ALBERT

Description: Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a 1° latitude by 1° longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFS-MODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437 μatm. The root mean square error (RMSE) of the neural network fit to the data is 11.6 μatm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

Description: Dimethylsulfoniopropionate (DMSP) is produced in surface seawater by phytoplankton. Phytoplankton culture experiments have shown that nanoeucaryotes (NANO) display much higher mean DMSP-to-Carbon or DMSP-to-Chlorophyll (Chl) ratios than Prochlorococcus (PRO), Synechococcus (SYN) or diatoms (DIAT). Moreover, the DMSP-lyase activity of algae which cleaves DMSP into dimethylsulfide (DMS) is even more group specific than DMSP itself. Ship-based observations have shown at limited spatial scales, that sea surface DMS-to-Chl ratios (DMS:Chl) are dependent on the composition of phytoplankton groups. Here we use satellite remote sensing of Chl (from SeaWiFS) and of Phytoplankton Group Dominance (PGD from PHYSAT) with ship-based sea surface DMS concentrations (8 cruises in total) to assess this dependence on an unprecedented spatial scale. PHYSAT provides PGD (either NANO, PRO, SYN, DIAT, Phaeocystis (PHAEO) or coccolithophores (COC)) in each satellite pixel (1/4° horizontal resolution). While there are identification errors in the PHYSAT method, it is important to note that these errors are lowest for NANO PGD which we typify by high DMSP:Chl. In summer, in the Indian sector of the Southern Ocean, we find that mean DMS:Chl associated with NANO + PHAEO and PRO + SYN + DIAT are 13.6±8.4 mmol g−1 (n=34) and 7.3±4.8 mmol g−1 (n=24), respectively. That is a statistically significant difference (P〈0.001) that is consistent with NANO and PHAEO being relatively high DMSP producers. However, in the western North Atlantic between 40° N and 60° N, we find no significant difference between the same PGD. This is most likely because coccolithophores account for the non-dominant part of the summer phytoplankton assemblages. Meridional distributions at 22° W in the Atlantic, and 95° W and 110° W in the Pacific, both show a marked drop in DMS:Chl near the equator, down to few mmol g−1, yet the basins exhibit different PGD (NANO in the Atlantic, PRO and SYN in the Pacific). In tropical and subtropical Atlantic and Pacific waters away from the equatorial and coastal upwelling, mean DMS:Chl associated with high and low DMSP producers are statistically significantly different, but the difference is opposite of that expected from culture experiments. Hence, in a majority of cases PGD is not of primary importance in controlling DMS:Chl variations. We therefore conclude that water-leaving radiance spectra obtained simultaneously from ocean color sensor measurements of Chl concentrations and dominant phytoplankton groups can not be used to predict global fields of DMS.

Description: We have combined the first satellite maps of the global distribution of phytoplankton functional type and new measurements of phytoplankton-specific isoprene productivities, with available remote marine isoprene observations and a global model, to evaluate our understanding of the marine isoprene source and its impacts on organic aerosol abundances. Using satellite products to scale up data on phytoplankton-specific isoprene productivity to the global oceans, we infer a mean "bottom-up" oceanic isoprene emission of 0.31±0.08 (1σ) Tg/yr. By minimising the mean bias between the model and isoprene observations in the marine atmosphere remote from the continents, we produce a "top-down" oceanic isoprene source estimate of 1.9 Tg/yr. We suggest our reliance on limited atmospheric isoprene data, difficulties in simulating in-situ isoprene production rates in laboratory phytoplankton cultures, and limited knowledge of isoprene production mechanisms across the broad range of phytoplankton communities in the oceans under different environmental conditions as contributors to this difference between the two estimates. Inclusion of secondary organic aerosol (SOA) production from oceanic isoprene in the model with a 2% yield produces small contributions (0.01–1.4%) to observed organic carbon (OC) aerosol mass at three remote marine sites in the Northern and Southern Hemispheres. Based on these findings we suggest an insignificant role for isoprene in modulating remote marine aerosol abundances, giving further support to a recently postulated primary OC source in the remote marine atmosphere.