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Error characterization of Atmospheric Motion VectorsPowerPoint Presentation

Error characterization of Atmospheric Motion Vectors

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Error characterization of Atmospheric Motion Vectors

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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

Direction consistency (pair)

Speed consistency (pair)

Vector consistency (pair)

Spatial Consistency

Forecast Consistency

QI = ∑wi.QVi/∑wi

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

Fig. 4 (b): Predicted error using the EE regression approach

Fig. 4 (a): Predicted error using the QI lookup table

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)

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

MODIS WINDS v2. Improved winds/QC use of EE

Accuracy of EE

Accuracy of EE