HR: 0800h
AN: B51A-0926    [Abstracts]
TI: Can the Variability in DMS Transfer Velocities be Explained by Wind Speed?
AU: * Huebert, B J
EM: huebert@hawaii.edu
AF: University of Hawaii, Dept. of Oceanography, Honolulu, HI 96822 United States
AU: Blomquist, B W
EM: blomquis@hawaii.edu
AF: University of Hawaii, Dept. of Oceanography, Honolulu, HI 96822 United States
AU: Hare, J E
EM: jeffrey.hare@colorado.edu
AF: University of Colorado, CIRES, Boulder, CO 80309 United States
AU: Fairall, C W
EM: chris.fairall@noaa.gov
AF: NOAA-ETL, 325 Broadwaay, Boulder, CO 80305 United States
AU: Johnson, J E
EM: james.e.johnson@noaa.gov
AF: NOAA-PMEL, 7600 Sand Point Way NE, Seattle, WA 98115 United States
AU: Bates, T S
EM: tim.bates@noaa.gov
AF: NOAA-PMEL, 7600 Sand Point Way NE, Seattle, WA 98115 United States
AB: We measured the sea/air flux of DMS by eddy correlation (EC) on an sub-hourly time scale in the Eastern Equatorial Pacific from the NOAA ship Ronald H. Brown in October and November of 2003. We used an atmospheric pressure ionization mass spectrometer (APIMS) with an internal isotopically-labeled standard (D3-DMS) to measure atmospheric DMS concentrations. Lab tests suggest that a Nafion drier limited our effective frequency response to about 1 Hz. Comparisons with water vapor power spectra suggest that this response was adequate to capture more than 90 percent of the flux. The fluxes often responded on a time scale of 10 minutes or less to changes in wind speed, u. We measured seawater DMS concentrations with a purge and trap system once each half hour, so that we could compute the DMS transfer velocity (Vt, the EC-derived flux divided by the interfacial concentration difference) on an hourly basis. A plot of Vt vs u shows that hourly values of Vt ranged from less than the Liss and Merlivat model to more than the Wanninkhof model's value. When binned by wind speed, the average values of Vt lay between the two theories, with standard deviations of 15 to 40 percent. This large variability demonstrates that factors other than wind also affect the exchange velocity: surface roughness, lipid films, bubble spectra, and mean-square wave slope are likely candidates. The APIMS technology for making rapid sea/air gas flux and exchange velocity measurements worked very well, producing results that agree with accepted theories on its first ship-borne trial. It can now be used to address the functionalities of the other controlling factors.
DE: 3339 Ocean/atmosphere interactions (0312, 4504)
DE: 1615 Biogeochemical processes (4805)
DE: 1635 Oceans (4203)
DE: 0312 Air/sea constituent fluxes (3339, 4504)
DE: 0315 Biosphere/atmosphere interactions
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting