GEOTRACES publishes the motivations and description of its first Intermediate Data Product

Science Highlights

25 November 2015

GEOTRACES proposes an article that describes its first integrated and quality controlled Intermediate Data Product 2014 (IDP2014): the digital data package and the eGEOTRACES electronic Atlas that provides section plots and animated 3D scenes of the data. The 3D scenes provide geographical and bathymetric context crucial for tracer assessment and interpretation.

With this release, GEOTRACES seeks to promote intensified collaboration within the marine geochemical community and beyond. The availability of a large integrated and quality controlled dataset, such as the IDP2014, will allow a much wider range of studies than would be possible with individual cruise data alone. Such open access is also an opportunity for other communities as for example physical and biological oceanographers, modellers but also policy makers…

eGEOTRACES dissolved Zn Atlantic Ocean

Figure: 3D scene showing the distribution of dissolved zinc (Zn) in the Atlantic Ocean.

Reference:

Mawji, E., Schlitzer, R., Masferrer-Dodas, E., et al. (2015). The GEOTRACES Intermediate Data Product 2014. Marine Chemistry, 177, 1–8. doi:10.1016/j.marchem.2015.04.005

 

Latest highlights

Major controls on the fate of dissolved manganese in the northeastern Indian Ocean

Malla and Singh investigated the key factors controlling dissolved manganese in the northeastern Indian Ocean.

An original approach to assess the particulate trace metal concentrations in seawater

Sohrin and co-workers propose defining particulate trace metal as the difference between total dissolvable and dissolved metals after a long storage of filtered and unfiltered acidified seawater.

Constraining aerosol deposition over the global ocean by the cosmogenic beryllium-7

He and co-workers propose a global estimate of aerosol deposition onto the ocean using the cosmogenic radionuclide beryllium-7.

Oceanic lead concentrations and isotopes mapped using explainable machine learning

Using three machine learning models, Olivelli and her colleagues generated global climatologies of lead concentrations and isotopes…

Rechercher