An Integrated Correction Method for 2 m Temperature and Its Application to Yanqing Competition Zone of Olympic Winter Games

Qiu Guiqiang; Shi Shaoying; Wang Hongxia; Jing Hao; Zhang Lei

doi:10.11898/1001-7313.20230402

Vol.34, NO.4, 2023

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Article Navigation > Journal of Applied Meteorological Science > 2023 > 34(4): 400-412

Qiu Guiqiang, Shi Shaoying, Wang Hongxia, et al. An integrated correction method for 2 m temperature and its application to Yanqing competition zone of Olympic Winter Games. J Appl Meteor Sci, 2023, 34(4): 400-412. DOI: 10.11898/1001-7313.20230402.

Citation:

Qiu Guiqiang, Shi Shaoying, Wang Hongxia, et al. An integrated correction method for 2 m temperature and its application to Yanqing competition zone of Olympic Winter Games. J Appl Meteor Sci, 2023, 34(4): 400-412. DOI: 10.11898/1001-7313.20230402.

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An Integrated Correction Method for 2 m Temperature and Its Application to Yanqing Competition Zone of Olympic Winter Games

DOI: 10.11898/1001-7313.20230402

1.
Shanxi Meteorological Observatory, Taiyuan 030006
2.
Beijing Meteorological Observatory, Beijing 100089

Received Date: 2023-01-30
Rev Recd Date: 2023-05-16
Publish Date: 2023-07-31

Abstract

Abstract

The snow events in Olympic Winter Games and Paralympic Winter Games are held outdoors in mountainous areas and especially weather sensitive. Unfavorable weather conditions can lead to delays or cancellations of competitions, and even affect the safety of athletes. With dramatic variability in the surface meteorological conditions at venues due to local topographic effects, the provision of timely and accurate high-quality weather prediction pose serious challenges to forecasters. Over the past decades, the accuracy of numerical weather prediction models is gradually improving, but there are still some systematic errors because of the inherent modeling deficiencies, especially in areas characterized by highly variable orography. Fortunately, the weather prediction accuracy is usually improved with the help of post-processing techniques.In order to improve the meteorological service capability of the snow events, an integrated correction method for 2 m temperature prediction, composed of the model bias correction based on terrain correction and support vector machine algorithm, is proposed at sites with different altitudes within 72 h at 3 h interval. European Center for Medium Range Weather Forecasts (ECMWF) model data from 1 January to 28 March during 2018-2021 and the observation of 2 m temperature at eight automatic weather stations in Yanqing competition zone are used. The performance of the integrated correction method is evaluated before and during Olympic Winter Games and Paralympic Winter Games. The results show that the accuracy of the correction method is 0.856 and the mean absolute error is 1.08℃ for 2 m temperature prediction in Yanqing competition zone. The integrated correction method is better than the single algorithm, and performs well in 2 m temperature prediction exceeding the threshold and key weather process forecasts. The performance of the integrated correction method is more outstanding especially for the sites higher than the terrain height of the model. For most of the sites, the mean absolute error of 2 m temperature predicted by the integrated correction method within 72 h at 3 h interval generally shows a certain diurnal variation, and the variation of mean absolute error within 0-24 h, 24-48 h and 48-72 h lead time is relatively stable, but the daily variation trend is different at different sites. With the increase of lead times, the mean absolute error of 2 m temperature predicted by the integrated correction method shows the altitude dependence. The relevant research results may be extended to other complex mountainous areas to improve the weather prediction accuracy.
- temperature forecasts;
- terrain correction;
- support vector machine;
- integrated correction

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References(31)

Figures and Tables

Fig. 1 Terrain height (the shaded) of Yanqing competition zone of Beijing Winter Olympics and main automatic weather stations (hollow triangles)

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Fig. 2 Evaluation of 2 m temperature predicted by the terrain correction method using temperatures at different model levels

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Fig. 3 Evaluation of 2 m temperature corrected by different methods from 1 Jan to 15 Mar in 2022

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Fig. 4 Mean absolute error of 2 m temperature corrected by different methods varing with different lead times from 1 Jan to 15 Mar in 2022

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Fig. 5 Mean absolute errors of 2 m temperature exceeding the threshold corrected by different methods from 1 Jan to 15 Mar in 2022

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Fig. 6 Comparison of 2 m temperature corrected by different methods to observation from 2000 BT 11 Feb to 2000 BT 14 Feb in 2022

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Fig. 7 Comparison of 2 m temperature corrected by different methods to observation from 0800 BT 7 Mar to 2000 BT 8 Mar in 2022

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Table 1 Optimal parameters of support vector machine model and corresponding performance

站号	参数		评估指标
站号	C	γ	准确率	平均绝对偏差/℃
A1701	0.09	100	0.858	1.07
A1703	0.10	1000	0.823	1.20
A1705	0.02	100	0.857	1.10
A1708	0.06	1000	0.806	1.23
A1710	0.02	1000	0.873	1.01
A1711	0.05	1000	0.866	1.07
A1712	0.02	1	0.864	1.07
A1489	0.10	100	0.713	1.53

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Table 2 Mean absolute errors of 2 m temperature corrected by different methods within different lead times from 1 Jan to 15 Mar in 2022 (unit:℃)

站号	方法	预报时效
站号	方法	0~24 h	24~48 h	48~72 h
A1701	地形订正	1.22	1.20	1.36
	支持向量机	1.27	1.16	1.23
	集成订正	1.14^*	1.11^*	1.23^*
A1703	地形订正	1.25	1.21	1.38
	支持向量机	1.27	1.17	1.32
	集成订正	1.11^*	1.05^*	1.19^*
A1705	地形订正	0.81	0.95	1.16
	支持向量机	0.85	0.91	1.13
	集成订正	0.77^*	0.89^*	1.10^*
A1708	地形订正	0.93	1.09	1.26
	支持向量机	1.06	1.08	1.15
	集成订正	0.96	1.06^*	1.17
A1710	地形订正	1.07	1.05	1.26
	支持向量机	1.12	1.06	1.23
	集成订正	0.95^*	0.92^*	1.10^*
A1711	地形订正	1.20	1.20	1.37
	支持向量机	1.07	0.95	1.11
	集成订正	1.01^*	0.96	1.10^*
A1712	地形订正	0.75	0.89	1.06
	支持向量机	0.83	0.86	1.02
	集成订正	0.75^*	0.88	1.05
A1489	地形订正	1.49	1.54	1.64
	支持向量机	1.30	1.33	1.38
	集成订正	1.34	1.40	1.45
注：*表示集成订正方法不高于地形订正方法和支持向量机方法。

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Table 3 Thresholds of 2 m temperature at different stations (unit:℃)

站号	超低温阈值	超高温阈值
A1701	-15.8	-4.9
A1703	-13.6	-2.7
A1705	-10.6	-0.6
A1708	-9.1	0.7
A1710	-12.6	-2.9
A1711	-12.0	-1.5
A1712	-10.2	-0.3
A1489	-8.0	2.1

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