UNCERTAINTIES IN CLIMATE CHANGE IMPACT ASSESSMENT CAUSED BY GCMS, DOWNSCALING TECHNIQUES, AND HYDROLOGIC MODELS

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Other Title
  • GCMs・ダウンスケーリング・水文モデルに起因する温暖化影響評価の不確実性

Abstract

We investigated uncertainties in climate change impact assessment caused by general circulation models (GCMs), downscaling techniques, and hydrologic models. Two GCMs (MRI-CGCM2 and CCSR/NIES/ FRCGC-MIROC) under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 scenario were dynamically downscaled to the Seyhan River Basin in Turkey. The downscaled data covered 10-year present (1990s) and 10-year future (2070s) time-slices and were used as inputs for two hydrologic models: the Simple Biosphere including Urban Canopy (SiBUC) model and the Tank Model. Results are summarized as follows. (1) There were huge uncertainties in the future projections by the GCMs. Therefore, the range of future projections should be shown using results from various GCMs. (2) Since there were huge errors in the dynamically downscaled data, bias-correction was necessary when using such data to assess climate change. (3) Like GCMs, hydrologic models can cause uncertainties. The performance of hydrologic models should be examined using maximum past flood and drought data, or multiple hydrologic models should be used to show the range of projections.

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Details 詳細情報について

  • CRID
    1390001205171311104
  • NII Article ID
    130004044041
  • DOI
    10.2208/prohe.52.373
  • ISSN
    18849172
    09167374
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
    • KAKEN
  • Abstract License Flag
    Disallowed

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