NSCAT

One sentence introductions to highlights, and links to more detailed descriptions. The highlights cover the work of many research teams, but only describe a small fraction of the NSCAT-related research. More additions from NSCAT research and applications are welcome.

Winds

Accuracy of Observations

• NSCAT wind speeds validated for the strongest in-situ winds observed during the calibration/validation period, with no indication of a drop in accuracy (Bourassa et al. 1997; Hans Graber et al., personal communications, 1997; Bob Atlas, personal communications, 1997; Ralph Millif, Peter Niiler and Bill Large, personal communications, 1997; Freilich and Dunbar 1999).

• Unlike other remote sensors of winds, NSCAT accurately determines wind directions as well as wind speeds (Bourassa et al. 1997; Hans Graber et al., personal communications, 1997; Bob Atlas, personal communications, 1997; Kathy Kelly et al., personal communications, 1997; Ralph Millif, Peter Niiler and Bill Large, personal communications, 1997; Freilich and Dunbar 1999).

• Validation with high-quality research vessel observations show unprecedented accuracy of remotely sensed winds (Bourassa et al. 1997).

• Validation of vector winds with buoys further reduces estimation of error in NSCAT observations (Freilich and Dunbar 1999).

• NSCAT winds sufficiently accurate to find small systematic errors in one minute averages of automated ship wind observations (Smith et al. 1999).

• In-situ surface pressure observations used to evaluate NSCAT wind speeds greater than available with in-situ wind observations. Winds from the NSCAT-1 model function found to underestimate the very high wind speeds, and this error was corrected in the NSCAT-2 model function (Ralph Foster and Bob Brown, personal communications, 1998).

• Upper estimate of NSCAT uncertainty (i.e., random error) in speed reduced by a factor of ~2.5 (to ~0.6 ms^-1) when the winds are considered surface relative, and there is a good estimate of the surface current (Peter Cornillon, personal communications, 1998).

Observational Coverage

• Observational coverage meets design specification of 90% global coverage every 48 hours (12,24, and 48 hour example, 24 hour example).

• 25 km resolution exceeds original design specification of 50 km resolution.

Tropical Storms

• First similtaneous view of hurricane winds and moisture (Liu and Tang 1997).

• Higher-resolution (25 vs. 50 km) footprint of NSCAT found to be a major asset in determining the wind field around tropical storms.

• Tropical storm in the Caribbean Sea observed to have strong influence on gap flow from the Gulf of Mexico into the Pacific Ocean (Bourassa et al., 1999).

Atmospheric Fronts

• Global wind maps show the locations of fronts and tropical storms (Liu and Tang, 1997).

• Warm and cold fronts can be identified in NSCAT swaths (Zierden, Bourassa and O'Brien, 1999).

Numerical Weather Prediction

• NSCAT winds improve prediction of tropical convection and precipitation (C. P. Chang, personal communication, 1998).

• NSCAT observations have very large positive impact on the forecasts of Atlantic tropical storm positions in five day forecasts (Ad Stoffelen, personal communication, 1998).

• High resolution NSCAT winds used to improve sub-grid-scale parameterizations in general circulation models (Gad Levy and Dean Vickers, personal communication, 1998).

• Surface pressure fields based on NSCAT observations remarkably detailed (Bob Brown and Ralph Foster, personal communication, 1997; Zierden, Bourassa, and O'Brien 1999).

Other Meteorological Studies

• NSCAT winds used with TOPEX/Posiden sea levels and Reynolds sea surface temperatures to observed the evolution of the Monsoon over the South China Sea (Tim Liu, personal communication, 1998).

• Wind flow changes due to orographic features of South Georges Island in the Falklands/Malvinas (Mike Freilich, personal communication, 1997).

• NSCAT derived surface pressures are used to study the evolution of mid-latitude cyclones and fronts (Zierden, Bourassa, and O'Brien 1999).

Gridded Wind Products

• Many research groups have produced gridded wind products that can be used in ocean and atmospheric models (Bourassa et al. 1998; Polito, Liu and Tang 1988; Cheng, Chao, and Liu, personal communication, 1998; Kutsuwada, personal communication, 1998; Legler, Bourassa and O'Brien, personal communication, 1998; Milliff, Large, Morzel, Danabasoglu and Chin, personal communication, 1998; Tang and Liu, personal communication, 1998; Bourassa et al. 1999; Verschell et al. 1999).

Ocean Modeling Results Based on NSCAT Winds

• Direction and strength of near-surface (Ekman) currents calculated from NSCAT wind observations found to be an excellent match to buoy observations.

• Results of models forced by NSCAT winds (vs. non-NSCAT winds) have substantially difference mixed-layer thicknesses (Tony Busalacchi, personal communication, 1998).

• Short-term wind variations have impacts that are confirmed in observations of sea-level anomalies and sea surface temperature (Tony Busalacchi, personal communication, 1998).

• NSCAT winds used to detect warm core rings off United State's Atlantic Coast (Peter Cornillon, personal communication, 1998).

• Study of influence of gap-flow near Vladivistok on forcing of ocean currents (Dong-Kyu Lee and Peter Niiler, personal communication, 1998).

• High-resolution NSCAT winds used to examine CO₂ fluxes at the air-sea interface (Jacqueline Etcheto, personal communication, 1998).

Long-Term Climatology and Global Change

• Statistical methods applied to NSCAT and other winds observations to help fill gaps in the historical record of winds over oceans (Donna L. Witter, personal communication, 1998).

Model Function Improvements

• NSCAT-1 model function wind speeds validated with in-situ winds for speeds up to 20 ms^-1 (Bourassa et al., 1997; Hans Graber, personal communication, 1998; Freilich and Dunbar 1999).

• Scientists working on NSCAT model functions are first to notice a 2° tilt in the ADEOS satellite's attitude, demonstrating the improved accuracy of the new model function.

• NSCAT-2 model function (the currently accepted one) corrects NSCAT-1 underestimations of very high wind speeds, and is still accurate when compared to in-situ observations (Scott Dunbar, Mike Freilich, and Frank Wentz, personal communications, 1998; Mark Bourassa, unpublished results, 1999).

• NSCAT-2 Wind model function has ice mask designed with 3-day and quarter degree resolution, with information on ice based solely on NSCAT observations (Scott Dunbar, personal communication, 1998).

• Geostrophic wind model function developed, and geostrophic wind direction found to differ from surface wind direction by the expected 19° (Bob Brown, personal communication, 1998).

Remote Sensing

• Systematic differences observed between NSCAT and altimeter based winds are shown to be a function sea state (Kristina Katsaros, personal communication, 1998).

• Systematic bias observed between SSM/I and NSCAT winds due to swell and rain (Jacqueline Etcheto, personal communication, 1998).

• For low wind speeds, ERS-2 winds found to be biased low compared to NSCAT wind speeds (Jacqueline Echteto, personal communication, 1998).

• Theoretical based air-sea interaction model demonstrates and explains the interaction between swell and the much shorter waves to which Ku-band scatterometry (e.g., NSCAT) is sensitive (Bourassa et al., 1999).

Stresses

Model Function

• A model function is developed to calculate stresses directly from NSCAT radar observations, rather than indirectly through the NSCAT winds.

Ocean Modeling Studies

• Differences in stresses derived from NSCAT stresses, compared to stresses based on NSCAT winds, result in better model predictions of sea level heights in areas of wind convergence (Vershell et al. 1999).

• A model forced with NSCAT stresses (compared the same model forced with NSCAT winds) produces a stronger El-Nino signal in the thickness of the ocean's upper layer (Vershell et al. 1999).

• Differences in forcing fields (stresses) due to NSCAT stresses, and stresses derived from NSCAT winds, found to be qualitatively consistent with ignoring stresses related to capillary waves (ripples) in a theory based flux model (Verschell et al. 1999).

Ice

• The mean atmospheric circulation influences the sea ice distribution in the Antarctic (Yuan, Martinson, and Liu 1998).

• Sea ice drift in the Arctic Basin derived from NSCAT observations (Liu, Zhao, and Liu 1998).

• Technique developed to enhance resolution in sea ice studies (David Long, personal communication, 1998).

• NSCAT and other satellite observations used to examine decadal changes in ice sheets (Mark Drinkwater, personal communication, 1998).

Land Studies

• South American deforestation seen in comparisons of NSCAT observations with SeaSat's from 20 years earlier (David Long, personal communication, 1997).

Plans for the Future

A longer period of these high quality winds will be foster a great number of oceanographic and meteorological studies, covering a wide range of scales and applications. The upcoming SeaWinds instrument on QuikSCAT is expected to provide the same quality of observations, with greater coverage. This is an exceptionally exciting time for oceanography and air-sea interaction, and the expected success of the QuikSCAT mission bodes well for the immediate future.

For the more distant future, we will have a SeaWinds instrument on ADEOS II and, perhaps, ADEOS III. Additional instruments for measuring vector winds are in development by the European Community (ASCAT) and the Office of Naval Research (WINDSAT). For the near future we can expect that sailors of all types will download the latest surface wind chart from satellites, and "see" the sea around them for safety, recreation, and marine operations. The successes of NSCAT have shown light on many future applications!

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Additions to this page

Please send updates to NSCAT-products@coaps.fsu.edu.

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References

• 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 Trans. of Amer. Geophys. Union, 597 & 602.

• Bourassa, M. A., D. M. Legler, J. J. O'Brien, J. N. Stricherz, and J. Whalley, 1998: High temporal and spatial resolution animations of winds observed with the NASA scatterometer. 14th International conference on IIPS, Phoenix, AZ, American Meteorological Society, 556-559.

• Bourassa, M. A., D. G. Vincent, W. L. Wood, 1999: A flux parameterization including the effects of capillary waves and sea state. Journal of the Atmospheric Sciences, 56, 1123-1139.

• Bourassa, M. A., L. Zamudio, and J. J. O'Brien, 1998: Non-inertial flow in NSCAT observations of Tehuantepec winds. J. Geophys. Res., 104, 11,311-11,320.

• Chelton, D. B., M. H. Freilich, and S. K. Esbensen, 1999: Satellite Observations of the wind jets off Central America, part I: Case studies and statistical characteristics. Submitted to Mon. Wea. Rev.

• Chelton, D. B., M. H. Freilich, and S. K. Esbensen, 1999: Satellite Observations of the wind jets off Central America, part II: Regional relationshsips and dynamical considerations. Submitted to Mon. Wea. Rev.

• Freilich, M. H., and R. S. Dunbar, 1999: The accuracy of the NSCAT-1 vector winds: comparisons with NDBC buoys. J. Geophys. Res., 104, 11,231-11,246.

• Liu, A. K., Y. Zhao, and W. T. Liu, 1998: Sea ice motion derived from satellite agrees with buoy observations. Eos Trans. Amer. Geophys. Union, 79, 353 & 359.

• Liu, W.T. and W. Tang, 1997: Spaceborne scatterometer in studies of atmospheric and oceanic phenomena form synoptic to interannual time scales. in Space Remote Sensing of Subtropical Ocean. C.T. Liu (ed.), Elsevier Press, Amsterdam

• Smith, R. S, M. A. Bourassa, and R. J. Sharp, 1998: Establishing more truth in true winds. J. Atmos. Oceanic Technol., in press.

• Verschell, M. A., M. A. Bourassa, D. E. Weissman, and J. J. O'Brien, 1998: Model Validation of the NASA Scatterometer Winds. J. Geophys. Res., 104, 11,359-11,374.

• Weissman, D. E., and H. C. Graber, 1999: Satellite scatterometer (NSCAT) studies of ocean surface stress and drag coefficients using a direct model. J. Geophys. Res., 104, 11,329-11,336.

• Yuan, X., D. G. Martinson, and W. T. Liu, 1998: The effect of air-sea-ice interaction on winter 1996 southern ocean subpolar storm distribution. J. Geophys. Res. - Atmosphere, accepted.