NPG Nonlinear Processes in Geophysics NPG Nonlin. Processes Geophys. 1607-7946 Copernicus Publications Göttingen, Germany 10.5194/npg-19-623-2012 Conditioning model output statistics of regional climate model precipitation on circulation patterns Wetterhall F. 1 2 Pappenberger F. 1 3 He Y. 4 Freer J. 5 Cloke H. L. 1 6 European Centre for Medium Range Weather Forecasts, Reading, UK Department of Geography, King's College London, London, UK Hohai University, Nanjing, China Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, UK School of Geographical Sciences, University of Bristol, UK Department of Geography & Environmental Science and Department of Meteorology, University of Reading, UK 13 11 2012 19 6 623 633 Copyright: © 2012 F. Wetterhall et al. 2012 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://npg.copernicus.org/articles/19/623/2012/npg-19-623-2012.html The full text article is available as a PDF file from https://npg.copernicus.org/articles/19/623/2012/npg-19-623-2012.pdf

Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potentially improves the usability of the output for hydrological impact studies. However, a further downscaling or interpolation of precipitation from RCMs is often needed to match the precipitation characteristics at the local scale. This study analysed three Model Output Statistics (MOS) techniques to adjust RCM precipitation; (1) a simple direct method (DM), (2) quantile-quantile mapping (QM) and (3) a distribution-based scaling (DBS) approach. The modelled precipitation was daily means from 16 RCMs driven by ERA40 reanalysis data over the 1961–2000 provided by the ENSEMBLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts) project over a small catchment located in the Midlands, UK. All methods were conditioned on the entire time series, separate months and using an objective classification of Lamb's weather types. The performance of the MOS techniques were assessed regarding temporal and spatial characteristics of the precipitation fields, as well as modelled runoff using the HBV rainfall-runoff model. The results indicate that the DBS conditioned on classification patterns performed better than the other methods, however an ensemble approach in terms of both climate models and downscaling methods is recommended to account for uncertainties in the MOS methods.

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