K. Schewel, Sarah Dickerson, B. Madson, Gabriela Nagle Alverio
{"title":"How well can we predict climate migration? A review of forecasting models","authors":"K. Schewel, Sarah Dickerson, B. Madson, Gabriela Nagle Alverio","doi":"10.3389/fclim.2023.1189125","DOIUrl":null,"url":null,"abstract":"Climate change will have significant impacts on all aspects of human society, including population movements. In some cases, populations will be displaced by natural disasters and sudden-onset climate events, such as tropical storms. In other cases, climate change will gradually influence the economic, social, and political realities of a place, which will in turn influence how and where people migrate. Planning for the wide spectrum of future climate-related mobility is a key challenge facing development planners and policy makers. This article reviews the state of climate-related migration forecasting models, based on an analysis of thirty recent models. We present the key characteristics, strengths, and weaknesses of different modeling approaches, including gravity, radiation, agent-based, systems dynamics and statistical extrapolation models, and consider five illustrative models in depth. We show why, at this stage of development, forecasting models are not yet able to provide reliable numerical estimates of future climate-related migration. Rather, models are best used as tools to consider a range of possible futures, to explore systems dynamics, to test theories or potential policy effects. We consider the policy and research implications of our findings, including the need for improved migration data collection, enhanced interdisciplinary collaboration, and scenarios-based planning.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":"54 15","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Climate","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fclim.2023.1189125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Climate change will have significant impacts on all aspects of human society, including population movements. In some cases, populations will be displaced by natural disasters and sudden-onset climate events, such as tropical storms. In other cases, climate change will gradually influence the economic, social, and political realities of a place, which will in turn influence how and where people migrate. Planning for the wide spectrum of future climate-related mobility is a key challenge facing development planners and policy makers. This article reviews the state of climate-related migration forecasting models, based on an analysis of thirty recent models. We present the key characteristics, strengths, and weaknesses of different modeling approaches, including gravity, radiation, agent-based, systems dynamics and statistical extrapolation models, and consider five illustrative models in depth. We show why, at this stage of development, forecasting models are not yet able to provide reliable numerical estimates of future climate-related migration. Rather, models are best used as tools to consider a range of possible futures, to explore systems dynamics, to test theories or potential policy effects. We consider the policy and research implications of our findings, including the need for improved migration data collection, enhanced interdisciplinary collaboration, and scenarios-based planning.