用高斯过程学习气候引起的人类迁移的驱动因素
Learning drivers of climate-induced human migrations with Gaussian processes
摘要：
在当前气候变化的背景下，极端热浪、干旱和洪水不仅影响生物圈和大气层，而且也影响着生物圈。人口被迫流离失所，现在被称为气候所致移民。在这项工作中，我们调查了在2017-2019年期间，哪些气候和结构性因素在洪水和风暴的存在下迫使主要的人类流离失所。我们建立、策划和协调了一个气象和遥感指标数据库，以及全球27个发展中国家的结构因素。我们展示了如何使用高斯过程来了解哪些变量可以解释洪水和风暴在被迫流离失所的背景下的影响，并开发重现移民流的模型。我们在区域、全球和灾害特定尺度上的研究结果表明了结构因素在确定位移幅度方面的重要性。这项研究可能具有社会、政治和经济影响。
英文摘要：
In the current context of climate change, extreme heatwaves, droughts, and floods are not only impacting the biosphere and atmosphere but the anthroposphere too. Human populations are forcibly displaced, which are now referred to as climate-induced migrants. In this work, we investigate which climate and structural factors forced major human displacements in the presence of floods and storms during the years 2017-2019. We built, curated, and harmonized a database of meteorological and remote sensing indicators along with structural factors of 27 developing countries worldwide. We show how we can use Gaussian Processes to learn what variables can explain the impact of floods and storms in the context of forced displacements and to develop models that reproduce migration flows. Our results at regional, global, and disaster-specific scales show the importance of structural factors in the determination of the magnitude of displacements. The study may have both societal, political, and economical implications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
