PDF(Pubmed)
Abstract：
Drought is one of the foremost outcomes of global warming and global climate change. It is a serious threat to humans and other living beings. To reduce the adverse impact of drought, mitigation strategies as well as sound projections of extreme events are essential. This research aims to strengthen the robustness of anticipated twenty-first century drought by combining different Global Climate Models (GCMs). In this article, we develop a new drought index, named Maximum Relevant Prior Feature Ensemble index that is based on the newly proposed weighting scheme, called weighted ensemble (WE). In the application, this study considers 32 randomly scattered grid points within the Tibetan Plateau region and 18 GCMs of Coupled Model Intercomparison Project Phase 6 (CMIP6) of precipitation. In this study, the comparative inferences of the WE scheme are made with the traditional simple model averaging (SMA). To investigate the trend and long-term probability of various classes, this research employs Markov chain steady states probability, Mann-Kendall trend test, and Sen\'s Slope estimator. The outcomes of this research are twofold. Firstly, the comparative inference shows that the proposed weighting scheme has greater efficiency than SMA to conflate GCMs. Secondly, the research indicates that the Tibetan Plateau is projected to experience \"moderate drought (MD)\" in the twenty-first century.
摘要：
干旱是全球变暖和全球气候变化的主要结果之一。这是对人类和其他生物的严重威胁。减少干旱的不利影响,缓解策略以及对极端事件的合理预测至关重要。这项研究旨在通过结合不同的全球气候模型（GCM）来增强预期的二十一世纪干旱的稳健性。在这篇文章中,我们开发了一个新的干旱指数，命名为最大相关先验特征集合索引，该索引基于新提出的加权方案，称为加权集合(WE)。在应用程序中，这项研究考虑了青藏高原地区的32个随机分散的网格点和降水的耦合模型比较项目6期（CMIP6）的18个GCM。在这项研究中,WE方案与传统的简单模型平均(SMA)进行了比较推断。为了调查各种类别的趋势和长期概率，这项研究采用了马尔可夫链稳态概率，Mann-Kendall趋势测试,和森的坡度估计器。这项研究的结果是双重的。首先,比较推断表明，所提出的加权方案比SMA具有更高的效率来合并GCM。其次，研究表明，预计青藏高原将在二十一世纪经历“中度干旱（MD）”。
