Comparing Methods to Constrain Future European Climate Projections Using a Consistent Framework

Author:

Brunner Lukas1,McSweeney Carol2,Ballinger Andrew P.3,Befort Daniel J.4,Benassi Marianna5,Booth Ben2,Coppola Erika6,de Vries Hylke7,Harris Glen2,Hegerl Gabriele C.3,Knutti Reto1,Lenderink Geert7,Lowe Jason2,Nogherotto Rita6,O’Reilly Chris4,Qasmi Saïd8,Ribes Aurélien8,Stocchi Paolo6,Undorf Sabine3

Affiliation:

1. a Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland

2. b Met Office Hadley Centre, Exeter, United Kingdom

3. c School of GeoSciences, University of Edinburgh, Edinburgh, United Kingdom

4. d Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, United Kingdom

5. e Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy

6. f The Abdus Salam International Centre for Theoretical Physics, Trieste, Italy

7. g Royal Netherlands Meteorological Institute, De Bilt, Netherlands

8. h CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

Abstract

AbstractPolitical decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. To provide these estimates, different approaches to constrain, filter, or weight climate model projections into probabilistic distributions have been proposed. However, an assessment of multiple such methods to, for example, expose cases of agreement or disagreement, is often hindered by a lack of coordination, with methods focusing on a variety of variables, time periods, regions, or model pools. Here, a consistent framework is developed to allow a quantitative comparison of eight different methods; focus is given to summer temperature and precipitation change in three spatial regimes in Europe in 2041–60 relative to 1995–2014. The analysis draws on projections from several large ensembles, the CMIP5 multimodel ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods’ key features are summarized, assumptions are discussed, and resulting constrained distributions are presented. Method agreement is found to be dependent on the investigated region but is generally higher for median changes than for the uncertainty ranges. This study, therefore, highlights the importance of providing clear context about how different methods affect the assessed uncertainty—in particular, the upper and lower percentiles that are of interest to risk-averse stakeholders. The comparison also exposes cases in which diverse lines of evidence lead to diverging constraints; additional work is needed to understand how the underlying differences between methods lead to such disagreements and to provide clear guidance to users.

Funder

H2020 European Research Council

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference87 articles.

1. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?;Aalbers,2018

2. ESD reviews: Model dependence in multi-model climate ensembles: Weighting, sub-selection and out-of-sample testing;Abramowitz;Earth Syst. Dyn.,2019

3. Checking for model consistency in optimal fingerprinting;Allen;Climate Dyn.,1999

4. Estimating signal amplitudes in optimal fingerprinting, Part I: Theory;Allen;Climate Dyn.,2003

5. Quantifying the uncertainty in forecasts of anthropogenic climate change;Allen;Nature,2000

Cited by 44 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3