Oscillation [MJO] and variability related to monsoonal circulations), but are not completely understood. In addition, ISI variability can be observed at a relatively high frequency (multiple times per year) when compared to longer-term phenomena (e.g., decadal or multi-decadal oscillations such as the Pacific Decadal Oscillation), providing researchers with a relatively greater number of “realizations” to exploit within the observational record.

ORGANIZATION OF THIS REPORT

The remainder of this report is organized into five chapters:


Chapter 2 reviews the concept of predictability, starting with an initial review of the historical background for climate prediction. Lorenz’s work on weather prediction in the 1960s and 1970s is a foundation for present efforts; work in the 1980s extended prediction timescales by exploiting ENSO variability in the tropical Pacific and its associated teleconnections. Chapter 2 also introduces the view that a meaningful definition associates predictability with sources of variability, such as: 1) the inertia, or memory, of that state of the environment; 2) the patterns of interaction or coupling between variables, which include “teleconnections”; and 3) the response to external forcing. Various processes in the atmosphere, ocean, and land offer such sources of predictability. However, many gaps remain in our understanding of these processes. Chapter 2 also introduces the reader to the methodologies used to quantitatively estimate prediction skill and discusses model validation and forecast verification. Appendix A provides more technical detail about statistical methods.


Chapter 3 presents the reader with an introductory review of ISI forecasting followed by the committee’s understanding of its critical components: observations, statistical models, dynamical models, and data assimilation. The processes for making and disseminating forecasts are also discussed, as well as their use by decision makers. It closes with the committee’s summary of the potential improvements to current ISI forecast systems.


Chapter 4 uses three case studies to amplify and illustrate the state of and challenges facing efforts to improve ISI prediction. The three examples are ENSO, MJO, and soil moisture.


Chapter 5 defines the “Best Practices” that could be implemented to improve ISI predictions. This section also discusses some of the synthesizing issues given the content of the preceding chapters, exploring how the suggested activities could improve forecast quality, lead to more effective use of observations, and relate to the concept of “seamless” forecasting. In addition, realistic expectations for the speed and extent of improvements are discussed.


Chapter 6 presents the committee’s recommendations and some remarks on their implementation.



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