数值预报中的再分析资料是什么

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数值预报中的再分析资料是什么，是更详细还是怎么回事？

二爷名声在外

In operational numerical weather prediction, forecast models are used to predict future states of the atmosphere, based on how the climate system evolves with time from an initial state. The initial state provided as input to the forecast must consist of data values for a range of "prognostic" meteorological fields – that is, those fields which determine the future evolution of the model. Spatially varying fields are required in the form used by the model, for example at each intersection point on a regular grid of longitude and latitude circles, and initial data must be valid at a single time that corresponds to the present or the recent past. By contrast, the available observational data usually do not include all of the model's prognostic fields, and may include other additional fields; these data also have different spatial distribution from the forecast model grid, are valid over a range of times rather than a single time, and are also subject to observational error. The technique of data assimilation is therefore used to produce an analysis of the initial state, which is a best fit of the numerical model to the available data, taking into account the errors in the model and the data.