Assessment of Intraseasonal to Interannual Climate Prediction and Predictability (2010) / Chapter Skim
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1 predictions for the climate system, to analyze how past improvements in these capabilities have been achieved, and to recommend opportunities for future improvement. ISI climate predictions occupy an intermediate timescale between traditional weather forecasts, which are useful for the coming days, and global climate simulations associated with climate change, which relate to changes occurring over decades and centuries (see Box S.1)
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The committee begins from the premise that the ability to predict the climate accurately at ISI timescales stems from our knowledge of "sources of predictability," the variables or processes operating within and among the atmosphere, ocean, and land that affect the state of the climate on ISI timescales. The sources of predictability are measured, represented, and simulated by ISI forecast systems through an assemblage of "building blocks," namely observational systems, statistical and dynamical models, and data assimilation schemes.
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For the y-axis, "A" indicates "atmosphere;" "L" indicates "land;" "I" indicates "ice;" and, "O" indicates "ocean." tied to exploiting new sources of predictability or improving the representation of known sources of predictability in current forecast systems. THE BUILDING BLOCKS OF AN ISI FORECAST SYSTEM ISI forecasting systems are composed of several "building blocks:" observations, statistical and dynamical models, and data assimilations systems.
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For ENSO, the perspective is somewhat historical, as many previous advances in ISI forecasting have come from an improved observational capacity that accompanied expanded understanding of physical processes and model development. For the MJO and soil moisture, the perspective is more forward-looking.
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Although adopting Best Practices may require some additional resources on the part of the operational centers, the barriers to adoption are relatively minimal; many of the recommendations involve modification to current protocols or expansion of current programs rather than a novel set of initiatives. The Improvements to the Building Blocks of ISI Forecast Systems pertain to both the operational and research communities and focus on the continued development of observations, statistical and dynamical models, and data assimilation systems.
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(2) Operational ISI forecasting centers should establish public archives of all data used in forecasts including observations, model code, hindcasts, analyses, forecasts, re-analyses, reforecasts, verifications, and official forecast outlooks.
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The physical processes underlying ISI variability are often poorly understood. Process studies that are closely tied to operational ISI model improvement should be carried out with the goal of transferring improvements into operational ISI forecasts.
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There are many available observations that are not currently being utilized in data assimilation schemes that could contribute to the initialization of dynamical models. More observations should be assimilated into operational ISI forecast systems.
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Over the next several years and coming decades, improvements to observational capabilities, statistical and dynamical models, and data assimilations systems should permit ISI forecast systems to better represent the variables and processes that serve as sources of predictability. Research to characterize sources of predictability that are poorly understood should also offer opportunities to improve ISI predictions as well as our understanding of important underlying climate processes.
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