Research on Information Entropy Time Series of CWC Based on Holt-ARIMA-Lagrange Multiplier
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1.Meteorological Center of Air Traffic Regulation of Civil Aviation in North China;2.School of Mathematics and Statistics,Nanjing University of Information Science and Technology;3.Experimental teaching center for meteorology and environment,Nanjing University of Information Science and Technology

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P457.6

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    Abstract:

    The development process and characteristic analysis of precipitation cloud system is an important problem in the field of cloud precipitation physics. In this paper, we select the 700 hPa cloud water content (CWC) and the 1h value of airflow velocity (OMG) in the vertical direction of the atmosphere, measure the chaos degree of CWC distribution with the information entropy as a tool, and OMG to judge the development of cloud, a combined prediction model is also proposed based on hybrid multi-scale decomposition, Holt model, autoregressive integrated moving average model (ARIMA) and Lagrange Multiplier. Results show that: 1) The CWC entropy has non-linear and non-stationary characteristics; 2) At the different development stages of the cloud, The means of the CWC entropy sequence of northern clouds are all smaller than those of southern clouds, The variance is generally greater than that of the southern cloud; 3) The OMG mean and the extreme point of the wavelet low-frequency reconstruction of the CWC entropy correspond well in time, Close extreme value points account for 50% of the southern cloud, In 83.3% of the northern cloud, It shows that CWC entropy can reflect the development of cloud system to a certain extent; 4) CWC entropy sequences often have multiple timescale features, Therefore, the accuracy of the Holt-ARIMA-Lagrange Multiplier model after multi-scale decomposition is improved by more than 3%, compared with the single prediction method and the prediction model of single-layer decomposition.

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History
  • Received:June 22,2022
  • Revised:October 07,2022
  • Adopted:October 11,2022
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