| 探空观测黑名单检查在变分同化系统中的应用 |
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| 引用本文： | 庄照荣,薛纪善,韩威,刘艳.探空观测黑名单检查在变分同化系统中的应用[J].应用气象学报,2014,25(3):274-283. |
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| 作者姓名： | 庄照荣 薛纪善 韩威 刘艳 |
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| 作者单位： | 1.国家气象中心，北京 100081 |
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| 基金项目： | 资助项目：国家自然科学基金项目（41305092），公益性行业（气象）科研专项（GYHY201206007），中国气象局数值预报中心GRAPES发展专项（GRAPES FZZX 2013 04） |
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| 摘 要： | 针对探空观测资料使用造成的某些区域GRAPES分析场存在虚假的高、低压系统问题，该文通过对比全球探空资料的位势高度观测与NCEP分析场，统计站点中观测质量较差的时次出现频数，确定探空位势高度观测黑名单。研究表明:500 hPa在印度地区、北大西洋和南极洲附近的探空位势高度观测与NCEP分析场的均方根误差在30 gpm以上的站点较多，且位势高度观测不可靠观测比率为20%以上的站点主要集中这些区域，以上观测站均列入黑名单。文中在GRAPES全球三维变分分析场的质量控制中加入探空位势高度观测黑名单检查，通过6 h分析预报循环试验表明:探空位势高度观测黑名单检查能有效提高分析场质量，GRAPES位势高度分析场在南极洲附近和印度地区有所改善。
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| 关 键 词： | 探空观测 黑名单 三维变分同化 分析预报循环 |
| 收稿时间： | 2013-05-14 |
| 修稿时间： | 3/6/2014 12:00:00 AM |
The Application of Radiosonde Observation Blacklisting Check to Variable Data Assimilation System |
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| Zhuang Zhaorong,Xue Jishan,Han Wei and Liu Yan.The Application of Radiosonde Observation Blacklisting Check to Variable Data Assimilation System[J].Quarterly Journal of Applied Meteorology,2014,25(3):274-283. |
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| Authors: | Zhuang Zhaorong Xue Jishan Han Wei and Liu Yan |
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| Institution: | 1.National Meteorological Center, Beijing 1000812.Center for Numerical Prediction, CMA, Beijing 1000813.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081 |
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| Abstract: | The radiosonde observations are very important for the numerical weather forecasting as they are more reliable data compared to other observations in the assimilation system. The radiosonde observation needs serious quality controlling before used in data assimilation, and the blacklisting check which uses monthly blacklist to delete the abnormal noise and bias data compared with background field is a significant step in observation quality monitoring. At present the radiosonde observations used in GRAPES (Global-Regional Assimilation and PrEdiction System) analysis system are scanned through preliminary checks such as climatological extreme check, consistency checks and background quality control in data assimilation system, but blacklisting check is not included. For the spurious high/low-pressure system structure of GRAPES analysis caused by the radiosonde observation in some region, the radiosonde observations are analyzed through comparing with NCEP analysis from June to August in 2007. Results show that the bias of radiosonde geopotential height observation and NCEP analysis is less than 50 gpm under 100 hPa. The bias is much bigger over 100 hPa and the radiosonde geopotential height is much smaller than NCEP analysis. Stations where the root mean square errors of the geopotential height between radiosonde observations and NCEP analysis for 500 hPa exceed 30 gpm are located in India, North Atlantic Ocean and Antarctic region. In those regions the unreliable observation ratios of some stations are above 20%, so they are listed in the blacklist. The geopotential height blacklist of radiosonde is provided by comparing observations with NCEP analysis and estimating the frequency of bad observation-quality station. The geopotential height blacklisting check of radiosonde is applied to GRAPES global 3D-var analysis system, and the cycle experiments of the analysis and forecast from 1 July to 21 July in 2009 are carried out. Two experiments are performed, Experiment 1 (control test) without blacklisting check and Experiment 2 with blacklisting check. The results indicate that the quality of geopotential height analysis of GRAPES is improved in India and Antarctic regions when considering geopotential height blacklist. The average root mean square errors of geopotential height GRAPES analysis and NCEP analysis for 500 hPa is reduced by 6 gpm in India Region and near 10 gpm in Antarctic Region after using blacklisting check in the 3D-var analysis system. In Antarctic region, the average biases and root mean square errors of geopotential height GRAPES analysis and NCEP analysis both decrease from 1000 hPa to high levels. The blacklisting check of radiosonde observation is a necessary step in the analysis system. The updated blacklist information will be used to assimilate the radiosonde observation more effectively. |
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| Keywords: | radiosonde observation blacklist three dimensional variable data assimilation analysis and forecast cycle |
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