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Harmonized gap-filled datasets from 20 urban flux tower sites

Lipson, M. ORCID:, Grimmond, S. ORCID:, Best, M., Chow, W. T. L., Christen, A., Chrysoulakis, N. ORCID:, Coutts, A., Crawford, B., Earl, S., Evans, J. ORCID:, Fortuniak, K. ORCID:, Heusinkveld, B. G. ORCID:, Hong, J.-W., Hong, J. ORCID:, Järvi, L. ORCID:, Jo, S., Kim, Y.-H., Kotthaus, S. ORCID:, Lee, K. ORCID:, Masson, V. , McFadden, J. P., Michels, O., Pawlak, W., Roth, M., Sugawara, H., Tapper, N., Velasco, E. ORCID: and Ward, H. C. ORCID: (2022) Harmonized gap-filled datasets from 20 urban flux tower sites. Earth System Science Data, 14 (11). pp. 5157-5178. ISSN 1866-3516

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To link to this item DOI: 10.5194/essd-14-5157-2022


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 (Lipson et al., 2022).

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:110116
Publisher:Copernicus Publications


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