Flexible Global Ocean Atmosphere Land System Model

Coupled climate system models are of central importance for climate studies. A new model known as FGOALS ( the Flexible Global Ocean-Atmosphere-Land System model), has been developed by the Sate Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP, CAS), a first-tier national geophysical laboratory. It serves as a powerful tool, both for deepening our understanding of fundamental mechanisms of the climate system and for making decadal prediction and scenario projections of future climate change. "Flexible Global Ocean-Atmosphere-Land System Model: A Modeling Tool for the Climate Change Research Community” is the first book to offer systematic evaluations of this model’s performance. It is comprehensive in scope, covering both developmental and application-oriented aspects of this climate system model. It also provides an outlook of future development of FGOALS and offers an overview of how to employ the model. It represents a valuable reference work for researchers and professionals working within the related areas of climate variability and change. Prof. Tianjun Zhou, Yongqiang Yu, Yimin Liu and Bin Wang work at LASG, the Institute of Atmospheric Physics, Chinese Academy of Sciences, China.

This book lays out a science plan for a major, international, 15-year research program. The past 10 years have seen significant progress in studies of short-term climate variations, in particular for the region of the tropical Pacific Ocean and the El Nino/Southern Oscillation phenomenon. Some forecast skill with lead times as long as a year in advance has already been developed and put to use. The GOALS program plans to capitalize on this progress by expanding efforts on observations and seasonal-to-interannual predictions to the remainder of the tropics and to higher latitudes.

This book covers all aspects related to climate change and agriculture. The book discusses Global Climate Models (GCMs), Coupled Model Intercomparison Project (CMIP) and application of strategic management tool that includes RCP (Representative concentration Pathway), SSP (Shared Socio-economic Pathways) and SPA (Shared climate Policy Assumptions). The book provides information on how climate change, agricultural productivity and food security are interlinked. The impacts of climate change on food security are studied through different climatic drivers e.g., ENSO (El Niño–Southern Oscillation) and SOI (Southern Oscillation Index). These drivers are responsible for the climatic extreme events hence early prediction of these drivers could help to design appropriate adaptive measures for the agriculture sector and could be considered as early warning tools for risk management. Similarly, climate change and process-based soil modeling as well as the role of soil microbes and climate smart agriculture are discussed in this book. Climate change impacts on legume crop production and adaptation strategies are presented, with details about cereal crop modeling, perspectives of Camelina sativa as well as low input biofuel and oilseed crop, greenhouse gases (GHGs) emissions and mitigation strategies.

The National Academies' Board on Atmospheric Sciences and Climate (BASC) held a workshop to explore and evaluate current efforts to model physical processes of coupled atmosphere-land-ocean (A-L-O) models. Numerical models of the atmosphere and ocean are central to weather prediction, research, and education. Although great strides have been made over the past few decades in understanding the atmosphere and ocean, modeling capabilities, and numerical A-L-O simulations, some unresolved processes in the models do not adequately represent knowledge of the underlying physics. Moreover, there is evidence that further progress in numerical simulations is being impeded by the slow pace of improvement in the representation of key physical processes in the models and the fact that geophysical flow models are not receiving the attention needed to make these tools more useful and accurate. These models often are used to predict future events, so it is imperative that their underlying physical processes be represented as robustly as possible. During the workshop, the parameterization of physical processes in A-L-O models was addressed, including associated errors, testing, and efforts to improve the use of parameterizations. Participants also examined intellectual and scientific challenges in modeling and highlighted the idea that some of the key impediments to progress in representing physical processes are primarily cultural in nature.

The report also provides a comprehensive assessment of past and future sea level change in a dedicated chapter.

Understanding Climate Change Impacts on Crop Productivity and Water examines the greenhouse gas emissions and their warming effect, climate change projections, crop productivity and water. The book explores the most important greenhouse gases that influence the climate system, technical terms associated with climate projections, and the different mechanisms impacting crop productivity and water balance. Adaptive and mitigative strategies are proposed to cope with negative effects of climate change in particular domains. This book will help researchers interested in climate change impacts on the atmosphere, soil and plants. Uncovers links between climate change and its impact on crop and water outputs Integrates information on greenhouse gas cycles and mathematical equations into climate/crop models for analysis and seasonal prediction systems Provides strategies for efficient resource management and sustainable crop production in future Helps researchers interested in climate change impacts on the atmosphere, soil and plants