On the quality of high‐resolution scatterometer winds

[1] High-resolution wind products based on space-borne scatterometer measurements by ASCAT and SeaWinds are used widely for various purposes. In this paper the quality of such products is assessed in terms of accuracy and resolution, using spectral analysis and triple collocation with buoy measurements and NWP model forecasts. An experimental ASCAT coastal product is shown to have a spectral behavior close to k−5/3 for scales around 100 km, as expected from theory and airborne measurements. The NWP spectra fall off more rapidly than the scatterometer wind spectra starting at scales of about 1000 km. Triple collocation is performed for four collocated data sets, each with a different scatterometer wind product: ASCAT at 12.5 km and 25 km, and SeaWinds at 25 km processed in two different ways. The spectral difference between scatterometer wind and model forecast is integrated to obtain the representation error which originates from the fact that global weather models miss small-scale details observed by the scatterometers and the buoys. The estimated errors in buoy winds and model winds are consistent over the data sets for the meriodional wind component; for the zonal wind component consistency is less, but still acceptable. Generally, enhanced detail in the scatterometer winds, as indicated at high spatial frequencies by a spectral tail close to k−5/3, results in better agreement with buoys and worse agreement with NWP predictions. The accuracy of the scatterometer winds is about 1 ms−1 or better. The calibration coefficients from triple collocation indicate that on average the ASCAT winds are slightly underestimated.

[1]  G. D. Nastrom,et al.  Kinetic energy spectrum of large-and mesoscale atmospheric processes , 1984, Nature.

[2]  Ronald M. Errico,et al.  Spectra Computed from a Limited Area Grid , 1985 .

[3]  G. D. Nastrom,et al.  A Climatology of Atmospheric Wavenumber Spectra of Wind and Temperature Observed by Commercial Aircraft , 1985 .

[4]  Michael H. Freilich,et al.  Wavenumber Spectra of Pacific Winds Measured by the Seasat Scatterometer , 1986 .

[5]  Donald B. Percival,et al.  Spectral Analysis for Physical Applications , 1993 .

[6]  Ad Stoffelen,et al.  Ambiguity removal and assimilation of scatterometer data , 1997 .

[7]  A. Stoffelen.  Toward the true near-surface wind speed: Error modeling and calibration using triple collocation , 1998 .

[8]  Frank J. Wentz,et al.  A model function for the ocean‐normalized radar cross section at 14 GHz derived from NSCAT observations , 1999 .

[9]  C. Winn,et al.  SeaWinds on QuikSCAT: sensor description and mission overview , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[10]  Jérôme Patoux,et al.  Spectral analysis of QuikSCAT surface winds and two-dimensional turbulence , 2001 .

[11]  Marcos Portabella,et al.  Characterization of residual information for SeaWinds quality control , 2002, IEEE Trans. Geosci. Remote. Sens..

[12]  M. Drinkwater,et al.  The advanced scatterometer (ASCAT) on the meteorological operational (MetOp) platform: A follow on for European wind scatterometers , 2002 .

[13]  Bryan W. Stiles,et al.  Direction interval retrieval with thresholded nudging: a method for improving the accuracy of QuikSCAT winds , 2002, IEEE Trans. Geosci. Remote. Sens..

[14]  J. Bidlot,et al.  Intercomparison of the Performance of Operational Ocean Wave Forecasting Systems with Buoy Data , 2002 .

[15]  Marcos Portabella,et al.  A comparison of KNMI quality control and JPL rain flag for SeaWinds , 2002 .

[16]  Marcos Portabella,et al.  A probabilistic approach for SeaWinds data assimilation , 2004 .

[17]  Marcos Portabella,et al.  On Bayesian scatterometer wind inversion , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Michael H. Freilich,et al.  On the Use of QuikSCAT Scatterometer Measurements of Surface Winds for Marine Weather Prediction , 2006 .

[19]  Marcos Portabella,et al.  Scatterometer Backscatter Uncertainty Due to Wind Variability , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Saleh Abdalla,et al.  Error Estimation of Buoy, Satellite, and Model Wave Height Data , 2007 .

[21]  H. Hersbach,et al.  An improved C-band scatterometer ocean geophysical model function: CMOD5 , 2007 .

[22]  R. Frehlich,et al.  The Use of Structure Functions and Spectra from Numerical Model Output to Determine Effective Model Resolution , 2008 .

[23]  Christopher C. Hennon,et al.  The Operational Use of QuikSCAT Ocean Surface Vector Winds at the National Hurricane Center , 2009 .

[24]  Marcos Portabella,et al.  On Scatterometer Ocean Stress , 2009 .

[25]  Ad Stoffelen,et al.  Validation of Two-Dimensional Variational Ambiguity Removal on SeaWinds Scatterometer Data , 2009 .