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Error characterization of Atmospheric Motion Vectors

Error characterization of Atmospheric Motion Vectors. Picture. J.Le Marshall. Quality Control (ERR) Considers       Correlation between images U acceleration V acceleration U deviation from first guess V deviation from first guess ………. Quality Indicator (QI) Considers

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Error characterization of Atmospheric Motion Vectors

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  1. Error characterization of Atmospheric Motion Vectors Picture J.Le Marshall

  2. Quality Control (ERR) Considers       Correlation between images U acceleration V acceleration U deviation from first guess V deviation from first guess ………

  3. Quality Indicator (QI) Considers       Direction consistency (pair)       Speed consistency (pair)       Vector consistency (pair)       Spatial Consistency       Forecast Consistency QI = ∑wi.QVi/∑wi

  4. EE - provides RMS Error (RMS)    Estimated from the five QI components wind speed vertical wind shear temperature shear pressure level which are used as predictands for root mean square error

  5. Fig. 4 (b): Predicted error using the EE regression approach Fig. 4 (a): Predicted error using the QI lookup table

  6. GMS-5 Table 3 AMV numbers and comparative errors in MMVD when selecting Upper level WV AMVs by MMVD (November, 2002 ) using EE and QI. (Here vectors are chosen with Av. MMVD equal to 5 and 6 ms-1 respectively)

  7. RT EE Computation at JCSDA EE computed for GOES-East and West SWIR, IR, WV and VIS AMVs EE also computed Terra and Aqua MODIS AMVs Currently being set up for NESDIS RT Test Length scale of correlated error to follow

  8. MODIS WINDS v2. Improved winds/QC use of EE

  9. Accuracy of EE

  10. Accuracy of EE

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