Browsing by Author "Bellerby, Tim"

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    Hydrological modelling using data from monthly GCMs in a regional catchment
    (Wiley, 2013-05-30) Remesan, Renji; Bellerby, Tim; Frostick, Lynne
    This study demonstrates the use of spatially downscaled, monthly general circulation model (GCM) rainfall and temperature data to drive the established HyMOD hydrological model to evaluate the prospective effects of climate change on the fluvial run-off of the River Derwent basin in the UK. The evaluation results of this monthly hydrological model using readily available, monthly GCM data are consistent with studies on nearby catchments employing high-temporal resolution data, indicating that useful hydro-climatic planning studies may be possible using standard datasets and modest computational resources. HyMOD was calibrated against 5 km2 gridded UK Climate Projections dataset data and then driven using monthly spatially interpolated (~5 km2) outputs from Hadley Centre Coupled Model, version 3 and the Canadian Centre for Climate Modelling and Analysis for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A2a and B2a covering the 2020s, 2050s and 2080s. Results for both GCMs project a decrease in annual run-off in both GCM models and scenarios with higher values in the summer/autumn months, whereas an increase in the later winter months. Both Hadley Centre Coupled Model, version 3 and the Canadian Centre for Climate Modelling and Analysis show higher ranges of uncertainty during the winter season with higher values of run-off associated with December in all three simulation periods and two scenarios. A seasonal comparison of run-off simulations shows that both GCMs give similar results in summer and autumn, whereas disparities due to GCM uncertainties are more conspicuous in winter and spring. In this study, both the GCMs under A2a scenario have demonstrated the high possibility of time shift in monthly average peak run-offs in the Derwent River by 2080s in comparison with the early 21st century.
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    WRF model sensitivity to choice of parameterization: a study of the ‘York Flood 1999’
    (Springer, 2014-10-11) Remesan, Renji; Bellerby, Tim; Holman, Ian P.; Frostick, Lynne
    Numerical weather modelling has gained considerable attention in the field of hydrology especially in un-gauged catchments and in conjunction with distributed models. As a consequence, the accuracy with which these models represent precipitation, sub-grid-scale processes and exceptional events has become of considerable concern to the hydrological community. This paper presents sensitivity analyses for the Weather Research Forecast (WRF) model with respect to the choice of physical parameterization schemes (both cumulus parameterisation (CPSs) and microphysics parameterization schemes (MPSs)) used to represent the ‘1999 York Flood’ event, which occurred over North Yorkshire, UK, 1st–14th March 1999. The study assessed four CPSs (Kain–Fritsch (KF2), Betts–Miller–Janjic (BMJ), Grell–Devenyi ensemble (GD) and the old Kain–Fritsch (KF1)) and four MPSs (Kessler, Lin et al., WRF single-moment 3-class (WSM3) and WRF single-moment 5-class (WSM5)] with respect to their influence on modelled rainfall. The study suggests that the BMJ scheme may be a better cumulus parameterization choice for the study region, giving a consistently better performance than other three CPSs, though there are suggestions of underestimation. The WSM3 was identified as the best MPSs and a combined WSM3/BMJ model setup produced realistic estimates of precipitation quantities for this exceptional flood event. This study analysed spatial variability in WRF performance through categorical indices, including POD, FBI, FAR and CSI during York Flood 1999 under various model settings. Moreover, the WRF model was good at predicting high-intensity rare events over the Yorkshire region, suggesting it has potential for operational use.