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19 - Outlook

from Part III - Downscaling in Practice and Outlook

Published online by Cambridge University Press:  27 December 2017

Douglas Maraun
Affiliation:
Karl-Franzens-Universität Graz, Austria
Martin Widmann
Affiliation:
University of Birmingham
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Summary

Now here I am, a fool for sure!

No wiser than I was before:

Master, Doctor's what they call me,

And I've been ten years, already,

Crosswise, arcing, to and fro,

Leading my students by the nose,

And see that we can know – nothing!

(Faust I, 1808, Johann Wolfgang von Goethe)

In Part I of the book, Chapter 5, we discussed that climate science is post-normal,“where the stakes are high, uncertainties large and decisions urgent, and where values are embedded in the way science is done and spoken” (Hulme 2007). This arena has lead to a serious imbalance of fundamental science and application. Delivery of actionable products is requested from scientists and often promised by eager scientists, where in many cases not even credibility has been established.

In fact, a recurrent theme of this book is that projecting regional climate change is indeed, as stated by Hewitson et al. (2014), still a matter of fundamental research. An often-repeated commonplace in statistical downscaling research is that no single method is applicable to all user problems. This vague statement might leave a user frustrated, and browsing through this book, one might get a similar impression. But is it nothing that we have learned, as sometimes claimed? Do we have to give ourselves to magic art, as Faust did? We believe that in many cases robust answers may be given already. In those cases, where more research is needed, a precise list of research questions exists; answering them may bring us a leap forward. The main purpose of this chapter is to summarise these questions.

Initially, let us revisit the key messages from the book. Downscaling is not always meaningless; it may add substantial value, and it may be crucial to provide credible information about regional climate change. Downscaling is highly uncertain if local climate change is dominated by changes in the large-scale circulation. In fact, largescale circulation errors of dynamical models cannot be overcome by any statistical postprocessing and strongly limit the use of downscaling. But downscaling has the potential for added value if circulation errors are moderate, in particular in complex terrain. And we know quite precisely which type of downscaling approach and method is suitable in which situation. In fact, where local feedbacks or small-scale processes are important, dynamical downscaling might be required.

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Publisher: Cambridge University Press
Print publication year: 2018

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  • Outlook
  • Douglas Maraun, Karl-Franzens-Universität Graz, Austria, Martin Widmann, University of Birmingham
  • Book: Statistical Downscaling and Bias Correction for Climate Research
  • Online publication: 27 December 2017
  • Chapter DOI: https://doi.org/10.1017/9781107588783.020
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  • Outlook
  • Douglas Maraun, Karl-Franzens-Universität Graz, Austria, Martin Widmann, University of Birmingham
  • Book: Statistical Downscaling and Bias Correction for Climate Research
  • Online publication: 27 December 2017
  • Chapter DOI: https://doi.org/10.1017/9781107588783.020
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Outlook
  • Douglas Maraun, Karl-Franzens-Universität Graz, Austria, Martin Widmann, University of Birmingham
  • Book: Statistical Downscaling and Bias Correction for Climate Research
  • Online publication: 27 December 2017
  • Chapter DOI: https://doi.org/10.1017/9781107588783.020
Available formats
×