World Library  
Flag as Inappropriate
Email this Article


Article Id: WHEBN0007637953
Reproduction Date:

Title: Downscaling  
Author: World Heritage Encyclopedia
Language: English
Subject: NFL Network, Regression-kriging, Numerical climate and weather models, Drought Research Initiative, Hallmark Movies & Mysteries
Publisher: World Heritage Encyclopedia


Global Climate Models (GCMs) used for climate studies and climate projections are run at coarse spatial resolution (in 2012, typically of the order 50 kilometres (31 mi)) and are unable to resolve important sub-grid scale features such as clouds and topography. As a result, GCM output can not be used for local impact studies.

To overcome this problem downscaling methods are developed to obtain local-scale weather and climate, particularly at the surface level, from regional-scale atmospheric variables that are provided by GCMs. Two main forms of downscaling technique exist. One form is dynamical downscaling, where output from the GCM is used to drive a regional, numerical model in higher spatial resolution, which therefore is able to simulate local conditions in greater detail. The other form is statistical downscaling, where a statistical relationship is established from observations between large scale variables, like atmospheric surface pressure, and a local variable, like the wind speed at a particular site. The relationship is then subsequently used on the GCM data to obtain the local variables from the GCM output.

In 1997, Wilby and Wigley divided downscaling into four categories: regression methods, weather pattern-based approaches, stochastic weather generators, which are all statistical downscaling methods, and limited-area modeling. Among these approaches regression methods are preferred because of its ease of implementation and low computation requirements.

Climate downscaling projections

In 2007 Reclamation collaborated with U.S. Department of Energy’s National Energy Technology Laboratory (DOE NETL), Santa Clara University (SCU), Lawrence Livermore National Laboratory (LLNL), and University of California’s Institute for Research on Climate Change and Its Societal Impacts (IRCCSI) to apply a proven technique called “Bias Correction Spatial Disaggregation” BCSD—Wood et al., 2004; see also “About on the Web site” to 112 contemporary global climate projections made available through the World Climate Research Program Couple Model Intercomparison Project, Phase 3 (WCRP CMIP3). These projections represent 16 GCMs simulating climate responses to three GHG scenarios from multiple initial climate system conditions.

The effort resulted in development of 112 monthly temperature and precipitation projections over the continental U.S. at 1/8° (12 kilometres (7.5 mi)) spatial resolution during a 1950–2099 climate simulation period.


In technology terms, downscaling means to bring down something, usually referring to the resolution. Downscaling would be a 1920x1080 monitor rendering 1280x720 graphics on screen. It usually increases performance (evident in video games) due to reducing the amount of pixels being displayed on screen. It is not recommended to do so unless performance is a key factor in a program.


  • Hessami, M., Quarda, T.B.M.J., Gachon, P., St-Hailaire, A., Selva, F. and Bobee, B., “Evaluation of statistical downscaling method over several regions of eastern Canada”, 57th Canadian water resources association annual congress, 2004.
  • Kim, J.W., Chang, J.T., Baker, N.L., Wilks, D.S., Gates, W.L., 1984. The statistical problem of climate inversion: determination of the relationship between local and large-scale climate. Monthly Weather Review 112, 2069–2077.
  • Maraun, D., Wetterhall, F., Ireson, A.M., Chandler, R.E., Kendon, E.J., Widmann, M., Brienen, S., Rust, H.W., Sauter, T., Themessl, M., Venema V.K.C., Chun, K.P., Goodess, C.M., Jones, R.G., Onof C., Vrac M. and Thiele-Eich, I., "Precipitation Downscaling under climate change. Recent developments to bridge the gap between dynamical models and the end user", Rev. Geophys. 48, RG3003, 2010.
  • von Storch, H., Zorita, E., Cubasch, U., 1993. Downscaling of global climate change estimates to regional scales: an application to Iberian rainfall in wintertime. Journal of Climate 6, 1161–1171.
  • Wilby, R.L. and Wigley, T.M.L., (1997) Downscaling general circulation model output: a review of methods and limitations, Progress in Physical Geography, 21, 530–548.
  • Wilby, R.L., Dawson, C.W. and Barrow E.M., (2002) SDSM - a decision support tool for the assessment of regional climate change impacts, Environmental Modelling & Software, 17, 147– 159.
  • Wood, A. W., Leung, L. 5 R., Sridhar, V., and Lettenmaier, D. P.: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs, Climatic Change, 62, 189–216, 2004.
  • Reclamation et al. “Bias Correction and Downscaled WCRP CMIP3 Climate and Hydrology Projections”
  • Xu, Z. and Z.-L. Yang, (2012) An Improved Dynamical Downscaling Method with GCM Bias Corrections and Its Validation with 30 Years of Climate Simulations. J. Climate, 25, 6271–6286.
  • Xu, Z. and Z.-L. Yang, (2015) A new dynamical downscaling approach with GCM bias corrections and spectral nudging. J. Geophys. Res. Atmos., doi:10.1002/2014JD022958
This article was sourced from Creative Commons Attribution-ShareAlike License; additional terms may apply. World Heritage Encyclopedia content is assembled from numerous content providers, Open Access Publishing, and in compliance with The Fair Access to Science and Technology Research Act (FASTR), Wikimedia Foundation, Inc., Public Library of Science, The Encyclopedia of Life, Open Book Publishers (OBP), PubMed, U.S. National Library of Medicine, National Center for Biotechnology Information, U.S. National Library of Medicine, National Institutes of Health (NIH), U.S. Department of Health & Human Services, and, which sources content from all federal, state, local, tribal, and territorial government publication portals (.gov, .mil, .edu). Funding for and content contributors is made possible from the U.S. Congress, E-Government Act of 2002.
Crowd sourced content that is contributed to World Heritage Encyclopedia is peer reviewed and edited by our editorial staff to ensure quality scholarly research articles.
By using this site, you agree to the Terms of Use and Privacy Policy. World Heritage Encyclopedia™ is a registered trademark of the World Public Library Association, a non-profit organization.

Copyright © World Library Foundation. All rights reserved. eBooks from Project Gutenberg are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.