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关于解决气候模型输出和其他地理空间数据集中的坐标问题
Clément Cherblanc1,2, Jeppe Peder Grejs Petersen1,2, Fredrick Bunt3
1National Center for Climate Research, Danish Meteorological Institute, Copenhagen, 2100, Denmark.
Open research Europe
|January 8, 2026
概括
本研究提出了简化区域气候模型 (RCM) 数据以方便使用的方法. 使用Python和气候数据运营商 (CDO) 后处理RCM输出可以提高气候科学应用的可访问性.
科学领域:
- 气候科学 气候科学
- 地理空间分析的研究.
- 数据科学数据科学数据科学
背景情况:
- 区域气候模型 (RCM) 的输出往往缺乏完整的坐标系元数据,使地理空间分析复杂化.
- 局限域的RCM,特别是在极地地区,经常使用旋转网格,增加了复杂性.
- 标准工具需要文件元数据中的坐标参考系统,这在RCM数据中往往是缺失或不一致的.
研究的目的:
- 为区域气候模型 (RCM) 输出提供可访问的后处理方法.
- 为了简化气候和相关科学非专家的RCM数据的使用.
- 为了更容易地将RCM数据集成到地理信息系统 (GIS) 和基于Python的分析工作流中.
主要方法:
- 开发了两个RCM数据的后处理技术.
- 使用了免费和广泛可用的软件:Python和气候数据运营商 (CDO).
- 演示了在其原生网格上读取RCM数据或将其重新样本到具有地理坐标的正规网格上的方法.
主要成果:
- 成功地使RCM输出更容易为非专家处理.
- 使RCM数据能够在没有插值或再投影的情况下被正确地读取,或重新采样到正规的网格.
- 便于在GIS和Python库中使用RCM数据,例如xarray用于分析和可视化.
结论:
- 使用Python和CDO对RCM输出的后处理显著提高了数据的可用性.
- 这些方法弥合了复杂气候模型数据和实际科学应用之间的差距.
- 增强的数据可访问性支持在气候研究,地理信息系统和数据分析中更广泛的使用.
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