HR: 14:25h
AN: GC23B-04    [Abstracts]
TI: Robustness of Future Changes in Local Precipitation Extremes
AU: * Kennett, E J
EM: elizabeth.kennett@metoffice.gov.uk
AF: UK Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, United Kingdom
AU: Rowell, D P
EM: dave.rowell@metoffice.gov.uk
AF: UK Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, United Kingdom
AU: Jones, R G
EM: richard.jones@metoffice.gov.uk
AF: UK Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, United Kingdom
AU: Buonomo, E
EM: erasmo.buonomo@metoffice.gov.uk
AF: UK Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, United Kingdom
AB: Reliable projections of future changes in local precipitation extremes are essential for informing policy decisions regarding mitigation and adaptation to climate change. In this study, we examine the extent to which natural climate variability affects our ability to project the anthropogenically forced component of change in daily precipitation extremes at the local scale. The work uses a three-member ensemble of the Hadley Centre Regional Climate Model HadRM3H and applies a statistical framework to estimate uncertainty due to natural variability on all timescales from daily to multi-decadal. We show that climate noise significantly impacts on our ability to measure robust signals of extreme precipitation change across Europe. In particular, extreme precipitation changes at the grid box level are found to be discernible above climate noise over much of northern and central Europe in winter, but over less than half of Europe in summer. In addition, the ability to quantify the change to within reasonable bounds is largely limited to isolated local regions in northern Europe. In general, where climate noise has a significant component varying on decadal timescales, single 30 year climate change projections are insufficient to infer changes in the extreme tail of the underlying precipitation distribution. Also generally on moving to finer spatial scales and when considering more extreme events, natural variability increases and it becomes increasingly difficult to discern an underlying change. In this context, we demonstrate the need for ensembles of integrations and explore the relative effectiveness of spatial pooling and averaging for generating robust signals of extreme precipitation change. We anticipate that the key conclusions for the HadRM3H climate projection will apply qualitatively to other models and forcing scenarios.
DE: 1630 Impacts of global change (1225)
DE: 1637 Regional climate change
DE: 1833 Hydroclimatology
DE: 3337 Global climate models (1626, 4928)
DE: 3355 Regional modeling
SC: Global Environmental Change [GC]
MN: 2007 Fall Meeting