Ocean Science www.ocean-sci.net 1812-0784 1812-0792 4 4 2008 10.5194/os-4-265-2008 http://www.ocean-sci.net/4/265/2008/ http://www.ocean-sci.net/4/265/2008/os-4-265-2008.html http://www.ocean-sci.net/4/265/2008/os-4-265-2008.pdf 265 274 2008-12-11 Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations A. Bentamy abderrahim.bentamy@ifremer.fr D. Croize-Fillon C. Perigaud Institut Français pour la Recherche et l'Exploitation de la MER (IFREMER), France Jet Propulsion Laboratory (JPL/NASA), USA The new scatterometer Advanced SCATterometer (ASCAT) onboard MetOp-A satellite provides surface wind speed and direction over global ocean with a spatial resolution of 25 km square over two swaths of 550 km widths. The accuracy of ASCAT wind retrievals is determined through various comparisons with moored buoys. The comparisons indicate that the remotely sensed wind speeds and directions agree well with buoy data. The root-mean-squared differences of the wind speed and direction are less than 1.72 m/s and 18°, respectively. At global scale, ASCAT winds are compared with surface winds derived from QuikSCAT scatterometer. The results confirm the buoy analyses, especially for wind speed ranging between 3 m/s and 20 m/s. For higher wind conditions, ASCAT is biased low. The ASCAT underestimation with respect to QuikSCAT winds is wind speed dependent. The comparisons based on the collocated scatterometer data collected after 17 of October 2007 indicate that there are significant improvements compared to previous periods. % vor jede Referenz Ayina, H.-L., Bentamy, A., Madec, G., and Nuñez, A. M.: The Impact of Satellite Winds and Latent Heat Fluxes in a Numerical Simulation of the Tropical Pacific Ocean, J. Climate, 19(22), 5889–5902, doi:10.1175/JCLI3939.1, 2006. Bentamy , A., Grima, N., and Quilfen, Y.: Validation of the gridded weekly and monthly wind fields calculated from ERS-1 scatterometer wind observations, Global Atmos. Ocean. System, 6, 373–396, 1998. Blanke, B., Speich, S., Bentamy, A., Roy, C., and Sow, B.: Modeling the structure and variability of the southern Benguela upwelling using QuikSCAT wind forcing, J. Geophys. Res., 110(C7), C07018, doi:10.1029/2004JC0025292005, 2005. Chelton, D. B. and Freilich, M. H.: Scatterometer-Based Assessment of 10-m Wind Analyses from the Operational ECMWF and NCEP Numerical Weather Prediction Models, Mon. Weather Rev., 133, 409–429, 2005. Ebuchi, N., Graber, H. C., and Caruso, M. J.: Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data, J. Atmos. Oceanic Technol., 19, 2049–2069, 2002. Figa, J. and Stoffelen, A.: On the assimilation of Ku-band scatterometer winds for weather analysis and forecasting, IEE Trans. Geosci. Remote Sens., 38, 1893–1902, 2000. Freilich, M. H.: Validation of vector magnitude data sets: Effects of random component errors, J. Atmos. Ocean. Tech., 14, 695–703, 1997. Hakeem, K. J.: Statistical dependencies of sea state characteristics on water temperature and wind-wave age, J. Mar. Sys., 4(2–3), 161–169, 1993. Hersbach, H., Stoffelen, A., and de Haan, S.: An improved C-band scatterometer ocean geophysical model function: CMOD5, J. Geophys. Res., 112, C03006, doi:10.1029/2006JC003743, 2007. JPL: QuikScat science data product user's manual (version 3.0), Jet Propulsion Laboratory Publ. D-18053, Pasadena, CA, 91~pp., available online: http://podaac.jpl.nasa.gov/DATA_CATALOG, 2006. Katsaros, K. B., Forde, E. B., Chang, P., and Liu, W. T.: QuikSCAT facilitates early identification of tropical depressions in 1999 hurricane season, Geophys. Res. Lett., 28, 1043–1046, 2001. Le Marshall, J., Leslie, L., Morison, R., Pescod, N., Seecamp, R., and Spinoso, C.: Recent Developments in the Continuous Assimilation of Satellite Wind Data for Tropical Cyclone Track Forecasting, Adv. Space Res., 25, 1077–1080, 2000. Pickett, M. H., Tang, W., Rosenfeld, L. K., and Wash, C. H.: QuikSCAT satellite comparisons with nearshore buoy wind data off the US west coast, J. Atmos. Ocean. Tecnol., 20, 1869–1879, 2003. Plant, W. J.: Effects of wind variability at low wind speed, J. Geophys. Res., 105(C7), 16 899–16 910, 2000. Stoffelen, A., de Haan, S., Quilfen, Y., and Schyberg, H.: ERS Scatterometer Ambiguity Removal Comparison, OSI SAF report, available online: http://www.knmi.nl/scatterometer/publications/, 2002. Wilks, D. S.: Statistical methods in the atmospheric sciences, Academic Press, 467~pp., 1995.