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Towards long-Term standardised carbon and greenhouse gas observations for monitoring Europe's terrestrial ecosystems : A review

Franz, Daniela; Acosta, Manuel; Altimir, Núria; Arriga, Nicola; Arrouays, Dominique; Aubinet, Marc; Aurela, Mika; Ayres, Edward; López-Ballesteros, Ana and Barbaste, Mireille, et al. (2018) In International Agrophysics 32(4). p.439-455
Abstract

Research infrastructures play a key role in launching a new generation of integrated long-Term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon... (More)

Research infrastructures play a key role in launching a new generation of integrated long-Term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-Access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

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Contribution to journal
publication status
published
subject
keywords
carbon cycle, GHG exchange, ICOS, observational network, standardised monitoring
in
International Agrophysics
volume
32
issue
4
pages
17 pages
publisher
De Gruyter
external identifiers
  • scopus:85056548378
ISSN
0236-8722
DOI
10.1515/intag-2017-0039
language
English
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yes
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c492f947-9351-46da-9a44-27572067d300
date added to LUP
2019-01-18 11:40:41
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2019-08-14 04:30:57
@article{c492f947-9351-46da-9a44-27572067d300,
  abstract     = {<p>Research infrastructures play a key role in launching a new generation of integrated long-Term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O, H<sub>2</sub>O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-Access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.</p>},
  author       = {Franz, Daniela and Acosta, Manuel and Altimir, Núria and Arriga, Nicola and Arrouays, Dominique and Aubinet, Marc and Aurela, Mika and Ayres, Edward and López-Ballesteros, Ana and Barbaste, Mireille and Berveiller, Daniel and Biraud, Sébastien and Boukir, Hakima and Brown, Timothy and Brömmer, Christian and Buchmann, Nina and Burba, George and Carrara, Arnaud and Cescatti, Allessandro and Ceschia, Eric and Clement, Robert and Cremonese, Edoardo and Crill, Patrick and Darenova, Eva and Dengel, Sigrid and D'Odorico, Petra and Filippa, Gianluca and Fleck, Stefan and Fratini, Gerardo and Fuß, Roland and Gielen, Bert and Gogo, Sébastien and Grace, John and Graf, Alexander and Grelle, Achim and Gross, Patrick and Grönwald, Thomas and Haapanala, Sami and Hehn, Markus and Heinesch, Bernard and Heiskanen, Jouni and Herbst, Mathias and Herschlein, Christine and Hörtnagl, Lukas and Hufkens, Koen and Kljun, Natascha and Lindroth, Anders and Mölder, Meelis and Nilsson, Mats B. and Vesala, Timo and Vestin, Patrik and , },
  issn         = {0236-8722},
  keyword      = {carbon cycle,GHG exchange,ICOS,observational network,standardised monitoring},
  language     = {eng},
  month        = {12},
  number       = {4},
  pages        = {439--455},
  publisher    = {De Gruyter},
  series       = {International Agrophysics},
  title        = {Towards long-Term standardised carbon and greenhouse gas observations for monitoring Europe's terrestrial ecosystems : A review},
  url          = {http://dx.doi.org/10.1515/intag-2017-0039},
  volume       = {32},
  year         = {2018},
}