DASH: a MATLAB toolbox for paleoclimate data assimilation

IF 4 3区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

Geoscientific Model Development Pub Date : 2023-10-12 DOI:10.5194/gmd-16-5653-2023

Jonathan King, Jessica Tierney, Matthew Osman, Emily J. Judd, Kevin J. Anchukaitis

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引用次数: 1

Abstract

Abstract. Paleoclimate data assimilation (DA) is a tool for reconstructing past climates that directly integrates proxy records with climate model output. Despite the potential for DA to expand the scope of quantitative paleoclimatology, these methods remain difficult to implement in practice due to the multi-faceted requirements and data handling necessary for DA reconstructions, the diversity of DA methods, and the need for computationally efficient algorithms. Here, we present DASH, a MATLAB toolbox designed to facilitate paleoclimate DA analyses. DASH provides command line and scripting tools that implement common tasks in DA workflows. The toolbox is highly modular and is not built around any specific analysis, and thus DASH supports paleoclimate DA for a wide variety of time periods, spatial regions, proxy networks, and algorithms. DASH includes tools for integrating and cataloguing data stored in disparate formats, building state vector ensembles, and running proxy (system) forward models. The toolbox also provides optimized algorithms for implementing ensemble Kalman filters, particle filters, and optimal sensor analyses with variable and modular parameters. This paper reviews the key components of the DASH toolbox and presents examples illustrating DASH's use for paleoclimate DA applications.

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一个用于古气候数据同化的MATLAB工具箱

摘要古气候资料同化(DA)是一种重建过去气候的工具，它直接将代理记录与气候模式输出相结合。尽管数据分析有可能扩大定量古气候学的范围，但由于数据分析重建所需的多方面要求和数据处理、数据分析方法的多样性以及对计算效率高的算法的需求，这些方法在实践中仍然难以实施。在这里，我们介绍DASH，一个MATLAB工具箱，旨在促进古气候数据分析。DASH提供命令行和脚本工具来实现DA工作流中的常见任务。工具箱是高度模块化的，不是围绕任何特定的分析而构建的，因此DASH支持各种时间段、空间区域、代理网络和算法的古气候数据分析。DASH包括用于集成和编目以不同格式存储的数据、构建状态向量集成和运行代理(系统)前向模型的工具。工具箱还提供了优化算法，用于实现集成卡尔曼滤波器，粒子滤波器，以及具有变量和模块化参数的最佳传感器分析。本文回顾了DASH工具箱的主要组成部分，并举例说明了DASH在古气候数据处理中的应用。

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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来源期刊

Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-

CiteScore

8.60

自引率

9.80%

发文量

352

审稿时长

6-12 weeks

期刊介绍： Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.