[1]杜开连,葛 忆,张佳丽,等.赤山湖流域TIGGE降水预报精度评价研究[J].江苏水利,2020,(07):48-51.
　DU Kailian,GE Yi,ZHANG Jiali,et al.Study on the evaluation of TIGGE precipitation forecast precision in Chishan Lake Catchment[J].JIANGSU WATER RESOURCES,2020,(07):48-51.
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赤山湖流域TIGGE降水预报精度评价研究()
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《江苏水利》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年07期
页码:
48-51
栏目:
水文水资源
出版日期:
2020-07-25

文章信息/Info

Title:
Study on the evaluation of TIGGE precipitation forecast precision in Chishan Lake Catchment
文章编号:
1007-7839(2020)07-0048-04
作者:
杜开连;  葛 忆;  张佳丽;  朱 力
句容市水利局, 江苏 镇江 212400
Author(s):
DU Kailian;  GE Yi;  ZHANG Jiali;  ZHU Li
Jurong Water Conservancy Bureau, Zhenjiang 212400, China
关键词:
TIGGE;  降水预报评估;  多模式集合预报
Keywords:
TIGGE;  precipitation forecast assessment;  multi-model ensemble
分类号:
TV125
文献标志码:
B
摘要:
为了提高赤山湖流域洪水预测预报的能力,对赤山湖流域TIGGE降水预报精度进行了评价研究。将TIGGE的ECMWF、KMA、JMA、UKMO、CMA等5个模式应用于赤山湖流域,基于2015—2019年汛期降雨预报数据和流域实测降雨资料,采用均方误根差指标RMSE和降雨预报三率综合评价指标对这5个模式的预报精度进行了评价。结果表明:在赤山湖流域TIGGE的5个模式中,JMA模式的降水预报精度最高,其次是ECMWF。
Abstract:
In order to improve the ability of flood forecast in Chishan Lake Catchment, the TIGGE precipitation forecast precision was evaluated. The 5 models of TIGGE including ECMWF, KMA, JMA, UKMO and CMA were applied to the Chishan Lake Catchment, and based on the rainfall forecast data of the flood season in 2015-2019 and the measured rainfall data of the watershed, the prediction accuracy of the five models was evaluated by using the mean square root error index RMSE and the three-rate comprehensive evaluation index of rainfall forecast. The results showed that among the five TIGGE models in the Chishan Lake Catchment, the JMA model had the highest precipitation forecast accuracy, followed by ECMWF.

参考文献/References:

[1] THIELEN J, BARTHOLEMES J, RAMOS M H, et al.The European flood alert system-part 1:concept and development[J]. Hydrology and earth system sciences,2009, 13(2):125-140.
[2] SCHAAKE J C, HAMILL T M, BUIZZA R, et al. HEPEX:the hydrological ensemble prediction experiment[J]. Bulletin of the American Meteorological Society, 2006, 3(5):1541-1547.
[3] FRANZ K, AJAMI N, SCHAAKE J, et al. Hydrologic ensemble prediction experiment focuses on reliable forecasts[J]. Eos Transactions American Geophysical Union, 2013, 86(25):239-239.
[4] BOUGEAULT P, TOTH Z, BISHOP C, et al. The THORPEX interactive grand global ensemble[J]. Bulletin of the American Meteorological Society, 2010. 91(8):1059-1072.
[5] HERRERA M A, SZUNYOGH I, TRIBBIA J. Forecast uncertainty dynamics in the THORPEX interactive grand global ensemble(TIGGE)[J]. Monthly Weather Review, 2016, 144(7):2739-2766.
[6] SWINBANK R, KYOUDA M, BUCHANAN P, et al. The TIGGE project and its achievements[J]. Bulletin of the American Meteorological Society, 2016, 97(1):49-67.
[7] 赵琳娜, 吴昊, 田付友, 等. 基于TIGGE资料的流域概率性降水预报评估[J]. 气象, 2010, 36(7):133-142.
[8] BAO H J, ZHAO L N, HE Y, et al. Coupling ensemble weather predictions based on TIGGE database eith Grid-Xinanjiang model for flood forecast[J]. Advances in Geosciences, 2011(29):61-67.
[9] 杜雅玲, 陆桂华, 吴志勇, 等. 基于TIGGE数据的中期降水预报在江苏省的应用效果评估[J]. 南水北调与水利科技, 2017(6):17-25.
[10] CAI Chenkai, WANG Jianqun, LI Zhijai. Improving TIGGE precipitation forecasts using an SVR ensemble approach in the Huaihe River Basin[EB/OL]. Advances in Meteorology. https://doi.org/10.1155/2018/7809302.

备注/Memo

备注/Memo:
收稿日期:2019-12-06
作者简介:杜开连(1974—),男,高级工程师,本科,主要从事水利管理与防汛防旱工作。E-mail:dukailian@163.com
更新日期/Last Update: 2020-07-20