The Recognition Method Of Potential Aircraft Icing Area Using Satellite Data

Aircraft icing threaten the safety of flight seriously, there has a certain significance to guarantee normal operation of flight and save the cost of the company if we can know distribution of the potential aircraft icing area before the delivery.Aiming at the existing aircraft icing detection and forecast mainly depend on synoptic method and the results accuracy is low and bounded by specific scope of space and time, combined with the using of satellite data, this paper put forward a recognition method of potential aircraft icing area using cloud micro physical parameters provided by satellite data in order to get icing probability and icing intensity of the large area. Firstly, used the cloud product data from MODIS to verify the availability and reliability of selected ice algorithm. Secondly described the steps of retrieving cloud physics parameters using FY-2F satellite data and analyzed the error and verified a case and a forecast of aircraft icing using retrieved cloud physics parameters. Finally, designed the potential icing region information service system through programming.Results show that the ice algorithm can accurately judge the geographic range of potential aircraft icing area, probability of icing and intensity of icing. In three cases, the analysis results are consistent with the actual situation of case2and case1. Due to low altitude of aircraft report point, the analysis icing intensity of case3higher than reported value.Compared cloud micro-physical parameter from FY-2F satellite with cloud product from MODIS data, they have a good consistency in the spatial distribution, but results from FY-2F have obvious differences in value from results of MODIS. On one hand, the optical thickness of the inversion results have relatively large differences, the consistency of the distribution area values correspond to is not good, the numerical range of inversion results are smaller decades than the one of MODIS. On the other hand, Effective particle radius has good spatial distribution with MODIS cloud product, the consistency of the distribution area values correspond to is consistent, but the inversion results have poor continuity.It is found the probability and intensity of potential aircraft icing area are consistent with the case and the forecast using cloud physical parameters inversed. It shows that the cloud micro physical parameters provided by satellite data can effectively identify potential aircraft icing area.