基于机载多普勒雷达数据的飓风内部三维风场反演算法

利用2002年NOAA海洋飓风实验中三维风雨微波成像仪(IWRAP,UMass Imaging Wind and Rain Airborne Profiler)数据,提出了两种自适应卡尔曼滤波算法进行飓风三维风矢量的反演。为验证不同自适应滤波算法的准确性,通过对实际风场以及相应的机载雷达观测数据进行仿真,得到一种最优自适应滤波;文中对滤波结果误差进行了初步分析,探讨了误差来源。根据仿真结果,利用最优自适应滤波对2002年10月2日飓风莉莉多普勒雷达测量数据进行处理,滤波得到的三维风场与本次实验中GPS下投式探空仪的三维风场同步测量数据,多波段微波辐射计的海面风场测量数据,以及飞机高度风场数据进行了比较。

3-D Hurricane Wind Retrieval Algorithm with Airborne Doppler Radar Measurements

This paper presents two Adaptive Kalman Filter Algorithms to retrieve the 3-D hurricane wind vectors. The algorithms are developed for the measurements of UMass Imaging Wind and Rain Airborne Profiler which was installed on the NOAA WP-3D research aircraft during the 2002 NOAA Hurricane Ocean Winds Experiment. Performance analyses of the algorithms are presented in this paper using simulation. Preliminary results of the actual 3-D wind estimates using the chosen algorithm are obtained and compared with simultaneous and independent wind vector measurements by GPS dropwindsondes, surface wind speed measurements by a microwave radiometer and flight level wind vector measurements.