计算气候科学和天气预报中基于olr的madden - julian振荡(OMI)指数的Python包

Q1 Social Sciences Journal of Open Research Software Pub Date : 2021-05-14 DOI:10.5334/JORS.331
C. Hoffmann, G. Kiladis, M. Gehne, C. von Savigny
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引用次数: 7

摘要

麦登-朱利安振荡(MJO)是大气季节内变化的一个突出特征。MJO强烈调节热带降水,并对全球天气、气候和基础大气研究产生影响。MJO的时间依赖状态由MJO指数描述,MJO指数是通过有时复杂的统计方法从气象变量中计算出来的。其中一个指数是基于OLR的MJO指数(OMI;OLR代表输出长波辐射)。据我们所知,本文中描述的Python包mjoindices提供了OMI算法的第一个开源实现。该软件包符合可持续研究软件的最先进标准,如自动测试和持久存档,以帮助科学结果的再现性。此处还总结了使用该软件包计算的OMI值与原始OMI值的一致性。有几种重用场景;最有可能的是基于大气模型的MJO相关研究,因为每次模型运行都必须重新计算指标值。
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A Python Package to Calculate the OLR-Based Index of the Madden-Julian-Oscillation (OMI) in Climate Science and Weather Forecasting
The Madden-Julian Oscillation (MJO) is a prominent feature of the intraseasonal variability of the atmosphere. The MJO strongly modulates tropical precipitation and has implications around the globe for weather, climate and basic atmospheric research. The time-dependent state of the MJO is described by MJO indices, which are calculated through sometimes complicated statistical approaches from meteorological variables. One of these indices is the OLR-based MJO Index (OMI; OLR stands for outgoing longwave radiation). The Python package mjoindices, which is described in this paper, provides the first open source implementation of the OMI algorithm, to our knowledge. The package meets state-of-the-art criteria for sustainable research software, like automated tests and a persistent archiving to aid the reproducibility of scientific results. The agreement of the OMI values calculated with this package and the original OMI values is also summarized here. There are several reuse scenarios; the most probable one is MJO-related research based on atmospheric models, since the index values have to be recalculated for each model run.
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来源期刊
Journal of Open Research Software
Journal of Open Research Software Social Sciences-Library and Information Sciences
CiteScore
6.50
自引率
0.00%
发文量
7
审稿时长
21 weeks
期刊最新文献
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