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MSc W. Feldmeijer (Wouter)

Darwin Center PhD student

VU University Amsterdam (VU)

Researchgroup: Mariene Biogeologie

Phone 1: +31 (0)20 598 7412
E-mail:

Visiting address:
De Boelelaan 1081- 1087
1081 HV Amsterdam
The Netherlands
Office F-338
Postal address:
de Boelelaan 1085
1081 HV Amsterdam
The Netherlands

MSc W. Feldmeijer (Wouter)

Darwin Center PhD student

VU University Amsterdam (VU)

Researchgroup: Mariene Biogeologie

Phone 1: +31 (0)20 598 7412
E-mail:

Visiting address:
De Boelelaan 1081- 1087
1081 HV Amsterdam
The Netherlands
Office F-338
Postal address:
de Boelelaan 1085
1081 HV Amsterdam
The Netherlands


Darwin Center programs and projects
3043: Seasonal extremes during rapid (sub-)millennial climate changes in the northern Arabian Sea

Projects
Abstract
Over the last decade, paleoceanographic proxy data have been used increasingly in conjunction with climate model experiments. However, there are major caveats which severely limit their usefulness. These limitations are mainly caused by the fact that paleoclimate records provide information on changes/ variability of climate parameters over a certain time period, while climate models often produce the state of the system for a given time-slice. Although the reconstruction of down to decadal climate variability has been improved, seasonal variability, i.e. climate variability within a certain time-slice, could not be addressed. We propose to reconstruct seasonal climate variability beyond the instrumental period that allows extraction of monsoon climate variability (i.e. seasonality) from sedimentary climate archives: i.e. for time-slices. By applying a refined multi-proxy approach (in combination with project 1) to sediment cores from the southwestern, central and northern part of the North Arabian Sea, a spatial reconstruction of the response in seasonal extremes of the upper ocean to Indian-Asian monsoon variability will be obtained for the selected periods of rapid climate change. The results will provide critical data for testing/validating climate models over times scales decisive for climate prediction.