Parallel Implementation of a Kalman Filter for Constituent Data Assimilation

A Kalman filter for the assimilation of long-lived atmospheric chemical constituents was developed for twodimensional transport models on isentropic surfaces over the globe. Since the Kalman filter calculates the error covariances of the estimated constituent field, there are five dimensions to this problem, x 1 , x 2 , and time, where x 1 and x 2 are the positions of two points on an isentropic surface. Only computers with large memory capacity and high floating point speed can handle problems of this magnitude.