Detection of the MJO Signal from QuikSCATSource: Journal of Atmospheric and Oceanic Technology:;2005:;volume( 022 ):;issue: 012::page 1885DOI: 10.1175/JTECH1822.1Publisher: American Meteorological Society
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 predetermined frequency response function of interior points. This method stands in contrast to the common practice of simply discarding those endpoints where a convolution cannot be computed.
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contributor author | Arguez, Anthony | |
contributor author | Bourassa, Mark A. | |
contributor author | O’Brien, James J. | |
date accessioned | 2017-06-09T17:23:01Z | |
date available | 2017-06-09T17:23:01Z | |
date copyright | 2005/12/01 | |
date issued | 2005 | |
identifier issn | 0739-0572 | |
identifier other | ams-84206.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4227517 | |
description 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 predetermined frequency response function of interior points. This method stands in contrast to the common practice of simply discarding those endpoints where a convolution cannot be computed. | |
publisher | American Meteorological Society | |
title | Detection of the MJO Signal from QuikSCAT | |
type | Journal Paper | |
journal volume | 22 | |
journal issue | 12 | |
journal title | Journal of Atmospheric and Oceanic Technology | |
identifier doi | 10.1175/JTECH1822.1 | |
journal fristpage | 1885 | |
journal lastpage | 1894 | |
tree | Journal of Atmospheric and Oceanic Technology:;2005:;volume( 022 ):;issue: 012 | |
contenttype | Fulltext |