Impliment Study On Hyperspectral Atmospheric Infrared Detectors AIRS Cloud Detect And Clear Channels Application Technology

Currently the method which Grapes-3DVar (global\regional assimilation prediction system) used could only detect the clear sky radiance data, this detection scheme is not applicable for the cloud radiance data assimilation. Research shows that in NWP, the region causes the growth of forecast error and some important weather situation occur is often cloudy, so in the cloud sensitive areas should prudent to retain the information without cloud pollution as far as possible and remove the polluted information. This detection scheme is not applicable for the field of view subject to the cloud of pollution. There for, a new cloudy detect plan can make these data increase the degree of using and avoid the discarding of potentially useful information.This paper references the though of cloudy detection by McNally and Watts, create a clear sky channel cloudy detection plan that could be suited to Grapes-3DVar mode, select the optimal threshold, this not only not only can detect the field data of clear sky, can also detect clear sky channel data from the field of cloud that without the effect of cloud, this lay the foundation for cloud data in numeric weather prediction data assimilation system. For AIRS observational data, use the field view of clear sky cloud detection scheme and clear channel cloud detection scheme respectively, from the results, the clear data detected by the field view of clear sky scheme has a9.14%of the total and by the clear channel cloud detection scheme the rate reach34.86%, it is the3.8times the traditional cloud detection scheme. These greatly increase the utilization rate of the data, especially for the high-level data.In all, the GRAPES3D-Var does the assimilation experiment to AIRS radiance data that has been gone through quality control and found that the clear channel cloud detection plan improve the effect of high-level analysis.