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全球未来干旱层基于下调的CMIP6模型和多种社会经济途径
Diogo S A Araujo1, Brian J Enquist2,3, Amy E Frazier4
1Department of Civil and Environmental Engineering, Rutgers University, Piscataway, NJ, 08854, USA.
Scientific data
|February 19, 2025
概括
本研究提供了从1980年到2100年的历史和预测干旱指数 (SPI和SPEI) 的全球数据集. 这种重要资源有助于理解和管理各种气候情景下的未来干旱影响.
科学领域:
- 气候科学 气候科学
- 环境科学 环境科学
- 数据科学数据科学数据科学
背景情况:
- 在全球范围内,干旱的频率和严重程度正在增加.
- 了解干旱特征对于抗旱能力至关重要.
- 现有的数据可能无法完全捕捉未来的干旱轨迹.
研究的目的:
- 开发一个全面的历史和预测干旱指数的全球数据集.
- 为了解不同气候场景下的干旱变化轨迹提供数据.
- 支持跨部门的干旱适应性规划.
主要方法:
- 使用了缩小规模的合模型对比项目第6阶段 (CMIP6) 全球气候模型 (GCM).
- 计算了标准化降水指数 (SPI) 和标准化降水蒸发透气指数 (SPEI).
- 在四个共享社会经济路径 (SSP) 下,为1980-2100年以0.25度分辨率生成网格空间数据集.
主要成果:
- 有23个GCM的SPI和SPEI数据集可用.
- 数据涵盖了历史时期 (1980-2014) 和未来时期 (2015-2100).
- 在每月的分辨率下,为3个,6个和12个月的时间表提供索引.
结论:
- 该数据集为全球干旱模式提供了有价值的见解.
- 它支持研究气候变化对干旱的影响.
- 促进改善干旱风险评估和管理策略.
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