Extreme Events and Climate Change. Группа авторов

Independent consultantSan José, Costa Rica

      D. Martínez Ventura Institute of Economic Research of the National Autonomous University of Mexico (UNAM) Mexico City, Mexico

      Shawn M. Milrad Department of Applied Aviation Sciences College of Aviation Embry‐Riddle Aeronautical University Daytona Beach, Florida, USA

      Sally Moyce College of Nursing Montana State University Bozeman, Montana, USA

      Bernardo Olvera Programa de Investigación de Cambio Climático Universidad Nacional Autónoma de Mexico Mexico City, Mexico

      Charles H. Paxton Private consultant Channelside Weather LLC Cocoa Beach, Florida, USA

      Ajay Raghavendra Department of Atmospheric and Environmental Sciences University at Albany Albany, New York, USA

      Juan Robalino Universidad de Costa Rica and CATIE San José, Costa Rica

      Yasmin Romitti Department of Earth and Environment Boston University Boston, Massachusetts, USA

      Milagro Saborío‐Rodríguez School of Economics and Institute of Economics Research University of Costa Rica San Pedro de Montes de Oca, Costa Rica

      Armando Sánchez Vargas Institute of Economic Research of the National Autonomous University of Mexico (UNAM) Mexico City, Mexico

      Catalina Sandoval Banco Central de Costa Rica San José, Costa Rica

      Colin Shaw Four Twenty Seven Inc. San Francisco, University of California Berkeley, California, USA

      Dáithí A. Stone Global Climate Adaptation Partnership Oxford, United Kingdom

      Yan Tan Department of Geography, Environment and Population University of Adelaide Adelaide, Australia

      Joshua Turner Four Twenty Seven Inc. San Francisco, California, USA

Jennifer Vanos School of Sustainability, College of Global Futures Arizona State University Tempe, Arizona, USA

      Raffaele Vignola CATIE Environmental Policy Group Turriabla, Costa Rica Wageningen University and Research Wageningen, The Netherlands

      Bárbara Viguera CATIE Turrialba, Costa Rica

      Michael Wehner Lawrence Berkeley National Laboratory Computational Research Division Berkeley, California, USA

      David Zilberman Department of Agricultural and Resource Economics University of California, Berkeley Berkeley, California, USA

      PREFACE

      Climate change has continued unabated since the second assessment report of the Intergovernmental Panel on Climate Change concluded in 1995 that “the balance of evidence suggests a discernible human influence on global climate” (Houghton et al., 1996, p. 4). Since then, confidence in the attribution of the human cause of global warming has increased to the point that by 2018 the Fourth United States National Climate Assessment report found that there is “no convincing evidence that natural variability can account for the amount of global warming observed over the industrial era” and that at best estimate, human changes to the composition of the atmosphere, mainly through the consumption of fossil fuels, accounted for all of that warming (Wuebbles et al., 2017). Because significant climate change is certain to continue into the future, attention to its impacts has become critically important (Field et al., 2014; Jay et al., 2018). As noted in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change:

      Global, regional, and local socioeconomic, environmental, and governance trends indicate that vulnerability and exposure of communities or social‐ecological systems to climate hazards related to extreme events are dynamic and thus vary across temporal and spatial scales (high confidence). Effective risk reduction and adaptation strategies consider these dynamics and the inter‐linkages between socioeconomic development pathways and the vulnerability and exposure of people.

      (Oppenheimer et al., 2014)

      Effective risk reduction therefore depends on multidisciplinary research that explores how past, current, and future extreme weather occurrence interacts with risk perceptions, adaptation efforts, and resilience mechanisms. For example, heat wave analysis has emphasized the impacts on health and on health care systems (Guirguis et al., 2014; Ostro et al., 2009; Stoecklin‐Marois et al., 2013) whereas the impact of floods, hurricanes, and drought on migration patterns has been mostly undertaken from a social science perspective (Hugo, 2011; Landry et al., 2007; Piguet et al., 2011). The need to approach the impacts of extreme events from a multidisciplinary approach provided the editors with the spark to organize the 2016 AGU Fall Meeting session, “Multidisciplinary Methods to Estimate the Impact of Climate‐Related Extreme Events,” which is the genesis of this book.

      This book presents a selection of contributions concerning the impacts of climate change. The authors are international experts in their fields, and their work represents the state of the art in attribution and socioeconomic impact analysis of extreme events. The work presented in this book is indicative of the multidisciplinary approaches that are needed to have a full assessment of the impact of extreme weather on society.

      Chapter 1 by Stone begins our discussion by outlining a detection and attribution approach to the general question of synthesizing the impacts of extreme weather in a changing climate. Using Arctic coast erosion as an example, Stone demonstrates the causal chain that must be developed to attribute individual impacts on anthropogenic climate change. The book then focuses on specific agricultural impacts for five chapters. In Chapter 2 Castillo et al. analyze the impact of heat waves on outdoor labor, particularly on agricultural labor in California. Using a Cobb‐Douglas production function approach and drawing from the medical literature, they use crop‐specific labor requirements together with climate and socioeconomic variables to determine the impact of heat on labor productivity and its resulting impact on crop productivity. They find that the impact of heat is crop specific, with particularly large impacts on crops that are labor intensive.

In Chapter 3 Grotjahn then takes a more targeted approach asking “What weather extremes affect various agricultural commodities?” He discusses the series of extreme weather events that can set in motion a series of changes affecting agricultural productivity. In Chapter 4 Lu et al. develop a theoretical framework that assesses the impact of extreme events on agricultural production systems. Using a stylized dynamic model, they suggest that an increase in temperatures will result in a geographical shift of agricultural production toward the poles and that there will be a transition from cold‐weather crops to hot‐weather crops. Despite this, due to the production costs in the new locations, there is a risk of supply shocks in the future. In Chapter 5 Casellas Connors and Janetos explore the teleconnection between regional crop failures finding that mitigation policies, including carbon taxes, will alter the geographic distribution of these impacts. In Chapter 6 Saborío‐Rodríguez et al. model adoption of adaptation practices among small bean and corn producers in Honduras and Guatemala in the presence of weather extremes. They find that the implementation of adaptation strategies is positively correlated with perceptions of repeated exposure and frequency of extreme event occurrence as well as human capital capacity building and land tenure regime, among others.

      The book then turns to the climate change impacts on the more complicated behavioral changes