Harmonized gap-filled datasets from 20 urban flux tower sites
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Published:2022-11-22
Issue:11
Volume:14
Page:5157-5178
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ISSN:1866-3516
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Container-title:Earth System Science Data
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language:en
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Short-container-title:Earth Syst. Sci. Data
Author:
Lipson MathewORCID, Grimmond SueORCID, Best Martin, Chow Winston T. L., Christen Andreas, Chrysoulakis NektariosORCID, Coutts Andrew, Crawford Ben, Earl Stevan, Evans JonathanORCID, Fortuniak KrzysztofORCID, Heusinkveld Bert G.ORCID, Hong Je-Woo, Hong JinkyuORCID, Järvi LeenaORCID, Jo Sungsoo, Kim Yeon-Hee, Kotthaus SimoneORCID, Lee KeunminORCID, Masson Valéry, McFadden Joseph P., Michels Oliver, Pawlak Wlodzimierz, Roth Matthias, Sugawara Hirofumi, Tapper Nigel, Velasco ErikORCID, Ward Helen ClaireORCID
Abstract
Abstract. A total of 20 urban neighbourhood-scale eddy covariance flux
tower datasets are made openly available after being harmonized to create a
50 site–year collection with broad diversity in climate and urban surface
characteristics. Variables needed as inputs for land surface models
(incoming radiation, temperature, humidity, air pressure, wind and
precipitation) are quality controlled, gap-filled and prepended with 10 years of reanalysis-derived local data, enabling an extended spin up to
equilibrate models with local climate conditions. For both gap filling and
spin up, ERA5 reanalysis meteorological data are bias corrected using
tower-based observations, accounting for diurnal, seasonal and local urban
effects not modelled in ERA5. The bias correction methods developed perform
well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015).
Other variables (turbulent and upwelling radiation fluxes) are harmonized
and quality controlled without gap filling. Site description metadata
include local land cover fractions (buildings, roads, trees, grass etc.),
building height and morphology, aerodynamic roughness estimates, population
density and satellite imagery. This open collection can help extend our
understanding of urban environmental processes through observational
synthesis studies or in the evaluation of land surface environmental models
in a wide range of urban settings. These data can be accessed from
https://doi.org/10.5281/zenodo.7104984
(Lipson et al.,
2022).
Funder
Climate Extremes HORIZON EUROPE European Research Council National Computational Infrastructure
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
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