Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017GL076101 |
Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations | |
Schneider, Tapio1,2; Lan, Shiwei1; Stuart, Andrew1; Teixeira, Joao2 | |
2017-12-28 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS
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ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2017 |
卷号 | 44期号:24 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it. |
英文关键词 | Earth system models parameterizations data assimilation machine learning Kalman inversion Markov chain Monte Carlo |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000422954700016 |
WOS关键词 | LARGE-EDDY SIMULATION ; RESOLVING CONVECTION PARAMETERIZATION ; NUMERICAL WEATHER PREDICTION ; GENERAL-CIRCULATION MODELS ; ENSEMBLE KALMAN FILTER ; LOW-CLOUD COVER ; DATA ASSIMILATION ; PART I ; BOUNDARY-LAYER ; DOUBLE-ITCZ |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/27083 |
专题 | 气候变化 |
作者单位 | 1.CALTECH, Pasadena, CA 91125 USA; 2.CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA |
推荐引用方式 GB/T 7714 | Schneider, Tapio,Lan, Shiwei,Stuart, Andrew,et al. Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations[J]. GEOPHYSICAL RESEARCH LETTERS,2017,44(24). |
APA | Schneider, Tapio,Lan, Shiwei,Stuart, Andrew,&Teixeira, Joao.(2017).Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations.GEOPHYSICAL RESEARCH LETTERS,44(24). |
MLA | Schneider, Tapio,et al."Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations".GEOPHYSICAL RESEARCH LETTERS 44.24(2017). |
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