur isotope analysis (delta(34)S) of bedrock samples, groundwater, playa brines, playa sediments, and gypsiferous crusts provides insight into the sources of gypsum in the region and sheds light on the processes that lead to gypsum crust formation. Results Suggest that recycling of marine gypsum is the most likely source of the sulphate in the groundwater, playa sediments and crusts. The low PS values found in Eocene and Mio-Pliocene samples suggest that this recycling has been going on for millions of years. Though bedrock appears to be the ultimate source of the gypsum in the crusts, transport of this sulphate to playas, concentration therein, and subsequent dispersal across the landscape by aeolian processes provides the most likely pathway for surticial gypsum crust formation. Comparison of these results with those from Australia, Chile and Namibia suggests that, although the source of the sulphur varies from region to region, the processes of surficial crust formation appear to be similar. Copyright (C) 2004 John Wiley Sons, Ltd.

The TIGGE project and its achievements

TIGGE was a major component of the THORPEX (The Observing System Research and Predictability Experiment) research program, whose aim is to accelerate improvements in forecasting high-impact weather. By providing ensemble prediction data from leading operational forecast centers, TIGGE has enhanced collaboration between the research and operational meteorological communities and enabled research studies on a wide range of topics. The paper covers the objective evaluation of the TIGGE data. For a range of forecast parameters, it is shown to be beneficial to combine ensembles from several data providers in a Multi-model Grand Ensemble. Alternative methods to correct systematic errors, including the use of reforecast data, are also discussed. TIGGE data have been used for a range of research studies on predictability and dynamical processes. Tropical cyclones are the most destructive weather systems in the world, and are a focus of multi-model ensemble research. Their extra-tropical transition also has a major impact on skill of mid-latitude forecasts. We also review how TIGGE has added to our understanding of the dynamics of extra-tropical cyclones and storm tracks. Although TIGGE is a research project, it has proved invaluable for the development of products for future operational forecasting. Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles. Finally the paper considers the legacy of TIGGE. We discuss the priorities and key issues in predictability and ensemble forecasting, including the new opportunities of convective-scale ensembles, links with ensemble data assimilation methods, and extension of the range of useful forecast skill.