A perturbation that is intended to produce the largest (optimal) change to a forecast measure J. For example, if J is a measure of forecast error, an optimal perturbation δx could represent a change to the forecast's initial conditions designed to minimize forecast error, given a constraint that δx has magnitude comparable to the typical analysis errors of operational forecast models. See adjoint sensitivity.