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Ensemble of Data Assimilations - EDA
An Ensemble of Data Assimilations(EDA) is an ensemble of independent 4D-Var data assimilations where the main analysis error sources (observation errors, model errors, and boundary condition errors) are represented by perturbing the related quantities - respectively observations, forecast model, and soil moisture + sea-surface temperature + sea ice, according to their estimated accuracy. The EDA analyses are generated by randomly perturbing the observations and, across appropriate length scales, the sea surface temperature, sea ice and soil moisture fields. The observations are assumed unbiased (once any dynamic bias correction has been applied), with observation errors assumed to have a normal distribution. Model error is simulated using the Stochastically Perturbed Parameterisation Tendencies scheme (SPPT). The same SPPT configuration is used in EDA as in ENS. Differences between pairs of analyses (and forecast) fields have the statistical characteristics of analysis (and forecast) error.
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- the variability of the perturbations does not grow sufficiently through the forecast (perturbations are currently under-dispersive).
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