Conference opportunities for sponsored students

European Space Agency (ESA) offers European students the opportunity to attend high-level space related conferences and workshops around the world.

Opportunities are available across a wide range of science and engineering fields. 

ESA Education will provide sponsorship to a select few students to support their participation in these conferences. The selection is competitive and clear priority will be given to students whose abstracts have been accepted by the conference organisers and who have not been sponsored by ESA before.

The full list of conferences for 2013 has been posted here.

Carbon fugacity new results

New results relevant to air-sea gas flux studies have come in from the SSTWIND-Carbon Fugacity project, carried out by ALTRAN Brest team in 2012 in collaboration with the Laboratoire d'Oceanographie Spatiale at IFREMER. 

The flux between ocean and atmosphere, F, of a gas such as CO₂ is given by

where k is the gas transfer velocity, α is the solubility of the gas in water and p is the partial pressure of the gas in question. 

We can substitute the fugacity of CO₂ as a proxy for pCO₂ and one aim of the project was to verify empirical formulae for fugacity of atmospheric and oceanic CO₂ (fCO_{2 ATM} and fCO_{2 OCEAN}, respectively). Once the accuracy of the formulae was assessed, the formulae were used to generate monthly mean climatologies of fCO_{2 OCEAN} and fCO_{2 ATM} and ΔfCO₂ (= fCO_{2 OCEAN} – fCO_{2 ATM} ) in the subtropical gyre of the North Atlantic.

The formula tested are of the form

where (pCO₂)_ATM is calculated as a function of molar fraction of CO₂, sea surface temperature (SST), sea surface salinity and atmospheric pressure. Two separate sets of constants (c₁ to c₅) are used for the periods February-July and August-January.

The data used to recreate the fugacities of atmospheric and ocean using these empiric functions come from different sources. Atmospheric molar fraction was measured at a World Meteorological Organisation (WMO) station in the Barbados. Surface air pressure was taken from the National Center for Envionmental Prediction (NCEP) reanalyses and SST from the satellite sensors AVHRR (Advanced Very High Resolution Radiometer) and AMSR (Advanced Microwave Surface Radiometer). A constant salinity was used, as the formulae are a weak function of this parameter.

To validate the formulae, data from the Surface Ocean CO₂ Atlas (SOCAT) were used. This database contains observations from Voluntary Observing Ships across the global oceans, gridded to a 1ºx1º monthly average value. The fields are very heterogenous in quality, however, with numerous  obervations per month along well-travelled ship routes but very few, if any, observations in other areas. Figure 1 shows the number of observations in the SOCAT database in the zone of study.

Figure 1. Number of observations in the SOCAT database over the study zone.

When the spatial heterogeneity is taken into account and the modelled fCO₂ is compared to points with more than 72 observations (equivalent to 6 consecutive years), the correlation with the observed fCO2 is greater than 0.9. Equally, the mean error is approximately 2% and the maximum error is 6% over the zone. 

Figure 2. Annual trend, in μatm/year, of fCO_{2 ATM} (top), fCO_{2 OCEAN} (middle) and ΔfCO₂ (bottom) between 1997 and 2012.

The trends of the fCO_{2 ATM} and fCO_{2 OCEAN} in the area increase over the period 1997-2012, being 1.85 uatm/year and 1.96 uatm/year respectively. These trends follow that of SST trends over the same period. Both show a marked annual cycle, with a phase lag of 6 months: fCO2_ATM peaks in winter, and fCO_{2 OCEAN} in summer. The fCO_{2 OCEAN} drives the spatial variability of ΔfCO₂, however, as shown in figure 2.

Figure 3. Monthly mean ΔfCO2, in μatm.

Figure 4. Monthly mean fCO_{2 ATM}, in μatm.

Figure 5. Monthly mean fCO_{2 OCEAN}, in μatm.

Monthly climatologies (figures 3, 4 and 5) show that the ocean acts as a sink of CO2 from January to April and as a source between May and December, with the most pronounced seasonal differences in the north of the study zone.