李华宏,王曼,薛纪善,杞明辉. 2008. FY-2C云迹风资料在中尺度数值模式中的应用研究[J]. 气象学报, 66(1):50-58, doi:10.11676/qxxb2008.005
FY-2C云迹风资料在中尺度数值模式中的应用研究
A study on the application of FY-2C cloud drift wind in a mesoscale numerical model.
投稿时间:2006-04-30  修订日期:2006-12-06
DOI:10.11676/qxxb2008.005
中文关键词:  云迹风,质量控制,变分同化,暴雨预报
英文关键词:Cloud drift wind, Quality control, Variational assimilation, Torrential rain forecast
基金项目:云南省气象局项目“精细化预报系统研究”和国家重点基础研究发展计划项目“我国南方致洪暴雨与预测的理论和方法研究”
作者单位
李华宏 季风与气象灾害研究开放试验室昆明650034
云南大学大气科学系昆明650091 
王曼 云南省气象科学研究所昆明650034 
薛纪善 中国气象科学研究院灾害天气国家重点实验室北京100081 
杞明辉 云南大学大气科学系昆明650091 
摘要点击次数: 2789
全文下载次数: 2372
中文摘要:
      利用探空观测资料对FY-2C云迹风资料进行统计检验和误差分析,并针对其误差特征进行偏差订正和热成风原理两种方法的质量控制。然后通过GRAPES-3Dvar同化到GRAPES Meso模式中,对2005年7月1日00时至7月2日00时发生在中国西北部的一次暴雨过程进行了数值对比试验。结果表明:云迹风数量在垂直方向上主要集中分布于500 hPa以上的对流层中高层,在250 hPa附近数量分布概率最大;高度在500 hPa以下云迹风存在明显的风向误差和很大的风速误差,而且误差分布发散,可用性较差。500 hPa以上层次的云迹风误差较小,且误差分布呈高斯分布具有一定的系统特性,可用性较好;通过质量控制后,可以把风向错误或风速偏差太大的云迹风予以剔除,进一步提高云迹风的精度;同化云迹风资料后,在暴雨区附近初始风场低层的西南气流明显加强,有利于暴雨区水汽输送和水汽辐合,最终能很好地改善24 h暴雨预报的强度和落区。
英文摘要:
      Though the cloud drift wind (CDW) has displayed its good application perspective in numerical weather prediction (NWP), up to the present the CDW data are not actually applied to the daily operation of NWP. The main reason is that the CDW data have abnormal error, and moreover, study on the errors and quality control of CDW data is very lacking. Further research is needed in order to effectively utilize the CDW data in the daily NWP. This paper attempted to explore the systematic error character of FY-2C CDW and its effects on the initial fields and forecast results of NWP model so as to promote the application of CDW data in operational NWP. At first, statistical test and error analysis to the CDW data of FY-2Cwere performed in terms of the radiosonde observations; the quality control of each record of the CDW data was realized individually through the systematic bias correction and the check of thermal wind relation; then, the CDW records after quality control were incorporated into and assimilated in the GRAPES Meso model by the GRAPES 3Dvar scheme; and at last, the effect of the CDW data were examined through the contrast experiments of a torrential rain event in Northwest China in the period from 00:00 UTC 1 to 00:00 UTC 2 July 2005. The analysis results of the CDW data indicate that: the number of CDWs vertically, mainly distributed in the mid upper troposphere above 500 hPa, with the maximum number at about 250 hPa. The CDW under 500 hPa was characteristic of wind direction error, large wind speed error and divergent error distribution, and therefore it has a bad usability; while the CDW above 500 hPa was characteristic of smaller wind direction and speed errors and a Gaussian error distribution, and therefore it has a better usability. Seeing that the CDW at higher levels had systemic bias error and the wind was coherently distributed in the vertical direction, so the bias correction and thermal wind relation were employed to control the quality of the FY-2 CDW data. In the quality control, the CDWs with wind direction error or bigger wind speed error were eliminated, the quality of the CDW used in the assimilation is improved. After the assimilation of CDWs, the southwest airflows near the torrential rain area became stronger in the initial wind fields of numerical experiments, which led to the enhancement of vapor transportation and convergence and finally to the evident improvement of the 24 hours forecast of the torrential rain in rain intensity and area. As a whole the proportional distribution of CDW data was inferior to the radiosonde observations data, but the local CDW was much more denser than the radiosonde observations' near the area of torrential rain occurred. The CDW data reflected information of the local torrential rain synoptic system more particularly and accurately, which is the reason why the 24 hrain forecast in CDW data assimilated experiment is better than the forecast in radiosonde data assimilated experiment. 
HTML   查看全文   查看/发表评论  下载PDF阅读器
分享按钮