多源降水预报集成技术应用研究

doi:10.3969/j.issn.1673-503X.2021.04.004

Abstract

Abstract:

The integrated forecasting of 3-d precipitation was conducted based on precipitation forecast results of the global high-resolution European Centre for Medium-Range Weather Forecasts (ECMWF) model, the Chinese new generation of operational Globe/Range Assimilation and Prediction Enhance System (GRAPES_Meso), and the Weather Research Forecast (WRF) model. Taking the three-source (ground-satellite-radar) hourly precipitation grid product in China (CMPA-Hourly V2.0) as the "observed value", we adopted a simple bias-removed ensemble mean (ENSM) method and a multi-model ensemble (MME) method to conduct integrated precipitation forecast in the mainland of China. The performance of integrated precipitation forecasts was evaluated using precipitation observation data from 2800 national automatic weather stations. The results indicated that the MME method can integrate the advantages of each model member's precipitation forecast field, and provide a more stable, reliable, and high-quality refined precipitation forecast product with a higher resolution. During the test period, the EST score of the precipitation forecast based on the MME method during the flood season in the mainland China is better than that using the ENSM method and using the optimal single-mode precipitation forecast. The BIAS score is closer to 1, and the anomaly correlation coefficients between the forecasts using the MME method and the observed values increases. The MME method has a better ability to capture large values of precipitation, especially for improving the prediction of grades above moderate precipitation.

Key words: Multi-source, Bias-removed ensemble mean method, Unbiased mean absolute error

CLC Number:

P457.6

Xian TANG,Rong-wei ZHOU,Xiao-feng HE,Jing-yu WANG,Xiao-chen REN. Research on application of multi-source precipitation forecast integration technology[J]. Journal of Meteorology and Environment, 2021, 37(4): 26-32.

Figures/Tables 9

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References 20

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实况	预报
实况	发生	未发生
发生	a	c
未发生	b	d

时长	MME	ENSM	ECMWF	GRAPES_Meso	WRF
1 d	0.57	0.54	0.44	0.39	0.45
2 d	0.48	0.45	0.37	0.30	0.34
3 d	0.39	0.35	0.25	0.19	0.30

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Research on application of multi-source precipitation forecast integration technology

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