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美国六个建模中心的气候模型调优实践与理念

Practice and philosophy of climate model tuning across six U.S. modeling centers.

作者信息

Schmidt Gavin A, Bader David, Donner Leo J, Elsaesser Gregory S, Golaz Jean-Christophe, Hannay Cecile, Molod Andrea, Neale Rich, Saha Suranjana

机构信息

NASA Goddard Institute for Space Studies, 2880 Broadway, New York.

DOE Lawrence Livermore National Laboratory, Livermore, California.

出版信息

Geosci Model Dev. 2017;10(9):3207-3223. doi: 10.5194/gmd-10-3207-2017. Epub 2017 Sep 1.

Abstract

Model calibration (or "tuning") is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major U.S. climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present day radiative imbalance vs. the implied balance in the pre-industrial as a target.

摘要

无论耦合海洋-大气气候模型的主要科学目的是什么,模型校准(或“调优”)都是开发和测试此类模型的必要环节。人们越来越认识到,对于气候模型输出的用户和其他开发者而言,这一过程需要变得更加透明。了解气候模型如何以及为何进行调优,以及使用了哪些目标,对于避免将巧妙的预测错误归因于数据拟合,反之亦然,至关重要。本文描述了美国六个主要气候建模中心的模型调优方法和实践。虽然各团队在科学任务、调优目标和可调参数方面存在细节差异,但在方法上存在核心共性。然而,在一些关键方面,实践差异显著,特别是在将初始化预报分析用作工具、明确使用历史瞬态记录,以及将当前的辐射不平衡与工业化前隐含的平衡作为目标的使用方面。

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本文引用的文献

1
The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2).
J Clim. 2017 Jun 20;Volume 30(Iss 13):5419-5454. doi: 10.1175/JCLI-D-16-0758.1.
3
Changes in global net radiative imbalance 1985-2012.
Geophys Res Lett. 2014 Aug 16;41(15):5588-5597. doi: 10.1002/2014GL060962. Epub 2014 Aug 5.
4
Values and uncertainties in the predictions of global climate models.
Kennedy Inst Ethics J. 2012 Jun;22(2):111-37. doi: 10.1353/ken.2012.0008.
5
Should we believe model predictions of future climate change?
Philos Trans A Math Phys Eng Sci. 2008 Dec 28;366(1885):4647-64. doi: 10.1098/rsta.2008.0169.
7
Earth's energy imbalance: confirmation and implications.
Science. 2005 Jun 3;308(5727):1431-5. doi: 10.1126/science.1110252. Epub 2005 Apr 28.

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