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Dimethylsulfide (DMS) concentrations have been measured in over 1000 Pacific surface seawater samples during the past 4 years. The data have been tabulated to take into account both regional and seasonal variations in concentration. The area-weighted summer and winter concentrations of DMS in the North Pacific Ocean are 2.2 and 1.3 nmol/L, respectively. Wind speed, surface seawater temperature, and DMS diffusivities are used to calculate air-sea exchange coefficients. The area-weighted summer and winter DMS piston velocities are 2.3 and 2.7 m/d, respectively. These exchange coefficients combined with the concentration data yield a net ocean to atmosphere DMS flux in the North Pacific Ocean of 0.12 Tmol/yr. Extrapolating this calculation by regional areas to the global ocean yields a net DMS flux of 0.50 Tmol/yr, less than earlier estimates of 1.2 Tmol/yr, but still consistent with excess sulfate deposition estimates and model studies of the marine atmospheric sulfur budget. The uncertainty in the flux estimate is roughly a factor of 2. INTRODUCTION The surface ocean plays an important role in the global biogeochemical sulfur cycle. Gaseous sulfur compounds emitted from the ocean are a major source of sulfate aerosol in the marine troposphere [Bonsang et al., 1980]. This aerosol is the major contributor to the acidity of natural precipitation [Charlson and Rodhe, 1982] and to cloud condensation nuclei and hence may be important to the radiative equilibrium of the earth [Shaw, 1983, and R. J. Charlson et al., Atmospheric sulfur: Geophysiology and climate, submitted to Nature, 19863. Observational studies to date have shown that dimethylsulfide (DMS) is the dominant volatile sulfur compound present in marine surface waters [Barnard et al., 1982; Andreae and Raemdonck, 1983; Cline and Bates, 1983]. This compound accounts for greater than 95% of the observed reduced sulfur in surface ocean waters [Cline and Bates, 1983] and is therefore thought to be the only significant source of gaseous sulfur to the marine troposphere [N•tuyen et al., 1983; Andreae, 1986]. Lovelock et al. [1972] were the first to describe a marine source of DMS, which has been subsequently verified by several investigators [Barnard et al., 1982; Andreae and Raerndonck, 1983; Cline and Bates, 1983]. The precursor of DMS (dimethylsulfoniopropionate, or DMSP) is produced by phytoplankton. DMS is both excreted by phytoplankton and released during zooplankton grazing [Dacey and Wakeham, 1986]. In support of its biological origin, DMS is normally restricted to the upper 200 m of the water column with maximum concentrations near the bottom of the mixed layer [Cline and Bates, 1983; Andreae and Barnard, 1984]. Below this maximum, the concentration decreases exponentially with depth to near-zero concentrations (< 10 pmol/L) at 200 m. The surface layers are always observed to be supersaturated with DMS, implying a net flux to the atmosphere [Barnard et XNow at Mobil Research and Development Corporation, Dallas, Texas. This paper is not subject to U.S. copyri...

The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.