Uncertainty Assessment of Future Climate Change Using Bias-Corrected High-Resolution Multi-Regional Climate Model Datasets over East Asia

Abstract

Abstract The quantitative assessment of the uncertainty components of future climate projections is critical for decision-makers and organizations to establish climate change adaptation and mitigation strategies at regional or local scales. This is the first study in which the changes in the uncertainty components of future temperature and precipitation projections are quantitatively evaluated using multiple regional climate models over East Asia, vulnerable to future climate change. For temperature, internal variability and model uncertainty were the main factors affecting the near-term projections. The scenario uncertainty continued to increase and was estimated to be the dominant factor affecting the uncertainty after the mid-term projections. Although precipitation has the same main uncertainty factors as the temperature in the near-term projections, it significantly differs from temperature because the internal variability notably contributes to the fraction to the total variance, even in the long-term projections. The internal variability of the temperature and precipitation in the near-term projections was predicted to be larger in Korea than that in East Asia. This was confirmed by regional climate models as well as previous studies using global climate models as to the importance of internal variability at smaller regional scales during the near-term projections. This study is of significance because it provides new possibilities with respect to the consideration of climate uncertainties to the establishment of climate change policies in more detail on the regional scale.