Journal of Arid Meteorology ›› 2022, Vol. 40 ›› Issue (3): 485-499.DOI: 10.11755/j.issn.1006-7639(2022)-03-0485
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WANG Junchao1,2,3(), WANG Zhibin1(
), LAI Anwei1,2, XIAO Yanjiao1, WANG Jue1
Received:
2021-07-13
Revised:
2021-11-23
Online:
2022-06-30
Published:
2022-06-28
Contact:
WANG Zhibin
王俊超1,2,3(), 王志斌1(
), 赖安伟1,2, 肖艳姣1, 王珏1
通讯作者:
王志斌
作者简介:
王俊超(1982—),男,硕士,高级工程师,主要从事数据融合和系统分析集成研究. E-mail: nanxingong@163.com。
基金资助:
CLC Number:
WANG Junchao, WANG Zhibin, LAI Anwei, XIAO Yanjiao, WANG Jue. Experimental study on short-term and impending prediction of precipitation echo based on blending method of numerical prediction and radar extrapolation prediction[J]. Journal of Arid Meteorology, 2022, 40(3): 485-499.
王俊超, 王志斌, 赖安伟, 肖艳姣, 王珏. 基于数值预报与雷达外推预报融合方法的降水回波短临预报试验研究[J]. 干旱气象, 2022, 40(3): 485-499.
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URL: http://www.ghqx.org.cn/EN/10.11755/j.issn.1006-7639(2022)-03-0485
降水过程 | 强降水时段(北京时) |
---|---|
“6·12” | 6月12日02:00—06:00和18:00—23:00 |
“6·27” | 6月27日20:00至28日08:00 |
“7·02” | 7月2日08:00—18:00 |
“7·05” | 7月5日04:00—12:00和5日23:00至6日06:00 |
Tab.1 The occurrence period of heavy precipitation during four precipitation processes from June to July 2020 in Hubei Province
降水过程 | 强降水时段(北京时) |
---|---|
“6·12” | 6月12日02:00—06:00和18:00—23:00 |
“6·27” | 6月27日20:00至28日08:00 |
“7·02” | 7月2日08:00—18:00 |
“7·05” | 7月5日04:00—12:00和5日23:00至6日06:00 |
Fig.3 Comparison of 1-hour precipitation echo forecast with different scales from radar extrapolation (a, e),RUC-Wuhan model (b, f) and blending technology (e, g) initiated from 12:00 UTC 12 June 2020 with the observation of radar (d, h) (Unit: dBZ) (The red box represents the intensive region of heavy precipitation. the same as below) (a, b, c, d) 0.01°× 0.01°, (e, f, g, h) 0.02°× 0.02°
Fig.4 Comparison of 1-hour precipitation echo forecast with different scales from radar extrapolation (a, e), RUC-Wuhan model (b, f) and blending technology (e, g) initiated from 16:00 UTC 5 July 2020 with the observation of radar (d, h) (Unit: dBZ) (a、b、c、d)0.01°× 0.01°,(e、f、g、h)0.04°× 0.04°
Fig.5 The change of average Bias of precipitation echo prediction by three methods for different thresholds with prediction time for four precipitation processes (a)10 dBZ,(b) 20 dBZ,(c) 30 dBZ,(d) 40 dBZ
Fig.6 The change of average Bias of 0-1 h precipitation echo prediction by three methods for different scales with thresholds for four precipitation processes (a)0.01°× 0.01°,(b)0.02°× 0.02°,(c)0.04°× 0.04°,(d)0.08°× 0.08°
Fig.7 The change of average ETS scores of precipitation echo prediction by two methods for different thresholds with prediction time for four precipitation processes (a)10 dBZ,(b)20 dBZ,(c)30 dBZ,(d)40 dBZ
Fig.8 The change of average ETS scores of 0-1 h precipitation echo forecast by three methods for different scales with thresholds for four precipitation processes (a)0.01°× 0.01°,(b)0.02°× 0.02°,(c)0.04°× 0.04°,(d)0.08°× 0.08°
Fig.9 The change of average POD (a, b, c, d) and MAE (e, f, g, h) of blending forecast for different thresholds with forecast time for four precipitation processes (a、e)10 dBZ,(b、f)20 dBZ,(c、g)30 dBZ,(d、h)40 dBZ
Fig.10 The change of average POD (a, b, c, d) and MAE (e, f, g, f) by three forecasts for different scales with thresholds for four precipitation processes (a、e)0.01°× 0.01°,(b、f)0.02°× 0.02°,(c、g)0.04°× 0.04°,(d、h)0.08°× 0.08°
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