风云三号卫星微波综合干旱指数全球近实时数据集

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Anzhi Zhang, Hao Gao, Ronghan Xu, Xiaoqing Li, Huichen Zhao, Gensuo Jia
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引用次数: 0

摘要

随着气候变暖的加剧,干旱变得更加频繁和严重,对生态系统、农业和水资源构成了广泛的风险,因此,有效和及时的干旱监测对干旱评估、管理和缓解至关重要。本文利用2014年6月至今的风云三号微波综合干旱指数(FY-3 MIDI)数据集,对经不一致校正的FY-3B/C/D导出的微波降水、土壤湿度和地表温度进行最优加权,构建了风云三号微波综合干旱指数(FY-3 MIDI)的全球月度和10天干旱数据集。根据标准化降水蒸散指数、自校准Palmer干旱严重程度指数和0.25°时的非fy MIDI对数据集进行了评估和验证。风云三号MIDI可有效观测参考数据集捕获的干旱状况和特征,具有全天候工作能力,在气象干旱监测中可靠。在风云三号系列卫星运行的基础上,提供了近实时的月、十天时间尺度的宝贵业务服务,保障了当前和未来的持续应用,支持全球和区域干旱监测与评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A global near real-time dataset of Microwave Integrated Drought Index from the Fengyun-3 satellites.

Droughts have become more frequent and intense with increasing climate warming, posing widespread risks on ecosystem, agricultural, and water resources, therefore effective and timely drought monitoring is critical to drought assessment, management, and mitigation. Here, we presented a global monthly and ten-day drought dataset of the Fengyun-3 Microwave Integrated Drought Index (FY-3 MIDI) by integrating the inconsistency corrected FY-3B/C/D derived microwave precipitation, soil moisture, and land surface temperature with optimal weights from June 2014 to present. The dataset was evaluated and validated against the Standardized Precipitation Evapotranspiration Index, the Self-calibrating Palmer Drought Severity Index, and the non-FY MIDI at 0.25°. The FY-3 MIDI can effectively observe drought condition and characteristics as captured by the reference datasets, and it was reliable in monitoring meteorological drought with the ability to work in all-weather condition. Based on the operational Fengyun-3 series satellite, it provided valuable operational service in near real-time on a monthly and ten-day time scale, guaranteeing present and future continuous applications to support global and regional drought monitoring and assessment.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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