郝民,龚建东,王瑞文,万晓敏,刘艳. 2015. 中国L波段探空湿度观测资料的质量评估及偏差订正[J]. 气象学报, 73(1):187-199, doi:10.11676/qxxb2015.002
中国L波段探空湿度观测资料的质量评估及偏差订正
The quality assessment and correction of the radiosonde humidity data biases of L-band in China
投稿时间:2014-03-03  修订日期:2014-08-04
DOI:10.11676/qxxb2015.002
中文关键词:  探空观测  湿度偏干  偏差订正  同化预报
英文关键词:Radiosonde observation  Humidity drier than normal  Bias correction  Assimilation prediction
基金项目:公益性行业(气象)科研专项(GYHY201106008)、国家自然科学基金项目(41275105、41375107)。
作者单位
郝民 国家气象中心, 中国气象局数值预报中心, 北京, 100081 
龚建东 国家气象中心, 中国气象局数值预报中心, 北京, 100081 
王瑞文 国家气象中心, 中国气象局数值预报中心, 北京, 100081 
万晓敏 国家气象中心, 中国气象局数值预报中心, 北京, 100081 
刘艳 国家气象中心, 中国气象局数值预报中心, 北京, 100081 
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中文摘要:
      L波段探空观测资料无论在天气预报还是数值预报中均为最基本和最重要的一类数据,而其湿度观测资料的质量对同化分析及降水预报有直接影响。通过用L波段探空湿度观测资料与不同类型的其他观测反演的湿度资料互校及与NCEP、GRAPES、EC等不同模式分析场为背景的湿度场比较,评估中国L波段探空湿度观测资料的质量状况,对探空湿度资料的质量有了新的认识,为更好地使用该资料提供依据。研究发现中国L波段探空湿度观测资料存在偏干的现象,特别是当背景场湿度大于60%时,观测湿度偏低更加明显。通过分析其偏差特征,找出了适合中国L波段探空湿度观测资料偏差特点的分段函数订正方法。个例试验表明,对探空湿度观测资料的偏差订正后,观测偏差明显减小,订正效果非常显著;模式降水强度预报能力有一定的提高。从连续试验检验的降水预报评分(TS)和预报偏差(Bias)看,中雨和暴雨的预报在探空湿度观测偏差订正后都表现出正效果。
英文摘要:
      The radiosonde observation data of L-band has been one kind of the most basic and important data used in either the weather forecast or the numerical prediction, and its quality for humidity observations has a direct impact on the precipitation forecast. In this study, by calibrating the humidity data from the radiosonde observations with those derived from other type observations and comparing to the background fields based on the NCEP, GRAPES and EC modeling analyses, the qualities for the humidity data from radiosonde observation of L-band in China were assessed. So we could have a new understanding about the quality of the radiosonde observation, which would provide basis information for better use of the data.It was found that these sounding humidity tended to be drier than the analyses, thus the piecewise functions were applied for the humidity data correction. When the humidity was more than 60% in the background field, the deviation of the radiosonde observations for humidity would be significant, and the correction effect would become very prominent. The results of case studies and continuous experiments showed that the forecasting capabilities of precipitation intensity could be significantly improved after applying the bias correction for sounding humidity observations. Meanwhile, in term of precipitation forecast test score (TS) and forecasting bias (B), the humidity correction could obviously have positive effects on both the moderate and torrential rain forecasts.
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