164 resultados para Nancy Swanger

em CentAUR: Central Archive University of Reading - UK


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Data assimilation is a sophisticated mathematical technique for combining observational data with model predictions to produce state and parameter estimates that most accurately approximate the current and future states of the true system. The technique is commonly used in atmospheric and oceanic modelling, combining empirical observations with model predictions to produce more accurate and well-calibrated forecasts. Here, we consider a novel application within a coastal environment and describe how the method can also be used to deliver improved estimates of uncertain morphodynamic model parameters. This is achieved using a technique known as state augmentation. Earlier applications of state augmentation have typically employed the 4D-Var, Kalman filter or ensemble Kalman filter assimilation schemes. Our new method is based on a computationally inexpensive 3D-Var scheme, where the specification of the error covariance matrices is crucial for success. A simple 1D model of bed-form propagation is used to demonstrate the method. The scheme is capable of recovering near-perfect parameter values and, therefore, improves the capability of our model to predict future bathymetry. Such positive results suggest the potential for application to more complex morphodynamic models.

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The Proceedings of the Ninth Annual Conference of the British Association for Biological Anthropology and Osteoarchaeology (BABAO) held at the University of Reading in 2007. Contents: 1) A life course perspective of growing up in medieval London: evidence of sub-adult health from St Mary Spital (London) (Rebecca Redfern and Don Walker); 2) Preservation of non-adult long bones from an almshouse cemetery in the United States dating to the late nineteenth to the early twentieth centuries (Colleen Milligan, Jessica Zotcavage and Norman Sullivan); 3) Childhood oral health: dental palaeopathology of Kellis 2, Dakhleh, Egypt. A preliminary investigation (Stephanie Shukrum and JE Molto); 4) Skeletal manifestation of non-adult scurvy from early medieval Northumbria: the Black Gate cemetery, Newcastle-upon-Tyne (Diana Mahoney-Swales and Pia Nystrom); 5) Infantile cortical hyperostosis: cases, causes and contradictions (Mary Lewis and Rebecca Gowland); 6) Biological Anthropology Tuberculosis of the hip in the Victorian Britain (Benjamin Clarke and Piers Mitchell); 7) The re-analysis of Iron Age human skeletal material from Winnall Down (Justine Tracey); 8) Can we estimate post-mortem interval from an individual body part? A field study using sus scrofa (Branka Franicevec and Robert Pastor); 9) The expression of asymmetry in hand bones from the medieval cemetery at Écija, Spain (Lisa Cashmore and Sonia Zakrezewski); 10) Returning remains: a curator’s view (Quinton Carroll); 11) Authority and decision making over British human remains: issues and challenges (Piotr Bienkowski and Malcolm Chapman); 12) Ethical dimensions of reburial, retention and repatriation of archaeological human remains: a British perspective (Simon Mays and Martin Smith); 13) The problem of provenace: inaccuracies, changes and misconceptions (Margaret Clegg); 14) Native American human remains in UK collections: implications of NAGPRA to consultation, repatriation, and policy development (Myra J Giesen); 15) Repatriation – a view from the receiving end: New Zealand (Nancy Tayles).

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The task of assessing the likelihood and extent of coastal flooding is hampered by the lack of detailed information on near-shore bathymetry. This is required as an input for coastal inundation models, and in some cases the variability in the bathymetry can impact the prediction of those areas likely to be affected by flooding in a storm. The constant monitoring and data collection that would be required to characterise the near-shore bathymetry over large coastal areas is impractical, leaving the option of running morphodynamic models to predict the likely bathymetry at any given time. However, if the models are inaccurate the errors may be significant if incorrect bathymetry is used to predict possible flood risks. This project is assessing the use of data assimilation techniques to improve the predictions from a simple model, by rigorously incorporating observations of the bathymetry into the model, to bring the model closer to the actual situation. Currently we are concentrating on Morecambe Bay as a primary study site, as it has a highly dynamic inter-tidal zone, with changes in the course of channels in this zone impacting the likely locations of flooding from storms. We are working with SAR images, LiDAR, and swath bathymetry to give us the observations over a 2.5 year period running from May 2003 – November 2005. We have a LiDAR image of the entire inter-tidal zone for November 2005 to use as validation data. We have implemented a 3D-Var data assimilation scheme, to investigate the improvements in performance of the data assimilation compared to the previous scheme which was based on the optimal interpolation method. We are currently evaluating these different data assimilation techniques, using 22 SAR data observations. We will also include the LiDAR data and swath bathymetry to improve the observational coverage, and investigate the impact of different types of observation on the predictive ability of the model. We are also assessing the ability of the data assimilation scheme to recover the correct bathymetry after storm events, which can dramatically change the bathymetry in a short period of time.