Information derived from climate modeling has become increasingly important in recent years. More and more we understand that climate variability and change impacts society and that dealing with climate-related disasters, conflicts, and opportunities requires the best possible information about the past, present, and future of the climate system. To this end, Improving the Effectiveness of U.S. Climate Modeling describes ways to improve the efficacy of the U.S. climate modeling enterprise, given the current needs and resources. It discusses enhanced and stable resources for modeling activities, focused and centralized operational activities, how to give researchers access to the best computing facilities, the creation of a common modeling and data infrastructure, and research studies on the socioeconomic aspects of climate and climate modeling.

As climate change has pushed climate patterns outside of historic norms, the need for detailed projections is growing across all sectors, including agriculture, insurance, and emergency preparedness planning. A National Strategy for Advancing Climate Modeling emphasizes the needs for climate models to evolve substantially in order to deliver climate projections at the scale and level of detail desired by decision makers, this report finds. Despite much recent progress in developing reliable climate models, there are still efficiencies to be gained across the large and diverse U.S. climate modeling community. Evolving to a more unified climate modeling enterprise-in particular by developing a common software infrastructure shared by all climate researchers and holding an annual climate modeling forum-could help speed progress. Throughout this report, several recommendations and guidelines are outlined to accelerate progress in climate modeling. The U.S. supports several climate models, each conceptually similar but with components assembled with slightly different software and data output standards. If all U.S. climate models employed a single software system, it could simplify testing and migration to new computing hardware, and allow scientists to compare and interchange climate model components, such as land surface or ocean models. A National Strategy for Advancing Climate Modeling recommends an annual U.S. climate modeling forum be held to help bring the nation's diverse modeling communities together with the users of climate data. This would provide climate model data users with an opportunity to learn more about the strengths and limitations of models and provide input to modelers on their needs and provide a venue for discussions of priorities for the national modeling enterprise, and bring disparate climate science communities together to design common modeling experiments. In addition, A National Strategy for Advancing Climate Modeling explains that U.S. climate modelers will need to address an expanding breadth of scientific problems while striving to make predictions and projections more accurate. Progress toward this goal can be made through a combination of increasing model resolution, advances in observations, improved model physics, and more complete representations of the Earth system. To address the computing needs of the climate modeling community, the report suggests a two-pronged approach that involves the continued use and upgrading of existing climate-dedicated computing resources at modeling centers, together with research on how to effectively exploit the more complex computer hardware systems expected over the next 10 to 20 years.

Warren M. Washington is consultant and advisor to a number of government officials and committees on climate-system modelling. Now along with Claire Parkinson (NASA) he gives the reader insight into the complex field of climate modelling. Updated and revised from the first edition, this book is a welcome reference on climate modeling; an area that is becoming more and more sought after in light of environmental changes. Suitable for those wanting an in-road into understanding climate modeling but also an excellent companion for those with some prior knowledge of modeling meteorological systems.