A Medium/Long-Range Forecast of Paci c Subtropical High Based on Dynamic Statistic Model Reconstruction |
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Affiliation: | Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101;Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101 |
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Abstract: | Based on the 500-hPa geopotential height eld series of T106 numerical forecast products, by empirical rthogonal function (EOF) time-space separation, and on the hypotheses of EOF space-models being stable,he EOF time coe cient series were taken as dynamical statistic model variables. The dynamic system econstruction idea and genetic algorithm were introduced to make the dynamical model parameters optimized, and a nonlinear dynamic statistic model of EOF separating time coefficient series was established. By he model time integral and EOF time-space reconstruction, a medium/long-range forecast of subtropical high was carried out. The results show that the dynamical model forecast and T106 numerical forecast were approximately similar in the short-range forecast (65 days), but in the medium/long-range forecast>5 days), the forecast results of dynamical model was superior to that of T106 numerical products. A new method and idea were presented for diagnosing and forecasting complicated weathers such as subtropical high, and showed a better application outlook. |
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Keywords: | dynamical statistic model reconstruction genetic algorithm empirical orthogonal function(EOF) subtropical high forecast |
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