Abstract
This paper investigates the nonlinear prediction of monthly rainfall time series which consists of phase space continuation of one-dimensional sequence, followed by least-square determination of the coefficients for the terms of the time-lag differential equation model and then fitting of the prognostic expression is made to 1951–1980 monthly rainfall datasets from Changsha station. Results show that the model is likely to describe the nonlinearity of the annual cycle of precipitation on a monthly basis and to provide a basis for flood prevention and drought combating for the wet season.
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This work is sponsored by the National Natural Science Foundation of China.
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Yongqing, P., Shaojin, Y. & Tongmei, W. A nonlinear time-lag differential equation model for predicting monthly precipitation. Adv. Atmos. Sci. 12, 319–324 (1995). https://doi.org/10.1007/BF02656980
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DOI: https://doi.org/10.1007/BF02656980