| 红外高光谱IASI卫星资料同化对一次大风过程的影响研究 |
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| 引用本文： | 许冬梅,李玮,武芳,闵锦忠.红外高光谱IASI卫星资料同化对一次大风过程的影响研究[J].新疆气象,2022,16(1):124-132. |
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| 作者姓名： | 许冬梅 李玮 武芳 闵锦忠 |
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| 作者单位： | 南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心,南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心,六安市气象局,南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心 |
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| 基金项目： | 国家自然科学(G41805016); 江苏省自然科学(BK20170940); 中国气象局沈阳大气环境研究所和东北冷涡研究重点开放实验室联合开放(2020SYIAE02, 2020SYIAE07); 高原与盆地暴雨旱涝灾害四川省重点实验室开放研究(SZKT201901, SZKT201904) |
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| 摘 要： | 以2019年4月24日发生在辽宁省的一次大风天气过程为例,选取GFS(全球预报系统) 0.25°×0.25°再分析资料,基于WRF模式三维变分同化技术,进行一组IASI资料同化试验,和未同化任何资料的控制试验(CTNL)。通过对比两组试验结果考察IASI资料同化改进数值模式初始场的分析及其后续预报的机制。研究结果表明：经过IASI资料同化的模拟结果质量有很大改善,分析场与背景场相比更靠近观测场；经过云检测之后不同通道使用的观测数目多少不一,资料同化对模拟的改善效果在通道0~800最佳；IASI资料同化对地表10 m风场的预报技巧有显著的提高作用,相比控制试验可以更精准地预报大风天气的区域和强度；IASI同化试验的预报质量高于控制试验且随时间比较稳定。
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| 关 键 词： | IASI WRF模式 资料同化 大风预报 |
| 收稿时间： | 2020/8/22 0:00:00 |
| 修稿时间： | 2020/11/3 0:00:00 |
Impact of assimilating IASI infrared radiances on the numerical results of a strong wind case |
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| Institution: | nanjing university information science and technology,,, |
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| Abstract: | A strong wind event that occurred in Liaoning Province on April 24, 2019 is selected as a study case for the numerical simulation and data assimilation. The simulation applies the GFS (Global Forecast System) 0.25 × 0.25 reanalysis data, based on the WRF (Weather Research and Forecasting). The impact of IASI data assimilation on improving the initial field and the mechanism of subsequent prediction are investigated by conducting two experiments. Based on the three-dimensional variational assimilation method, a IASI data assimilation experiment and a control experiment (CTNL) without any data assimilation processing were conducted. The results show that, the quality of the simulation results after IASI data assimilation has been greatly improved. The analysis field fits better with the observation field than the background field. For the cloud detection procedure, the number of observations is dependent on the weighting peak of the channels. The improvement of the data assimilation on the simulation is significant in channels 0 ~ 800; The forecasting skills of the 10-meter wind field on the surface are obviously enhanced with the IASI data assimilation. Compared with the control experiment, it is able to more accurately predict the location and the intensity of windy fields; The forecast quality of the IASI assimilation experiment is higher than that of the control experiment and is relatively stable with the forecast leading time. |
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| Keywords: | IASI WRF mode data assimilation gale forecast |
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