The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change

IF 4 3区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Geoscientific Model Development Pub Date : 2023-12-21 DOI:10.5194/gmd-16-7461-2023

R. Kopp, G. Garner, T. Hermans, S. Jha, Praveen Kumar, Alexander Reedy, A. Slangen, M. Turilli, T. Edwards, J. Gregory, George Koubbe, A. Levermann, André Merzky, S. Nowicki, M. Palmer, Christopher J. Smith

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引用次数: 9

Abstract

Abstract. Future sea-level rise projections are characterized by both quantifiable uncertainty and unquantifiable structural uncertainty. Thorough scientific assessment of sea-level rise projections requires analysis of both dimensions of uncertainty. Probabilistic sea-level rise projections evaluate the quantifiable dimension of uncertainty; comparison of alternative probabilistic methods provides an indication of structural uncertainty. Here we describe the Framework for Assessing Changes To Sea-level (FACTS), a modular platform for characterizing different probability distributions for the drivers of sea-level change and their consequences for global mean, regional, and extreme sea-level change. We demonstrate its application by generating seven alternative probability distributions under multiple emissions scenarios for both future global mean sea-level change and future relative and extreme sea-level change at New York City. These distributions, closely aligned with those presented in the Intergovernmental Panel on Climate Change Sixth Assessment Report, emphasize the role of the Antarctic and Greenland ice sheets as drivers of structural uncertainty in sea-level change projections.

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海平面变化评估框架 (FACTS)v1.0：描述未来全球、相对和极端海平面变化的参数和结构不确定性的平台

摘要。未来海平面上升预测具有可量化的不确定性和不可量化的结构不确定性。要对海平面上升预测进行全面的科学评估，就必须对这两方面的不确定性进行分析。海平面上升概率预测评估的是可量化的不确定性；对其他概率方法的比较则表明了结构性的不确定性。在此，我们介绍了海平面变化评估框架（FACTS），这是一个模块化平台，用于描述海平面变化驱动因素的不同概率分布及其对全球平均、区域和极端海平面变化的影响。我们通过在多种排放情景下生成纽约市未来全球平均海平面变化以及未来相对和极端海平面变化的七种备选概率分布来演示其应用。这些分布与政府间气候变化专门委员会第六次评估报告中提出的分布密切相关，强调了南极和格陵兰冰盖作为海平面变化预测结构不确定性驱动因素的作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-

CiteScore

8.60

自引率

9.80%

发文量

352

审稿时长

6-12 weeks

期刊介绍： Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.