.png){kind=icon}
返回
Are general circulation models obsolete?
.png){kind=icon}
OA
AI
DOI：10.1073/pnas.2202075119.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Traditional general circulation models, or GCMs-that is, three-dimensional dynamical models with unresolved terms represented in equations with tunable parameters-have been a mainstay of climate research for several decades, and some of the pioneering studies have recently been recognized by a Nobel prize in Physics. Yet, there is considerable debate around their continuing role in the future. Frequently mentioned as limitations of GCMs are the structural error and uncertainty across models with different representations of un-resolved scales and the fact that the models are tuned to reproduce certain aspects of the observed Earth. We consider these shortcomings in the context of a future generation of models that may address these issues through substantially higher resolution and detail, or through the use of machine learning techniques to match them better to observations, theory, and process models. It is our contention that calibration, far from being a weakness of models, is an essential element in the simulation of complex systems, and contributes to our understanding of their inner workings. Models can be calibrated to reveal both fine-scale detail and the global response to external perturbations. New methods enable us to articulate and improve the connections between the different levels of abstract representation of climate processes, and our understanding resides in an entire hierarchy of models where GCMs will continue to play a central role for the foreseeable future.
Keyword:
climate modeling
machine learning
model calibration
model hierarchy
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
P
IF:
9.1
论文数:
10.8W
被引数:
73.5W
机构
引用论文
Using a resolution function to regulate parameterizations of oceanic mesoscale eddy effects使用分辨率函数来调节海洋中尺度涡旋效应的参数化.png)
OCEAN MODELLING
OCEAN MODELLINGIF2.9
PREAI
分享收藏Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6来自CMIP6的情景模型比对项目 (scenaromip) 的气候模型预测
OAAI
OAAI分享收藏Trace elements; copper, zinc and selenium, in breast cancer afflicted female patients in LAUTECH Osogbo, Nigeria微量元素; 尼日利亚LAUTECH Osogbo的女性乳腺癌患者中的铜，锌和硒
PREAI
分享收藏A facile route for the preparation of ZnO/C composites with high photocatalytic activity and adsorption capacityCrystEngComm
CrystEngCommIF0
PREAI
分享收藏
查看更多内容