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Regional climate models for hydrological impact studies at the catchment scale: A review of recent modeling strategies
Department of Physical Geography and Quaternary Geology, Stockholm University, Sweden.ORCID iD: 0000-0002-3344-2468
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
2010 (English)In: Geography Compass, Vol. 4, no 7, 834-860 p.Article in journal (Refereed) Published
Abstract [en]

This article reviews recent applications of regional climate model (RCM) output for hydrological impact studies. Traditionally, simulations of global climate models (GCMs) have been the basis of impact studies in hydrology. Progress in regional climate modeling has recently made the use of RCM data more attractive, although the application of RCM simulations is challenging due to often considerable biases. The main modeling strategies used in recent studies can be classified into (i) very simple constructed modeling chains with a single RCM (S-RCM approach) and (ii) highly complex and computing-power intensive model systems based on RCM ensembles (E-RCM approach). In the literature many examples for S-RCM can be found, while comprehensive E-RCM studies with consideration of several sources of uncertainties such as different greenhouse gas emission scenarios, GCMs, RCMs and hydrological models are less common. Based on a case study using control-run simulations of fourteen different RCMs for five Swedish catchments, the biases of and the variability between different RCMs are demonstrated. We provide a short overview of possible bias-correction methods and show that inter-RCM variability also has substantial consequences for hydrological impact studies in addition to other sources of uncertainties in the modeling chain. We propose that due to model bias and inter-model variability, the S-RCM approach is not advised and ensembles of RCM simulations (E-RCM) should be used. The application of bias-correction methods is recommended, although one should also be aware that the need for bias corrections adds significantly to uncertainties in modeling climate change impacts. © 2010 The Authors. Journal Compilation © 2010 Blackwell Publishing Ltd.

Place, publisher, year, edition, pages
2010. Vol. 4, no 7, 834-860 p.
Keyword [en]
catchment, climate change, climate modeling, computer simulation, ensemble forecasting, hydrological change, hydrological modeling, numerical model, regional climate
National Category
Earth and Related Environmental Sciences
URN: urn:nbn:se:uu:diva-143469DOI: 10.1111/j.1749-8198.2010.00357.OAI: oai:DiVA.org:uu-143469DiVA: diva2:390109
Formas, 2007-1433

Source: Scopus

Available from: 2011-01-20 Created: 2011-01-20 Last updated: 2013-12-03

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Publisher's full texthttp://www.scopus.com/inward/record.url?eid=2-s2.0-77956631042&partnerID=40&md5=4892b54dfa2079f5423d4ccd476c8540

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Teutschbein, ClaudiaSeibert, J.
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