This study examines the effects of cumulus parameterizations and microphysics schemes on the track forecast of typhoon Nabi using the Weather Research Forecast model. The study found that the effects of cumulus parameterizations on typhoon track forecast were comparatively strong and the typhoon track forecast of Kain-Fritsch (KF) was superior to that of Betts-Miller (BM). When KF was selected, the simulated results would be improved if microphysics schemes were selected than otherwise. The results from Ferrier, WSM6, and Lin were very close to those in the best track. KF performed well with the simulations of the western extension and eastern contraction changes of a North Pacific high as well as the distribution and strength of the typhoon wind field.
利用傅里叶相位分析方法与最大相关法结合的云导风技术TCFM(Technique based on combination of Fourier phase analysis and maximum correlation),对2005-08-05的强热带风暴"麦莎"天气过程中静止气象卫星得到的30min间隔云图时间序列进行导风计算,并将导风结果应用于中尺度数值模式ARPS(The Advanced Regional Prediction System),结合其资料分析系统ADAS(ARPS Data Analysis System),对台风"麦莎"登陆前的过程进行模拟。尽管洋面上常规资料稀缺,但卫星导风数据的同化使用结果表明,TCFM技术得到的导风资料能够显著改善台风眼壁东部区域的垂直气流活动,使台风螺旋雨带更加明显,符合实际。
The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors （AMVs） in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference （NEdT） performance of FY-2E split win- dow （10.3-11.5 μm, 11.6-12.8 μm） channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference （SD） methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the ＂truth＂. The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.
