【摘要】 利用卫星可见光/红外资料遥感降水有其独特的优势,依据该资料反演获得的云光学厚度和云滴有效半径被证明能够对降水判别产生明显效应。以现有两种降水云识别方案为基础,进一步考察云顶红外亮温信息的价值,探索了红外亮温、云光学厚度及云滴有效半径综合信息对降水事件的指示能力。选取2006和2007年夏季热带测雨卫星(TRMM)可见光/红外辐射计(VIRS)和测雨雷达(PR)的融合观测资料,以PR探测为真值,采用3种二元预报评价因子对识别结果进行了评估,并与现有降水云识别方案进行了比较。研究表明:由于引入了云顶红外亮温信息,降水云识别能力比仅采用光学厚度和有效半径的方案明显提高。无论陆地还是海洋区域,新增红外亮温信息之后,能够更有效地识别弱降水,出现降水误判和漏判的区域面积比现有方案更小。特别是在洋面上,降水云识别比率达79%,而同时对非降水云的误判率仅为8%,相应其CSI、ETS和HSS因子值明显提升。以此为基础建立的IPCTC方案适用于常见星载多通道可见光/红外探测仪,可应用于卫星实时降水监测。更多还原

【Abstract】 Satellite visible and infrared observations have their own advantages in precipitation remote sensing,it`s proved that cloud optical thickness and effective radius,retrieved from visible and infrared observations,and have obvious effects in discriminating precipitation.Based on two existing precipitating clouds identification schemes,infrared bright temperature is added and the abilities of discriminating precipitation events from infrared bright temperature,optical thickness and effective radius are explored in this study.Comparisons to PR standard rain products from 2006 to 2007 boreal summers are conducted to verify the IPCTC results,in which three dimidiate-forecast factors are utilized and three existing precipitating-cloud identification schemes are also evaluated.The study shows that,by adding infrared bright temperature information,the capability of the new scheme in identifying precipitation has significantly improved.After adding infrared bright temperature information,weakly rainy areas can be identified more effectively,and both the missing and false alarm areas are spatially very smaller and narrower than the existing methods,which gives better performance both in land and oceanic areas.Especially,in oceanic areas,about 79% of rainy pixels observed by PR are correctly determined,and the probability of false detection remains just 8%,and the CSI,ETS and HSS factor values increase significantly.The IPCTC,which is proposed on these bases,is available for common multi-channel visible and infrared sensors,and can be applied in real-time satellite precipitation monitoring.更多还原