MPCID,一个新的高分辨率多重降雨度指标数据集,用于中国大陆
Dongyang Zhang1,2,3, Xuemei Li4,5,6, Lanhai Li7
1Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Scientific data
|January 6, 2026
概括
对于中国而言,一个新的数据集,即多重降水度指标数据集 (MPCID),提供连续的历史和未来降水数据. 它有助于理解气候变化对水资源和生态系统的影响.
科学领域:
- 水文和气候科学 水文和气候科学
- 环境数据科学环境数据科学
背景情况:
- 全球气候变化加剧了水文循环,增加了极端降水事件.
- 现有的降水度指标面临数据限制,阻碍了对历史和未来趋势的分析.
研究的目的:
- 为中国大陆引入多重降雨度指标数据集 (MPCID),提供1961年至2001年间的时空连续数据.
- 将历史观测与未来气候预测相结合,以进行全面的降水分析.
主要方法:
- 综合历史现场和网格观测 (1961-2022年) 与下调的CMIP6预测 (2015年至100年) 在四个SSP场景中.
- 纳入了四个关键指标:降水度度 (PCD),降水度周期 (PCP),每日降水度指数 (DPCI) 和每月降水度指数 (MPCI).
- 与站点数据对比的验证指标,以评估可靠性和性能.
主要成果:
- 降水度 (PCD) 被确定为最可靠的指标,显示最小的错误,高相关性和微不足道的偏差.
- 每日降水度指数 (DPCI) 显示出中度的误差控制,但由于降水随机性,每日尺度的相关性有限.
- 月度降水度指数 (MPCI) 降低了对极端事件的敏感性,而PCP有时间阶段对齐限制.
结论:
- MPCID克服了数据碎片化,为研究降水动态提供了持续的资源.
- 该数据集对于评估气候变化对水文和农业的影响至关重要.
- MPCID为开发水资源适应性管理策略提供了基础.
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