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Footprints for Paris-Romainville at 30-min resolution - 2023-02-13

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2023-02-13
11676/18vj8cpkftej547ztB1omsu5 (link)

Daily flux footprints for the Paris-Romainville flux-tower in France at 30-minute temporal resolution. Each dataset contains up to 48 footprints with the following variables each: Time, X, Y, Boundary Layer Height Quality Flag, and Footprint Climatology. The flux footprints are computed using FFP as described in Kljun et al. (2015), https://doi.org/10.5194/gmd-8-3695-2015, at 10-meter spatial resolution using ETC L2 Fluxes from Romainville, PID: 11676/TwGCXiTNxEpW-Iq_r8esdE5v. The projection can be customized, but the footprints were calculated in UTM 32N.

This work is part of the ICOS Cities/PAUL Pilot Applications in Urban Landscapes project. In this version, footprints have been calculated using the ETC L2 Flux dataset for Romainville, PID: 11676/TwGCXiTNxEpW-Iq_r8esdE5v.

2023-02-13 00:30:00
2023-02-13 21:30:00
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Molinier, B., Kljun, N. (2026). Footprints for Paris-Romainville at 30-min resolution - 2023-02-13, 2023-02-13, ICOS Cities, https://hdl.handle.net/11676/18vj8cpkftej547ztB1omsu5
BibTex
@misc{https://hdl.handle.net/11676/18vj8cpkftej547ztB1omsu5,
  author={Molinier, Betty and Kljun, Natascha},
  title={Footprints for Paris-Romainville at 30-min resolution - 2023-02-13, 2023-02-13},
  year={2026},
  note={Daily flux footprints for the Paris-Romainville flux-tower in France at 30-minute temporal resolution. Each dataset contains up to 48 footprints with the following variables each: Time, X, Y, Boundary Layer Height Quality Flag, and Footprint Climatology. The flux footprints are computed using FFP as described in Kljun et al. (2015), https://doi.org/10.5194/gmd-8-3695-2015, at 10-meter spatial resolution using ETC L2 Fluxes from Romainville, PID: 11676/TwGCXiTNxEpW-Iq_r8esdE5v. The projection can be customized, but the footprints were calculated in UTM 32N.

This work is part of the ICOS Cities/PAUL Pilot Applications in Urban Landscapes project. In this version, footprints have been calculated using the ETC L2 Flux dataset for Romainville, PID: 11676/TwGCXiTNxEpW-Iq_r8esdE5v.},
  keywords={Flux footprints, atmospheric modelling, urban flux, ICOS Cities},
  url={https://hdl.handle.net/11676/18vj8cpkftej547ztB1omsu5},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/18vj8cpkftej547ztB1omsu5}
}
RIS
TY - DATA
T1 - Footprints for Paris-Romainville at 30-min resolution - 2023-02-13, 2023-02-13
ID - 11676/18vj8cpkftej547ztB1omsu5
PY - 2026
AB - Daily flux footprints for the Paris-Romainville flux-tower in France at 30-minute temporal resolution. Each dataset contains up to 48 footprints with the following variables each: Time, X, Y, Boundary Layer Height Quality Flag, and Footprint Climatology. The flux footprints are computed using FFP as described in Kljun et al. (2015), https://doi.org/10.5194/gmd-8-3695-2015, at 10-meter spatial resolution using ETC L2 Fluxes from Romainville, PID: 11676/TwGCXiTNxEpW-Iq_r8esdE5v. The projection can be customized, but the footprints were calculated in UTM 32N.

This work is part of the ICOS Cities/PAUL Pilot Applications in Urban Landscapes project. In this version, footprints have been calculated using the ETC L2 Flux dataset for Romainville, PID: 11676/TwGCXiTNxEpW-Iq_r8esdE5v.
UR - https://hdl.handle.net/11676/18vj8cpkftej547ztB1omsu5
PB - Carbon Portal
AU - Molinier, Betty
AU - Kljun, Natascha
KW - Flux footprints
KW - atmospheric modelling
KW - urban flux
KW - ICOS Cities
ER - 
paris_footprint_230213.nc
37 MB (38290597 bytes)
3

Production

2026-02-03 11:00:00

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Submission

2026-02-12 14:46:09
2026-02-12 14:46:07

Technical information

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18vj8cpkftej547ztB1omsu5XgK7KtCfPndF7XX07P8
S: 48.813187, W: 2.313349, N: 48.956981, E: 2.531389
Flux footprints ICOS Cities atmospheric modelling urban flux
3 pilot cities
15 countries
15 cities
30 scientific partners
13M€ funding
2021-2025
EU flag PAUL, Pilot Applications in Urban Landscapes - Towards integrated city observatories for greenhouse gases (ICOS Cities), has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 101037319.