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In recent years, it causes disasters increasingly by too much or too little precipitation. Therefore, accurate prediction of precipitation is of great significance and practical application value to human life and social development. Based on the monthly precipitation data of Zhengzhou from 1990 to 2019, monthly precipitation was forecasted from 2020 to 2021 by utilizing SARIMA, Prophet and LSTM model, respectively. In order to improve the prediction accuracy of the model for monthly precipitation, two combined models of the SARIMA-EMD-LSTM and Prophet-EMD-LSTM were proposed. Empirical analysis shows that the proposed two combined models have higher prediction accuracy and decrease the root mean square error significantly. Furthermore, Prophet-EMD-LSTM model has comparatively better prediction effect. The monthly precipitations in Zhengzhou from April to December, 2022 were forecasted with higher precision.

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近年来，由降水量过多或过少引起的灾害日益增加，因此准确地预测降水量对人类的生活和社会的发展具有重大意义和实际应用价值。基于郑州市1990~2019年的月降水量数据，分别利用SARIMA、Prophet、LSTM单一模型对郑州市2020~2021年的月降水量进行预测。为了提高月降水量的预测精度，提出SARIMA-EMD-LSTM、Prophet-EMD-LSTM两种组合模型，实证表明这两种组合模型预测精度更高，均方根误差显著减少，其中Prophet-EMD-LSTM组合模型的预测效果相对较优。最后利用该模型对郑州市2022年4~12月的月降水量进行了预测，精度较高。

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程桂芳（1979-），女，博士、副教授、硕导，研究方向为统计与大数据分析，E-mail：gfcheng@zzu.edu.cn

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程桂芳（1979-），女，博士、副教授、硕导，研究方向为统计与大数据分析，E-mail：gfcheng@zzu.edu.cn

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