ICOS

ETC NRT AuxData from Degero

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2023-09-30–2023-12-15

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11676/M7k5asbqSM6I_erKgeCXeXzh (link)

Automatically-produced, daily-growing (by data object deprecation) half-hourly specific diagnostic and derived variables needed to evaluate the correct functioning of the sensors, in particular the EC system. The data starts from the last respective L2 release.

Work was funded by grant National Research Infrastructure ICOS Sweden (2019-00205) from Swedish Research Council
Peichl, M., Marklund, P., Nilsson, M., Holst, J., Smith, P., Kozii, N., Dignam, R., Larmanou, E., Lofvenius, P., Molder, M., Lindgren, K. (2023). ETC NRT AuxData from Degero, 2023-09-30–2023-12-15, ICOS RI, https://hdl.handle.net/11676/M7k5asbqSM6I_erKgeCXeXzh
BibTex
@misc{https://hdl.handle.net/11676/M7k5asbqSM6I_erKgeCXeXzh,
  author={Peichl, Matthias and Marklund, Per and Nilsson, Mats and Holst, Jutta and Smith, Paul and Kozii, Nataliia and Dignam, Rowan and Larmanou, Eric and Lofvenius, Pernilla and Molder, Meelis and Lindgren, Kim},
  title={ETC NRT AuxData from Degero, 2023-09-30–2023-12-15},
  year={2023},
  url={https://hdl.handle.net/11676/M7k5asbqSM6I_erKgeCXeXzh},
  publisher={Ecosystem Thematic Centre},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/M7k5asbqSM6I_erKgeCXeXzh}
}
RIS
TY - DATA
T1 - ETC NRT AuxData from Degero, 2023-09-30–2023-12-15
ID - 11676/M7k5asbqSM6I_erKgeCXeXzh
PY - 2023
UR - https://hdl.handle.net/11676/M7k5asbqSM6I_erKgeCXeXzh
PB - Ecosystem Thematic Centre
AU - Peichl, Matthias
AU - Marklund, Per
AU - Nilsson, Mats
AU - Holst, Jutta
AU - Smith, Paul
AU - Kozii, Nataliia
AU - Dignam, Rowan
AU - Larmanou, Eric
AU - Lofvenius, Pernilla
AU - Molder, Meelis
AU - Lindgren, Kim
ER - 
ICOSETC_SE-Deg_AUXDATA_NRT.zip
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Acquisition

2023-09-30 22:30:00
2023-12-15 23:00:00

Production

2023-12-16 07:07:52

Statistics

1

Submission

2023-12-16 06:07:55
2023-12-16 06:07:53

Technical information

33b9396ac6ea48ce88fdeaca81e097797ce1e36861fb55f3fb95daad236598ca
M7k5asbqSM6I/erKgeCXeXzh42hh+1Xz+5XarSNlmMo