The theoretical background on sensitivity analysis, especially on the deterministic approach, is described along with definitions on the forward sensitivity coefficient, adjoint sensitivity coefficient, and relative sensitivity coefficient along with examples of their practical applications. Concept, strategies, and applications of adaptive (targeted) observations are discussed, using adjoint sensitivity analysis, singular vectors, the ensemble transform Kalman filter, and conditional nonlinear optimal perturbations. Forecast sensitivity of observations is also discussed as a tool for assessing the impact of observations. In addition, various targeting field programs are introduced.