The study showed that El Niño no longer strikes the same fear as it used to, even in the agricultural sector where the negative impacts of the 1997-98 and 1982-83 events are within living memory. The widespread drought associated with the El Niño event of 2015/16 (subsequent to this study) may, however, reverse this trend and promote greater interest in the role of ENSOs in seasonal forecasts. There is little demand for El Niño-specific forecasts outside of agricultural research. However there is evidence for the use of seasonal forecasts in the agriculture, water and disaster preparedness and response sectors in South Africa.

Originally formed around a set of lectures presented at a NATO Advanced Study Institute (ASI), this book has grown to become organised and presented rather more as a textbook than as a standard "collection of proceedings". This therefore is the first unified reference ‘textbook’ in seasonal to interannual climate predictions and their practical uses. Written by some of the world’s leading experts, the book covers a rapidly-developing science of prime social concern.

The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction is an ideal reference for researchers and practitioners across the range of disciplines involved in the science, modeling, forecasting and application of this new frontier in sub-seasonal to seasonal (S2S) prediction. It provides an accessible, yet rigorous, introduction to the scientific principles and sources of predictability through the unique challenges of numerical simulation and forecasting with state-of-science modeling codes and supercomputers. Additional coverage includes the prospects for developing applications to trigger early action decisions to lessen weather catastrophes, minimize costly damage, and optimize operator decisions. The book consists of a set of contributed chapters solicited from experts and leaders in the fields of S2S predictability science, numerical modeling, operational forecasting, and developing application sectors. The introduction and conclusion, written by the co-editors, provides historical perspective, unique synthesis and prospects, and emerging opportunities in this exciting, complex and interdisciplinary field. - Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science, forecasting and applications - Provides a one-stop shop for graduate students, academic and applied researchers, and practitioners in an emerging and interdisciplinary field - Offers a synthesis of the state of S2S science through the use of concrete examples, enabling potential users of S2S forecasts to quickly grasp the potential for application in their own decision-making - Includes a broad set of topics, illustrated with graphic examples, that highlight interdisciplinary linkages

El Nino has been with us for centuries, but now we can forcast it, and thus can prepare far in advance for the extreme climatic events it brings. The emerging ability to forecast climate may be of tremendous value to humanity if we learn how to use the information well. How does society cope with seasonal-to-interannual climatic variations? How have climate forecasts been usedâ€"and how useful have they been? What kinds of forecast information are needed? Who is likely to benefit from forecasting skill? What are the benefits of better forecasting? This book reviews what we know about these and other questions and identifies research directions toward more useful seasonal-to-interannual climate forecasts. In approaching their recommendations, the panel explores: Vulnerability of human activities to climate. State of the science of climate forecasting. How societies coevolved with their climates and cope with variations in climate. How climate information should be disseminated to achieve the best response. How we can use forecasting to better manage the human consequences of climate change.

As the nation's economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices. Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation's S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.

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.