P1.13 USING QUIKSCAT-DERIVED SURFACE WINDS AND A GCM TO IMPROVE PREDICTED WIND SPEED VARIABILITY AND OCEAN SURFACE FLUXES

Winds at the surface play a key role in climate processes by determining air-sea energy and gas exchanges. Although steady and continuous in some regions, these non-linear exchanges can be dominated by the tail of the wind speed distribu-tion in regions and periods of strong wind vari-ability. Such variability includes climatically exten-sive regions such as the Intertropical Convergence Zone (ITCZ) where convective downdrafts are com-mon (Donelan et al., 2002), to propagating westerly wind bursts on intra-seasonal timescales (Weller and Anderson, 1996), to storm track gustiness. Sur-face heat and energy fluxes depend non-linearly on wind speed magnitude (Freely et al., 2004; Renfrew et al., 2002; Wang et al., 1998), are sensitive to the tails of the wind distribution, and hence vary sig-nificantly on spatio-temporal scales not resolved by GCMs. NASA QuikSCAT data offer the opportunity to characterize wind speed probability density func-tions (PDFs) across climatically significant spatial and temporal scales (e.g., Monahan, 2006a). I pro-pose to use these data to improve understanding and prediction of fluxes from sub-gridscale winds, and thus improve atmosphere-ocean coupling in models contributing to the fifth IPCC assessment report. The NASA QuikSCAT scatterometer dataset 1 provides six complete years (Jan./2000–Dec./2005) of accurate (Bourassa et al., 2003), twice-daily in-stantaneous ocean surface wind speed estimates (Chelton and Freilich, 2005) at 0.25 ◦ × 0.25 ◦ res-olution. The 2000–2005 climatological mean of four statistics of the surface wind speed PDF