DATE2018-05-17 09:20:07
AUTHORSA Bruggeman (1), G Zittis (1), U Ulbrich (2), HW Rust (2), E Meredith (2), KA Kpogo-Nuwoklo (2)
  1. The Cyprus Institute, Nicosia, Cyprus
  2. Institute for Meteorology, Freie Universität, Berlin, Germany
ABSTRACTThe H2020 project BINGO aims to provide knowledge and tools to end users affected by near-future climate variations, i.e. water managers, decision and policy-makers, etc., so that they can better plan for regional changes in the hydrological cycle and develop adaptation strategies for climate-change-related challenges, such as a changed risk of drought and floods. The BINGO project includes three research catchments in the Mediterranean region – two in Iberia and one in Cyprus – for which improved and downscaled climate variables, based on the present and near-future are produced. The time horizon of main interest is from the present out to 2024, though climate scenarios are also considered. A key aspect of the BINGO project is a strong interaction between hydrological modellers and stakeholders at the different catchments. Here we present an overview of the BINGO project, focusing on the climate services required by hydrologists and other stakeholders for flood/drought management, and the methodologies employed by BINGO to generate the necessary data. In particular, hydrologists benefit greatly from high-resolution climate data O(1 km) to model their catchments, though such data are rarely available, either due to the computational expense associated with running climate simulations at such high resolution, or insufficiently dense observational networks. To overcome this problem, BINGO adopts a two-pronged approach based on (1) targeted high-resolution dynamical downscaling of episodes with an increased likelihood of extreme precipitation; and (2) conditional stochastic weather generators, which inexpensively produce large ensembles of spatio-temporal forcing data. The first approach relies on the identification of characteristic "extremal" weather patterns for the relevant catchment, while the latter involves the setting-up of a weather generator which realistically simulates relevant variables for the recent climate at the catchment, before applying it to the future period. The overarching goal is to provide better estimates of potential extreme event intensities and probabilities at the research catchments. Our overview of the BINGO project will be illustrated with specific examples and outcomes from our three Mediterranean catchments.