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Footprints for Zurich-Hardau at 30-min resolution - 2022-08-25

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2022-08-25
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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.

2022-08-25 01:00:00
2022-08-25 23:30:00
half-hourly
Molinier, B., Kljun, N. (2026). Footprints for Zurich-Hardau at 30-min resolution - 2022-08-25, 2022-08-25, ICOS Cities, https://hdl.handle.net/11676/NXNhGhVPZqPlpFuqwK2HhdeH
BibTex
@misc{https://hdl.handle.net/11676/NXNhGhVPZqPlpFuqwK2HhdeH,
  author={Molinier, Betty and Kljun, Natascha},
  title={Footprints for Zurich-Hardau at 30-min resolution - 2022-08-25, 2022-08-25},
  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/NXNhGhVPZqPlpFuqwK2HhdeH},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/NXNhGhVPZqPlpFuqwK2HhdeH}
}
RIS
TY - DATA
T1 - Footprints for Zurich-Hardau at 30-min resolution - 2022-08-25, 2022-08-25
ID - 11676/NXNhGhVPZqPlpFuqwK2HhdeH
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/NXNhGhVPZqPlpFuqwK2HhdeH
PB - Carbon Portal
AU - Molinier, Betty
AU - Kljun, Natascha
KW - Flux footprints
KW - atmospheric modelling
KW - urban flux
KW - ICOS Cities
ER - 
zurich_footprint_220825.nc
34 MB (35318738 bytes)
3

Production

2026-02-04 11:00:00

Statistics

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Submission

2026-02-12 15:05:33
2026-02-12 15:05:28

Technical information

3573611a154f66a3e5a45baac0ad8785d7873424e386b011be8d03288814b866
NXNhGhVPZqPlpFuqwK2HhdeHNCTjhrARvo0DKIgUuGY
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.