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Footprints for Zurich-Hardau at 30-min resolution - 2022-08-02

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2022-08-02
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Daily flux footprints for the Zurich-Hardau flux-tower in Switzerland 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 Hardau, PID: 11676/Lg2RRHAdsLee0lsF-9KsTC-r. 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 Hardau PID: 11676/Lg2RRHAdsLee0lsF-9KsTC-r.

2022-08-02 00:00:00
2022-08-02 19:30:00
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Molinier, B., Kljun, N. (2026). Footprints for Zurich-Hardau at 30-min resolution - 2022-08-02, 2022-08-02, ICOS Cities, https://hdl.handle.net/11676/UQQ7UG2CoEUVU71IcFwiYlpL
BibTex
@misc{https://hdl.handle.net/11676/UQQ7UG2CoEUVU71IcFwiYlpL,
  author={Molinier, Betty and Kljun, Natascha},
  title={Footprints for Zurich-Hardau at 30-min resolution - 2022-08-02, 2022-08-02},
  year={2026},
  note={Daily flux footprints for the Zurich-Hardau flux-tower in Switzerland 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 Hardau, PID: 11676/Lg2RRHAdsLee0lsF-9KsTC-r. 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 Hardau PID: 11676/Lg2RRHAdsLee0lsF-9KsTC-r.},
  keywords={Flux footprints, atmospheric modelling, urban flux, ICOS Cities},
  url={https://hdl.handle.net/11676/UQQ7UG2CoEUVU71IcFwiYlpL},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/UQQ7UG2CoEUVU71IcFwiYlpL}
}
RIS
TY - DATA
T1 - Footprints for Zurich-Hardau at 30-min resolution - 2022-08-02, 2022-08-02
ID - 11676/UQQ7UG2CoEUVU71IcFwiYlpL
PY - 2026
AB - Daily flux footprints for the Zurich-Hardau flux-tower in Switzerland 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 Hardau, PID: 11676/Lg2RRHAdsLee0lsF-9KsTC-r. 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 Hardau PID: 11676/Lg2RRHAdsLee0lsF-9KsTC-r.
UR - https://hdl.handle.net/11676/UQQ7UG2CoEUVU71IcFwiYlpL
PB - Carbon Portal
AU - Molinier, Betty
AU - Kljun, Natascha
KW - Flux footprints
KW - atmospheric modelling
KW - urban flux
KW - ICOS Cities
ER - 
zurich_footprint_220802.nc
41 MB (42645225 bytes)
3

Production

2026-02-04 11:00:00

Statistics

0

Submission

2026-02-12 15:03:41
2026-02-12 15:03:38

Technical information

51043b506d82a0451553bd48705c22625a4b1510a26d7412a34af41b29b5c8b2
UQQ7UG2CoEUVU71IcFwiYlpLFRCibXQSo0r0Gym1yLI
S: 47.32634, W: 8.429202, N: 47.436353, E: 8.591174
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.