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.

Recent food shortages in Southern Africa, induced by rainfall variability but compounded by problems of governance and rising food prices, have resulted in massive relief efforts. A recent scientific innovation - supplying farmers with seasonal climate forecasts - has been touted as a way to increase preparedness for such situations.

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

This study contributes to a broader effort of institutions toward improving seasonal forecasts over southern Africa. The primary objective is to understand where global models show shortcomings in their simulations, and how this impacts on their seasonal forecast skill. It is proposed that the skill of a model in simulating natural climate variability is an appropriate metric for a model's potential skill in seasonal forecasting. Thus the study investigates the performance of two global models in simulating the regional processes in relation to the processes variability, and how this is related to their forecast skill. The study significantly provides more insight into models ability to simulate the general circulation features that modulate rainfall and temperature, and the relationship of rainfall with global SST. This study therefore provides useful information for modellers, forecasters, and climate researchers on the global models used in the study.

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.