Introduction to Climate Change Scenario Derived by Statistical Downscaling

Toshichika Iizumi, Motoki Nishimori, Yasushi Ishigooka, Masayuki Yokozawa

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


This article outlined the statistical downscaling methods (SDMs) and how they derive climatic inputs for the impact models (referred to as the climate change scenario) from the outputs of dynamic global/regional climate models. To help select an appropriate method from various SDMs, the authors categorizes the SDMs into four functional categories, i.e. (1) temporal disaggregation, (2) spatial disaggregation, (3) estimation of elements not directly supplied by climate models, and (4) bias correction, and referred to some anecdotal studies of each category. In addition, a practical example of the generation of climate change scenario at a site was demonstrated to provide a concrete image for researchers trying to use SDMs. This introductory guide will help select an appropriate SDM to fill the gap between accessible climate model outputs and the requirements of impact studies.

Original languageEnglish
Pages (from-to)131-143
Number of pages13
Journaljournal of agricultural meteorology
Issue number2
Publication statusPublished - 2010 Sept 1
Externally publishedYes


  • Bias correction
  • Climate change scenario
  • Climate model output
  • Statistical downscaling

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Atmospheric Science


Dive into the research topics of 'Introduction to Climate Change Scenario Derived by Statistical Downscaling'. Together they form a unique fingerprint.

Cite this