The invention discloses a dimension reduction and correction model based on a spacial multi-correlation solution set algorithm. The processing method of the model comprises the steps of (1) obtainingdata, wherein the data includes a climate pattern grid data series Xt = (x1, t, x2, t, ..., xm, t) and actual measurement data series Yt= (y1, t, y2, t, ..., yn, t) of each site, m refers to the number of the grids, t refers to time and n refers to the number of the sites; (2) constructing the dimension reduction and correction model based on the spacial multi-correlation solution set algorithm: Y= B + AX + epsilon (epsilon - N (0, sigma 2)), wherein A and B are used for reflecting a related structural relationship between the grid data and the actual measurement data of the sites, and the sigma is a standardized independent random vector; (3) adopting a particle swarm optimization algorithm to figure out the solutions to the coefficient matrix A and the coefficient matrix B in an equation(1). The dimension reduction and correction model based on the spacial multi-correlation solution set algorithm has the advantage of increasing the simulation precision.