High Temporal and Spatial Resolution

Wind Fields From Scatterometer Observations

Mark A. Bourassa, David M. Legler, James J. O'Brien

Center for Ocean-Atmospheric Prediction Studies (COAPS),

Florida State University

2035 E. Dirac Dr., Suite 200 Johnson Bldg., Tallahassee, FL 32306-2840.

1. Introduction

Daily wind fields of 1 spatial resolution are produced from satellite observations of the winds over water. There is considerable call for daily marine wind products for forecasting, research, and commercial activities such as fishing and offshore oil drilling. Traditional wind observations are sparse, and the output of general circulation models (GCMs) has been questionable. In recent years, space-borne scatterometer (Seasat, ERS-1/2, NSCAT) observations of wind speed and direction over the ocean surface have greatly enhanced the coverage and observational density of marine winds. The processing of scatterometer data is relatively easy (i.e., rapid and cost effective) in comparison to other remote sensing techniques such as synthetic aperture radar (SAR), and has much better coverage than winds derived from altimetry. The NSCAT scatterometer (Bourassa et al., 1997) is an active microwave sensor that covers approximately 77% of the ice-free ocean in one day, and 90% in two days. A new technique is developed to fill the gaps in the fields of daily observations.

These daily gridded wind fields are used in animations showing moving wind vectors, and the evolution of divergence and vorticity fields (http://www.coaps.fsu.edu/nscat/). The animations show surface airflows that have not been identifiable from previous in-situ or satellite observations.

2. Methodology

The production of daily wind fields, appropriate for forcing ocean models, requires that gaps in the coverage are filled by accurate estimates of the wind. The wind fields must also be smooth at the edges of these gaps, otherwise the winds could excite spurious Kelvin waves. Our solution to this problem is to use observations from closely related times. The observations closer in time to the day of interest are weighted much more heavily than those further away in time. This approach retains the dominance of winds observed on the day in question, and it also allows for a relatively smooth transition into regions where there were no observations during the day of interest.

3. Animations

The above wind fields were used to produce animations (http://www.coaps.fsu.edu/nscat/) of the winds and related fields. The winds are shown with moving vectors. The motion of the vectors is Lagrangian, and the vector length indicates the wind speed. The vector positions are calculated by interpolating the daily wind fields to one hour time steps, and integrating with a fourth order Runge-Kutta method. The Runge-Kutta technique uses an adaptive time step, with a first guess of ten minutes. Each animation shows one week of wind fields and vorticities.

5. Results

The NCEP wind fields (Figs. 3 and 4) can be compared to the fields generated by this filling technique (Figs. 1 and 2). The NCEP fields have a resolution of only 2 latitude and 2 longitude. The NCEP winds capture most of the large scale features in Fig. 1; however, the position of the cyclone is too far North, the wind direction in the western Gulf of Mexico has too large an easterly component, and the strong winds flowing through the Isthmus of Tehauntepec are too weak. The NCEP field tends to be too smooth in the data sparse regions (i.e., the bulk of the Pacific ocean). The differences in data rich regions, such as the North Sea, are smaller than the difference in Equatorial and Southern latitudes.

6. Conclusions

The new methodology for filling data void in scatterometer observations is accurate and easily implemented for NSCAT observations. High resolution (1 x 1 ) daily wind fields were created. The averaging process makes acceptably smooth fields and retains the vast majority of synoptic scale details. The mean difference between observed and averaged speeds was typically less than 2 m s-1, although the difference could be up to 5 m s-1 for the 'worst case' example of a rapidly translating cyclone. The wind fields are more accurate and detailed than those available from the NCEP reanalysis.

These fields were used to produce moving vector animations. The NSCAT animations are excellent as educational tools, and as a first look product for research. The animations demonstrate observed atmospheric circulation and evolution with a clarity that is unprecedented.


Bourassa, M. A., M. H. Freilich, D. M. Legler, W. T. Liu, and J. J. O'Brien, 1997: Wind observations from new satellite and research vessels agree. EOS, accepted.

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