University of California, Irvine, E4130 Engineering Gateway Irvine , Irvine, CA 92697-2175, USA.
Sci Data. 2014 Mar 11;1:140001. doi: 10.1038/sdata.2014.1. eCollection 2014.
Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe.
干旱是迄今为止最昂贵的自然灾害，它可能导致广泛的影响，包括水和粮食危机。在这里，我们展示了来自全球综合干旱监测和预测系统（GIDMaPS）的数据，该系统基于多个干旱指标提供干旱信息。该系统基于多个卫星和基于模型的降水和土壤湿度数据集提供气象和农业干旱信息。GIDMaPS 包括一个接近实时的监测组件和一个季节性概率预测模块。数据集包括监测组件的历史干旱严重程度数据，以及预测模块的概率季节性预测。概率预测为预警、采取预防措施和规划缓解策略提供了重要信息。GIDMaPS 数据集是对当前全球干旱评估和预警能力和数据集的重要扩展。所提供的数据集将有助于减少干旱的影响，特别是在发展中国家。我们的结果表明，GIDMaPS 数据集可靠地捕捉了全球各地的几次重大干旱。
