Datasynthesis

WG 3: Datasynthesis

Coordinators

Dr. Stefan Mulitza

MARUM - Zentrum für Marine Umweltwissenschaften der Universität Bremen, Leobener Strasse, 28359 Bremen

 

 

Prof. Dr. Ulrike Herzschuh

Alfred-Wegener-Institut (AWI) Helmholtz-Zentrum für Polar- und Meeresforschung, Telegrafenberg, Potsdam

 

Participating institutions

1.    MARUM - Zentrum für Marine Umweltwissenschaften der Universität Bremen, Bremen
2.    Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven and Potsdam
3.    Helmholtz-Zentrum Potsdam – Deutsches GeoForschungsZentrum (GFZ), Potsdam
4.    Department of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's, NL A1B 3X7, Canada

 

Summary

Proxy data are key to validate the comprehensive ESMs used in WG 1 and 2. The aim of WG3 is to generate a quality-controlled synthesis of quantitative proxy records from the marine and terrestrial realms. This synthesis will allow to diagnose individual aspects of the model simulations (ocean circulation, ocean biogeochemistry, hydrological cycle, land cover and vegetation and the pattern of climate variability) in CC.2. In the 2nd phase, the existing effort in the synthesis of proxy time series will be extended from the last 40,000 years to the entire last glacial-interglacial cycle. In addition to the extension of proxy data sets created in Phase I, novel types of proxy data of particular relevance to WG1 will be compiled in Phase II, including ice-sheet distribution and stable isotope data from lake sediments. To advance the proxy-model-comparison in cooperation with CC.2, WG3 will particularly focus on modelling the processes of proxy formation (i.e. habitat effects of proxy-signal carriers) and the processes that distort primary signals in climate archives (i.e. bioturbation). The application of proxy models will result in improved estimates of the spectrum of climate variability and more realistic proxy error margins, needed for a meaningful model-data comparison in CC.2. The evaluation of climate model results against robust paleoclimatic evidence is essential to inform our confidence into future climate projections by the same models.