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The method for calculating time sequences through ordinal analysis, unlike correlation coefficient calculation, is presented, in which the idea comes from the closeness of the geometry between the variable sequences. For the sequences with the geometry closer to each other, the index that measures the closeness is bigger and vice versa. Putting the closeness in numerical order, the ranking of degree of contact between the variable sequences can be obtained. Four sequence calculation methods for different nature of the data from the practical point of view are proposed. Choosing the scheme of calculating the weighted squared distance, the related calculation is conducted with air pollution and its related meteorological elements data. By calculating the closeness degree of sequences and comparing with the coefficient method, it is concluded that by the method it is more reliable to use a meteorological element in forecasting. The relationship between the ordinal analysis and the correlation degree of absolute values, as well as the Euclidean distance mathematically, is proved, and the mathematical foundation of ordinal analysis is thus demonstrated. Mathematical derivation and numerical calculations both confirm the availability of ordinal analysis; especially it is useful in the case of measurements for small samples.