气候变化领域集成服务门户(CCPortal): Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles

CCPortal

DOI	10.1002/wcc.654
	Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles
	Zumwald M.; Knüsel B.; Baumberger C.; Hirsch Hadorn G.; Bresch D.N.; Knutti R.
发表日期	2020
ISSN	1757-7780
EISSN	1757-7779
英文摘要	In climate science, observational gridded climate datasets that are based on in situ measurements serve as evidence for scientific claims and they are used to both calibrate and evaluate models. However, datasets only represent selected aspects of the real world, so when they are used for a specific purpose they can be a source of uncertainty. Here, we present a framework for understanding this uncertainty of observational datasets which distinguishes three general sources of uncertainty: (1) uncertainty that arises during the generation of the dataset; (2) uncertainty due to biased samples; and (3) uncertainty that arises due to the choice of abstract properties, such as resolution and metric. Based on this framework, we identify four different types of dataset ensembles—parametric, structural, resampling, and property ensembles—as tools to understand and assess uncertainties arising from the use of datasets for a specific purpose. We advocate for a more systematic generation of dataset ensembles by using these sorts of tools. Finally, we discuss the use of dataset ensembles in climate model evaluation. We argue that a more systematic understanding and assessment of dataset uncertainty is needed to allow for a more reliable uncertainty assessment in the context of model evaluation. The more systematic use of such a framework would be beneficial for both scientific reasoning and scientific policy advice based on climate datasets. This article is categorized under:. Paleoclimates and Current Trends > Modern Climate Change. © 2020 The Authors. WIREs Climate Change published by Wiley Periodicals LLC.
英文关键词	climate datasets; dataset ensembles; framework; model evaluation; uncertainty
语种	英语
来源期刊	Wiley Interdisciplinary Reviews: Climate Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/129906
作者单位	Institute for Environmental Decisions, ETH Zürich, Zürich, Switzerland; Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland; Swiss Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
推荐引用方式 GB/T 7714	Zumwald M.,Knüsel B.,Baumberger C.,et al. Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles[J],2020.
APA	Zumwald M.,Knüsel B.,Baumberger C.,Hirsch Hadorn G.,Bresch D.N.,&Knutti R..(2020).Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles.Wiley Interdisciplinary Reviews: Climate Change.
MLA	Zumwald M.,et al."Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles".Wiley Interdisciplinary Reviews: Climate Change (2020).