Newcastle University has extensive risk analysis research in the fields of Climate Change adaption and mitigation (e.g., SINATRA: NE/K008781/1; CONVEX: NE/I006680/1) and Geohazards (e.g. Li: NE/L010794/1; Li: NERC COMET), with a long established record of applying modern analytical and modelling approaches (e.g., ITRC: EP/I01344X/1) coupled with high performance computing (e.g., Urban flood modelling using the Cloud: EP/I034351/1; LTURF: EP/J501359/1; iTURF: EP/K003593/1). Much of our work deals directly with managing and analysing ‘Big Data’ to address explicit issues of uncertainty and risk analysis using algorithms that can handle multiple realisations and large samples of complex models.
Climate Change risk research has been underpinned by the strategically vital stochastic weather generator developed by Kilsby [EP/G061254/1]. Flood risk research (EPSRC/NERC and Microsoft Azure funded) uses data intensive GPU and Cloud hydrodynamic models (e.g., CityCAT) to model cities and catchments worldwide (Newcastle, London and Melbourne). Very high resolution RCM runs and new hydrodynamic models are employed to study future changes in heavy rainfall and flash flooding [Fowler: NERC CONVEX NE/I006680/1; NERC SINATRA NE/K008781/1]. Pioneering research by Kilsby for the Willis Research Network and FloodMEMORY [EP/K013661/1] investigates the clustering in time (persistence) and spatial dependence of catastrophic flood events. Our Drought risk analysis uses large scale probabilistic spatial rainfall models in the NERC IMPETUS project [Fowler: NE/L010518/1] to analyse drought in climate model runs. Hydrological Cycle risk analysis employs terabytes of ERS/ENVISAT and CRYOSAT2 data to undertake waveform altimetry over inland waters bodies for ungauged basins [Moore & Berry: ESA Contract 1/6287/11/I-NB; EU FP7 313238], while broad scale climate change over the Himalayan region has been investigated using climate model runs and AVHRR/MODIS EO products [Fowler; IAHS]. In the Cryosphere and Sea Level Change NU plays a leading role in the analysis of terabytes of satellite and GNSS data to study ice sheets, glacier mass balance and sea level rise; GRACE data is used to observe mass transfer using Earth’s time-variable gravity field [Clarke & Moore: NE/F102519/1], global GNSS networks are used to constrain glacial isostatic adjustment and present-day surface mass loading [Clarke: NE/K004085/1; Penna: NE/K005944/1], aerial and satellite optical imagery is employed to derive ice sheet surface elevation change [Mills: NE/K005340/1], and ‘smart dust’ networks of GNSS sensors are used to observe glacier flow and calving [Edwards: NE/J005762/1]. Climate Change research and risk analysis at NU is coordinated by the Centre for Earth Systems Engineering (CESER) and funded via a £1.3M EPSRC Platform Grant [EP/G013403/1]. Kilsby, Fowler and Dawson were extensively cited and have been expert reviewers for the IPCC (5th Assessment and Special Report on Extremes). Dawson was awarded the 2012 Lloyds Science of Risk prize and Fowler a Royal Society Wolfson Award in 2014.
In Geohazard risk research Tsunami models employ multiple GPUs and adaptive grid techniques to allow the rapid modelling of trans-oceanic tsunamis. Multisource remote analysis (spaceborne, aerial, UAV and terrestrial laser scanning) is employed in Slope Instability and Landslide monitoring applied to coastal erosion and engineering infrastructure (e.g. railway embankments) [Mills, Barr & Glendinning: EP/D023726/1] and earthquake impacts [Wilkinson EP/I01778X/1]. Terabytes of geodetic satellite radar data (ERS-1/2, Envisat, Sentinel-1 etc.) and GNSS networks play a key role in Earthquake and Continental Deformation research in the LICS [NE/L010794/1] and COMET [BGS agreement ref: GA/13M/031] projects, as well as Landslide and Ground Subsidence risk analysis [Li: ESRC UBDRC project; ES/L011921/1]. Ecological risk analysis focuses on vegetation dynamics and health via remotely-sensed monitoring, using laser scanning technology to detect drought stress in trees [Gaulton: NE/I01702X/1; NE/K000071/1] and UAV and airborne hyperspectral and thermal imaging for forest health and disease monitoring [Gaulton: Royal Society].
Advanced geospatial data capture, management, analysis and modelling are routinely employed. LTURF [Dawson & James: EP/J501359/1] employs massive heterogeneous sensor networks for real time analysis of cities. Instrumented systems analysis/modelling is further augmented in iTURF where crowd sourced data (e.g., twitter feeds) parameterises in real-time GPU based flood models [Liang & James: EP/K003593/]. Big Data management plays a critical role in risk analysis research; CARIWIG [DfID; CDKN: RSGL-0024H] utilises terabytes of RCM outputs and spatial database technologies for a weather generator of the Caribbean, while the ITRC project [Barr & Kilsby: EP/I01344X/1] has developed a UK national scale spatial database of infrastructure systems. NU’s standing in high performance computing, in particular cloud computing and the use of Big Data, is recognised by its EPSRC CDT in Cloud Computing for Big Data award to the Cloud Innovation Centre, while its Digital Institute provides advanced ‘CAVE’ decision support and visualisation environments.
 Glenis, V., McGough, A., Kutija, V., Kilsby, C. and Woodman, S. (2013) Flood modelling for cities using Cloud computing. J Cloud Computing: Advances, Systems and Applications, 2(1), 7.
Kendon, E., Roberts, N., Fowler, H., Roberts, M., Chan, S., Senior, C. (2014) Heavier summer downpours with climate change revealed by weather forecast resolution model. Nature Climate Change. doi:10.1038/nclimate2258.
Serinaldi F and Kilsby C. (2014). Simulating daily rainfall fields over large areas for collective risk estimation. Journal of Hydrology, 512, 285-302.
King, M., Bingham, R., Moore, P., Whitehouse, P., Bentley, M., Milne, G. (2012). Lower satellite-gravimetry estimates of Antarctic sea-level contribution. Nature 491, 586-589, doi:510.1038/nature11621.
Dawson, R., Dickson, M., Nicholls, R., Hall, J., Walkden, M., Stansby, P., Mokrech, M., Richards, J., Zhou, J., Milligan, J., Jordan, A., Pearson, S., Rees, J., Bates, P., Koukoulas, S., and Watkinson, A. (2009), Integrated analysis of risks of coastal flooding and cliff erosion under scenarios of long term change, Climatic Change, 95:249–288.
Smith, L. and Liang, Q. (2013) Towards a generalised GPU/CPU shallow-flow modelling tool. Computers & Fluids, 88: 334–343.
Liang, Q. (2012) A simplified adaptive Cartesian grid system for solving the 2D shallow water equations. International Journal for Numerical Methods in Fluids, 69(2): 442–458.
Miller, P., Mills, J., Edwards, S., Bryan, P., Marsh, S., Mitchell, H. and Hobbs, P. (2008) A robust surface matching technique for coastal geohazard assessment and management. ISPRS Journal of Photogrammetry and Remote Sensing 2008, 63(5), 529-542.