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Record W4393846779 · doi:10.5281/zenodo.5517550

Data for "Harmonized gap-filled dataset from 20 urban flux tower sites" for the Urban-PLUMBER project

2022· dataset· en· W4393846779 on OpenAlexaboutno aff
Mathew Lipson, Sue Grimmond, Martin Best, Winston Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, J. G. Evans, Krzysztof Fortuniak, B.G. Heusinkveld, Je‐Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, J. P. McFadden, Oliver Michels, Włodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, Helen C. Ward

Bibliographic record

VenueSocio-Environmental Systems Modeling · 2022
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsTowerFlux (metallurgy)Transport engineeringComputer scienceEngineeringCivil engineeringChemistry

Abstract

fetched live from OpenAlex

Flux tower observations, model spin-up and site characteristics data for Urban-PLUMBER sites associated with the manuscript: "Harmonized, gap-filled dataset from 20 urban flux tower sites" https://doi.org/10.5194/essd-14-5157-2022 Use of any data must give credit through citation of the above manuscript and other site sources as appropriate (see below). We recommend data users consult with site contributing authors and/or the coordination team in the project planning stage. Relevant site contacts are included in site metadata. Data can be downloaded from the bottom of this page. Sitename City Country Observed period References AU-Preston Melbourne Australia Aug 2003 – Nov 2004 (Coutts et al., 2007a, b) AU-SurreyHills Melbourne Australia Feb 2004 – Jul 2004 (Coutts et al., 2007a, b) CA-Sunset Vancouver Canada Jan 2012 – Dec 2016 (Christen et al., 2011; Crawford and Christen, 2015) FI-Kumpula Helsinki Finland Dec 2010 – Dec 2013 (Karsisto et al., 2016) FI-Torni Helsinki Finland Dec 2010 – Dec 2013 (Järvi et al., 2018; Nordbo et al., 2013) FR-Capitole Toulouse France Feb 2004 – Mar 2005 (Masson et al., 2008; Goret et al., 2019) GR-HECKOR Heraklion Greece Jun 2019 – Jun 2020 (Stagakis et al., 2019) JP-Yoyogi Tokyo Japan Mar 2016 – Mar 2020 (Hirano et al., 2015; Ishidoya et al., 2020) KR-Jungnang Seoul South Korea Jan 2017 – Apr 2019 (Jo et al., n.d.; Hong et al., 2020) KR-Ochang Ochang South Korea Jun 2015 – Jul 2017 (Hong et al., 2019, 2020) MX-Escandon Mexico City Mexico Jun 2011 – Sep 2012 (Velasco et al., 2011, 2014) NL-Amsterdam Amsterdam Netherlands Jan 2019 – Oct 2020 (Steeneveld et al., 2020) PL-Lipowa Łódź Poland Jan 2008 – Dec 2012 (Fortuniak et al., 2013; Pawlak et al., 2011) PL-Narutowicza Łódź Poland Jan 2008 – Dec 2012 (Fortuniak et al., 2013, 2006) SG-TelokKurau Singapore Singapore Feb 2015 – Feb 2016 (Roth et al., 2017) UK-KingsCollege London UK Apr 2012 – Jan 2014 (Bjorkegren et al., 2015; Kotthaus and Grimmond, 2014a, b) UK-Swindon Swindon UK May 2011 – Apr 2013 (Ward et al., 2013) US-Baltimore Baltimore USA Jan 2002 – Jan 2007 (Crawford et al., 2011) US-Minneapolis Minneapolis USA Jun 2006 – May 2009 (Peters et al., 2011; Menzer and McFadden, 2017) US-WestPhoenix Phoenix USA Dec 2011 – Jan 2013 (Chow, 2017; Chow et al., 2014) For further site information and timeseries plots see https://urban-plumber.github.io/sites. For processing code see https://github.com/matlipson/urban-plumber_pipeline. Data Two data archives are available on this page. The full collection includes all observed, gap-filled, spin-up and site characteristic data, in both netcdf and text form. The "obs_only" archive includes a duplicate of site observation timeseries (after quality control) in a single netcdf file. Full collection The full archive includes site folders with: index.html: A summary page with site characteristics and timeseries plots. SITENAME_sitedata_v1.csv: comma separated file for numerical site characteristics e.g. location, surface cover fraction etc. timeseries/ (following files are available as netCDF and txt) SITENAME_raw_observations_v1: site observed timeseries before project-wide quality control. SITENAME_clean_observations_v1: site observed timeseries after project-wide quality control. SITENAME_metforcing_v1: gap-filled and prepended (10yr spinup) site observation forcing dataset for model evaluation. SITENAME_era5_corrected_v1: site ERA5 surface data (1990-2020) with bias corrections as applied in the final dataset. "Obs Only" This archive contains duplicate data from the full collection (observations after QC): UP_all_clean_observations_UTC_v1.nc: in coordinated universal time (UTC) UP_all_clean_observations_localstandardtime_v1.nc: in local standard time Site references Bjorkegren, A. B., Grimmond, C. S. B., Kotthaus, S., and Malamud, B. D.: CO2 emission estimation in the urban environment: Measurement of the CO2 storage term, Atmospheric Environment, 122, 775–790, https://doi.org/10.1016/j.atmosenv.2015.10.012, 2015. Chow, W.: Eddy covariance data measured at the CAP LTER flux tower located in the west Phoenix, AZ neighborhood of Maryvale from 2011-12-16 through 2012-12-31, https://doi.org/10.6073/PASTA/FED17D67583EDA16C439216CA40B0669, 2017. Chow, W. T. L., Volo, T. J., Vivoni, E. R., Jenerette, G. D., and Ruddell, B. L.: Seasonal dynamics of a suburban energy balance in Phoenix, Arizona, International Journal of Climatology, 34, 3863–3880, https://doi.org/10.1002/joc.3947, 2014. Christen, A., Coops, N. C., Crawford, B. R., Kellett, R., Liss, K. N., Olchovski, I., Tooke, T. R., van der Laan, M., and Voogt, J. A.: Validation of modeled carbon-dioxide emissions from an urban neighborhood with direct eddy-covariance measurements, Atmospheric Environment, 45, 6057–6069, https://doi.org/10.1016/j.atmosenv.2011.07.040, 2011. Coutts, A. M., Beringer, J., and Tapper, N. J.: Characteristics influencing the variability of urban CO2 fluxes in Melbourne, Australia, Atmospheric Environment, 41, 51–62, https://doi.org/10.1016/j.atmosenv.2006.08.030, 2007a. Coutts, A. M., Beringer, J., and Tapper, N. J.: Impact of Increasing Urban Density on Local Climate: Spatial and Temporal Variations in the Surface Energy Balance in Melbourne, Australia, J. Appl. Meteor. Climatol., 46, 477–493, https://doi.org/10.1175/JAM2462.1, 2007b. Crawford, B. and Christen, A.: Spatial source attribution of measured urban eddy covariance CO2 fluxes, Theor Appl Climatol, 119, 733–755, https://doi.org/10.1007/s00704-014-1124-0, 2015. Crawford, B., Grimmond, C. S. B., and Christen, A.: Five years of carbon dioxide fluxes measurements in a highly vegetated suburban area, Atmospheric Environment, 45, 896–905, https://doi.org/10.1016/j.atmosenv.2010.11.017, 2011. Fortuniak, K., Kłysik, K., and Siedlecki, M.: New measurements of the energy balance components in Łódź, in: Preprints, sixth International Conference on Urban Climate: 12-16 June, 2006, Göteborg, Sweden, Sixth International Conference On Urban Climate, Göteborg, Sweden, 64–67, 2006. Fortuniak, K., Pawlak, W., and Siedlecki, M.: Integral Turbulence Statistics Over a Central European City Centre, Boundary Layer Meteorology; Dordrecht, 146, 257–276, https://doi.org/10.1007/s10546-012-9762-1, 2013. Goret, M., Masson, V., Schoetter, R., and Moine, M.-P.: Inclusion of CO2 flux modelling in an urban canopy layer model and an evaluation over an old European city centre, Atmospheric Environment: X, 3, 100042, https://doi.org/10.1016/j.aeaoa.2019.100042, 2019. Hirano, T., Sugawara, H., Murayama, S., and Kondo, H.: Diurnal Variation of CO2 Flux in an Urban Area of Tokyo, Sola, 11, 100–103, https://doi.org/10.2151/sola.2015-024, 2015. Hong, J., Lee, K., and Hong, J.-W.: Observational data of Ochang and Jungnang in Korea, 2020. Hong, J.-W., Hong, J., Chun, J., Lee, Y. H., Chang, L.-S., Lee, J.-B., Yi, K., Park, Y.-S., Byun, Y.-H., and Joo, S.: Comparative assessment of net CO2 exchange across an urbanization gradient in Korea based on eddy covariance measurements, Carbon Balance and Management, 14, 13, https://doi.org/10.1186/s13021-019-0128-6, 2019. Ishidoya, S., Sugawara, H., Terao, Y., Kaneyasu, N., Aoki, N., Tsuboi, K., and Kondo, H.: O2 : CO2 exchange ratio for net turbulent flux observed in an urban area of Tokyo, Japan, and its application to an evaluation of anthropogenic CO2 emissions, Atmospheric Chemistry and Physics, 20, 5293–5308, https://doi.org/10.5194/acp-20-5293-2020, 2020. Järvi, L., Rannik, Ü., Kokkonen, T. V., Kurppa, M., Karppinen, A., Kouznetsov, R. D., Rantala, P., Vesala, T., and Wood, C. R.: Uncertainty of eddy covariance flux measurements over an urban area based on two towers, Atmospheric Measurement Techniques, 11, 5421–5438, https://doi.org/10.5194/amt-11-5421-2018, 2018. Jo, S., Hong, J.-W., and Hong, J.: The observational flux measurement data of suburban and low-residential areas in Korea (in preparation), n.d. Karsisto, P., Fortelius, C., Demuzere, M., Grimmond, C. S. B., W., O. K., Kouznetsov, R., Masson, V., and Järvi, L.: Seasonal surface urban energy balance and wintertime stability simulated using three land‐surface models in the high‐latitude city Helsinki, Q.J.R. Meteorol. Soc., 142, 401–417, https://doi.org/10.1002/qj.2659, 2016. Kotthaus, S. and Grimmond, C. S. B.: Energy exchange in a dense urban environment – Part I: Temporal variability of long-term observations in central London, Urban Climate, 10, Part 2, 261–280, https://doi.org/10.1016/j.uclim.2013.10.002, 2014a. Kotthaus, S. and Grimmond, C. S. B.: Energy exchange in a dense urban environment – Part II: Impact of spatial heterogeneity of the surface, Urban Climate, 10, Part 2, 281–307, https://doi.org/10.1016/j.uclim.2013.10.001, 2014b. Masson, V., Gomes, L., Pigeon, G., Liousse, C., Pont, V., Lagouarde, J.-P., Voogt, J., Salmond, J., Oke, T. R., Hidalgo, J., Legain, D., Garrouste, O., Lac, C., Connan, O., Briottet, X., Lachérade, S., and Tulet, P.: The Canopy and Aerosol Particles Interactions in TOulouse Urban Layer (CAPITOUL) experiment, Meteorol Atmos Phys, 102, 135, https://doi.org/10.1007/s00703-008-0289-4, 2008. Menzer, O. and McFadden, J. P.: Statistical partitioning of a three-year time series of direct urban net CO2 flux measurements into biogenic and anthropogenic components, Atmospheric Environment, 170, 319–333, https://doi.org/10.1016/j.atmosenv.2017.09.049, 2017. Nordbo, A., Järvi, L., Haapanala, S., Moilanen, J., and Vesala, T.: Intra-City Variation in Urban Morphology and Turbulence Structure in Helsinki, Finland, Boundary-Layer Meteorol, 146, 469–496, https://doi.org/10.1007/s10546-012-9773-y, 2013. Pawlak, W., Fortuniak, K., and Siedlecki, M.: Carbon dioxide flux in the centre of Łódź, Pola

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.049
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0490.057

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.122
GPT teacher head0.285
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2022
Admission routes1
Has abstractyes

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