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一个大型的全球数据集,用于气候影响评估
Xiang Gao1, Andrei Sokolov2, C Adam Schlosser2
1MIT Joint Program on the Science and Policy of Global Change, Cambridge, MA, 02139, USA. xgao304@mit.edu.
Scientific data
|November 14, 2023
概括
这项研究提供了一个高分辨率的全球气候数据集,用于长期的未来预测,考虑到温室气体排放和气候变化模式的不确定性. 这些数据支持对农业和水资源等部门的区域影响评估.
科学领域:
- 气候科学 气候科学
- 环境科学 环境科学
- 地球系统科学 地球系统科学
背景情况:
- 未来的气候预测对于理解人为影响至关重要.
- 气候系统应对和地理模式的不确定性需要强大的数据集.
- 现有的数据集可能缺乏详细影响研究的分辨率或全面的变量覆盖.
研究的目的:
- 开发一个自相一致的,大型的,高分辨率的全球气候数据集,用于长期的未来预测.
- 考虑到气候系统对温室气体排放和地理气候变化模式的反应中的不确定性.
- 为各个部门提供区域范围的气候相关影响评估资源.
主要方法:
- 应用一个集成的空间分类 (SD) -偏差校正 (BC) 方法.
- 利用了麻省理工学院综合全球系统模型 (IGSM) 的气候预测.
- 考虑了四种不同的排放场景 (参考,巴黎永远,巴黎2°C,巴黎1.5°C).
主要成果:
- 从2021年到2100年生成了一个包含9个主要气象变量 (降水,温度,风速,辐射,湿度) 的数据集.
- 在月度尺度上达到0.5°x0.5°的空间分辨率.
- 证明了数据集能够代表全球气候变化反应的能力.
结论:
- 开发的数据集为未来的气候影响分析提供了全面的资源.
- 它解决了气候模型中的不确定性,并提供了详细的区域气候信息.
- 促进关键部门的风险评估,如水资源,农业和生态系统.
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