HUANG Zihao,WANG Lei,LI Xiehui.Impact of Microwave Radiance Data Assimilation on Numerical Simulation of Heavy Rainfall in the Three-River-Source Region[J].Journal of Chengdu University of Information Technology,2026,41(01):125-133.[doi:10.16836/j.cnki.jcuit.2026.01.017]
微波辐射资料同化对三江源暴雨数值模拟的影响
- Title:
- Impact of Microwave Radiance Data Assimilation on Numerical Simulation of Heavy Rainfall in the Three-River-Source Region
- 文章编号:
- 2096-1618(2026)01-0125-09
- Keywords:
- Three-River-Source region; extreme rainfall; WRF; assimilation; AMSUA; MHS
- 分类号:
- P456.7
- 文献标志码:
- A
- 摘要:
- 为提升三江源地区降水预报和暴雨的防灾减灾,基于中尺度数值模式WRF,采用WRF-3DVAR方法对2018年7月22-23日该地区一次暴雨过程进行同化敏感实验,对比分析NOAA-19搭载的AMSUA微波温度仪和MHS微波湿度仪上两种同化资料对数值模拟结果的影响。结果表明,对于24 h累计降水预报,同化MHS资料对15 mm以下的降水改善效果显著,同时同化AMSUA、MHS资料对20～35 mm的降水改善效果显著。同化微波辐射资料对500 hPa水汽通量大值区和槽区位置有所改善,其中同化AMSUA资料对高空风改善效果显著。同时同化AMSUA、MHS资料对高空温度和比湿改善效果显著。同化敏感实验证明,同化AMSUA、MHS两种微波辐射资料对三江源地区暴雨数值预报有一定的业务应用价值。
- Abstract:
- To improve precipitation forecasting and enhance disaster prevention and mitigation for the Three-River-Source region, the WRF model, a mesoscale numerical model, was utilized. The WRF-3DVAR method was employed to perform assimilation sensitivity experiments for an extreme rainfall event that occurred in the region from July 22nd to 23rd, 2018. A detailed comparative analysis was conducted to assess the impact of two assimilation datasets from the AMSUA microwave temperature sounder and MHS microwave humidity sounder aboard the NOAA-19 satellite on the numerical simulation results. The results indicate that assimilating MHS data significantly improves precipitation forecasts for accumulations below 15 mm while assimilating both AMSUA and MHS data significantly improves precipitation forecasts in the range of 20-35 mm. Assimilating microwave radiance data improves the identification of high values of water vapor flux and the positioning of trough areas at the 500 hPa level. Specifically, assimilating AMSUA data significantly improves upper-level wind forecasts. Moreover, assimilating both AMSUA and MHS data significantly improves upper-level temperature and specific humidity forecasts. The assimilation sensitivity experiments demonstrate that assimilating the two microwave radiance datasets from AMSUA and MHS holds certain operational values for numerical rainfall forecasting in the Three-River-Source region.
参考文献/References:
[1] 陈德辉,薛纪善.数值天气预报业务模式现状与展望[J].气象学报,2004,62(5):623-633.
[2] Charney J q Fjortoft R,Neumann J.Numerical integration of the barotropic vorticity equation[J].Tellus,1950,2(4):237-254.
[3] 马原,邹晓蕾.气象卫星微波湿度计资料简介[J].气象科技进展,2013,3(6):45-51.
[4] 龚俊强.ATOVS微波资料同化对台风“鲶鱼”(2016)预报的影响[D].上海:华东师范大学,2019.
[5] 希爽,马刚,张鹏.ATOVS微波观测对2008年台风预报影响的初步评估[J].热带气象学报,2014,30(4):700-706.
[6] 李明星,张庆河,杨华.卫星资料连续同化在“威马逊”台风浪模拟中的应用[J].水道港口,2017,38(3):235-239.
[7] 张钊扬,钟剑,周炯,等.AMSU-A资料在台风模拟中的循环同化研究[J].气象与环境科学,2018(4):9-16.
[8] 段华,潘晓滨,臧增亮,等.基于GSI同化系统的卫星辐射率资料的同化试验[J].干旱气象,2015,33(6):895-901.
[9] 毛璐,张述文,王恬,等.集合平方根滤波同化AMSU-A辐射率的观测系统模拟试验[J].兰州大学学报(自科版),2015,51(3):351-357.
[10] 李刚,曲美慧,张华.微波湿度计资料在GRAPES模式中偏差订正方法研究[J].大气科学学报,2016,39(5):653-660.
[11] 曲美慧.ATOVS微波湿度计MHS资料在GRAPES-GFS模式中的同化应用技术研究[D].南京:南京信息工程大学,2015.
[12] 于晓晶,韩威,马秀梅,等.卫星微波辐射资料同化在新疆降水预报中的应用初探[J].暴雨灾害,2018(4):337-346.
[13] 张亚洲,邓文彬,赵文斌.台风暴雨数值预报中ATOVS资料的变分同化试验[J].气象与减灾研究,2012,35(3):8-17.
[14] 张斌,张立凤,熊春晖.ATOVS资料同化方案对暴雨模拟效果的影响[J].大气科学,2014,38(5):1017-1027.
[15] 张利红.ATOVS资料的变分同化及在暴雨预报中的应用研究[D].南京:南京信息工程大学,2006.
[16] 姚秀萍,谢启玉,黄逸飞.中国三江源地区降水研究的进展与展望[J].大气科学学报,2022,45(5):688-699.
[17] 黄桂玲,许清霞.2019年海北州2次夏季大雨形成机制对比分析[J].青海科技,2020,27(1):76-80.
[18] Wang F,Han Y,Van Delst P,et al.JCSDA Community Radiative Transfer Model(CRTM)[C].Proceedings of the 14th International TOVS Study Conference,Beijing,2005.
[19] 刘君,黄江平,董佩明,等.卫星资料循环同化应用对区域数值预报效果影响分析[J].气象,2013,39(2):156-165.
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备注/Memo
收稿日期:2024-04-16
基金项目:第二次青藏高原综合科学考察研究资助项目(2019QZKK0105); 四川省科技计划资助项目(2021YJ0025)
通信作者:李谢辉.E-mail:lixiehui@cuit.edu.cn