lite missions, or transitions between systems.


Climate observations come from a diverse system of instruments and are spatially and/or temporally incomplete (Figure 5.2). Meshing them with global climate models to produce a best estimate of the state of the climate at a given point in time can enhance the value of diverse climate observations. The past decade has seen a proliferation of efforts to synthesize these diverse observations into a common framework to produce global synoptic data sets for evaluating the atmospheric, oceanic, and terrestrial components of climate and Earth system models. Such global analyses of climate fields have supported many needs of the research and climate modeling communities. Because they are primarily produced by operational forecasting centers, which are less concerned with long-term data consistency, many changes are made to both the models and the assimilation systems over time. These changes produce spurious “climate changes” in the analysis fields, which obscure the signals of true short-term climate changes or interannual climate variability.

For the atmosphere a solution has been to redo the assimilation of the historical collection of diverse atmospheric observations using a constant state-of-the-art numerical weather prediction model. These “reanalysis” efforts have produced fairly reliable atmospheric climate records that have enabled (i) climatologies to be established, (ii) anomalies to be calculated, (iii) empirical and quantitative diagnostic studies to be conducted, (iv) exploration and improved understanding of climate system processes, and (v) model initialization and validation to be performed (Trenberth, 2010). These products provide the essential foundation for an accurate assessment of current climate, diagnostic studies of features such as weather systems, monsoons, El Niño/Southern Oscillation and other natural climate variations, seasonal prediction, and climate predictability. Importantly, the reanalyses have also provided a vitally needed

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