.png){kind=icon}
返回
Rewiring climate modeling with machine learning emulators
.png){kind=icon}
OA
AI
DOI：10.1038/s43247-026-03238-z.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Earth system models, or simulators, are foundational for projecting climate change impacts, but their computational expense limits the number and diversity of simulations available. Machine learning-based emulators, statistical surrogates trained on simulator outputs, can replicate components of climate models at orders-of-magnitude lower cost, enabling ensembles and interpolation across scenarios. We argue that the next phase of climate modeling hinges on closer collaboration between simulator and emulator communities. We outline three priorities: (1) co-design of simulators and emulators so that experimental design, diagnostics, and data products support training, evaluation, and targeted simulation; (2) shared, machine learning-ready benchmarks with data partitions and metrics that emphasize physical fidelity; and (3) treating emulators as reliable software components with interfaces, documentation, and deployment pathways for sensitivity analyses, scenario exploration, and uncertainty decomposition. This perspective envisions emulators not as statistical shortcuts, but core tools that accelerate the pace of climate science. This Perspective argues that machine learning emulators could transform climate modeling by co-designing with simulators, aligning goals, data, and diagnostics, and building shared infrastructure and robust software to accelerate science.
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
8.9
论文数:
905
被引数:
0
机构
引用论文
.png){kind=icon}
分享收藏Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization耦合模型比对项目第六阶段 (CMIP6) 实验设计和组织概述OAAI
OAAI分享收藏Surrogate modeling for the climate sciences dynamics with machine learning and data assimilation
OAAI
OAAI分享收藏分享收藏The Impact of Internal Variability on Benchmarking Deep Learning Climate Emulators内部变异性对基准测试深度学习气候模拟器的影响OAAI
OAAI分享收藏
查看更多内容