Applicability Evaluation of Provincial Precipitation Real-time Analysis Product in Beijing

Zhao Wenfang; Wang Huiying; Meng Huifang; Miao Yupeng; Huang Mingming; Fan Min; Tang Wei

doi:10.11898/1001-7313.20240309

Vol.35, NO.3, 2024

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Article Navigation > Journal of Applied Meteorological Science > 2024 > 35(3): 361-372

Zhao Wenfang, Wang Huiying, Meng Huifang, et al. Applicability evaluation of provincial precipitation real-time analysis product in Beijing. J Appl Meteor Sci, 2024, 35(3): 361-372. DOI: 10.11898/1001-7313.20240309.

Citation:

Zhao Wenfang, Wang Huiying, Meng Huifang, et al. Applicability evaluation of provincial precipitation real-time analysis product in Beijing. J Appl Meteor Sci, 2024, 35(3): 361-372. DOI: 10.11898/1001-7313.20240309.

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Applicability Evaluation of Provincial Precipitation Real-time Analysis Product in Beijing

DOI: 10.11898/1001-7313.20240309

1.
Beijing Meteorological Data Center, Beijing 100089
2.
National Meteorological Information Center, Beijing 100081
3.
CMA Institute for Development and Program Design, Beijing 100081

Received Date: 2024-01-08
Rev Recd Date: 2024-03-25
Publish Date: 2024-05-31

Abstract

Abstract

The national precipitation real-time analysis product is a gridded product developed using probability density matching, Bayesian model averaging, multi grid variation, optimal interpolation and other technologies by National Meteorological Information Center. It has advantages of high accuracy, high quality, and spatiotemporal continuity, and is widely used in national nowcasting forecasting operations. In September 2022, National Meteorological Information Center issues a provincial multi-source fusion real-time analysis system to promote the collaborative application of precipitation analysis in different provinces. The same core multi-source fusion algorithms for real-time precipitation analysis products are applied in this system, allowing access to additional provincial local observations. The consistency and accuracy of the provincial precipitation analysis products in Beijing from September 2022 to August 2023 are evaluated by automatic weather station observations, error analysis, effective precipitation time proportion, and other methods. "23·7" extreme precipitation event is also analyzed in terms of cumulative precipitation, precipitation intensity, and hourly precipitation error. Results show that root mean square error of the provincial precipitation analysis product is less than 1 mm, and the average absolute deviation is below 0.16 mm, which closely aligns with observations from automatic weather stations. The bias of provincial precipitation real-time analysis product increases with magnitude of precipitation. The intensity of light rain exceeds the observation, while the spatial distribution difference of bias is evident. The maximum negative deviation occurs in both moderate rain and rainstorm magnitudes of Yanqing, while the maximum positive deviation is observed at Changping. During the extreme precipitation event of "23·7", the spatial distribution of provincial precipitation real-time analysis product is largely consistent with observations from automatic weather stations. The precipitation intensity is consistent with the trend of time variation observed by automatic weather stations, with an average root mean square error of 1.8 mm and an average absolute deviation of 0.806 mm, which more accurately reflects the trend of precipitation intensity variation. Overall, the provincial precipitation real-time analysis product has high accuracy in Beijing and can reflect the spatial distribution of precipitation, but the estimate is lower than the observation in the precipitation course of local heavy rainstorm.
- real-time analysis product;
- skill scoring;
- multi-source fusion;
- accuracy evaluation

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Figures and Tables

Fig. 1 Monthly root mean square error, mean absolute bias and mean bias of provincial precipitation real-time analysis product interpolation results to observations of all verification stations from Sep 2022 to Aug 2023

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Fig. 2 Bias and bias rate of all verification stations for moderate rain and rainstorm

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Fig. 3 Spatial distributions of bias and bias rate of all verification stations for moderate rain and rainstorm

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Fig. 4 Hourly root mean square error and mean bias of provincial precipitation real-time analysis product in the 3rd and the 12th precipitation courses

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Fig. 5 Percentage of effective precipitation hours in observation and provincial precipitation real-time analysis product for different daily precipitation and hourly precipitation classifications in Beijing in the summer of 2023

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Fig. 6 Spatial distribution of accumulation precipitation in observation and provincial precipitation real-time analysis product from 2000 BT 29 Jul to 0700 BT 2 Aug in 2023

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Fig. 7 Hourly root mean square error(a), precipitation intensity(b) and estimated precipitation at Xincun, Fangshan(c) in provincial precipitation real-time analysis product from 2000 BT 29 Jul to 0700 BT 2 Aug in 2023

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Table 1 Bias and bias rate of provincial precipitation real-time analysis product at different hourly precipitation classifications

小时降水量等级	偏差/mm	偏差率/%
小雨(0.1~1.5 mm)	0.01	3.59
中雨(1.6~6.9 mm)	-0.23	-4.54
大雨(7.0~14.9 mm)	-0.68	-5.38
暴雨(15.0~29.9 mm)	-1.23	-5.74
大暴雨(不低于30 mm)	-1.76	-7.95

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Table 2 13 precipitation courses in the summer of 2023

降水过程序号	开始时间	结束时间	累积降水量/mm	持续时长/h	降水量均方根误差/mm
1	06-03T13:00	06-04T03:00	144.3	15	0.02
2	06-28T06:00	06-28T16:00	4644.8	9	0.52
3	07-03T19:00	07-04T12:00	7534.3	18	0.33
4	07-10T19:00	07-11T05:00	1670.9	11	0.39
5	07-20T17:00	07-22T20:00	32373.7	52	0.24
6	07-23T14:00	07-24T03:00	597.7	14	0.99
7	07-24T19:00	07-25T03:00	7312.0	9	0.42
8	07-27T17:00	07-28T06:00	5104.0	14	1.80
9	07-29T20:00	08-02T07:00	155530.8	84	0.04
10	08-05T20:00	08-06T04:00	79.1	9	0.21
11	08-09T16:00	08-10T08:00	433.0	17	0.31
12	08-11T09:00	08-12T08:00	7320.9	24	0.72
13	08-20T12:00	08-21T08:00	15417.4	21	0.28

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