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How strict selection of the raw eddy-covariance data influences gpp estimation of a temperate beech forest

Abstract : The data quality and the selection of the correct Eddy Covariance (EC) records become an important step in the CO2 flux determination procedure. An innovative combination of existing assessment tests is used to give a relatively complete evaluation of the net ecosystem exchange measurements. For the 2005 full-leaf season at the Hesse site, the percentage of bad quality data is relatively high (59.6%) especially during night-time (68.9%). This result strengthens the importance of the data gap filling method. The filtering used does not lead to a real improvement of the accuracy of the relationship between the CO2 fluxes and the climatic factors. The soil respiration spatial heterogeneity (on a site with relatively homogenous vegetation pattern) seems to be too important to allow this improvement. However, the data rejected present some common characteristics. Their removal lead to a 10% increase in the total amount of CO2 respired (Reco) and photosynthesised (GPP) during the 2005 full-leaf season. Consequently the application of our combination of multiple quality tests is able improve the inter-annual analysis. The question of a systematic application on the large database like the CarboEurope and FLUXNET is legitimate.
Type de document :
Liste complète des métadonnées
Déposant : Migration Prodinra <>
Soumis le : samedi 6 juin 2020 - 13:19:23
Dernière modification le : vendredi 12 juin 2020 - 10:43:26


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  • HAL Id : hal-02815801, version 1
  • PRODINRA : 29323



Bernard Longdoz, Patrick Gross, André Granier. How strict selection of the raw eddy-covariance data influences gpp estimation of a temperate beech forest. 5. Réunion du projet Carbo Europe, Oct 2007, Poznan, Poland. 1 p., 2007. ⟨hal-02815801⟩



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