A Comparison of the Impact of QuikScat and WindSat Wind Vector Products on Met Office Analyses and Forecasts

Several studies have demonstrated that retrievals of wind vectors from the WindSat polarimetric radiometer are of sufficient quality to be considered for assimilation in operational numerical weather prediction models. In this paper, WindSat data are used in a state-of-the-art global meteorological...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2009-06, Vol.47 (6), p.1632-1640
Main Authors: Candy, B., English, S.J., Keogh, S.J.
Format: Article
Language:English
Subjects:
Applied geophysics
Assimilation
Cyclones
Data analysis
Earth sciences
Earth, ocean, space
Error analysis
Exact sciences and technology
Information analysis
Internal geophysics
Mathematical analysis
Mathematical models
Meteorology
Numerical models
Offices
Predictive models
QuikScat
Radar measurements
Radiometry
Scatterometers
Tropical cyclones
Vectors (mathematics)
Weather forecasting
Wind
Wind forecasting
WindSat
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Summary:Several studies have demonstrated that retrievals of wind vectors from the WindSat polarimetric radiometer are of sufficient quality to be considered for assimilation in operational numerical weather prediction models. In this paper, WindSat data are used in a state-of-the-art global meteorological analysis and forecasting system. Each wind vector contains a directional ambiguity and so is assimilated in a similar way to that of scatterometer data. The forecast impact of using analyses containing information from WindSat data was investigated for a period during August and September of 2005, when a large number of tropical cyclones were present. Forecast errors were reduced in the surface pressure fields, and the average improvement across the forecast range was found to be 1.0%. This is comparable to the improvement of 1.1% found in the same fields when winds were assimilated from the QuikScat scatterometer. The impact on tropical cyclone tracks in the forecasts was also studied. The scatterometer improved (reduced) the track errors markedly by 25% in the analyses. When impacts across the forecast range out to five days were also included, the improvement was found to be 8%. In contrast, the assimilation of WindSat data improved the analysis track errors by 7%, although this figure was found to be 10% across the complete forecast range.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2008.2009993