展望美国气候预测和预报,迎接新挑战

IF 7.3 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Earths Future Pub Date : 2024-06-26 DOI:10.1029/2023EF004187
Annarita Mariotti, David C. Bader, Susanne E. Bauer, Gokhan Danabasoglu, John Dunne, Brian Gross, L. Ruby Leung, Steven Pawson, William R. Putman, Venkatachalam Ramaswamy, Gavin A. Schmidt, Vijay Tallapragada
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引用次数: 0

摘要

面对不断变化的气候,对自然和人类系统的了解、预测和预报对于防备和应对极端天气和连环灾害、确定意外反馈和潜在临界点、为长期适应战略提供信息以及指导减缓气候变化的方法越来越重要。日益复杂的社会经济系统需要更强的预测信息来支持先进的实践。这些新的预测挑战促使我们必须充分利用雄心勃勃的科技机遇。这些机遇包括:对全球到地方的地球系统过程进行跨时间尺度的高分辨率建模、减少模型偏差、加强人类系统与地球系统的整合、更好地量化可预测性和不确定性、加快从科学到服务的途径,以及与利益相关者共同制作可操作的信息等尚未实现的潜力。有利的技术机遇包括超大规模计算、先进的数据存储、新型观测和强大的数据分析,包括人工智能和机器学习。美国联邦政府资助的建模团体的代表们希望就如何加快美国气候预测和预报的进展进行社区讨论,他们在此概述了以气候科学为基础的六大支柱国家方法的观点,该方法建立在美国建模团体的优势和机构目标的基础之上。这需要前所未有的协调水平,以利用变革机会,增强和补充当前建模中心的能力和计划,支持机构的任务。具体成果包括:水平空间分辨率超过 10 千米的预测,更详细地反映极端情况和相关风险,减少模型误差,更好地估计可预测性,以及更多支持下一代气候服务的定制预测。
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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Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways, and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.

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来源期刊
Earths Future
Earths Future ENVIRONMENTAL SCIENCESGEOSCIENCES, MULTIDI-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
11.00
自引率
7.30%
发文量
260
审稿时长
16 weeks
期刊介绍: Earth’s Future: A transdisciplinary open access journal, Earth’s Future focuses on the state of the Earth and the prediction of the planet’s future. By publishing peer-reviewed articles as well as editorials, essays, reviews, and commentaries, this journal will be the preeminent scholarly resource on the Anthropocene. It will also help assess the risks and opportunities associated with environmental changes and challenges.
期刊最新文献
Issue Information Projected Increasing Negative Impact of Extreme Events on Gross Primary Productivity During the 21st Century in CMIP6 Models Quantifying Global Wetland Methane Emissions With In Situ Methane Flux Data and Machine Learning Approaches Integrating Values to Improve the Relevance of Climate-Risk Research Blue Carbon Assessment in the Salt Marshes of the Venice Lagoon: Dimensions, Variability and Influence of Storm-Surge Regulation
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