Conditioning model output statistics of regional climate model precipitation on circulation patterns

F. Wetterhall*, F. Pappenberger, Y. He, J. Freer, H. L. Cloke

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

35 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)623-633
Number of pages11
JournalNonlinear Processes in Geophysics
Volume19
Issue number6
DOIs
Publication statusPublished - 1 Dec 2012

Fingerprint Dive into the research topics of 'Conditioning model output statistics of regional climate model precipitation on circulation patterns'. Together they form a unique fingerprint.

  • Projects

    Cite this