摘要
目前GRAPES-3DVar(全球\区域同化预报系统)使用的AIRS云检测方案只能够检测出完全晴空时的视场资料,对于受到云污染的视场,所有通道资料全部被剔除。研究表明有云视场当中的云顶以上资料对数值预报的影响更加重要,研究也更加有意义。因此,文章借鉴McNally和Watts云检测方案,结合GRAPES-3DVar系统和仪器特征,建立了一种适合于GRAPES-3DVar模式的晴空通道检测方案。该方案不但可以检测出完全晴空的视场资料,同时也可以检测出有云视场当中不受云影响的云顶以上通道资料;另外,还可以求出云顶高度,判断出高、中和低云。然后,将AIRS观测资料分别用晴空视场检测方案和晴空通道检测方案进行云检测,从结果分析看,晴空视场检测方案可以检测出的晴空资料占总资料的9.14%,而晴空通道检测方案检测出的晴空资料达到了34.86%,是传统云检测方案的3.8倍,大大增加了资料的使用度。
Currently the method which GRAPES-3DVar （global／regional assimilation and prediction sys- tem） used can only detect the data of clear FOV, the whole channel data needs to be removed if the FOV is polluted by cloud. In fact, studies have shown that the data above cloud top in cloud FOV is more impor- tant to numerical prediction. Therefore, refering to McNally and Watts cloud detection schemes and, com- bining GRAPES-3DVar system and instrument characteristics, we built a detection scheme which is suit able for GRAPES 3DVar mode. This scheme can not only detect the field data of clear sky, but also detect the channel data above cloud top which is not influenced by cloud in cloud FOV. Besides, it can calculate the height of cloud top, and judge the cloud base of high, middle and low cloud. The detection scheme for the field view of clear sky cloud and the detection scheme for clear channel cloud are used to detect the AIRS observational data. The results show that the clear data detected by the field view of clear skyscheme stands for a 9.14% of the total and those by the clear channel cloud detection scheme the rate reaches 34.86%, 3.8 times more than the traditional cloud detection scheme.
出处
《气象》
CSCD
北大核心
2013年第5期633-644,共12页
Meteorological Monthly
基金
公益性行业(气象)科研专项(GYHY200806003和GYHY2011 06008)
山东省超级计算科技专项项目(2011YD01106)共同资助
