Core theme 1 WP4: North Atlantic observing system WP 5: Southern Ocean WP6: Data synthesis and modelling

Sea-surface CO2 fugacity in the subpolar North Atlantic A. Olsen, K. R. Brown, M. Chierici, T. Johannessen, and C. Neill ΔpCO 2

SOM estimates of annual cycles, 2004, 2005, 2006.(Telszewski et al, submitted)

Rates of increase (uatm per year) of pCO2 in the North Atlantic, linear fit Schuster et al., in press, DSR II Rapid increases in the subpolar gyre slightly above atmospheric increase in the subtropical gyre

Accurate Air-sea fluxes of CO 2 in the North Atlantic in 2005 from an in – situ observing system Watson et al., about to be submitted (promise!)

Monitoring of fCO 2 in the Southern Ocean using CARIOCA drifters: Results Since 2006, in the frame of CarboOcean, 6 CARIOCA recording fCO 2 : -Exploration of the polar zone and of the subantarctic zone -Combination with CARIOCA measurements since 2001 in the Pacific and Indian Oceans => SAZ sink ~0.8PgC/yr ; PF sink <0.1PgC/yr (Boutin et al., Limnol. Ocean., 2008) -Combination with ship measurements =>Influence of SAMW formation in the Southern Pacific Ocean (Barbero et al., in preparation, 2008) -Evidence of a strong diurnal cycle => methodology to estimate in situ net biological community production from CARIOCA measurements (Boutin and Merlivat, in revision, GRL,2008) PF SAF

Monitoring of fCO 2 in the Southern Ocean using CARIOCA drifters: Perspectives 2-New in situ estimates of biological net community production from biological activity signature on fCO 2 and on DIC for all CARIOCA drifters (at present, study limited to 2006 drifter in the polar zone) => improve spatio-temporal distribution of NCP Sunset ~ ~ 0. 3  mol/kg/day 9 days (Nov-Dec06) in polar zone; high fluorescence ~Gross Community Production-Respiration fCO 2 (  atm) 1-Influence of mesoscale activity on fCO 2 and DIC; combination of satellite/in situ measurements DIC (  mol/kg) Process studies at local scale

Simulated interannual variability (from LSCE)  4 th year progress on sensitivity to 3 factors : 1.Effect of model resolution ? –Mercator-vert collaboration ORCA/PISCES model simulations (2º, ½ º, & ¼º) completed Mercator ocean reanalysis fields: 2001 to 2005 completed –DRAKKAR collaboration Global: Forced NEMO (OPA9) global ocean-model dynamic simulations (2º, ½ º, & ¼º) over last 50 years completed (started - coupling with BGC model) Southern Ocean, high-res (1/12º) regional simulations with NEMO/PISCES in preparation (started - thesis study of Carolina Dufour)  Does explictly resolving eddies change estimated ongoing slowdown in Southern- Ocean CO 2 uptake? 2.Effect of forcing fields ?  NEMO/PISCES simulations over last ~50 years Coding and tests underway (started, Jennifer Simeon) at 3 resolutions (2º, ½ º, & ¼º) & different sets of forcing fields with different sets of forcing fields (NCEP, ERA40, CORE, DFS3, DFS4) Effect of physical data assimilation (SST, altimetry, …)? –Ongoing study within the Mercator-vert project (Moulin et al., 2008)

this study CO 2 Gas Exchange Rates from Inversion of Water Column Data R. Schlitzer, Alfred Wegener Institute, Bremerhaven Pre-industrial (“natural”) annual-mean CO 2 Fluxes from inversion of ocean interior DIC data Mikaloff Fletcher, 2007 and other models broad agreement with Mikaloff Fletcher, 2007 and other models net outgasing in Southern Ocean 0.6 PgC yr -1 south of 50°S net outgasing in Southern Ocean 0.6 PgC yr -1 south of 50°S near-zero interhemispheric oceanic C transport near-zero interhemispheric oceanic C transport

Seasonal mean RMSE for ARGO-based pCO2 estimates

ARGO-based Position+SST+Chl MLD+SST+Chl Annual cycle of basinwide RMS-error for remote-sensing and ARGO-based pCO2 estimates Friedrich, T., and A. Oschlies 2008, Neural-network based estimates of North Atlantic surface pCO2 from satellite data - a methodological study, submitted Friedrich, T., and A. Oschlies 2008, How to estimate North Atlantic surface pCO2 from ARGO float data, submitted

Assimilation of pCO2 data into an obgc model: rationale and progress The Met Office uses the Forecast Ocean Assimilation Model (FOAM) for its operational ocean forecasts. FOAM assimilates SST (and SSH) data to adjust the T and S fields (and so indirectly also the velocity fields). As part of the UK CASIX project, a scheme was developed to assimilate ocean colour data into a simple obgc model (the HadOCC model) embedded in FOAM. As well as altering the plankton, compensating adjustments are made to nutrients, DIC and alkalinity. However this does not affect errors in the background DIC and alkalinity fields., This work aims to adjust those background fields by assimilating pCO 2 data from SOO and from surveys (method explained on the next slide). Unfortunately, this project has not progressed this year due to personnel being required for development of the operational model (now completed). Work should restart in the new year.

Assimilation of pCO2 data into an obgc model: the scheme pCO 2 Model pCO 2 Effect of ocean colour assimilation Option A: orthogonal to pCO2 isobar DIC Alkalinity Target pCO 2 Option B: orthogonal to ocean colour The model pCO 2 is adjusted when the ocean colour is assimilated (compensating increments in DIC and Alk). We will test two options for adjusting towards the target pCO 2 (we assume pCO 2 data are available but not DIC or Alkalinity). Option A: the shift is orthogonal to the lines of constant pCO 2 Option B: the shift is orthogonal to the adjustment due to ocean colour assimilation.