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Volume 7, issue 2
Earth Syst. Sci. Data, 7, 157–171, 2015
https://doi.org/10.5194/essd-7-157-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Earth Syst. Sci. Data, 7, 157–171, 2015
https://doi.org/10.5194/essd-7-157-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  13 Jul 2015

13 Jul 2015

Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis

N. Vuichard1 and D. Papale2,3 N. Vuichard and D. Papale
  • 1Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL – UMR CEA/CNRS/UVSQ 8212 CEA Saclay, Orme des Merisiers, Bât 712, 91191 Gif-sur-Yvette, France
  • 2Department for Innovation in Biological, Agro-food and Forest systems (DIBAF), University of Tuscia, Viterbo, Italy
  • 3Euro-Mediterranean Center on Climate Change (CMCC), Via Augusto Imperatore 16, 73100 Lecce, Italy

Abstract. Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.

The ERA-Interim reanalysis data de-biased at FLUXNET sites can be downloaded from the PANGAEA data centre (http://doi.pangaea.de/10.1594/PANGAEA.838234).

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Short summary
In order to fill the gaps in the in situ meteorological data that is acquired at FLUXNET stations, we develop a method that makes use of the reanalysis ERA-interim, which is available globally and at a high temporal resolution. Because the ERA-interim data are not measured at site level, we bias-correct them. The developed method is applied and evaluated at 153 FLUXNET stations. The final product consists of uninterrupted meteorological records that can be used for running most ecosystem models.
In order to fill the gaps in the in situ meteorological data that is acquired at FLUXNET...
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