A physical-model-based, field-wise and self-contained algorithm for removing directional ambiguities of ocean surface winds retrieved from scatterometer measurements

Details A physical-model-based, field-wise and self-contained algorithm for removing directional ambiguities of ocean surface winds retrieved from scatterometer measurements A physical-model-based, field-wise and self-contained algorithm for removing directional ambiguities of ocean surface winds retrieved from scatterometer measurements

Sep 2000

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000georl..27.2665k&link_type=abstract

Geophysical Research Letters, Volume 27, Issue 17, p. 2665-2668

Physics

2

Meteorology And Atmospheric Dynamics: Boundary Layer Processes, Meteorology And Atmospheric Dynamics: Remote Sensing, Oceanography: General: Remote Sensing And Electromagnetic Processes, Radio Science: Remote Sensing

Scientific paper

An algorithm is introduced to remove the directional ambiguities in ocean surface winds measured by scatterometers, which requires scatterometer data only. It is based on two versions of PBL (planetary boundary layer) models and a low-pass filter. A pressure field is first derived from the median-filtered scatterometer winds, is then noise-filtered, and is finally converted back to the winds, respectively, by an inverted PBL model, a smoothing algorithm, and a PBL model. The derived wind field is used to remove the directional ambiguities in the scatterometer data. This new algorithm is applied to Hurricane Eugene and produces results comparable to those from the current standard ambiguity removal algorithm for NASA/JPL SeaWinds project, which requires external numerical weather forecast/analyses data.

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