Radiolarian artificial neural network based estimation of the paleo sea surface temperatures and salinities in the Arctic and Antarctic Ocean and their response to insolation forcing

Project Information

RADANN

Grant agreement ID: 7718

Project closed

Start date 1 October 2005

End date 30 September 2007

Funded under

• Human resources and Mobility in the specific programme for research, technological development and demonstration "Structuring the European Research Area" under the Sixth Framework Programme 2002-2006

Total cost No data

EU contribution € 227 191,00

Coordinated by

GÖTEBORG UNIVERSITY
Sweden

Objective

The modern Boreal summer corresponds to Antarctic winter season and vice versa, while their summer and winter are separated by 6 months due to anti-phase bipolar seesaw in the solar insolation. Similarly, Boreal (65oN) and Austral (65oS) summer insolations suggest an anti-phase relationship, implying warmer Arctic corresponding to cooler Antarctic in the geological past. Sea surface temperature (SST) estimates for the 18000 years BP last glacial maximum (LGM) are suggested to be underestimated by recent studies.

Artificial neural networks (ANN) are a branch of artificial intelligence, computer systems that have the ability to learn in a way similar to the mammalian brain. ANN-based SST estimates have been found to be far better than standard methods in paleoclimate research. The IIF candidate has generated radiolarian ANN with lower errors in estimates than previously used methods. Therefore, it is envisaged that radiolarian ANN will be used to estimate the paleo-SSTs and salinities for the last 150,000 years BP using high resolution data (2-3 k) from sediment cores from the Arctic and Antarctic Oceans with emphasis on comparison between the Holocene, LGM and Emian interglacial during the tenure of the IIF fellowship under supervision of Prof. Malmgren at Goteborg University, Sweden.

We expect that thermal changes in the world ocean at 18K BP reported by CLIMAP would be quite different, which would have a wider implications on boundary conditions used in general circulation models currently used. Radiolarian ANN-based paleo-SSTs and salinities are envisaged to reveal more realistic thermohaline changes in the subtropical and subpolar regions in both hemispheres, at the strategically located gateway of the thermohaline conveyor belt, which transports tropical heat to the north Atlantic resulting in warmer winters in the northern Europe than the scenario projected by shutting down of the conveyor belt due to abrupt climatic changes.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.

• natural sciences › earth and related environmental sciences › palaeontology › paleoclimatology
• natural sciences › computer and information sciences › artificial intelligence › computational intelligence

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Keywords

• Antarctic Ocean
• Arctic Ocean
• Artificial neural networks
• Climate change
• Orbital forcing
• Paleoceanography
• Quantitative analysis
• Radiolaria
• Reconstructions
• Salinity

Programme(s)

• FP6-MOBILITY - Human resources and Mobility in the specific programme for research, technological development and demonstration "Structuring the European Research Area" under the Sixth Framework Programme 2002-2006

Topic(s)

• MOBILITY-2.3 - Marie Curie Incoming International Fellowships (IIF)

Call for proposal

FP6-2002-MOBILITY-7
See other projects for this call

Funding Scheme

IIF - Marie Curie actions-Incoming International Fellowships

Coordinator

GÖTEBORG UNIVERSITY

• EU contribution: No data
• Address: Vasaparken ; 100 GÖTEBORG ; Sweden
• Total cost: No data