Introduction to climate change scenario derived by statistical downscaling
Introduction to climate change scenario derived by statistical downscaling
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DOI：
10.2480/agrmet.66.2.5
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发表时间：
2010-06-01
影响因子：
1.3
通讯作者：
Yokozawa, Masayuki
中科院分区：
文献类型：
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作者：
Iizumi, Toshichika;Nishimori, Motoki;Yokozawa, Masayuki
本文概述了统计降尺度方法(SDMS)及其如何从动态全球/区域气候模型的输出中得出影响模型(称为气候变化情景)的气候输入。为了帮助从不同的SDMS中选择合适的方法，作者将SDMS分为四个功能类别，即(1)时间分解，(2)空间分解，(3)估计不直接由气候模式提供的元素，(4)偏差校正，并参考了每一类的一些轶事研究。此外，还展示了一个现场气候变化情景生成的实际例子，为试图使用SDMS的研究人员提供了一个具体的图像。本介绍性指南将帮助选择适当的SDM，以填补可获得的气候模型产出与影响研究要求之间的差距。
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.