Detection of the MJO Signal from QuikSCAT
Detection of the MJO Signal from QuikSCAT
复制标题
QuikSCAT 的 MJO 信号检测
DOI：
10.1175/jtech1822.1
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发表时间：
2005
影响因子：
2.2
通讯作者：
J. O'Brien
中科院分区：
文献类型：
--
作者：
A. Arguez;M. Bourassa;J. O'Brien
摘要利用美国国家航空航天局（NASA）快速散射计（QuikSCAT）卫星上的SeaWinds仪器的风数据，研究了Madden-Julian振荡（MJO）的表面表现形式。MJO信号检测非过滤网格化数据使用扩展的纬向风场，阴影的年度，半年，季风相关的模式。经过带通滤波与Lanczos权重，MJO信号清楚地检测到几个运动学量，包括纬向风速，纬向伪应力，和速度潜力。使用QuikSCAT风提取的MJO与使用NCEP再分析2的提取相比毫不逊色，除了QuikSCAT信号似乎更强大。此外，一个替代的带通滤波技术，使用可变滤波器的权重附近的时间序列端点。该方法使用最小二乘最小化匹配新创建的频率响应函数在边缘区域尽可能接近的预…
Abstract Wind data from the SeaWinds instrument on NASA’s Quick Scatterometer (QuikSCAT) satellite are investigated to ascertain how well the surface manifestation of the Madden–Julian oscillation (MJO) can be resolved. The MJO signal is detected in nonfiltered gridded data using extended EOF analysis of the zonal wind field, overshadowed by annual, semiannual, and monsoon-related modes. After bandpass filtering with Lanczos weights, MJO signals are clearly detected in several kinematic quantities, including the zonal wind speed, the zonal pseudostress, and the velocity potential. Extraction of the MJO using QuikSCAT winds compares favorably with extraction using NCEP Reanalysis 2, except that the QuikSCAT signal appears to be more robust. In addition, an alternative bandpass-filtering technique using variable filter weights near time series endpoints is presented. The method uses least squares minimization to match newly created frequency response functions in edge zones as closely as possible to the pre...