It is well known that the interactions between land surfaces and the atmosphere, and the resulting exchanges in water and energy have a tremendous affect on climate. The inadequate representation of land-atmosphere interactions is a major weakness in current climate models, and is providing the motivation for the HAPEX and ISLSCP experiments as well as the proposed Global Energy and Water Experiment (GEWEX) and the Earth Observing System (EOS) mission. The inadequate representation reflects the recognition that the well-known phys ical relationships, which are well described at small scales, result in different relationships when represented at the scales used in climate models. Understanding this transition in the mathematical relationships with increased space-time scales appears to be very difficult, and has led to different approaches; at one extreme, the famous "bucket" model where the land-surface is a simple one layer storage without vegetation; the other extreme may be Seller's Simple Biosphere Model (Sib) where one big leaf covers the climate model grid. Given the heterogeneous nature of landforms, soils and vegetation within a climate model grid, the development of new land surface parameterizations, and their verification through large scale experiments is perceived to be a challenging area of research for the hydrology and meteorology communities. This book evolved from a workshop held at Princeton University to explore the status of land surface parameterizations within climate models, and how observa tional data can be used to assess these parameterizations and improve models.

This text aims to promote a better understanding of land use and land-cover change in the assessment and management of global environmental resources, and to develop a comparative framework for assessing these changes.

Global Physical Climatology is an introductory text devoted to the fundamental physical principles and problems of climate sensitivity and change. Addressing some of the most critical issues in climatology, this text features incisive coverage of topics that are central to understanding orbital parameter theory for past climate changes, and for anthropogenic and natural causes of near-future changes--Key Features* Covers the physics of climate change* Examines the nature of the current climate and its previous changes* Explores the sensitivity of climate and the mechanisms by which humans are likely to produce near-future climate changes* Provides instructive end-of-chapter exercises and appendices

This book demystifies the models we use to simulate present and future climates, allowing readers to better understand how to use climate model results. In order to predict the future trajectory of the Earth’s climate, climate-system simulation models are necessary. When and how do we trust climate model predictions? The book offers a framework for answering this question. It provides readers with a basic primer on climate and climate change, and offers non-technical explanations for how climate models are constructed, why they are uncertain, and what level of confidence we should place in them. It presents current results and the key uncertainties concerning them. Uncertainty is not a weakness but understanding uncertainty is a strength and a key part of using any model, including climate models. Case studies of how climate model output has been used and how it might be used in the future are provided. The ultimate goal of this book is to promote a better understanding of the structure and uncertainties of climate models among users, including scientists, engineers and policymakers.

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.