Linda O. Mearns – författare

Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for policy makers and practitioners interested in climate risk and resilience.

Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for policy makers and practitioners interested in climate risk and resilience.

Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for policy makers and practitioners interested in climate risk and resilience.

This volume presents a collection of articles concerning key topics which examine the impacts of climate change and variability on agriculture. The application region is the southeastern United States. The main topics include an investigation of the effect of variations in the spatial scale of climate change scenarios on an agricultural integrated assessment, methods of simulating adaptations of climate change, and the relationship between large scale climate variability and local climate and vegetation. The book should be useful for researchers and policy makers involved in climate change impacts.

This edited volume with open access discusses all aspects of uncertainty in climate change research, with a unique emphasis on decision making under uncertainty and the assessment of various uncertainties in the landscape of decision making. By analyzing uncertainty through the lens of decision making, the book seeks to understand and assess the various uncertainties inherent in climate change research, including uncertainties in economic impacts, human health and vulnerability, fluctuations in the physical climate system, changes in infrastructure, and future climate projections. Very little published material exists on the uncertainties regarding vulnerability of different populations to climate change, and so the book characterizes the uncertainty in vulnerability to better formulate solutions to climate change problems in affected populations. The volume will be of interest to students, post-docs, early career scientists, and researchers interested in all aspects of climate change. After an introduction that addresses the issue of uncertainty in general as it pertains to climate change research, the book is divided into 5 main sections. Section 1 focuses on uncertainty in policy and decision making, and how climate-related policy choices impact risk management, impact mitigation, and adaptation. Section 2 discusses uncertainty in climate change impacts, including impacts in agriculture, water resources, transportation infrastructure, and human health and vulnerability. Section 3 analyzes physical climate uncertainties, such as Earth system projections, emissions concentrations, and sea-level rise projections. Section 4 details the methods for quantifying uncertainty from a statistical perspective. Section 5 concludes the volume with discussions on special topics and integrated themes on uncertainty, including ethics and uncertainty, communication, the economics of climate change, and integrated modeling for decision support.

This book presents a collection of articles concerning key topics which examine the impacts of climate change and variability on agriculture. The application region is the southeastern United States. The main topics include an investigation of the effect of variations in the spatial scale of climate change scenarios on an agricultural integrated assessment, methods of simulating adaptations of climate change, and the relationship between large scale climate variability and local climate and vegetation. This book will be very useful for researchers and policy makers involved in climate change impacts.