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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/17684

Title: The Statistical Downscaling Model - Decision Centric (SDSM-DC): conceptual basis and applications
Authors: Wilby, Robert L.
Dawson, Christian W.
Murphy, Conor
O'Connor, P.
Hawkins, E.
Keywords: Downscaling
Climate scenario
Weather generator
Stress test
Data reconstruction
Issue Date: 2014
Publisher: © Inter-Research
Citation: WILBY, R.L. ... et al, 2014. The Statistical Downscaling Model - Decision Centric (SDSM-DC): conceptual basis and applications. Climate Research, 61 (3), pp. 259 - 276.
Abstract: Regional climate downscaling has arrived at an important juncture. Some in the research community favour continued refinement and evaluation of downscaling techniques within a broader framework of uncertainty characterisation and reduction. Others are calling for smarter use of downscaling tools, accepting that conventional, scenario-led strategies for adaptation planning have limited utility in practice. This paper sets out the rationale and new functionality of the Decision Centric (DC) version of the Statistical DownScaling Model (SDSM-DC). This tool enables synthesis of plausible daily weather series, exotic variables (such as tidal surge), and climate change scenarios guided, not determined, by climate model output. Two worked examples are presented. The first shows how SDSM-DC can be used to reconstruct and in-fill missing records based on calibrated predictor-predictand relationships. Daily temperature and precipitation series from sites in Africa, Asia and North America are deliberately degraded to show that SDSM-DC can reconstitute lost data. The second demonstrates the application of the new scenario generator for stress testing a specific adaptation decision. SDSM-DC is used to generate daily precipitation scenarios to simulate winter flooding in the Boyne catchment, Ireland. This sensitivity analysis reveals the conditions under which existing precautionary allowances for climate change might be insufficient. We conclude by discussing the wider implications of the proposed approach and research opportunities presented by the new tool.
Description: This article was published in the journal, Climate Research [© Inter-Research] and the definitive version is available at: http://www.int-res.com/abstracts/cr/v61/n3/p259-276/
Version: Accepted for publication
DOI: 10.3354/cr01254
URI: https://dspace.lboro.ac.uk/2134/17684
Publisher Link: http://dx.doi.org/10.3354/cr01254
ISSN: 0936-577X
Appears in Collections:Published Articles (Geography and Environment)

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