English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling

MPS-Authors
/persons/resource/persons62529

Rödenbeck,  Christian
Inverse Data-driven Estimation, Dr. C. Rödenbeck, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

External Resource
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

BGC2380.pdf
(Publisher version), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Bastos, A., Janssens, I. A., Gouveia, C. M., Trigo, R. M., Ciais, P., Chevallier, F., et al. (2016). European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling. Nature Communications, 7: 10315. doi:10.1038/ncomms10315.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0029-5996-2
Abstract
Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic
(EA) pattern is known to modulate NAO strength and location. Using observation-driven and
modelled data sets, we show that multi-annual variability patterns of European Net Biome
Productivity (NBP) are linked to anomalies in heat and water transport controlled by the
NAO–EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase,
associated with cool summers with wet soils which enhance photosynthesis. During
anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in
photosynthesis and respiration. The predominance of anti-phase years in the early 2000s
may explain the European-wide reduction of carbon uptake during this period, reported in
previous studies. Results show that improving the capability of simulating atmospheric
circulation patterns may better constrain regional carbon sink variability in coupled
carbon-climate models.