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Influence of changed vegetation fields on regional climate simulations in the Barents Sea region

MPG-Autoren
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Goettel,  H.
The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Alexander,  J.
The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Keup-Thiel,  E.
Model & Data Group, MPI for Meteorology, Max Planck Society;

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Rechid,  D.
The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Hagemann,  S.
The Land in the Earth System, MPI for Meteorology, Max Planck Society;
Terrestrial Hydrology, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Blome,  T.
The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Jacob,  D.
The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;
B 2 - Land Use and Land Cover Change, Research Area B: Climate Manifestations and Impacts, The CliSAP Cluster of Excellence, External Organizations;

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Zitation

Goettel, H., Alexander, J., Keup-Thiel, E., Rechid, D., Hagemann, S., Blome, T., et al. (2008). Influence of changed vegetation fields on regional climate simulations in the Barents Sea region. Climatic Change, 87(1-2), 35-50. doi:10.1007/s10584-007-9341-5.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0011-F9DE-C
Zusammenfassung
In the context of the EU-Project BALANCE (http://balance-eu.info) the regional climate model REMO was used for extensive calculations of the Barents Sea climate to investigate the vulnerability of this region to climate change. The regional climate model REMO simulated the climate change of the Barents Sea Region between 1961 and 2100 (Control and Climate Change run, CCC-Run). REMO on ~50 km horizontal resolution was driven by the transient ECHAM4/OPYC3 IPCC SRES B2 scenario. The output of the CCC-Run was applied to drive the dynamic vegetation model LPJ-GUESS. The results of the vegetation model were used to repeat the CCC-Run with dynamic vegetation fields. The feedback effect of the modified vegetation on the climate change signal is investigated and discussed with focus on precipitation, temperature and snow cover. The effect of the offline coupled vegetation feedback run is much lower than the greenhouse gas effect.