摘要
应用FY-3A微波湿度计2010年1月份的Level-1c观测亮度温度O,NCEP GFS 6 h的预报场作为背景场,用RTTOV 9.3版本辐射传输模式模拟的亮度温度B以及美国NOAA-18 MHS业务微波地表和降水产品,研究了双权重质量控制算法对FY-3A MWHS通道3至5云和降水视场的识别能力。研究表明双权重质量控制算法判断的负观测增量O-B的离群点中,大多数都受云和降水影响。通道3约占60%,通道4约80%,通道5超过80%。当降水率大于0.2 mm·h-1时,通道3负离群点可识别超过60%降水云,随着降水率增大识别率超过80%。而通道4对大于0.2 mm·h-1的降水的识别率超过90%。通道5负离群点几乎可以剔除100%的降水影响资料。在目前还没有MWHS自身云检测产品的条件下,双权重质量控制算法可剔除大部分云和降水影响视野。
The ability that using bi-weighting quality control to identify FY-3A MWHS （Microwave Humidity Sounder） channel 3 -5 clouds has been researched in this paper. The used data include FY-3A MWHS observed brightness temperature （O）, simulated brightness temperature （B） by the Radiative Transfer Model（9.3V） based on 6 h forecast fields of the National Centers for Environmental Pre diction, Global Forecast System（GFS） and NOAA-18 MHS retrieval products generated by NOAA Micro wave Surface and Precipitation Products System during January 2010. The results show most of the nega tive O-B outliers identified by bi-weighting quality control are influenced by cloudy or rainy conditions. The percentage（ % ） of cloudy data shows all the negative outliers from FY-3A MWHS channel 3 to channel 5 are about 60% ,80% and over 80% respectively. The high matching percentage between negative O-B outliers and precipitating clouds by traditional cloud-detection algorithm is over 60% for channel 3, more than 90% for channel 4 and nearly 100% for channel 5 when the rain rate is more than 0.2 ram. h-1, which confirms that O-B can identify precipitable clouds quite well. The lack of 89 GHz prohibits the application of traditional cloud-detection algorithm to FY-3A microwave sounding data in NWP, how ever the bi-weighting quality control of O-B can identify most cloudy or rainy effects.
出处
《气象科学》
CSCD
北大核心
2013年第5期536-542,共7页
Journal of the Meteorological Sciences
基金
国家自然科学基金资助项目(41175034)
