A NEW DATA ASSIMILATION APPROACH

A significant attempt for designing a timesaving and efficient 4-dimensional variational data assimilation (4DVar) was made, and a new data assimilation approach called“3-Dimensional Variational data assimilation of Mapped observation (3DVM)” was proposed, based on the new concept of mapped observationand the new idea of backward 4DVar. Like the available 4DVar, 3DVM produces an optimal initial condition (IC) that is consistent with the prediction model due to the inclusion of dynamical and physical constraints of the model and is best fitting to the observations in the assimilation window through the model solution trajectory. Different from the 4DVar, the IC derived from 3DVM is not located at the beginning but the end of the assimilation window. It is the change of the IC time that makes the computing cost of the new approach greatly reduced. Actually, 3DVM costs almost the same as the 3-Dimensional Variational data assimilation (3DVar) does, but performs as same as the 4DVar does. Especially, it is able to improve the assimilation accuracy because it does not need the tangent linear and adjoint approximations for calculating the gradient of cost function anymore. The new approach produced better IC for 72- hour simulation of TY9914 (Dan) than 4DVar does, by assimilating the three-dimensional fields of temperature retrieved from the Advanced Microwave Sounding Unit-A (AMSU-A) observations. Meanwhile, it takes only 1/7 of the computing costs the 4DVar requires for the same initialization with the same retrieved data.