pyam:综合评估和宏观能源场景的分析和可视化
Daniel Huppmann1, Matthew J Gidden1,2, Zebedee Nicholls3,4
1Energy, Climate and Environment Program (ECE), International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.
Open research Europe
|August 30, 2023
概括
开源的pyam包简化了分析和可视化来自各种模型的气候和能源数据. 它增强了研究人员和模型设计人员使用场景数据的工作可重复性.
科学领域:
- 科学软件开发科学软件开发
- 气候变化建模的模型.
- 能源系统分析 能源系统分析
背景情况:
- 综合评估模型为气候和能源研究生成复杂的场景数据.
- 现有的工具往往缺乏灵活性,被绑定到特定的建模框架.
- 对场景数据的可重复分析对于气候政策和可持续发展至关重要.
研究的目的:
- 介绍pyam,一个开源的Python包,用于分析,验证和可视化场景数据.
- 弥合专门建模输出和通用数据分析工具之间的差距.
- 提高气候和能源场景处理的可靠性和可重复性.
主要方法:
- 使用经过充分测试和记录的方法开发一个Python包.
- 支持各种数据格式,包括次年度分辨率和代表时间切片.
- 采用合作科学软件开发的最佳实践进行实施.
主要成果:
- pyam提供了一套灵活的功能套件,用于时间序列数据分析.
- 该套件有助于与各种场景组合一起工作,例如IPCC报告.
- 通过最近在能源转型和气候减缓方面的几项应用来证明其实用性.
结论:
- 在气候和能源系统的场景分析中,pyam提高了可重复性和可靠性.
- 该包可供不同级别的Python专业知识的用户使用.
- 皮亚姆支持科学界在气候变化减缓和可持续发展方面的研究.
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